Use merlin-dataloader package #845

edknv · 2022-11-02T04:45:21Z

Goals ⚽

Use the new merlin-dataloader package under the hood.

Implementation Details 🚧

merlin.Loader inherits from the merlin-dataloader's tensorflow.Loader, mainly to make cat_names, cont_names and label_names available.
merlin.DataLoader (the parent class of merlin.Loader) is completely removed.
The transform in merlin.Loader(transform=...) was previously implemented for PredictMaksed in session-based models, so that we could have mm.Loader(..., transform=PredictMasked(...))' but we didn't end up using this approach. Thus, this PR proposes to remove transformand revert back to usingLoader.map()`.
One notebook did not work with the new dataloader. Previously the Models dataloader worked even if a ListColumn did not have value_count in the schema, but the new dataloader will raise an error if a list doesn't have or infer value_count. he obvious solution is to the ValueCount op after ListSlice but padding in ListSlice also had to be removed. See related issue: [BUG] to_parquet throws an error when ListSlice(..., pad=True) and ValueCount() are combined. NVTabular#1700.
The files related to Models version of Torch dataloader have been simply removed. When Torch dataloader is needed in Models in the future, it should use merlin.loader.torch.Loader instead.

Testing Details 🔍

All existing unit tests. Some tests are updated to work with the new format.
Updated examples/usecases/ecommerce-session-based-next-item-prediction-for-fashion.ipynb to work with the new dataloader.

nvidia-merlin-bot · 2022-11-02T05:12:34Z

Click to view CI Results

GitHub pull request #845 of commit fd4b593d4ae4a2586d455608764812148d627003, no merge conflicts.
Running as SYSTEM
Setting status of fd4b593d4ae4a2586d455608764812148d627003 to PENDING with url https://10.20.13.93:8080/job/merlin_models/1692/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse fd4b593d4ae4a2586d455608764812148d627003^{commit} # timeout=10
Checking out Revision fd4b593d4ae4a2586d455608764812148d627003 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f fd4b593d4ae4a2586d455608764812148d627003 # timeout=10
Commit message: "Use merlin-dataloader package"
 > git rev-list --no-walk 192a08dcbccd1660fcbc64028c478153d6de2063 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins913317431965210484.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/1/merlin-models-0.9.0+22.gfd4b593d.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.26.5,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.28.5,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+22.gfd4b593d,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='2470620573'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-st88axkx
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-st88axkx
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
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  Preparing metadata (pyproject.toml): started
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Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (59.8.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+5.g563be4b) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-uf6ou8e0

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-uf6ou8e0

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit 5905283777ff5ebd748a1c91b7c9fde5710ae775

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+1.g5905283) (0.8.0+5.g563be4b)

Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.3.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (4.64.1)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.5.0)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.2.5)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (7.0.0)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.3.5)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (21.3)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.3.0)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.10.0)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (0.55.1)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (3.19.5)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (0.4.3)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.2.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.2.0)

Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (5.4.1)

Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2.2.0)

Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (0.12.0)

Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (3.1.2)

Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (6.2)

Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (5.8.0)

Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2.4.0)

Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.7.0)

Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2.0.0)

Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.0.4)

Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (8.1.3)

Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (0.38.1)

Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (59.8.0)

Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.20.3)

Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (3.0.9)

Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2.8.2)

Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.2.1)

Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.2.0)

Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.52.0)

Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (0.2.1)

Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.15.0)

Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.0.1)

Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (6.0.2)

Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (4.1.0)

Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2.0.1)

Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (4.0.0)

Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+1.g5905283) (6.0.1)

Building wheels for collected packages: merlin-dataloader

Building wheel for merlin-dataloader (pyproject.toml): started

Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'

Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+1.g5905283-py3-none-any.whl size=31625 sha256=bebea9ff4c86c58873c6d181b60014a61231eacb88ec0e8902bf189fea3334b6

Stored in directory: /tmp/pip-ephem-wheel-cache-ed5xgilo/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1

Successfully built merlin-dataloader

Installing collected packages: merlin-dataloader

Attempting uninstall: merlin-dataloader

Found existing installation: merlin-dataloader 0.0.2

Uninstalling merlin-dataloader-0.0.2:

Successfully uninstalled merlin-dataloader-0.0.2

Successfully installed merlin-dataloader-0.0.2+1.g5905283
[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-sgywa1oh

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-sgywa1oh

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 59579f2c46006fcb22795623ee9400c658166670

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+2.g59579f2c) (1.8.1)

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+2.g59579f2c) (0.8.0+5.g563be4b)

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+2.g59579f2c) (0.0.2+1.g5905283)

Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (2022.3.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (4.64.1)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (2022.5.0)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (1.2.5)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (7.0.0)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (1.3.5)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (21.3)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (2022.3.0)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (1.10.0)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (0.55.1)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (3.19.5)

Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+2.g59579f2c) (1.20.3)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (0.4.3)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (1.2.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (1.2.0)

Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (5.4.1)

Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (2.2.0)

Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (0.12.0)

Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (3.1.2)

Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (6.2)

Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (5.8.0)

Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (2.4.0)

Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (1.7.0)

Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (2.0.0)

Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (1.0.4)

Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+2.g59579f2c) (8.1.3)

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[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/test-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 830 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss                              [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py .................................       [ 13%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 16%]

.....................                                                    [ 19%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 19%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 19%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 21%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 21%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 21%]

tests/unit/tf/core/test_aggregation.py .........                         [ 22%]

tests/unit/tf/core/test_base.py ..                                       [ 22%]

tests/unit/tf/core/test_combinators.py s....................             [ 25%]

tests/unit/tf/core/test_encoder.py ..                                    [ 25%]

tests/unit/tf/core/test_index.py ...                                     [ 26%]

tests/unit/tf/core/test_prediction.py ..                                 [ 26%]

tests/unit/tf/core/test_tabular.py ......                                [ 26%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 27%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 27%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 27%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 27%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 27%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 27%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 27%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 27%]

[ 27%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 28%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 28%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 28%]

tests/unit/tf/inputs/test_continuous.py .......                          [ 29%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]

........                                                                 [ 34%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 36%]

tests/unit/tf/layers/test_queue.py ..............                        [ 38%]

tests/unit/tf/losses/test_losses.py .......................              [ 40%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 41%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 44%]

tests/unit/tf/models/test_base.py s........................              [ 47%]

tests/unit/tf/models/test_benchmark.py ..                                [ 47%]

tests/unit/tf/models/test_ranking.py ..................................  [ 51%]

tests/unit/tf/models/test_retrieval.py ................................. [ 55%]

..........................................                               [ 60%]

tests/unit/tf/outputs/test_base.py ......                                [ 61%]

tests/unit/tf/outputs/test_classification.py ......                      [ 62%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 63%]

tests/unit/tf/outputs/test_regression.py ..                              [ 64%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 64%]

tests/unit/tf/outputs/test_topk.py .                                     [ 64%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 65%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 66%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 67%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 68%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 68%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 69%]

tests/unit/tf/transformers/test_block.py .....................           [ 71%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 72%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 73%]

tests/unit/tf/transforms/test_features.py s............................. [ 76%]

....................s......                                              [ 79%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 80%]

tests/unit/tf/transforms/test_noise.py .....                             [ 81%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 83%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 84%]

tests/unit/tf/utils/test_batch.py ....                                   [ 84%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 85%]

tests/unit/torch/test_dataset.py FFFFFFFFF                               [ 86%]

tests/unit/torch/test_public_api.py .                                    [ 86%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 87%]

tests/unit/torch/features/test_continuous.py ..                          [ 87%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 89%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 92%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 93%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________
tb = <testbook.client.TestbookNotebookClient object at 0x7fe3ea0db040>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:

../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7fe3ea0db040>

cell = {'cell_type': 'code', 'execution_count': 22, 'id': 'f0ddad65', 'metadata': {'execution': {'iopub.status.busy': '2022-1...n the schema"]}], 'source': 'train_dl = mm.Loader(\n    train,\n    batch_size = BATCH_SIZE,\n    shuffle = False \n)'}

cell_index = 43

exec_reply = {'buffers': [], 'content': {'ename': 'ValueError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'f4b4b936-f009-412a...e, 'engine': 'f4b4b936-f009-412a-b15c-9ea844150060', 'started': '2022-11-02T04:54:59.040276Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E E           ------------------
 E           train_dl = mm.Loader(
 E               train,
 E E               shuffle = False
 E           )
 E           ------------------
 E
 E E E E E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E
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 E E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E           �[1;32m E
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 E E

nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:
 batch_size = BATCH_SIZE,
 �[0;31m---------------------------------------------------------------------------�[0m
 �[0;31mValueError�[0m                                Traceback (most recent call last)
 Cell �[0;32mIn [22], line 1�[0m
 �[0;32m----> 1�[0m train_dl �[38;5;241m=�[39m �[43mmm�[49m�[38;5;241;43m.�[39;49m�[43mLoader�[49m�[43m(�[49m
 2�[0m �[43m    �[49m�[43mtrain�[49m�[43m,�[49m
 3�[0m �[43m    �[49m�[43mbatch_size�[49m�[43m �[49m�[38;5;241;43m=�[39;49m�[43m �[49m�[43mBATCH_SIZE�[49m�[43m,�[49m
 4�[0m �[43m    �[49m�[43mshuffle�[49m�[43m �[49m�[38;5;241;43m=�[39;49m�[43m �[49m�[38;5;28;43;01mFalse�[39;49;00m�[43m �[49m
 5�[0m �[43m)�[49m
 File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/loader.py:283�[0m, in �[0;36mLoader.__init__�[0;34m(self, paths_or_dataset, batch_size, transform, label_names, feature_columns, cat_names, cont_names, engine, shuffle, seed_fn, buffer_size, device, parts_per_chunk, reader_kwargs, global_size, global_rank, drop_last, sparse_names, sparse_max, multi_label_as_dict, sparse_as_dense, schema)�[0m
 281�[0m device �[38;5;241m=�[39m device �[38;5;129;01mor�[39;00m �[38;5;241m0�[39m
 282�[0m device �[38;5;241m=�[39m �[38;5;124m"�[39m�[38;5;124mcpu�[39m�[38;5;124m"�[39m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m HAS_GPU �[38;5;28;01melse�[39;00m device
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 284�[0m �[43m    �[49m�[38;5;28;43mself�[39;49m�[43m,�[49m
 285�[0m �[43m    �[49m�[43mdataset�[49m�[43m,�[49m
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 288�[0m �[43m    �[49m�[43mcat_names�[49m�[38;5;241;43m=�[39;49m�[43mcat_names�[49m�[43m,�[49m
 289�[0m �[43m    �[49m�[43mcont_names�[49m�[38;5;241;43m=�[39;49m�[43mcont_names�[49m�[43m,�[49m
 290�[0m �[43m    �[49m�[43mlabel_names�[49m�[38;5;241;43m=�[39;49m�[43mlabel_names�[49m�[43m,�[49m
 291�[0m �[43m    �[49m�[43mseed_fn�[49m�[38;5;241;43m=�[39;49m�[43mseed_fn�[49m�[43m,�[49m
 292�[0m �[43m    �[49m�[43mparts_per_chunk�[49m�[38;5;241;43m=�[39;49m�[43mparts_per_chunk�[49m�[43m,�[49m
 293�[0m �[43m    �[49m�[43mdevice�[49m�[38;5;241;43m=�[39;49m�[43mdevice�[49m�[43m,�[49m
 294�[0m �[43m    �[49m�[43mglobal_size�[49m�[38;5;241;43m=�[39;49m�[43mglobal_size�[49m�[43m,�[49m
 295�[0m �[43m    �[49m�[43mglobal_rank�[49m�[38;5;241;43m=�[39;49m�[43mglobal_rank�[49m�[43m,�[49m
 296�[0m �[43m    �[49m�[43mdrop_last�[49m�[38;5;241;43m=�[39;49m�[43mdrop_last�[49m�[43m,�[49m
 297�[0m �[43m    �[49m�[43msparse_names�[49m�[38;5;241;43m=�[39;49m�[43msparse_names�[49m�[43m,�[49m
 298�[0m �[43m    �[49m�[43msparse_max�[49m�[38;5;241;43m=�[39;49m�[43msparse_max�[49m�[43m,�[49m
 299�[0m �[43m    �[49m�[43msparse_as_dense�[49m�[38;5;241;43m=�[39;49m�[43msparse_as_dense�[49m�[43m,�[49m
 300�[0m �[43m�[49m�[43m)�[49m
 301�[0m �[38;5;28mself�[39m�[38;5;241m.�[39m_transforms �[38;5;241m=�[39m [(�[38;5;124m"�[39m�[38;5;124mall�[39m�[38;5;124m"�[39m, transform)] �[38;5;28;01mif�[39;00m transform �[38;5;28;01melse�[39;00m []
 302�[0m �[38;5;28mself�[39m�[38;5;241m.�[39mmulti_label_as_dict �[38;5;241m=�[39m multi_label_as_dict
 File �[0;32m~/workspace/merlin_models/models/merlin/models/loader/backend.py:55�[0m, in �[0;36mDataLoader.__init__�[0;34m(self, dataset, batch_size, shuffle, cat_names, cont_names, label_names, seed_fn, parts_per_chunk, device, global_size, global_rank, drop_last, sparse_names, sparse_max, sparse_as_dense)�[0m
 37�[0m �[38;5;28;01mdef�[39;00m �[38;5;21m__init__�[39m(
 38�[0m     �[38;5;28mself�[39m,
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 53�[0m     sparse_as_dense�[38;5;241m=�[39m�[38;5;28;01mFalse�[39;00m,
 �[0;32m---> 55�[0m     �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[38;5;21;43m__init__�[39;49m�[43m(�[49m
 56�[0m �[43m        �[49m�[43mdataset�[49m�[38;5;241;43m=�[39;49m�[43mdataset�[49m�[43m,�[49m
 57�[0m �[43m        �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[43mbatch_size�[49m�[43m,�[49m
 58�[0m �[43m        �[49m�[43mshuffle�[49m�[38;5;241;43m=�[39;49m�[43mshuffle�[49m�[43m,�[49m
 59�[0m �[43m        �[49m�[43mseed_fn�[49m�[38;5;241;43m=�[39;49m�[43mseed_fn�[49m�[43m,�[49m
 60�[0m �[43m        �[49m�[43mparts_per_chunk�[49m�[38;5;241;43m=�[39;49m�[43mparts_per_chunk�[49m�[43m,�[49m
 61�[0m �[43m        �[49m�[43mglobal_size�[49m�[38;5;241;43m=�[39;49m�[43mglobal_size�[49m�[43m,�[49m
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 117�[0m �[43m        �[49m�[38;5;28;43mself�[39;49m�[43m,�[49m
 118�[0m �[43m        �[49m�[43mdataset�[49m�[43m,�[49m
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 122�[0m �[43m        �[49m�[43mparts_per_chunk�[49m�[38;5;241;43m=�[39;49m�[43mparts_per_chunk�[49m�[43m,�[49m
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 105�[0m                     �[38;5;124mf�[39m�[38;5;124m"�[39m�[38;5;124mDense column �[39m�[38;5;132;01m{�[39;00mcol_name�[38;5;132;01m}�[39;00m�[38;5;124m doesn�[39m�[38;5;124m'�[39m�[38;5;124mt have the max value_count defined�[39m�[38;5;124m"�[39m
 106�[0m                     �[38;5;124m"�[39m�[38;5;124m in the schema�[39m�[38;5;124m"�[39m
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 �[0;31mValueError�[0m: Dense column f_47_list_seq doesn't have the max value_count defined in the schema
 ValueError: Dense column f_47_list_seq doesn't have the max value_count defined in the schema
../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-02 04:54:45.490155: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-02 04:54:48.821830: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-02 04:54:48.822005: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-02 04:54:48.822798: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-02 04:54:48.822855: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-02 04:54:48.823488: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-02 04:54:48.823539: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-02 04:54:48.824179: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-02 04:54:48.824227: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

________________________________ test_shuffling ________________________________
def test_shuffling():
    num_rows = 10000
    batch_size = 10000

    df = pd.DataFrame({"a": np.asarray(range(num_rows)), "b": np.asarray([0] * num_rows)})

    train_dataset = torch_dataloader.Dataset(
        Dataset(df), conts=["a"], labels=["b"], batch_size=batch_size, shuffle=True
    )

    batch = next(iter(train_dataset))


  first_batch = batch[0]["a"].cpu()


E       AttributeError: 'str' object has no attribute 'cpu'
tests/unit/torch/test_dataset.py:38: AttributeError

______________________ test_torch_drp_reset[100-True-10] _______________________
tmpdir = local('/tmp/pytest-of-jenkins/pytest-34/test_torch_drp_reset_100_True_0')

batch_size = 10, drop_last = True, num_rows = 100
@pytest.mark.parametrize("batch_size", [10, 9, 8])
@pytest.mark.parametrize("drop_last", [True, False])
@pytest.mark.parametrize("num_rows", [100])
def test_torch_drp_reset(tmpdir, batch_size, drop_last, num_rows):
    df = make_df(
        {
            "cat1": [1] * num_rows,
            "cat2": [2] * num_rows,
            "cat3": [3] * num_rows,
            "label": [0] * num_rows,
            "cont3": [3.0] * num_rows,
            "cont2": [2.0] * num_rows,
            "cont1": [1.0] * num_rows,
        }
    )
    cat_names = ["cat3", "cat2", "cat1"]
    cont_names = ["cont3", "cont2", "cont1"]
    label_name = ["label"]

    data_itr = torch_dataloader.Dataset(
        Dataset(df),
        cats=cat_names,
        conts=cont_names,
        labels=label_name,
        batch_size=batch_size,
        drop_last=drop_last,
        device="cpu",
    )

    all_len = len(data_itr) if drop_last else len(data_itr) - 1
    all_rows = 0
    df_cols = df.columns.to_list()


  for idx, chunk in enumerate(data_itr):


tests/unit/torch/test_dataset.py:77:

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:243: in next

return self._get_next_batch()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:276: in _get_next_batch

self._fetch_chunk()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:255: in _fetch_chunk

raise chunks

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:669: in load_chunks

self.chunk_logic(itr)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:649: in chunk_logic

chunks = self.dataloader.make_tensors(chunks, self.dataloader._use_nnz)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

merlin/models/loader/backend.py:125: in make_tensors

chunk = self._split_fn(chunk, split_idx)

merlin/models/torch/dataset.py:122: in _split_fn

return torch.split(tensor, idx, dim=axis)

tensor = 'torch.FloatTensor'

split_size_or_sections = [10, 10, 10, 10, 10, 10, ...], dim = 0
def split(
    tensor: Tensor, split_size_or_sections: Union[int, List[int]], dim: int = 0
) -> List[Tensor]:
    r"""Splits the tensor into chunks. Each chunk is a view of the original tensor.

    If :attr:`split_size_or_sections` is an integer type, then :attr:`tensor` will
    be split into equally sized chunks (if possible). Last chunk will be smaller if
    the tensor size along the given dimension :attr:`dim` is not divisible by
    :attr:`split_size`.

    If :attr:`split_size_or_sections` is a list, then :attr:`tensor` will be split
    into ``len(split_size_or_sections)`` chunks with sizes in :attr:`dim` according
    to :attr:`split_size_or_sections`.

    Args:
        tensor (Tensor): tensor to split.
        split_size_or_sections (int) or (list(int)): size of a single chunk or
            list of sizes for each chunk
        dim (int): dimension along which to split the tensor.

    Example::

        >>> a = torch.arange(10).reshape(5,2)
        >>> a
        tensor([[0, 1],
                [2, 3],
                [4, 5],
                [6, 7],
                [8, 9]])
        >>> torch.split(a, 2)
        (tensor([[0, 1],
                 [2, 3]]),
         tensor([[4, 5],
                 [6, 7]]),
         tensor([[8, 9]]))
        >>> torch.split(a, [1,4])
        (tensor([[0, 1]]),
         tensor([[2, 3],
                 [4, 5],
                 [6, 7],
                 [8, 9]]))
    """
    if has_torch_function_unary(tensor):
        return handle_torch_function(
            split, (tensor,), tensor, split_size_or_sections, dim=dim)
    # Overwriting reason:
    # This dispatches to two ATen functions depending on the type of
    # split_size_or_sections. The branching code is in _tensor.py, which we
    # call here.


  return tensor.split(split_size_or_sections, dim)


E       TypeError: must be str or None, not list
/usr/local/lib/python3.8/dist-packages/torch/functional.py:189: TypeError

_______________________ test_torch_drp_reset[100-True-9] _______________________
tmpdir = local('/tmp/pytest-of-jenkins/pytest-34/test_torch_drp_reset_100_True_1')

batch_size = 9, drop_last = True, num_rows = 100
@pytest.mark.parametrize("batch_size", [10, 9, 8])
@pytest.mark.parametrize("drop_last", [True, False])
@pytest.mark.parametrize("num_rows", [100])
def test_torch_drp_reset(tmpdir, batch_size, drop_last, num_rows):
    df = make_df(
        {
            "cat1": [1] * num_rows,
            "cat2": [2] * num_rows,
            "cat3": [3] * num_rows,
            "label": [0] * num_rows,
            "cont3": [3.0] * num_rows,
            "cont2": [2.0] * num_rows,
            "cont1": [1.0] * num_rows,
        }
    )
    cat_names = ["cat3", "cat2", "cat1"]
    cont_names = ["cont3", "cont2", "cont1"]
    label_name = ["label"]

    data_itr = torch_dataloader.Dataset(
        Dataset(df),
        cats=cat_names,
        conts=cont_names,
        labels=label_name,
        batch_size=batch_size,
        drop_last=drop_last,
        device="cpu",
    )

    all_len = len(data_itr) if drop_last else len(data_itr) - 1
    all_rows = 0
    df_cols = df.columns.to_list()


  for idx, chunk in enumerate(data_itr):


tests/unit/torch/test_dataset.py:77:

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:243: in next

return self._get_next_batch()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:276: in _get_next_batch

self._fetch_chunk()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:255: in _fetch_chunk

raise chunks

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:669: in load_chunks

self.chunk_logic(itr)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:649: in chunk_logic

chunks = self.dataloader.make_tensors(chunks, self.dataloader._use_nnz)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

merlin/models/loader/backend.py:125: in make_tensors

chunk = self._split_fn(chunk, split_idx)

merlin/models/torch/dataset.py:122: in _split_fn

return torch.split(tensor, idx, dim=axis)

tensor = 'torch.FloatTensor', split_size_or_sections = [9, 9, 9, 9, 9, 9, ...]

dim = 0
def split(
    tensor: Tensor, split_size_or_sections: Union[int, List[int]], dim: int = 0
) -> List[Tensor]:
    r"""Splits the tensor into chunks. Each chunk is a view of the original tensor.

    If :attr:`split_size_or_sections` is an integer type, then :attr:`tensor` will
    be split into equally sized chunks (if possible). Last chunk will be smaller if
    the tensor size along the given dimension :attr:`dim` is not divisible by
    :attr:`split_size`.

    If :attr:`split_size_or_sections` is a list, then :attr:`tensor` will be split
    into ``len(split_size_or_sections)`` chunks with sizes in :attr:`dim` according
    to :attr:`split_size_or_sections`.

    Args:
        tensor (Tensor): tensor to split.
        split_size_or_sections (int) or (list(int)): size of a single chunk or
            list of sizes for each chunk
        dim (int): dimension along which to split the tensor.

    Example::

        >>> a = torch.arange(10).reshape(5,2)
        >>> a
        tensor([[0, 1],
                [2, 3],
                [4, 5],
                [6, 7],
                [8, 9]])
        >>> torch.split(a, 2)
        (tensor([[0, 1],
                 [2, 3]]),
         tensor([[4, 5],
                 [6, 7]]),
         tensor([[8, 9]]))
        >>> torch.split(a, [1,4])
        (tensor([[0, 1]]),
         tensor([[2, 3],
                 [4, 5],
                 [6, 7],
                 [8, 9]]))
    """
    if has_torch_function_unary(tensor):
        return handle_torch_function(
            split, (tensor,), tensor, split_size_or_sections, dim=dim)
    # Overwriting reason:
    # This dispatches to two ATen functions depending on the type of
    # split_size_or_sections. The branching code is in _tensor.py, which we
    # call here.


  return tensor.split(split_size_or_sections, dim)


E       TypeError: must be str or None, not list
/usr/local/lib/python3.8/dist-packages/torch/functional.py:189: TypeError

_______________________ test_torch_drp_reset[100-True-8] _______________________
tmpdir = local('/tmp/pytest-of-jenkins/pytest-34/test_torch_drp_reset_100_True_2')

batch_size = 8, drop_last = True, num_rows = 100
@pytest.mark.parametrize("batch_size", [10, 9, 8])
@pytest.mark.parametrize("drop_last", [True, False])
@pytest.mark.parametrize("num_rows", [100])
def test_torch_drp_reset(tmpdir, batch_size, drop_last, num_rows):
    df = make_df(
        {
            "cat1": [1] * num_rows,
            "cat2": [2] * num_rows,
            "cat3": [3] * num_rows,
            "label": [0] * num_rows,
            "cont3": [3.0] * num_rows,
            "cont2": [2.0] * num_rows,
            "cont1": [1.0] * num_rows,
        }
    )
    cat_names = ["cat3", "cat2", "cat1"]
    cont_names = ["cont3", "cont2", "cont1"]
    label_name = ["label"]

    data_itr = torch_dataloader.Dataset(
        Dataset(df),
        cats=cat_names,
        conts=cont_names,
        labels=label_name,
        batch_size=batch_size,
        drop_last=drop_last,
        device="cpu",
    )

    all_len = len(data_itr) if drop_last else len(data_itr) - 1
    all_rows = 0
    df_cols = df.columns.to_list()


  for idx, chunk in enumerate(data_itr):


tests/unit/torch/test_dataset.py:77:

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:243: in next

return self._get_next_batch()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:276: in _get_next_batch

self._fetch_chunk()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:255: in _fetch_chunk

raise chunks

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:669: in load_chunks

self.chunk_logic(itr)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:649: in chunk_logic

chunks = self.dataloader.make_tensors(chunks, self.dataloader._use_nnz)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

merlin/models/loader/backend.py:125: in make_tensors

chunk = self._split_fn(chunk, split_idx)

merlin/models/torch/dataset.py:122: in _split_fn

return torch.split(tensor, idx, dim=axis)

tensor = 'torch.FloatTensor', split_size_or_sections = [8, 8, 8, 8, 8, 8, ...]

dim = 0
def split(
    tensor: Tensor, split_size_or_sections: Union[int, List[int]], dim: int = 0
) -> List[Tensor]:
    r"""Splits the tensor into chunks. Each chunk is a view of the original tensor.

    If :attr:`split_size_or_sections` is an integer type, then :attr:`tensor` will
    be split into equally sized chunks (if possible). Last chunk will be smaller if
    the tensor size along the given dimension :attr:`dim` is not divisible by
    :attr:`split_size`.

    If :attr:`split_size_or_sections` is a list, then :attr:`tensor` will be split
    into ``len(split_size_or_sections)`` chunks with sizes in :attr:`dim` according
    to :attr:`split_size_or_sections`.

    Args:
        tensor (Tensor): tensor to split.
        split_size_or_sections (int) or (list(int)): size of a single chunk or
            list of sizes for each chunk
        dim (int): dimension along which to split the tensor.

    Example::

        >>> a = torch.arange(10).reshape(5,2)
        >>> a
        tensor([[0, 1],
                [2, 3],
                [4, 5],
                [6, 7],
                [8, 9]])
        >>> torch.split(a, 2)
        (tensor([[0, 1],
                 [2, 3]]),
         tensor([[4, 5],
                 [6, 7]]),
         tensor([[8, 9]]))
        >>> torch.split(a, [1,4])
        (tensor([[0, 1]]),
         tensor([[2, 3],
                 [4, 5],
                 [6, 7],
                 [8, 9]]))
    """
    if has_torch_function_unary(tensor):
        return handle_torch_function(
            split, (tensor,), tensor, split_size_or_sections, dim=dim)
    # Overwriting reason:
    # This dispatches to two ATen functions depending on the type of
    # split_size_or_sections. The branching code is in _tensor.py, which we
    # call here.


  return tensor.split(split_size_or_sections, dim)


E       TypeError: must be str or None, not list
/usr/local/lib/python3.8/dist-packages/torch/functional.py:189: TypeError

______________________ test_torch_drp_reset[100-False-10] ______________________
tmpdir = local('/tmp/pytest-of-jenkins/pytest-34/test_torch_drp_reset_100_False0')

batch_size = 10, drop_last = False, num_rows = 100
@pytest.mark.parametrize("batch_size", [10, 9, 8])
@pytest.mark.parametrize("drop_last", [True, False])
@pytest.mark.parametrize("num_rows", [100])
def test_torch_drp_reset(tmpdir, batch_size, drop_last, num_rows):
    df = make_df(
        {
            "cat1": [1] * num_rows,
            "cat2": [2] * num_rows,
            "cat3": [3] * num_rows,
            "label": [0] * num_rows,
            "cont3": [3.0] * num_rows,
            "cont2": [2.0] * num_rows,
            "cont1": [1.0] * num_rows,
        }
    )
    cat_names = ["cat3", "cat2", "cat1"]
    cont_names = ["cont3", "cont2", "cont1"]
    label_name = ["label"]

    data_itr = torch_dataloader.Dataset(
        Dataset(df),
        cats=cat_names,
        conts=cont_names,
        labels=label_name,
        batch_size=batch_size,
        drop_last=drop_last,
        device="cpu",
    )

    all_len = len(data_itr) if drop_last else len(data_itr) - 1
    all_rows = 0
    df_cols = df.columns.to_list()


  for idx, chunk in enumerate(data_itr):


tests/unit/torch/test_dataset.py:77:

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:243: in next

return self._get_next_batch()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:276: in _get_next_batch

self._fetch_chunk()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:255: in _fetch_chunk

raise chunks

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:669: in load_chunks

self.chunk_logic(itr)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:649: in chunk_logic

chunks = self.dataloader.make_tensors(chunks, self.dataloader._use_nnz)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

merlin/models/loader/backend.py:125: in make_tensors

chunk = self._split_fn(chunk, split_idx)

merlin/models/torch/dataset.py:122: in _split_fn

return torch.split(tensor, idx, dim=axis)

tensor = 'torch.FloatTensor'

split_size_or_sections = [10, 10, 10, 10, 10, 10, ...], dim = 0
def split(
    tensor: Tensor, split_size_or_sections: Union[int, List[int]], dim: int = 0
) -> List[Tensor]:
    r"""Splits the tensor into chunks. Each chunk is a view of the original tensor.

    If :attr:`split_size_or_sections` is an integer type, then :attr:`tensor` will
    be split into equally sized chunks (if possible). Last chunk will be smaller if
    the tensor size along the given dimension :attr:`dim` is not divisible by
    :attr:`split_size`.

    If :attr:`split_size_or_sections` is a list, then :attr:`tensor` will be split
    into ``len(split_size_or_sections)`` chunks with sizes in :attr:`dim` according
    to :attr:`split_size_or_sections`.

    Args:
        tensor (Tensor): tensor to split.
        split_size_or_sections (int) or (list(int)): size of a single chunk or
            list of sizes for each chunk
        dim (int): dimension along which to split the tensor.

    Example::

        >>> a = torch.arange(10).reshape(5,2)
        >>> a
        tensor([[0, 1],
                [2, 3],
                [4, 5],
                [6, 7],
                [8, 9]])
        >>> torch.split(a, 2)
        (tensor([[0, 1],
                 [2, 3]]),
         tensor([[4, 5],
                 [6, 7]]),
         tensor([[8, 9]]))
        >>> torch.split(a, [1,4])
        (tensor([[0, 1]]),
         tensor([[2, 3],
                 [4, 5],
                 [6, 7],
                 [8, 9]]))
    """
    if has_torch_function_unary(tensor):
        return handle_torch_function(
            split, (tensor,), tensor, split_size_or_sections, dim=dim)
    # Overwriting reason:
    # This dispatches to two ATen functions depending on the type of
    # split_size_or_sections. The branching code is in _tensor.py, which we
    # call here.


  return tensor.split(split_size_or_sections, dim)


E       TypeError: must be str or None, not list
/usr/local/lib/python3.8/dist-packages/torch/functional.py:189: TypeError

______________________ test_torch_drp_reset[100-False-9] _______________________
tmpdir = local('/tmp/pytest-of-jenkins/pytest-34/test_torch_drp_reset_100_False1')

batch_size = 9, drop_last = False, num_rows = 100
@pytest.mark.parametrize("batch_size", [10, 9, 8])
@pytest.mark.parametrize("drop_last", [True, False])
@pytest.mark.parametrize("num_rows", [100])
def test_torch_drp_reset(tmpdir, batch_size, drop_last, num_rows):
    df = make_df(
        {
            "cat1": [1] * num_rows,
            "cat2": [2] * num_rows,
            "cat3": [3] * num_rows,
            "label": [0] * num_rows,
            "cont3": [3.0] * num_rows,
            "cont2": [2.0] * num_rows,
            "cont1": [1.0] * num_rows,
        }
    )
    cat_names = ["cat3", "cat2", "cat1"]
    cont_names = ["cont3", "cont2", "cont1"]
    label_name = ["label"]

    data_itr = torch_dataloader.Dataset(
        Dataset(df),
        cats=cat_names,
        conts=cont_names,
        labels=label_name,
        batch_size=batch_size,
        drop_last=drop_last,
        device="cpu",
    )

    all_len = len(data_itr) if drop_last else len(data_itr) - 1
    all_rows = 0
    df_cols = df.columns.to_list()


  for idx, chunk in enumerate(data_itr):


tests/unit/torch/test_dataset.py:77:

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:243: in next

return self._get_next_batch()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:276: in _get_next_batch

self._fetch_chunk()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:255: in _fetch_chunk

raise chunks

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:669: in load_chunks

self.chunk_logic(itr)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:649: in chunk_logic

chunks = self.dataloader.make_tensors(chunks, self.dataloader._use_nnz)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

merlin/models/loader/backend.py:125: in make_tensors

chunk = self._split_fn(chunk, split_idx)

merlin/models/torch/dataset.py:122: in _split_fn

return torch.split(tensor, idx, dim=axis)

tensor = 'torch.FloatTensor', split_size_or_sections = [9, 9, 9, 9, 9, 9, ...]

dim = 0
def split(
    tensor: Tensor, split_size_or_sections: Union[int, List[int]], dim: int = 0
) -> List[Tensor]:
    r"""Splits the tensor into chunks. Each chunk is a view of the original tensor.

    If :attr:`split_size_or_sections` is an integer type, then :attr:`tensor` will
    be split into equally sized chunks (if possible). Last chunk will be smaller if
    the tensor size along the given dimension :attr:`dim` is not divisible by
    :attr:`split_size`.

    If :attr:`split_size_or_sections` is a list, then :attr:`tensor` will be split
    into ``len(split_size_or_sections)`` chunks with sizes in :attr:`dim` according
    to :attr:`split_size_or_sections`.

    Args:
        tensor (Tensor): tensor to split.
        split_size_or_sections (int) or (list(int)): size of a single chunk or
            list of sizes for each chunk
        dim (int): dimension along which to split the tensor.

    Example::

        >>> a = torch.arange(10).reshape(5,2)
        >>> a
        tensor([[0, 1],
                [2, 3],
                [4, 5],
                [6, 7],
                [8, 9]])
        >>> torch.split(a, 2)
        (tensor([[0, 1],
                 [2, 3]]),
         tensor([[4, 5],
                 [6, 7]]),
         tensor([[8, 9]]))
        >>> torch.split(a, [1,4])
        (tensor([[0, 1]]),
         tensor([[2, 3],
                 [4, 5],
                 [6, 7],
                 [8, 9]]))
    """
    if has_torch_function_unary(tensor):
        return handle_torch_function(
            split, (tensor,), tensor, split_size_or_sections, dim=dim)
    # Overwriting reason:
    # This dispatches to two ATen functions depending on the type of
    # split_size_or_sections. The branching code is in _tensor.py, which we
    # call here.


  return tensor.split(split_size_or_sections, dim)


E       TypeError: must be str or None, not list
/usr/local/lib/python3.8/dist-packages/torch/functional.py:189: TypeError

______________________ test_torch_drp_reset[100-False-8] _______________________
tmpdir = local('/tmp/pytest-of-jenkins/pytest-34/test_torch_drp_reset_100_False2')

batch_size = 8, drop_last = False, num_rows = 100
@pytest.mark.parametrize("batch_size", [10, 9, 8])
@pytest.mark.parametrize("drop_last", [True, False])
@pytest.mark.parametrize("num_rows", [100])
def test_torch_drp_reset(tmpdir, batch_size, drop_last, num_rows):
    df = make_df(
        {
            "cat1": [1] * num_rows,
            "cat2": [2] * num_rows,
            "cat3": [3] * num_rows,
            "label": [0] * num_rows,
            "cont3": [3.0] * num_rows,
            "cont2": [2.0] * num_rows,
            "cont1": [1.0] * num_rows,
        }
    )
    cat_names = ["cat3", "cat2", "cat1"]
    cont_names = ["cont3", "cont2", "cont1"]
    label_name = ["label"]

    data_itr = torch_dataloader.Dataset(
        Dataset(df),
        cats=cat_names,
        conts=cont_names,
        labels=label_name,
        batch_size=batch_size,
        drop_last=drop_last,
        device="cpu",
    )

    all_len = len(data_itr) if drop_last else len(data_itr) - 1
    all_rows = 0
    df_cols = df.columns.to_list()


  for idx, chunk in enumerate(data_itr):


tests/unit/torch/test_dataset.py:77:

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:243: in next

return self._get_next_batch()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:276: in _get_next_batch

self._fetch_chunk()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:255: in _fetch_chunk

raise chunks

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:669: in load_chunks

self.chunk_logic(itr)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:649: in chunk_logic

chunks = self.dataloader.make_tensors(chunks, self.dataloader._use_nnz)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

merlin/models/loader/backend.py:125: in make_tensors

chunk = self._split_fn(chunk, split_idx)

merlin/models/torch/dataset.py:122: in _split_fn

return torch.split(tensor, idx, dim=axis)

tensor = 'torch.FloatTensor', split_size_or_sections = [8, 8, 8, 8, 8, 8, ...]

dim = 0
def split(
    tensor: Tensor, split_size_or_sections: Union[int, List[int]], dim: int = 0
) -> List[Tensor]:
    r"""Splits the tensor into chunks. Each chunk is a view of the original tensor.

    If :attr:`split_size_or_sections` is an integer type, then :attr:`tensor` will
    be split into equally sized chunks (if possible). Last chunk will be smaller if
    the tensor size along the given dimension :attr:`dim` is not divisible by
    :attr:`split_size`.

    If :attr:`split_size_or_sections` is a list, then :attr:`tensor` will be split
    into ``len(split_size_or_sections)`` chunks with sizes in :attr:`dim` according
    to :attr:`split_size_or_sections`.

    Args:
        tensor (Tensor): tensor to split.
        split_size_or_sections (int) or (list(int)): size of a single chunk or
            list of sizes for each chunk
        dim (int): dimension along which to split the tensor.

    Example::

        >>> a = torch.arange(10).reshape(5,2)
        >>> a
        tensor([[0, 1],
                [2, 3],
                [4, 5],
                [6, 7],
                [8, 9]])
        >>> torch.split(a, 2)
        (tensor([[0, 1],
                 [2, 3]]),
         tensor([[4, 5],
                 [6, 7]]),
         tensor([[8, 9]]))
        >>> torch.split(a, [1,4])
        (tensor([[0, 1]]),
         tensor([[2, 3],
                 [4, 5],
                 [6, 7],
                 [8, 9]]))
    """
    if has_torch_function_unary(tensor):
        return handle_torch_function(
            split, (tensor,), tensor, split_size_or_sections, dim=dim)
    # Overwriting reason:
    # This dispatches to two ATen functions depending on the type of
    # split_size_or_sections. The branching code is in _tensor.py, which we
    # call here.


  return tensor.split(split_size_or_sections, dim)


E       TypeError: must be str or None, not list
/usr/local/lib/python3.8/dist-packages/torch/functional.py:189: TypeError

__________________________ test_sparse_tensors[False] __________________________
sparse_dense = False
@pytest.mark.parametrize("sparse_dense", [False, True])
def test_sparse_tensors(sparse_dense):
    # create small Dataset, add values to sparse_list
    df = make_df(
        {
            "spar1": [[1, 2, 3, 4], [4, 2, 4, 4], [1, 3, 4, 3], [1, 1, 3, 3]],
            "spar2": [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14], [15, 16]],
        }
    )
    spa_lst = ["spar1", "spar2"]
    spa_mx = {"spar1": 5, "spar2": 6}
    batch_size = 2
    data_itr = torch_dataloader.Dataset(
        Dataset(df),
        cats=spa_lst,
        conts=[],
        labels=[],
        batch_size=batch_size,
        sparse_names=spa_lst,
        sparse_max=spa_mx,
        sparse_as_dense=sparse_dense,
    )


  for batch in data_itr:


tests/unit/torch/test_dataset.py:115:

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:243: in next

return self._get_next_batch()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:276: in _get_next_batch

self._fetch_chunk()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:255: in _fetch_chunk

raise chunks

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:667: in load_chunks

self.chunk_logic(itr)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:649: in chunk_logic

chunks = self.dataloader.make_tensors(chunks, self.dataloader._use_nnz)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

merlin/models/loader/backend.py:107: in make_tensors

chunks = self._create_tensors(gdf)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

self = <merlin.models.torch.dataset.Dataset object at 0x7fe378458b80>

gdf = Empty DataFrame

Columns: []

Index: [0, 1, 2, 3]
@annotate("_create_tensors", color="darkgreen", domain="merlin_dataloader")
def _create_tensors(self, gdf):
    """
    Breaks a dataframe down into the relevant
    categorical, continuous, and label tensors.
    Can be overrideen
    """
    workflow_nodes = (self.cat_names, self.cont_names, self.label_names)
    dtypes = (self._LONG_DTYPE, self._FLOAT32_DTYPE, self._FLOAT32_DTYPE)
    tensors = []
    offsets = make_df(device=self.device)
    for column_names, dtype in zip(workflow_nodes, dtypes):
        if len(column_names) == 0:
            tensors.append(None)
            continue
        if hasattr(column_names, "column_names"):
            column_names = column_names.column_names

        gdf_i = gdf[column_names]
        gdf.drop(columns=column_names, inplace=True)

        scalars, lists = self._separate_list_columns(gdf_i)

        x = None
        if scalars:
            # should always return dict column_name: values, offsets (optional)
            x = self._to_tensor(gdf_i[scalars])
        if lists:
            list_tensors = OrderedDict()
            for column_name in lists:
                column = gdf_i.pop(column_name)
                leaves, col_offsets = pull_apart_list(column)
                if isinstance(leaves[0], list):

                    leaves, nest_offsets = pull_apart_list(leaves)
                    col_offsets = nest_offsets.iloc[col_offsets[:]]
                offsets[column_name] = col_offsets.reset_index(drop=True)
                list_tensors[column_name] = self._to_tensor(leaves)
            x = x, list_tensors
        tensors.append(x)

    if not offsets.empty:
        offsets_tensor = self._to_tensor(offsets)


      if len(offsets_tensor.shape) == 1:


E           AttributeError: 'str' object has no attribute 'shape'
merlin/models/loader/backend.py:229: AttributeError

__________________________ test_sparse_tensors[True] ___________________________
sparse_dense = True
@pytest.mark.parametrize("sparse_dense", [False, True])
def test_sparse_tensors(sparse_dense):
    # create small Dataset, add values to sparse_list
    df = make_df(
        {
            "spar1": [[1, 2, 3, 4], [4, 2, 4, 4], [1, 3, 4, 3], [1, 1, 3, 3]],
            "spar2": [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14], [15, 16]],
        }
    )
    spa_lst = ["spar1", "spar2"]
    spa_mx = {"spar1": 5, "spar2": 6}
    batch_size = 2
    data_itr = torch_dataloader.Dataset(
        Dataset(df),
        cats=spa_lst,
        conts=[],
        labels=[],
        batch_size=batch_size,
        sparse_names=spa_lst,
        sparse_max=spa_mx,
        sparse_as_dense=sparse_dense,
    )


  for batch in data_itr:


tests/unit/torch/test_dataset.py:115:

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:243: in next

return self._get_next_batch()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:276: in _get_next_batch

self._fetch_chunk()

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:255: in _fetch_chunk

raise chunks

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:667: in load_chunks

self.chunk_logic(itr)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:649: in chunk_logic

chunks = self.dataloader.make_tensors(chunks, self.dataloader._use_nnz)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

merlin/models/loader/backend.py:107: in make_tensors

chunks = self._create_tensors(gdf)

/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101: in inner

result = func(*args, **kwargs)

self = <merlin.models.torch.dataset.Dataset object at 0x7fe379496b80>

gdf = Empty DataFrame

Columns: []

Index: [0, 1, 2, 3]
@annotate("_create_tensors", color="darkgreen", domain="merlin_dataloader")
def _create_tensors(self, gdf):
    """
    Breaks a dataframe down into the relevant
    categorical, continuous, and label tensors.
    Can be overrideen
    """
    workflow_nodes = (self.cat_names, self.cont_names, self.label_names)
    dtypes = (self._LONG_DTYPE, self._FLOAT32_DTYPE, self._FLOAT32_DTYPE)
    tensors = []
    offsets = make_df(device=self.device)
    for column_names, dtype in zip(workflow_nodes, dtypes):
        if len(column_names) == 0:
            tensors.append(None)
            continue
        if hasattr(column_names, "column_names"):
            column_names = column_names.column_names

        gdf_i = gdf[column_names]
        gdf.drop(columns=column_names, inplace=True)

        scalars, lists = self._separate_list_columns(gdf_i)

        x = None
        if scalars:
            # should always return dict column_name: values, offsets (optional)
            x = self._to_tensor(gdf_i[scalars])
        if lists:
            list_tensors = OrderedDict()
            for column_name in lists:
                column = gdf_i.pop(column_name)
                leaves, col_offsets = pull_apart_list(column)
                if isinstance(leaves[0], list):

                    leaves, nest_offsets = pull_apart_list(leaves)
                    col_offsets = nest_offsets.iloc[col_offsets[:]]
                offsets[column_name] = col_offsets.reset_index(drop=True)
                list_tensors[column_name] = self._to_tensor(leaves)
            x = x, list_tensors
        tensors.append(x)

    if not offsets.empty:
        offsets_tensor = self._to_tensor(offsets)


      if len(offsets_tensor.shape) == 1:


E           AttributeError: 'str' object has no attribute 'shape'
merlin/models/loader/backend.py:229: AttributeError

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 6 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 119 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 6 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 85 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:960: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 54 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filehvk2xy1o.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:614: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     60    24%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    3      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     15    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        145     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         114     10    91%

merlin/models/tf/blocks/optimizer.py                                   173     13    92%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   245     49    80%

merlin/models/tf/core/base.py                                          244     56    77%

merlin/models/tf/core/combinators.py                                   421     54    87%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       288     30    90%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   452     50    89%

merlin/models/tf/loader.py                                             139     33    76%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        707     75    89%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       122     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                422     40    91%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  107      2    98%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/dataset.py                                          68     27    60%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                10834   2161    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 10 failed, 808 passed, 12 skipped, 1347 warnings in 1555.69s (0:25:55) ====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   test-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins15951735015710199361.sh

nvidia-merlin-bot · 2022-11-02T23:14:02Z

Click to view CI Results

GitHub pull request #845 of commit 081331a957f791adacdda5b240b7dcbfc4e5e843, no merge conflicts.
Running as SYSTEM
Setting status of 081331a957f791adacdda5b240b7dcbfc4e5e843 to PENDING with url https://10.20.13.93:8080/job/merlin_models/1710/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 081331a957f791adacdda5b240b7dcbfc4e5e843^{commit} # timeout=10
Checking out Revision 081331a957f791adacdda5b240b7dcbfc4e5e843 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 081331a957f791adacdda5b240b7dcbfc4e5e843 # timeout=10
Commit message: "remove torch.dataset in favor of merlin.loader.torch"
 > git rev-list --no-walk 601391386295c15777656f23057aaf5603671f4c # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins15306544602734756866.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
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Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
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Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/1/merlin-models-0.9.0+23.g081331a9.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.0,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.0,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@5905283777ff5ebd748a1c91b7c9fde5710ae775,merlin-models==0.9.0+23.g081331a9,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='4032103209'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-pkblwh4l
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-pkblwh4l
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (3.19.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.10.0)
Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.5.1)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.5.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (21.3)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (1.3.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.2.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (4.64.1)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (7.0.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.12.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (3.1.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.4.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (8.1.3)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (6.2)
Collecting dask>=2022.3.0
  Downloading dask-2022.3.0-py3-none-any.whl (1.1 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 9.0 MB/s eta 0:00:00
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.8.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (59.8.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+5.g563be4b) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.0.0)
Installing collected packages: dask
  Attempting uninstall: dask
    Found existing installation: dask 2022.5.1
    Uninstalling dask-2022.5.1:
      Successfully uninstalled dask-2022.5.1
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
feast 0.19.4 requires dask<2022.02.0,>=2021.*, but you have dask 2022.3.0 which is incompatible.
Successfully installed dask-2022.3.0
[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-1_ak81d8

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-1_ak81d8

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit 5905283777ff5ebd748a1c91b7c9fde5710ae775

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+1.g5905283) (0.8.0+5.g563be4b)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (0.55.1)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (3.19.5)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.10.0)

Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.3.0)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.5.0)

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[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-t7bkbvdk

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-t7bkbvdk

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 8e7edbafd3006f56e73efdc0c01c4445ab57d028

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+3.g8e7edbaf) (0.8.0+5.g563be4b)

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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (4.0.0)
[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/test-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 821 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss                              [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py .................................       [ 13%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 17%]

.....................                                                    [ 19%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 19%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 20%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 21%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 21%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 21%]

tests/unit/tf/core/test_aggregation.py .........                         [ 22%]

tests/unit/tf/core/test_base.py ..                                       [ 23%]

tests/unit/tf/core/test_combinators.py s....................             [ 25%]

tests/unit/tf/core/test_encoder.py ..                                    [ 25%]

tests/unit/tf/core/test_index.py ...                                     [ 26%]

tests/unit/tf/core/test_prediction.py ..                                 [ 26%]

tests/unit/tf/core/test_tabular.py ......                                [ 27%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 27%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 27%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 27%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 27%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 27%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 28%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 28%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 28%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 28%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 28%]

tests/unit/tf/inputs/test_continuous.py .......                          [ 29%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]

........                                                                 [ 34%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 36%]

tests/unit/tf/layers/test_queue.py ..............                        [ 38%]

tests/unit/tf/losses/test_losses.py .......................              [ 41%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 41%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 44%]

tests/unit/tf/models/test_base.py s........................              [ 47%]

tests/unit/tf/models/test_benchmark.py ..                                [ 48%]

tests/unit/tf/models/test_ranking.py ..................................  [ 52%]

tests/unit/tf/models/test_retrieval.py ................................. [ 56%]

..........................................                               [ 61%]

tests/unit/tf/outputs/test_base.py ......                                [ 62%]

tests/unit/tf/outputs/test_classification.py ......                      [ 62%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 64%]

tests/unit/tf/outputs/test_regression.py ..                              [ 64%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 65%]

tests/unit/tf/outputs/test_topk.py .                                     [ 65%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 65%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 67%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 68%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 69%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 69%]

tests/unit/tf/transformers/test_block.py .....................           [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 73%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

....................s......                                              [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 85%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_public_api.py .                                    [ 86%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 87%]

tests/unit/torch/features/test_continuous.py ..                          [ 87%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 89%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 92%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 93%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________
tb = <testbook.client.TestbookNotebookClient object at 0x7fd61ed7f070>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:

../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7fd61ed7f070>

cell = {'cell_type': 'code', 'execution_count': 22, 'id': 'f0ddad65', 'metadata': {'execution': {'iopub.status.busy': '2022-1...n the schema"]}], 'source': 'train_dl = mm.Loader(\n    train,\n    batch_size = BATCH_SIZE,\n    shuffle = False \n)'}

cell_index = 43

exec_reply = {'buffers': [], 'content': {'ename': 'ValueError', 'engine_info': {'engine_id': -1, 'engine_uuid': '3f9042f2-476a-449c...e, 'engine': '3f9042f2-476a-449c-8a35-7a5b225a99b7', 'started': '2022-11-02T22:56:19.863248Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           train_dl = mm.Loader(

E               train,

E               batch_size = BATCH_SIZE,

E               shuffle = False

E           )

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mValueError�[0m                                Traceback (most recent call last)

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E

E           �[0;31mValueError�[0m: Dense column f_47_list_seq doesn't have the max value_count defined in the schema

E           ValueError: Dense column f_47_list_seq doesn't have the max value_count defined in the schema
../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-02 22:56:06.238772: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-02 22:56:09.577116: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-02 22:56:09.577282: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-02 22:56:09.578077: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-02 22:56:09.578130: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-02 22:56:09.578724: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-02 22:56:09.578773: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-02 22:56:09.579359: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-02 22:56:09.579409: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 6 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 119 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 6 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 85 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:960: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 54 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filer1c0vjrx.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:614: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     60    24%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    3      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     15    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        145     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         114     10    91%

merlin/models/tf/blocks/optimizer.py                                   173     13    92%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   245     49    80%

merlin/models/tf/core/base.py                                          244     56    77%

merlin/models/tf/core/combinators.py                                   421     54    87%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       288     30    90%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   452     50    89%

merlin/models/tf/loader.py                                             139     33    76%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        707     75    89%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       122     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                422     40    91%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  107      2    98%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                10766   2134    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 808 passed, 12 skipped, 1347 warnings in 1566.17s (0:26:06) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   test-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins1433789155300141500.sh

nvidia-merlin-bot · 2022-11-02T23:41:25Z

Click to view CI Results

GitHub pull request #845 of commit 594639674c2bb4ae520bede89cb3ee59b71bfbb4, no merge conflicts.
Running as SYSTEM
Setting status of 594639674c2bb4ae520bede89cb3ee59b71bfbb4 to PENDING with url https://10.20.13.93:8080/job/merlin_models/1711/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 594639674c2bb4ae520bede89cb3ee59b71bfbb4^{commit} # timeout=10
Checking out Revision 594639674c2bb4ae520bede89cb3ee59b71bfbb4 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 594639674c2bb4ae520bede89cb3ee59b71bfbb4 # timeout=10
Commit message: "Merge branch 'main' into merlin_dataloader"
 > git rev-list --no-walk 081331a957f791adacdda5b240b7dcbfc4e5e843 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins5208099379945923444.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/1/merlin-models-0.9.0+26.g59463967.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.0,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.0,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@5905283777ff5ebd748a1c91b7c9fde5710ae775,merlin-models==0.9.0+26.g59463967,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='274412947'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-_hhj122k
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-_hhj122k
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.5.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (3.19.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.10.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (7.0.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (1.3.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.2.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (4.64.1)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (0.55.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (21.3)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (0.4.3)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.12.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (6.2)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (3.1.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.8.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.7.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.4)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.4.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (8.1.3)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (59.8.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+5.g563be4b) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-orsery2m

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-orsery2m

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit 5905283777ff5ebd748a1c91b7c9fde5710ae775

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+1.g5905283) (0.8.0+5.g563be4b)

Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.3.0)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.5.0)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (3.19.5)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.10.0)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.3.5)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (2022.3.0)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (1.2.5)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (4.64.1)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+1.g5905283) (0.55.1)

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[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-od20lp5m

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-od20lp5m

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 8e7edbafd3006f56e73efdc0c01c4445ab57d028

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

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[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/test-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 824 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss                              [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py .................................       [ 13%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 17%]

.....................                                                    [ 19%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 19%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 20%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 21%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 21%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 21%]

tests/unit/tf/core/test_aggregation.py .........                         [ 22%]

tests/unit/tf/core/test_base.py ..                                       [ 23%]

tests/unit/tf/core/test_combinators.py s....................             [ 25%]

tests/unit/tf/core/test_encoder.py ..                                    [ 25%]

tests/unit/tf/core/test_index.py ...                                     [ 26%]

tests/unit/tf/core/test_prediction.py ..                                 [ 26%]

tests/unit/tf/core/test_tabular.py ......                                [ 27%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 27%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 27%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 27%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 27%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 27%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 27%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 28%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 28%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 28%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 28%]

tests/unit/tf/inputs/test_continuous.py .......                          [ 29%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]

........                                                                 [ 34%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 36%]

tests/unit/tf/layers/test_queue.py ..............                        [ 38%]

tests/unit/tf/losses/test_losses.py .......................              [ 41%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 41%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 44%]

tests/unit/tf/models/test_base.py s........................              [ 47%]

tests/unit/tf/models/test_benchmark.py ..                                [ 48%]

tests/unit/tf/models/test_ranking.py ..................................  [ 52%]

tests/unit/tf/models/test_retrieval.py ................................. [ 56%]

..........................................                               [ 61%]

tests/unit/tf/outputs/test_base.py ......                                [ 62%]

tests/unit/tf/outputs/test_classification.py ......                      [ 62%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 64%]

tests/unit/tf/outputs/test_regression.py ..                              [ 64%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 65%]

tests/unit/tf/outputs/test_topk.py .                                     [ 65%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 65%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 67%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 68%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 68%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 69%]

tests/unit/tf/transformers/test_block.py .....................           [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 73%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 84%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_public_api.py .                                    [ 86%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 87%]

tests/unit/torch/features/test_continuous.py ..                          [ 87%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 89%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 92%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 93%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________
tb = <testbook.client.TestbookNotebookClient object at 0x7ff04014cdf0>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:

../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7ff04014cdf0>

cell = {'cell_type': 'code', 'execution_count': 22, 'id': 'f0ddad65', 'metadata': {'execution': {'iopub.status.busy': '2022-1...n the schema"]}], 'source': 'train_dl = mm.Loader(\n    train,\n    batch_size = BATCH_SIZE,\n    shuffle = False \n)'}

cell_index = 43

exec_reply = {'buffers': [], 'content': {'ename': 'ValueError', 'engine_info': {'engine_id': -1, 'engine_uuid': '732c5ca1-9ed3-4ea5...e, 'engine': '732c5ca1-9ed3-4ea5-a844-abf63e349268', 'started': '2022-11-02T23:23:39.655072Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           train_dl = mm.Loader(

E               train,

E               batch_size = BATCH_SIZE,

E               shuffle = False

E           )

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mValueError�[0m                                Traceback (most recent call last)

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E

E           �[0;31mValueError�[0m: Dense column f_47_list_seq doesn't have the max value_count defined in the schema

E           ValueError: Dense column f_47_list_seq doesn't have the max value_count defined in the schema
../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-02 23:23:26.039326: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-02 23:23:29.374053: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-02 23:23:29.374224: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-02 23:23:29.375016: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-02 23:23:29.375073: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-02 23:23:29.375681: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-02 23:23:29.375731: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-02 23:23:29.376348: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-02 23:23:29.376399: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 6 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 119 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 6 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 85 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:960: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 54 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filejkisbaw0.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:614: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     60    24%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    3      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     15    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        145     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         114     10    91%

merlin/models/tf/blocks/optimizer.py                                   173     13    92%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   245     49    80%

merlin/models/tf/core/base.py                                          244     56    77%

merlin/models/tf/core/combinators.py                                   424     54    87%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       288     30    90%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   452     50    89%

merlin/models/tf/loader.py                                             139     33    76%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        707     75    89%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       122     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                425     41    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  107      2    98%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                10772   2135    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 811 passed, 12 skipped, 1347 warnings in 1576.94s (0:26:16) =====

/usr/local/lib/python3.8/dist-packages/coverage/data.py:130: CoverageWarning: Data file '/var/jenkins_home/workspace/merlin_models/models/.coverage.10.20.17.231.2486.432680' doesn't seem to be a coverage data file: cannot unpack non-iterable NoneType object

data._warn(str(exc))

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   test-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins5698725475240031588.sh

nvidia-merlin-bot · 2022-11-03T22:17:36Z

Click to view CI Results

GitHub pull request #845 of commit c1c607d1ac5781a3489f0c0da267577a5f1cef47, no merge conflicts.
Running as SYSTEM
Setting status of c1c607d1ac5781a3489f0c0da267577a5f1cef47 to PENDING with url https://10.20.13.93:8080/job/merlin_models/1733/console and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse c1c607d1ac5781a3489f0c0da267577a5f1cef47^{commit} # timeout=10
Checking out Revision c1c607d1ac5781a3489f0c0da267577a5f1cef47 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f c1c607d1ac5781a3489f0c0da267577a5f1cef47 # timeout=10
Commit message: "Merge branch 'main' into merlin_dataloader"
 > git rev-list --no-walk 7b80215e65ccd58c02210754ab1884aebb52dc9f # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins8379287896847687811.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
test-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+32.gc1c607d1.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
test-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.1,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,boto3==1.24.75,botocore==1.29.1,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.8.2,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@5905283777ff5ebd748a1c91b7c9fde5710ae775,merlin-models==0.9.0+32.gc1c607d1,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.3.2,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.42,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
test-gpu run-test-pre: PYTHONHASHSEED='2143268882'
test-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-uefor8ng
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-uefor8ng
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 563be4bf5ef675940d5fff2b5e4666424a7f7947
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (1.3.5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.2.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (21.3)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (1.10.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.5.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (4.64.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+5.g563be4b) (3.19.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (0.55.1)
Requirement already satisfied: dask>=2022.3.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+5.g563be4b) (2022.3.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.12.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (3.1.2)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/test-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (6.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (5.8.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.4.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (8.1.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/test-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (59.8.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+5.g563be4b) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+5.g563be4b) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+5.g563be4b) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+5.g563be4b) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+5.g563be4b) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-gzvveuzr

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-gzvveuzr

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit 61ca2edae832da4eb2c6b93390c24920e68de1ae

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/test-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+2.g61ca2ed) (0.8.0+5.g563be4b)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (1.3.5)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (2022.3.0)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (1.2.5)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (21.3)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (7.0.0)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (1.10.0)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (2022.5.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (4.64.1)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (3.19.5)

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Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+2.g61ca2ed) (6.0.1)

Building wheels for collected packages: merlin-dataloader

Building wheel for merlin-dataloader (pyproject.toml): started

Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'

Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+2.g61ca2ed-py3-none-any.whl size=31619 sha256=e4436e85c25a45139798a10cb0eec7676c73ba5929660c90a3ec7512c7d05cc1

Stored in directory: /tmp/pip-ephem-wheel-cache-lryotq4w/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1

Successfully built merlin-dataloader

Installing collected packages: merlin-dataloader

Attempting uninstall: merlin-dataloader

Found existing installation: merlin-dataloader 0.0.2+1.g5905283

Uninstalling merlin-dataloader-0.0.2+1.g5905283:

Successfully uninstalled merlin-dataloader-0.0.2+1.g5905283

Successfully installed merlin-dataloader-0.0.2+2.g61ca2ed
[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-k_wugncn

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-k_wugncn

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 8e7edbafd3006f56e73efdc0c01c4445ab57d028

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+3.g8e7edbaf) (1.8.1)

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+3.g8e7edbaf) (0.8.0+5.g563be4b)

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Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/test-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (2.0.1)

Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (4.0.0)

Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+3.g8e7edbaf) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3

[notice] To update, run: pip install --upgrade pip

test-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/test-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 827 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss                              [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py .................................       [ 13%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 17%]

.....................                                                    [ 19%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 19%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 19%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 21%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 21%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 21%]

tests/unit/tf/core/test_aggregation.py .........                         [ 22%]

tests/unit/tf/core/test_base.py ..                                       [ 22%]

tests/unit/tf/core/test_combinators.py s.....................            [ 25%]

tests/unit/tf/core/test_encoder.py ..                                    [ 25%]

tests/unit/tf/core/test_index.py ...                                     [ 26%]

tests/unit/tf/core/test_prediction.py ..                                 [ 26%]

tests/unit/tf/core/test_tabular.py ......                                [ 27%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 27%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 27%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 27%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 27%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 27%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 27%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 28%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 28%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 28%]

[ 28%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 28%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 28%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 29%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 33%]

........                                                                 [ 34%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 36%]

tests/unit/tf/layers/test_queue.py ..............                        [ 38%]

tests/unit/tf/losses/test_losses.py .......................              [ 41%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 41%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 44%]

tests/unit/tf/models/test_base.py s........................              [ 47%]

tests/unit/tf/models/test_benchmark.py ..                                [ 48%]

tests/unit/tf/models/test_ranking.py ..................................  [ 52%]

tests/unit/tf/models/test_retrieval.py ................................. [ 56%]

...........................................                              [ 61%]

tests/unit/tf/outputs/test_base.py ......                                [ 62%]

tests/unit/tf/outputs/test_classification.py ......                      [ 62%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 64%]

tests/unit/tf/outputs/test_regression.py ..                              [ 64%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 65%]

tests/unit/tf/outputs/test_topk.py .                                     [ 65%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 65%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 67%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 68%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 68%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 68%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 69%]

tests/unit/tf/transformers/test_block.py .....................           [ 72%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 73%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 73%]

tests/unit/tf/transforms/test_features.py s............................. [ 77%]

.......................s......                                           [ 80%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 81%]

tests/unit/tf/transforms/test_noise.py .....                             [ 82%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 85%]

tests/unit/tf/utils/test_batch.py ....                                   [ 85%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 86%]

tests/unit/torch/test_public_api.py .                                    [ 86%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 87%]

tests/unit/torch/features/test_continuous.py ..                          [ 87%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 89%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 92%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 93%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________
tb = <testbook.client.TestbookNotebookClient object at 0x7ef9412ba1c0>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:

../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7ef9412ba1c0>

cell = {'cell_type': 'code', 'execution_count': 22, 'id': 'f0ddad65', 'metadata': {'execution': {'iopub.status.busy': '2022-1...n the schema"]}], 'source': 'train_dl = mm.Loader(\n    train,\n    batch_size = BATCH_SIZE,\n    shuffle = False \n)'}

cell_index = 43

exec_reply = {'buffers': [], 'content': {'ename': 'ValueError', 'engine_info': {'engine_id': -1, 'engine_uuid': '235f294f-5259-4645...e, 'engine': '235f294f-5259-4645-80cf-b7d11d67642f', 'started': '2022-11-03T21:59:37.211419Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           train_dl = mm.Loader(

E               train,

E               batch_size = BATCH_SIZE,

E               shuffle = False

E           )

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mValueError�[0m                                Traceback (most recent call last)

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E           File �[0;32m~/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/loader/loader_base.py:104�[0m, in �[0;36mLoaderBase.__init__�[0;34m(self, dataset, batch_size, shuffle, seed_fn, parts_per_chunk, global_size, global_rank, drop_last)�[0m

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E

E           �[0;31mValueError�[0m: Dense column f_47_list_seq doesn't have the max value_count defined in the schema

E           ValueError: Dense column f_47_list_seq doesn't have the max value_count defined in the schema
../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-03 21:59:23.697708: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-03 21:59:27.031552: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-03 21:59:27.031722: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-03 21:59:27.032540: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-03 21:59:27.032599: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-03 21:59:27.033263: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-03 21:59:27.033314: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-03 21:59:27.033957: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-03 21:59:27.034006: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 2 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 26 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_fileeafzyj0h.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     60    24%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    3      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     15    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        145     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         114     10    91%

merlin/models/tf/blocks/optimizer.py                                   173     13    92%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     49    80%

merlin/models/tf/core/base.py                                          244     56    77%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     50    89%

merlin/models/tf/loader.py                                             141     33    77%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        708     75    89%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       122     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                10832   2145    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:62: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:78: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:92: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 814 passed, 12 skipped, 1352 warnings in 1588.73s (0:26:28) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/test-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   test-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins6984541488010699230.sh

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GitHub pull request #845 of commit 315c7d3558486b4c4bfa5a36a7c4ec0683a4b6c8, no merge conflicts.
Running as SYSTEM
Setting status of 315c7d3558486b4c4bfa5a36a7c4ec0683a4b6c8 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1784/ and message: 'Pending'
Using context: Jenkins
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using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
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 > git --version # timeout=10
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 > git rev-parse 315c7d3558486b4c4bfa5a36a7c4ec0683a4b6c8^{commit} # timeout=10
Checking out Revision 315c7d3558486b4c4bfa5a36a7c4ec0683a4b6c8 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 315c7d3558486b4c4bfa5a36a7c4ec0683a4b6c8 # timeout=10
Commit message: "update dressipi notebook"
 > git rev-list --no-walk 5b9cc1e440ec6599522864b1f58880266841612c # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins6119410210928795168.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+38.g315c7d35.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.4,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.4,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+38.g315c7d35,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='661135621'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-9hryxobw
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-9hryxobw
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 64755badd4e5756601f66e7e568201aedb8a4144
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.5.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (1.2.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (1.3.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (1.10.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.3.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (3.19.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (7.0.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (21.3)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.3.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (0.4.3)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.4.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (8.1.3)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (6.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.0.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.0.4)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.8.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (3.1.2)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (65.4.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+7.g64755ba) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-1k4nbr1l

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-1k4nbr1l

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit b6f9a67b2c0caf1b0b1ded10e5491b5a0f13230a

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+3.gb6f9a67) (0.8.0+7.g64755ba)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.5.0)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.5)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (4.64.1)

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Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (6.0.1)

Building wheels for collected packages: merlin-dataloader

Building wheel for merlin-dataloader (pyproject.toml): started

Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'

Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+3.gb6f9a67-py3-none-any.whl size=38322 sha256=dfaabc7e4283398a07f16a9beef915435ae01cdf5a91c55fcf7839e94392f4d6

Stored in directory: /tmp/pip-ephem-wheel-cache-zca90_r_/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1

Successfully built merlin-dataloader

Installing collected packages: merlin-dataloader

Attempting uninstall: merlin-dataloader

Found existing installation: merlin-dataloader 0.0.2

Uninstalling merlin-dataloader-0.0.2:

Successfully uninstalled merlin-dataloader-0.0.2

Successfully installed merlin-dataloader-0.0.2+3.gb6f9a67
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-zmgh93si

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-zmgh93si

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+7.g64755ba)

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Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2+3.gb6f9a67)

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Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)

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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.0.0)

Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 866 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

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tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s........................              [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 66%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

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tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

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tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py .....................           [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

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tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 83%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

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tests/unit/tf/utils/test_tf_utils.py .....                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 87%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

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tests/unit/torch/tabular/test_transformations.py .......                 [ 93%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 27 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file0r_mwldf.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           107     80    25%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        145     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     50    80%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     31    93%

merlin/models/tf/loader.py                                             164     54    67%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        751    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       122     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11018   2202    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 853 passed, 13 skipped, 1431 warnings in 1707.09s (0:28:27) ==========

/usr/local/lib/python3.8/dist-packages/coverage/data.py:130: CoverageWarning: Data file '/var/jenkins_home/workspace/merlin_models/models/.coverage.10.20.17.231.15635.208179' doesn't seem to be a coverage data file: cannot unpack non-iterable NoneType object

data._warn(str(exc))

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py

py38-multi-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+38.g315c7d35.zip

WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.

py38-multi-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.4,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.4,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+38.g315c7d35,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0

py38-multi-gpu run-test-pre: PYTHONHASHSEED='942325990'

py38-multi-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/core.git

Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-jqkt149m

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-jqkt149m

Resolved https://github.com/NVIDIA-Merlin/core.git to commit 64755badd4e5756601f66e7e568201aedb8a4144

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (21.3)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (0.55.1)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (4.64.1)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.5.0)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (3.19.5)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (7.0.0)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (1.10.0)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.3.0)

Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.3.0)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (1.3.5)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (1.2.5)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (0.4.3)

Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.2.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)

Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (0.12.0)

Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.4.1)

Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.8.0)

Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (3.1.2)

Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (8.1.3)

Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.7.0)

Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-multi-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (6.2)

Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.4.0)

Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.0.4)

Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.0.0)

Requirement already satisfied: setuptools in ./.tox/py38-multi-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (65.4.1)

Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (1.20.3)

Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-multi-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (0.38.1)

Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+7.g64755ba) (3.0.9)

Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2022.2.1)

Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2.8.2)

Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.52.0)

Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)

Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (0.2.1)

Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.15.0)

Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.0.1)

Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (6.0.2)

Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (4.1.0)

Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-multi-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.0.1)

Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (4.0.0)

Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-multi-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-80vybjnr

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-80vybjnr

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-multi-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2)

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-multi-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+7.g64755ba)

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (21.3)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.55.1)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.64.1)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.5.0)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (7.0.0)

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-multi-gpu run-test: commands[2] | horovodrun -np 2 sh examples/usecases/multi-gpu/hvd_wrapper.sh python -m pytest -m horovod -rxs tests/unit

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[1,0]:cachedir: .tox/py38-multi-gpu/.pytest_cache

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[1,0]:plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

[1,0]:�[1mcollecting ... �[0m[1,1]:cachedir: .tox/py38-multi-gpu/.pytest_cache

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[1,1]:../../../../../usr/lib/python3/dist-packages/requests/init.py:89

[1,1]:  /usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

[1,1]:    warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "[1,1]:

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

[1,1]:    import imp[1,1]:

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

[1,1]:    'nearest': pil_image.NEAREST,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

[1,1]:    'bilinear': pil_image.BILINEAR,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

[1,1]:    'bicubic': pil_image.BICUBIC,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

[1,1]:    'hamming': pil_image.HAMMING,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

[1,1]:    'box': pil_image.BOX,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

[1,1]:    'lanczos': pil_image.LANCZOS,

[1,1]:

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_dlrm[True]

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_dlrm[False]

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower[1,1]:

[1,1]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

[1,1]:    warnings.warn(

[1,1]:

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,1]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

[1,1]:    warnings.warn([1,1]:

[1,1]:

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,1]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

[1,1]:    warnings.warn([1,1]:

[1,1]:

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,1]:  /tmp/autograph_generated_file7ev93aar.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

[1,1]:    ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)[1,1]:

[1,1]:

[1,1]:-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

[1,1]:�[33m=============== �[32m3 passed�[0m, �[33m�[1m863 deselected�[0m, �[33m�[1m14 warnings�[0m�[33m in 46.69s�[0m�[33m ================�[0m

[1,0]:�[32m.�[0m[1,0]:�[33m                                [100%]�[0m[1,0]:

[1,0]:

[1,0]:�[33m=============================== warnings summary ===============================�[0m

[1,0]:../../../../../usr/lib/python3/dist-packages/requests/init.py:89

[1,0]:  /usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

[1,0]:    warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

[1,0]:    import imp[1,0]:

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

[1,0]:    'nearest': pil_image.NEAREST,

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

[1,0]:    'bilinear': pil_image.BILINEAR,

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

[1,0]:    'bicubic': pil_image.BICUBIC,

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

[1,0]:    'hamming': pil_image.HAMMING,

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

[1,0]:    'box': pil_image.BOX,

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

[1,0]:    'lanczos': pil_image.LANCZOS,[1,0]:

[1,0]:

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_dlrm[True]

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_dlrm[False]

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

[1,0]:    warnings.warn(

[1,0]:

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

[1,0]:    warnings.warn(

[1,0]:

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

[1,0]:    warnings.warn(

[1,0]:

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:  /tmp/autograph_generated_file_qwss7xj.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

[1,0]:    ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

[1,0]:

[1,0]:-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

[1,0]:�[33m=============== �[32m3 passed�[0m, �[33m�[1m863 deselected�[0m, �[33m�[1m16 warnings�[0m�[33m in 51.31s�[0m�[33m ================�[0m

___________________________________ summary ____________________________________

py38-multi-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins11033541701623826737.sh

nvidia-merlin-bot · 2022-11-09T05:34:07Z

Click to view CI Results

GitHub pull request #845 of commit 00ca57bf3f7efc1f6b476beaf921ce9ee7769ffd, no merge conflicts.
Running as SYSTEM
Setting status of 00ca57bf3f7efc1f6b476beaf921ce9ee7769ffd to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1785/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 00ca57bf3f7efc1f6b476beaf921ce9ee7769ffd^{commit} # timeout=10
Checking out Revision 00ca57bf3f7efc1f6b476beaf921ce9ee7769ffd (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 00ca57bf3f7efc1f6b476beaf921ce9ee7769ffd # timeout=10
Commit message: "Merge branch 'main' into merlin_dataloader"
 > git rev-list --no-walk 315c7d3558486b4c4bfa5a36a7c4ec0683a4b6c8 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins2491821936732513099.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
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Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+42.g00ca57bf.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.4,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.4,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader @ git+https://github.com/NVIDIA-Merlin/dataloader.git@b6f9a67b2c0caf1b0b1ded10e5491b5a0f13230a,merlin-models==0.9.0+42.g00ca57bf,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2053624642'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-k7px4k7h
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-k7px4k7h
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 64755badd4e5756601f66e7e568201aedb8a4144
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (0.55.1)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (1.10.0)
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Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (7.0.0)
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Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.0.4)
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Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (6.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.8.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.0.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (3.1.2)
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Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (65.4.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+7.g64755ba) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2022.2.1)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)
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Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (6.0.2)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-v1eaamsm

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-v1eaamsm

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit b6f9a67b2c0caf1b0b1ded10e5491b5a0f13230a

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+3.gb6f9a67) (0.8.0+7.g64755ba)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.55.1)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.10.0)

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Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (3.19.5)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.3.5)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.5.0)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.3.0)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (7.0.0)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.5)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.0)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.4.3)

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Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (5.4.1)

Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.2.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.0)

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Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.7.0)

Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.4.0)

Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (6.2)

Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (5.8.0)

Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.0.0)

Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (3.1.2)

Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (8.1.3)

Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.20.3)

Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.38.1)

Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (65.4.1)

Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (3.0.9)

Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.8.2)

Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.2.1)

Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.0)

Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.52.0)

Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.2.1)

Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.15.0)

Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.0.1)

Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (4.1.0)

Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (6.0.2)

Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.0.1)

Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (4.0.0)

Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-igvy8n2h

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-igvy8n2h

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+7.g64755ba)

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2+3.gb6f9a67)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.55.1)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.10.0)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (21.3)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.64.1)

Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.3.5)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.5.0)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (7.0.0)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.5)

Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+4.gba4c1415) (1.20.3)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.4.3)

Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.12.0)

Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (5.4.1)

Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.2.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)

Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.0.4)

Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.7.0)

Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.4.0)

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Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.0.0)

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Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (8.1.3)

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Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.0.9)

Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2.8.2)

Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.2.1)

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Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.52.0)

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Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 867 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

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tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 67%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 70%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py .....................           [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 78%]

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tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 83%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 86%]

tests/unit/tf/utils/test_batch.py ....                                   [ 86%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file2ny2oxln.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           107     80    25%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        145     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     50    80%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       170     29    83%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     31    93%

merlin/models/tf/loader.py                                             164     54    67%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        753    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        97      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11021   2202    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 854 passed, 13 skipped, 1433 warnings in 1690.78s (0:28:10) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py

py38-multi-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+42.g00ca57bf.zip

WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.

py38-multi-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.4,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.4,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+42.g00ca57bf,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0

py38-multi-gpu run-test-pre: PYTHONHASHSEED='1945474422'

py38-multi-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/core.git

Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-4lmtlsr5

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-4lmtlsr5

Resolved https://github.com/NVIDIA-Merlin/core.git to commit 64755badd4e5756601f66e7e568201aedb8a4144

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (7.0.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (4.64.1)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (1.2.5)

Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.3.0)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (3.19.5)

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Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (2022.5.0)

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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+7.g64755ba) (21.3)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+7.g64755ba) (1.3.5)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+7.g64755ba) (0.4.3)

Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (0.12.0)

Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.2.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.2.0)

Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.4.1)

Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (2.0.0)

Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (1.0.4)

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Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (3.1.2)

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Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+7.g64755ba) (5.8.0)

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Requirement already satisfied: setuptools in ./.tox/py38-multi-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+7.g64755ba) (65.4.1)

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Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2022.2.1)

Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+7.g64755ba) (2.8.2)

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-multi-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-ye0iu8b4

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-ye0iu8b4

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-multi-gpu run-test: commands[2] | horovodrun -np 2 sh examples/usecases/multi-gpu/hvd_wrapper.sh python -m pytest -m horovod -rxs tests/unit

[1,0]:�[1m============================= test session starts ==============================�[0m

[1,0]:platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

[1,1]:�[1m============================= test session starts ==============================�[0m

[1,1]:platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

[1,1]:cachedir: .tox/py38-multi-gpu/.pytest_cache

[1,1]:rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

[1,1]:plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

[1,0]:cachedir: .tox/py38-multi-gpu/.pytest_cache

[1,0]:rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

[1,0]:plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

[1,1]:�[1mcollecting ... �[0m[1,0]:�[1mcollecting ... �[0m[1,0]:�[1m

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[1,1]:tests/unit/tf/horovod/test_horovod.py [1,1]:�[32m.�[0m[1,0]:�[32m.�[0m[1,1]:�[32m.�[0m[1,0]:�[32m.�[0m[1,1]:�[32m.�[0m[1,1]:�[33m                                [100%]�[0m[1,1]:

[1,1]:

[1,1]:�[33m=============================== warnings summary ===============================�[0m

[1,1]:../../../../../usr/lib/python3/dist-packages/requests/init.py:89

[1,1]:  /usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

[1,1]:    warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

[1,1]:    import imp

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

[1,1]:    'nearest': pil_image.NEAREST,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

[1,1]:    'bilinear': pil_image.BILINEAR,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

[1,1]:    'bicubic': pil_image.BICUBIC,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

[1,1]:    'hamming': pil_image.HAMMING,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

[1,1]:    'box': pil_image.BOX,

[1,1]:

[1,1]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

[1,1]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

[1,1]:    'lanczos': pil_image.LANCZOS,

[1,1]:

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_dlrm[True]

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_dlrm[False]

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,1]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

[1,1]:    warnings.warn([1,1]:

[1,1]:

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,1]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

[1,1]:    warnings.warn([1,1]:

[1,1]:

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,1]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

[1,1]:    warnings.warn(

[1,1]:

[1,1]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,1]:  /tmp/autograph_generated_fileeji1ia9c.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

[1,1]:    ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)

[1,1]:

[1,1]:-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

[1,1]:�[33m=============== �[32m3 passed�[0m, �[33m�[1m864 deselected�[0m, �[33m�[1m14 warnings�[0m�[33m in 46.74s�[0m�[33m ================�[0m

[1,0]:�[32m.�[0m[1,0]:�[33m                                [100%]�[0m[1,0]:

[1,0]:

[1,0]:�[33m=============================== warnings summary ===============================�[0m

[1,0]:../../../../../usr/lib/python3/dist-packages/requests/init.py:89

[1,0]:  /usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

[1,0]:    warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "[1,0]:

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

[1,0]:    import imp[1,0]:

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

[1,0]:    'nearest': pil_image.NEAREST,[1,0]:

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

[1,0]:    'bilinear': pil_image.BILINEAR,[1,0]:

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

[1,0]:    'bicubic': pil_image.BICUBIC,[1,0]:

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

[1,0]:    'hamming': pil_image.HAMMING,[1,0]:

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

[1,0]:    'box': pil_image.BOX,[1,0]:

[1,0]:

[1,0]:../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

[1,0]:  /var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

[1,0]:    'lanczos': pil_image.LANCZOS,[1,0]:

[1,0]:

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_dlrm[True]

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_dlrm[False]

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

[1,0]:    warnings.warn(

[1,0]:

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

[1,0]:    warnings.warn(

[1,0]:

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:  /var/jenkins_home/workspace/merlin_models/models/.tox/py38-multi-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

[1,0]:    warnings.warn(

[1,0]:

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:tests/unit/tf/horovod/test_horovod.py::test_horovod_multigpu_two_tower

[1,0]:  /tmp/autograph_generated_filehuqwov8i.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

[1,0]:    ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)[1,0]:

[1,0]:

[1,0]:-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html

[1,0]:�[33m=============== �[32m3 passed�[0m, �[33m�[1m864 deselected�[0m, �[33m�[1m16 warnings�[0m�[33m in 51.34s�[0m�[33m ================�[0m

___________________________________ summary ____________________________________

py38-multi-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins11459271463050577991.sh

nvidia-merlin-bot · 2022-11-09T18:42:49Z

Click to view CI Results

GitHub pull request #845 of commit 1c2d424c60bf01e909b10eb15d0a523d6045d933, no merge conflicts.
Running as SYSTEM
Setting status of 1c2d424c60bf01e909b10eb15d0a523d6045d933 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1796/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 1c2d424c60bf01e909b10eb15d0a523d6045d933^{commit} # timeout=10
Checking out Revision 1c2d424c60bf01e909b10eb15d0a523d6045d933 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 1c2d424c60bf01e909b10eb15d0a523d6045d933 # timeout=10
Commit message: "Merge branch 'main' into merlin_dataloader"
 > git rev-list --no-walk 3accd0dea116c78a0e65a70b5f8aedbe132819f9 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins16426436830067624676.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+45.g1c2d424c.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.5,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.5,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+45.g1c2d424c,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='786117897'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-e_fnr6z9
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-e_fnr6z9
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit c1ddc198bc1b0c39b5008a4ec07f2b7f02fd22c1
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.3.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (0.55.1)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.2.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.10.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (7.0.0)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (3.19.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.5.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (4.64.1)
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Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (6.0.2)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-bcipqy1v

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-bcipqy1v

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit b6f9a67b2c0caf1b0b1ded10e5491b5a0f13230a

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+3.gb6f9a67) (0.8.0+8.gc1ddc19)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.3.5)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.55.1)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.5)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.10.0)

Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.3.0)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (3.19.5)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (7.0.0)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.5.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (4.64.1)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.3.0)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (21.3)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.0)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.4.3)

Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (5.4.1)

Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.12.0)

Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.2.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.0)

Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.4.0)

Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.0.4)

Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (5.8.0)

Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.0.0)

Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (3.1.2)

Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (8.1.3)

Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.7.0)

Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (6.2)

Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.38.1)

Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.20.3)

Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (65.4.1)

Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (3.0.9)

Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.2.1)

Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.8.2)

Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.52.0)

Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.2.0)

Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.2.1)

Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.15.0)

Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.0.1)

Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (4.1.0)

Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (6.0.2)

Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2.0.1)

Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (4.0.0)

Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-p7ztvtpt

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-p7ztvtpt

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+8.gc1ddc19)

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2+3.gb6f9a67)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.3.5)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.55.1)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.5)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.10.0)

Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (7.0.0)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.5.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.64.1)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (21.3)

Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+4.gba4c1415) (1.20.3)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.4.3)

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 867 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

...........................................                              [ 63%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 67%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 70%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py .....................           [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 78%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 83%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 86%]

tests/unit/tf/utils/test_batch.py ....                                   [ 86%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________
tb = <testbook.client.TestbookNotebookClient object at 0x7fbdb0d80700>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:

../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7fbdb0d80700>

cell = {'cell_type': 'code', 'execution_count': 15, 'id': '65f5c222', 'metadata': {'execution': {'iopub.status.busy': '2022-1...train/"), output_files=10)\nworkflow.transform(valid).to_parquet(os.path.join(DATA_FOLDER, "valid/"), output_files=1)'}

cell_index = 29

exec_reply = {'buffers': [], 'content': {'ename': 'TypeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '240ddf7b-0cf0-42b7-...e, 'engine': '240ddf7b-0cf0-42b7-9736-4e17de762625', 'started': '2022-11-09T18:23:42.827599Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           # fit data

E           workflow.fit(train)

E

E           # transform and save data

E           workflow.transform(train).to_parquet(os.path.join(DATA_FOLDER, "train/"), output_files=10)

E           workflow.transform(valid).to_parquet(os.path.join(DATA_FOLDER, "valid/"), output_files=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mTypeError�[0m                                 Traceback (most recent call last)

E           Cell �[0;32mIn [15], line 2�[0m

E           �[1;32m      1�[0m �[38;5;66;03m# fit data�[39;00m

E           �[0;32m----> 2�[0m �[43mworkflow�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mtrain�[49m�[43m)�[49m

E           �[1;32m      4�[0m �[38;5;66;03m# transform and save data�[39;00m

E           �[1;32m      5�[0m workflow�[38;5;241m.�[39mtransform(train)�[38;5;241m.�[39mto_parquet(os�[38;5;241m.�[39mpath�[38;5;241m.�[39mjoin(DATA_FOLDER, �[38;5;124m"�[39m�[38;5;124mtrain/�[39m�[38;5;124m"�[39m), output_files�[38;5;241m=�[39m�[38;5;241m10�[39m)

E

E           File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/nvtabular/workflow/workflow.py:198�[0m, in �[0;36mWorkflow.fit�[0;34m(self, dataset)�[0m

E           �[1;32m    194�[0m �[38;5;28;01mif�[39;00m �[38;5;129;01mnot�[39;00m current_phase:

E           �[1;32m    195�[0m     �[38;5;66;03m# this shouldn't happen, but lets not infinite loop just in case�[39;00m

E           �[1;32m    196�[0m     �[38;5;28;01mraise�[39;00m �[38;5;167;01mRuntimeError�[39;00m(�[38;5;124m"�[39m�[38;5;124mfailed to find dependency-free StatOperator to fit�[39m�[38;5;124m"�[39m)

E           �[0;32m--> 198�[0m �[38;5;28;43mself�[39;49m�[38;5;241;43m.�[39;49m�[43mexecutor�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mddf�[49m�[43m,�[49m�[43m �[49m�[43mcurrent_phase�[49m�[43m)�[49m

E           �[1;32m    200�[0m �[38;5;66;03m# Remove all the operators we processed in this phase, and remove�[39;00m

E           �[1;32m    201�[0m �[38;5;66;03m# from the dependencies of other ops too�[39;00m

E           �[1;32m    202�[0m �[38;5;28;01mfor�[39;00m node �[38;5;129;01min�[39;00m current_phase:

E

E           File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/dag/executors.py:329�[0m, in �[0;36mDaskExecutor.fit�[0;34m(self, ddf, nodes)�[0m

E           �[1;32m    321�[0m transformed_ddf �[38;5;241m=�[39m �[38;5;28mself�[39m�[38;5;241m.�[39mtransform(

E           �[1;32m    322�[0m     ddf,

E           �[1;32m    323�[0m     node�[38;5;241m.�[39mparents_with_dependencies,

E           �[1;32m    324�[0m     additional_columns�[38;5;241m=�[39maddl_input_cols,

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E           �[1;32m    326�[0m )

E           �[1;32m    328�[0m �[38;5;28;01mtry�[39;00m:

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E

E           File �[0;32m~/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/nvtabular/ops/value_counts.py:39�[0m, in �[0;36mValueCount.fit�[0;34m(self, col_selector, ddf)�[0m

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-09 18:23:37.320142: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-09 18:23:40.678179: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-09 18:23:40.678291: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-09 18:23:40.679095: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-09 18:23:40.679155: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-09 18:23:40.679729: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-09 18:23:40.679779: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-09 18:23:40.680372: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-09 18:23:40.680423: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filecf1_0lao.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           107     80    25%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        145     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     50    89%

merlin/models/tf/loader.py                                             164     54    67%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        753    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11027   2249    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 853 passed, 13 skipped, 1433 warnings in 1668.28s (0:27:48) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins1664738635859814290.sh

nvidia-merlin-bot · 2022-11-09T19:12:12Z

Click to view CI Results

GitHub pull request #845 of commit 3e6bf948af88686fca0fed0b9adba0e7228ef9d9, no merge conflicts.
Running as SYSTEM
Setting status of 3e6bf948af88686fca0fed0b9adba0e7228ef9d9 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1797/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 3e6bf948af88686fca0fed0b9adba0e7228ef9d9^{commit} # timeout=10
Checking out Revision 3e6bf948af88686fca0fed0b9adba0e7228ef9d9 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 3e6bf948af88686fca0fed0b9adba0e7228ef9d9 # timeout=10
Commit message: "minor clean up"
 > git rev-list --no-walk 1c2d424c60bf01e909b10eb15d0a523d6045d933 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins7981518897766938339.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu inst-nodeps: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/2/merlin-models-0.9.0+46.g3e6bf948.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.5,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.5,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+46.g3e6bf948,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.982,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.2.1,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.0,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='982519330'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-lxnfb4kp
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-lxnfb4kp
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit c1ddc198bc1b0c39b5008a4ec07f2b7f02fd22c1
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.3.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.10.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (4.64.1)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (0.55.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.3.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (7.0.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (2022.5.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (21.3)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (3.19.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.2.5)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (0.4.3)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (5.4.1)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (5.8.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.4.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (3.1.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (8.1.3)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.0.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.0.4)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (6.2)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+8.gc1ddc19) (65.4.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+8.gc1ddc19) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+8.gc1ddc19) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+8.gc1ddc19) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+8.gc1ddc19) (6.0.1)
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-291jjyph

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-291jjyph

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit b6f9a67b2c0caf1b0b1ded10e5491b5a0f13230a

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+3.gb6f9a67) (0.8.0+8.gc1ddc19)

Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.3.0)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.10.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (4.64.1)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (0.55.1)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.5.0)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (2022.3.0)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (1.3.5)

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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+3.gb6f9a67) (21.3)

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-menlibda

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-menlibda

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

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[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 867 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 22%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py F         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

...........................................                              [ 63%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 67%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 70%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py .....................           [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 78%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 83%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 86%]

tests/unit/tf/utils/test_batch.py ....                                   [ 86%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=================================== FAILURES ===================================

_____________________ test_usecase_ecommerce_session_based _____________________
tb = <testbook.client.TestbookNotebookClient object at 0x7f3ad18f0610>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_ecommerce_session_based(tb):
    tb.inject(
        """
        import os
        from unittest.mock import patch
        from merlin.datasets.synthetic import generate_data
        mock_train, mock_valid = generate_data(
            input="dressipi2022-preprocessed",
            num_rows=10000,
            set_sizes=(0.8, 0.2)
        )
        p1 = patch(
            "merlin.datasets.ecommerce.get_dressipi2022",
            return_value=[mock_train, mock_valid]
        )
        p1.start()
        os.environ["DATA_FOLDER"] = "/tmp/dressipi2022/"
        os.environ["EPOCHS"] = "1"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_ecommerce_session_based.py:35:

../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7f3ad18f0610>

cell = {'cell_type': 'code', 'execution_count': 15, 'id': '65f5c222', 'metadata': {'execution': {'iopub.status.busy': '2022-1...train/"), output_files=10)\nworkflow.transform(valid).to_parquet(os.path.join(DATA_FOLDER, "valid/"), output_files=1)'}

cell_index = 29

exec_reply = {'buffers': [], 'content': {'ename': 'TypeError', 'engine_info': {'engine_id': -1, 'engine_uuid': '2a12d5cc-c03b-4733-...e, 'engine': '2a12d5cc-c03b-4733-b48a-6ac7847ec1fc', 'started': '2022-11-09T18:52:43.014335Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           # fit data

E           workflow.fit(train)

E

E           # transform and save data

E           workflow.transform(train).to_parquet(os.path.join(DATA_FOLDER, "train/"), output_files=10)

E           workflow.transform(valid).to_parquet(os.path.join(DATA_FOLDER, "valid/"), output_files=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mTypeError�[0m                                 Traceback (most recent call last)

E           Cell �[0;32mIn [15], line 2�[0m

E           �[1;32m      1�[0m �[38;5;66;03m# fit data�[39;00m

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E           File �[0;32m~/.local/lib/python3.8/site-packages/dask/local.py:554�[0m, in �[0;36mget_sync�[0;34m(dsk, keys, **kwargs)�[0m

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../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-11-09 18:52:37.527896: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-11-09 18:52:40.891400: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-11-09 18:52:40.891498: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-11-09 18:52:40.892283: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-11-09 18:52:40.892344: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 14500 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-11-09 18:52:40.893004: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-11-09 18:52:40.893053: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 14500 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-11-09 18:52:40.893679: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-11-09 18:52:40.893728: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 14500 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_file2o3emtbj.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           107     80    25%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        141     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     20    67%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     50    89%

merlin/models/tf/loader.py                                             165     54    67%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        753    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     42    90%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11024   2249    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 1 failed, 853 passed, 13 skipped, 1433 warnings in 1698.67s (0:28:18) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins12215478256879323390.sh

nvidia-merlin-bot · 2022-11-10T15:24:43Z

Click to view CI Results

GitHub pull request #845 of commit e51835e55c2f27ee2ed72d57fc72dfd693793d8f, no merge conflicts.
Running as SYSTEM
Setting status of e51835e55c2f27ee2ed72d57fc72dfd693793d8f to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1810/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse e51835e55c2f27ee2ed72d57fc72dfd693793d8f^{commit} # timeout=10
Checking out Revision e51835e55c2f27ee2ed72d57fc72dfd693793d8f (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f e51835e55c2f27ee2ed72d57fc72dfd693793d8f # timeout=10
Commit message: "Update tox to not use sitepackages"
 > git rev-list --no-walk 5e4094e670a6679b61dc04fbb566bccd84ec1374 # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins15599502018102469546.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+47.ge51835e5.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.6,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.6,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2022.9.24,cffi==1.15.1,charset-normalizer==2.1.1,check-manifest==0.48,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,docker-pycreds==0.4.0,docutils==0.16,entrypoints==0.4,exceptiongroup==1.0.1,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==3.4,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==8.0.2,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==3.0.3,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+47.ge51835e5,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.990,mypy-extensions==0.4.3,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular==1.4.0+8.g95e12d347,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.28.1,requests-oauthlib==1.3.1,rsa==4.7.2,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.16.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,tabulate==0.8.10,tblib==1.7.0,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==4.0.3,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3811903611'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-864mctab
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-864mctab
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit c1ddc198bc1b0c39b5008a4ec07f2b7f02fd22c1
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: tqdm>=4.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (4.64.1)
Requirement already satisfied: packaging in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (21.3)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-core==0.8.0+8.gc1ddc19) (1.10.0)
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Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+8.gc1ddc19-py3-none-any.whl size=118556 sha256=d90ef5f4ee94e9b49bb1ab59c186d2ffd8d5a2d2b2bc835089f6fcaed85f8b5e
  Stored in directory: /tmp/pip-ephem-wheel-cache-rwn6gx19/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.8.0
    Uninstalling merlin-core-0.8.0:
      Successfully uninstalled merlin-core-0.8.0
Successfully installed merlin-core-0.8.0+8.gc1ddc19
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-2eawtua4

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-2eawtua4

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit db6a1fe5d000c4c5ebe37ad04db188964da2657d

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+4.gdb6a1fe) (0.8.0+8.gc1ddc19)

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Requirement already satisfied: hyperframe<7,>=6.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (6.0.1)

Requirement already satisfied: hpack<5,>=4.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (4.0.0)

Building wheels for collected packages: merlin-dataloader

Building wheel for merlin-dataloader (pyproject.toml): started

Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'

Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+4.gdb6a1fe-py3-none-any.whl size=37916 sha256=3b09f2ce102b629c8a461ec7f70c5fbfd15d14f7cb50b8803bdf6a057b02ae19

Stored in directory: /tmp/pip-ephem-wheel-cache-7bhex3pi/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1

Successfully built merlin-dataloader

Installing collected packages: merlin-dataloader

Attempting uninstall: merlin-dataloader

Found existing installation: merlin-dataloader 0.0.2

Uninstalling merlin-dataloader-0.0.2:

Successfully uninstalled merlin-dataloader-0.0.2

Successfully installed merlin-dataloader-0.0.2+4.gdb6a1fe
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-x56zio5u

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-x56zio5u

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+8.gc1ddc19)

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Building wheels for collected packages: nvtabular

Building wheel for nvtabular (pyproject.toml): started

Building wheel for nvtabular (pyproject.toml): finished with status 'done'

Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257596 sha256=e4ecec7c641c29d98e757b23d64770f462f9416283d5963eff8fcf57924058da

Stored in directory: /tmp/pip-ephem-wheel-cache-t42ycocw/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b

Successfully built nvtabular

Installing collected packages: nvtabular

Successfully installed nvtabular-1.6.0+4.gba4c1415
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.2.0, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.6.2, xdist-3.0.2, cov-4.0.0

collected 783 items / 18 skipped
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py .....s                             [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  9%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 14%]

............................                                             [ 18%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 22%]

.....................                                                    [ 25%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 25%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 25%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 26%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 27%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 27%]

tests/unit/tf/core/test_aggregation.py .........                         [ 28%]

tests/unit/tf/core/test_base.py ..                                       [ 28%]

tests/unit/tf/core/test_combinators.py s.....................            [ 31%]

tests/unit/tf/core/test_encoder.py ..                                    [ 31%]

tests/unit/tf/core/test_index.py ...                                     [ 32%]

tests/unit/tf/core/test_prediction.py ..                                 [ 32%]

tests/unit/tf/core/test_tabular.py ......                                [ 33%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 33%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 33%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 33%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 33%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 33%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 33%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 33%]

[ 33%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code -15 (SIGTERM)) (exited with code -15)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build was aborted

Aborted by �[8mha:////4I6AZwo/1Z8Fal8AhZTEatjIwqNwCcqT21311HdysuK+AAAAlx+LCAAAAAAAAP9b85aBtbiIQTGjNKU4P08vOT+vOD8nVc83PyU1x6OyILUoJzMv2y+/JJUBAhiZGBgqihhk0NSjKDWzXb3RdlLBUSYGJk8GtpzUvPSSDB8G5tKinBIGIZ+sxLJE/ZzEvHT94JKizLx0a6BxUmjGOUNodHsLgAzWEgZu/dLi1CL9xJTczDwAj6GcLcAAAAA=�[0madmin

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins8342089040871753891.sh

nvidia-merlin-bot · 2022-11-10T15:24:57Z

Click to view CI Results

GitHub pull request #845 of commit 3e6bf948af88686fca0fed0b9adba0e7228ef9d9, no merge conflicts.
Running as SYSTEM
Setting status of 3e6bf948af88686fca0fed0b9adba0e7228ef9d9 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1811/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 3e6bf948af88686fca0fed0b9adba0e7228ef9d9^{commit} # timeout=10
Checking out Revision 3e6bf948af88686fca0fed0b9adba0e7228ef9d9 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 3e6bf948af88686fca0fed0b9adba0e7228ef9d9 # timeout=10
Commit message: "minor clean up"
 > git rev-list --no-walk e51835e55c2f27ee2ed72d57fc72dfd693793d8f # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins8004953083712006905.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
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Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
ERROR: invocation failed (exit code -15), logfile: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/log/py38-gpu-1.log
================================== log start ===================================
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: tensorflow<2.10 in /var/jenkins_home/.local/lib/python3.8/site-packages (2.9.2)
Collecting bokeh
  Downloading bokeh-3.0.1-py3-none-any.whl (16.4 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 16.4/16.4 MB 78.8 MB/s eta 0:00:00
Collecting check-manifest
  Downloading check_manifest-0.48-py3-none-any.whl (20 kB)
Requirement already satisfied: pytest>=5 in /usr/local/lib/python3.8/dist-packages (from -r requirements/dev.txt (line 4)) (7.1.3)
Requirement already satisfied: pytest-cov>=2 in /usr/local/lib/python3.8/dist-packages (from -r requirements/dev.txt (line 5)) (4.0.0)
Requirement already satisfied: pytest-xdist in /usr/local/lib/python3.8/dist-packages (from -r requirements/dev.txt (line 6)) (3.0.2)
Collecting black==20.8b1
  Downloading black-20.8b1.tar.gz (1.1 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.1/1.1 MB 104.8 MB/s eta 0:00:00
  Installing build dependencies: started
  Installing build dependencies: finished with status 'error'
=================================== log end ====================================

ERROR: could not install deps [-rrequirements/dev.txt, tensorflow<2.10]; v = InvocationError("/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pip install -rrequirements/dev.txt 'tensorflow<2.10'", -15)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: could not install deps [-rrequirements/dev.txt, tensorflow<2.10]; v = InvocationError("/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pip install -rrequirements/dev.txt 'tensorflow<2.10'", -15)

Terminated

Build was aborted

Aborted by �[8mha:////4I6AZwo/1Z8Fal8AhZTEatjIwqNwCcqT21311HdysuK+AAAAlx+LCAAAAAAAAP9b85aBtbiIQTGjNKU4P08vOT+vOD8nVc83PyU1x6OyILUoJzMv2y+/JJUBAhiZGBgqihhk0NSjKDWzXb3RdlLBUSYGJk8GtpzUvPSSDB8G5tKinBIGIZ+sxLJE/ZzEvHT94JKizLx0a6BxUmjGOUNodHsLgAzWEgZu/dLi1CL9xJTczDwAj6GcLcAAAAA=�[0madmin

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins12203130265373546083.sh

nvidia-merlin-bot · 2022-11-10T18:25:53Z

Click to view CI Results

GitHub pull request #845 of commit d9f76d5f4050f8704f8f35289b7212317da39acc, no merge conflicts.
Running as SYSTEM
Setting status of d9f76d5f4050f8704f8f35289b7212317da39acc to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1816/ and message: 'Pending'
Using context: Jenkins
Building on master in workspace /var/jenkins_home/workspace/merlin_models
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse d9f76d5f4050f8704f8f35289b7212317da39acc^{commit} # timeout=10
Checking out Revision d9f76d5f4050f8704f8f35289b7212317da39acc (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f d9f76d5f4050f8704f8f35289b7212317da39acc # timeout=10
Commit message: "Merge branch 'main' into merlin_dataloader"
 > git rev-list --no-walk ffee2b01b8a2c95d033bcdc86d1fb0ea00afc3fe # timeout=10
[merlin_models] $ /bin/bash /tmp/jenkins4467337148887619415.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/3/merlin-models-0.9.0+48.gd9f76d5f.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.6,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.1,boto3==1.24.75,botocore==1.29.6,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.0.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.5.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==5.0.4,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.3,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.2,merlin-models==0.9.0+48.gd9f76d5f,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.990,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,nvtabular @ git+https://github.com/NVIDIA-Merlin/NVTabular.git@ba4c14159a8e858c8998d4158a4376e65a8fa266,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.1,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.9.1,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==2.5.0,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.43,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,tensorflow-ranking==0.5.1,tensorflow-serving-api==2.9.2,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='465849412'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-yai9lfju
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-yai9lfju
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 1d9d3542725badd7c337bd2a7e47c4327ebb684c
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+10.g1d9d354) (7.0.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+10.g1d9d354) (1.3.5)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+10.g1d9d354) (1.2.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+10.g1d9d354) (3.19.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+10.g1d9d354) (0.55.1)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+10.g1d9d354) (2022.3.0)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+10.g1d9d354) (2022.5.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+10.g1d9d354) (4.64.1)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+10.g1d9d354) (21.3)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.8.0+10.g1d9d354) (2022.3.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.8.0+10.g1d9d354) (1.10.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+10.g1d9d354) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.8.0+10.g1d9d354) (1.2.0)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (2.2.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (1.0.4)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (6.2)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (1.7.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (2.0.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (3.1.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (8.1.3)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (5.8.0)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+10.g1d9d354) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+10.g1d9d354) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.8.0+10.g1d9d354) (65.4.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.8.0+10.g1d9d354) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+10.g1d9d354) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+10.g1d9d354) (2.8.2)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+10.g1d9d354) (1.2.0)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.8.0+10.g1d9d354) (1.52.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.8.0+10.g1d9d354) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+10.g1d9d354) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.8.0+10.g1d9d354) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.8.0+10.g1d9d354) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+10.g1d9d354) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.8.0+10.g1d9d354) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.8.0+10.g1d9d354-py3-none-any.whl size=118620 sha256=7cb2dd8f0a5b4dfd3e17966ea54ec67cfed93357d861422fee4fb2da996e55db
  Stored in directory: /tmp/pip-ephem-wheel-cache-f2242rtf/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.8.0+10.g1d9d354
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git

Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-t5pftol9

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-t5pftol9

Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit db6a1fe5d000c4c5ebe37ad04db188964da2657d

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+4.gdb6a1fe) (0.8.0+10.g1d9d354)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (7.0.0)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.3.5)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.2.5)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (3.19.5)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (0.55.1)

Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2022.3.0)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2022.5.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (4.64.1)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (21.3)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2022.3.0)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.10.0)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (0.4.3)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.2.0)

Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (0.12.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.2.0)

Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (5.4.1)

Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2.2.0)

Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.0.4)

Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2.4.0)

Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (6.2)

Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.7.0)

Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2.0.0)

Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (3.1.2)

Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (8.1.3)

Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (5.8.0)

Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.20.3)

Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (0.38.1)

Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (65.4.1)

Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (3.0.9)

Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2022.2.1)

Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2.8.2)

Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.2.0)

Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.52.0)

Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (0.2.1)

Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.15.0)

Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (1.0.1)

Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (4.1.0)

Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (6.0.2)

Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (2.0.1)

Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (4.0.0)

Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core->merlin-dataloader==0.0.2+4.gdb6a1fe) (6.0.1)

Building wheels for collected packages: merlin-dataloader

Building wheel for merlin-dataloader (pyproject.toml): started

Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'

Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+4.gdb6a1fe-py3-none-any.whl size=38323 sha256=3fa5d3047f86ec925820559077bb67dcc24cdfca210a1559a7202e967f2e892f

Stored in directory: /tmp/pip-ephem-wheel-cache-6uixp9ha/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1

Successfully built merlin-dataloader

Installing collected packages: merlin-dataloader

Attempting uninstall: merlin-dataloader

Found existing installation: merlin-dataloader 0.0.2

Not uninstalling merlin-dataloader at /usr/local/lib/python3.8/dist-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu

Can't uninstall 'merlin-dataloader'. No files were found to uninstall.

Successfully installed merlin-dataloader-0.0.2+4.gdb6a1fe
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git

Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com

Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git

Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-h3o9zejs

Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-h3o9zejs

Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ba4c14159a8e858c8998d4158a4376e65a8fa266

Installing build dependencies: started

Installing build dependencies: finished with status 'done'

Getting requirements to build wheel: started

Getting requirements to build wheel: finished with status 'done'

Preparing metadata (pyproject.toml): started

Preparing metadata (pyproject.toml): finished with status 'done'

Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.8.0+10.g1d9d354)

Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+4.gba4c1415) (0.0.2+4.gdb6a1fe)

Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+4.gba4c1415) (1.8.1)

Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (7.0.0)

Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.3.5)

Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.5)

Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (3.19.5)

Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.55.1)

Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)

Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.5.0)

Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (4.64.1)

Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (21.3)

Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (2022.3.0)

Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.10.0)

Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+4.gba4c1415) (1.20.3)

Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.4.3)

Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)

Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (0.12.0)

Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (1.2.0)

Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+4.gba4c1415) (5.4.1)

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Building wheels for collected packages: nvtabular

Building wheel for nvtabular (pyproject.toml): started

Building wheel for nvtabular (pyproject.toml): finished with status 'done'

Created wheel for nvtabular: filename=nvtabular-1.6.0+4.gba4c1415-cp38-cp38-linux_x86_64.whl size=257746 sha256=ce84329f6e8f5846b1698c19dae48f09b36d3313b62dfdfe6f6343dc88ba825e

Stored in directory: /tmp/pip-ephem-wheel-cache-l7yt4jnn/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b

Successfully built nvtabular

Installing collected packages: nvtabular

Attempting uninstall: nvtabular

Found existing installation: nvtabular 1.1.1

Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu

Can't uninstall 'nvtabular'. No files were found to uninstall.

Successfully installed nvtabular-1.6.0+4.gba4c1415
[notice] A new release of pip available: 22.2.2 -> 22.3.1

[notice] To update, run: pip install --upgrade pip

py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit

============================= test session starts ==============================

platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0

cachedir: .tox/py38-gpu/.pytest_cache

rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml

plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0

collected 867 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ......                             [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  5%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  8%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 22%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 30%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 31%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 32%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 43%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

...........................................                              [ 63%]

tests/unit/tf/outputs/test_base.py ......                                [ 63%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 66%]

tests/unit/tf/outputs/test_topk.py .                                     [ 67%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 70%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py .....................           [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 74%]

tests/unit/tf/transforms/test_features.py s............................. [ 78%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 82%]

tests/unit/tf/transforms/test_noise.py .....                             [ 83%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 86%]

tests/unit/tf/utils/test_batch.py ....                                   [ 86%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 87%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 91%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 6 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 120 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 15 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 5 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 7 warnings

tests/unit/tf/core/test_index.py: 3 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 86 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 9 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:968: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/models/test_retrieval.py: 55 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filehxmloc67.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_encoder.py: 1 warning

tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classfication_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           107     80    25%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           147     14    90%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                        141     14    90%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              169     62    63%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          244     50    80%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         104     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         60     10    83%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     31    93%

merlin/models/tf/loader.py                                             165     54    67%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        753    102    86%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59      6    90%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     36    92%

merlin/models/tf/transforms/negative_sampling.py                        77      3    96%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  158     13    92%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                206     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     42    80%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     22    72%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                11024   2201    80%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 854 passed, 13 skipped, 1433 warnings in 1743.29s (0:29:03) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[merlin_models] $ /bin/bash /tmp/jenkins13889884960536993827.sh

oliverholworthy · 2022-11-30T15:48:31Z

tests/unit/tf/horovod/test_horovod.py

+            inputs, target = next(train_loader)
+            losses = model.fit(inputs, target)
+            steps += 1
+    except StopIteration:


can use .peek instead now that we have it on the loader and then won't need the StopIteration handler. What is the while loop checking for here? could the same thing be achieved passing an epochs parameter?

We want to count the total number of steps in each epoch here, so .peek won't work. Added some comments in 1a89c9f.

is this equivalent to looping through the batches like this without a try/except?

for x, y in train_loader: losses = model.fit(x, y) steps += 1

Yes, thanks! Updated in d6de79d.

edknv · 2022-12-01T05:04:42Z

rerun tests

nvidia-merlin-bot · 2022-12-01T05:32:27Z

Click to view CI Results

GitHub pull request #845 of commit 84218a039bb97138f9ef89702a981f4b381ba74f, no merge conflicts.
Running as SYSTEM
Setting status of 84218a039bb97138f9ef89702a981f4b381ba74f to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1979/ and message: 'Pending'
Using context: Jenkins
Building on the built-in node in workspace /var/jenkins_home/jobs/merlin_models/workspace
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 84218a039bb97138f9ef89702a981f4b381ba74f^{commit} # timeout=10
Checking out Revision 84218a039bb97138f9ef89702a981f4b381ba74f (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 84218a039bb97138f9ef89702a981f4b381ba74f # timeout=10
Commit message: "Merge branch 'main' into merlin_dataloader"
 > git rev-list --no-walk b6963ab2c07b00e5019b961cfee4d666a40d107b # timeout=10
[workspace] $ /bin/bash /tmp/jenkins17098413690005421571.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
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Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
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Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
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Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+85.g84218a03.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.20,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.20,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==6.0.0,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.3,merlin-models==0.9.0+85.g84218a03,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.10.0,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==3.0.1,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3916687125'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-gfduuyxd
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-gfduuyxd
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 78f1f0b0952fd14b76913b0dd258565c06694abe
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.2.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.10.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.3.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (4.64.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (3.19.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (0.55.1)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (1.3.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (21.3)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+13.g78f1f0b) (2022.5.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+13.g78f1f0b) (7.0.0)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (0.4.3)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (0.12.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (8.1.3)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (3.1.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.0.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (6.2)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.4.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.0.4)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.7.0)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (5.8.0)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+13.g78f1f0b) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+13.g78f1f0b) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+13.g78f1f0b) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+13.g78f1f0b) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+13.g78f1f0b) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+13.g78f1f0b) (2.8.2)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+13.g78f1f0b) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+13.g78f1f0b) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+13.g78f1f0b) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+13.g78f1f0b) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+13.g78f1f0b) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+13.g78f1f0b-py3-none-any.whl size=118889 sha256=75f65e0604081e418a73f4f5088b6543c40fba76394e0e1e777dbaeafc576071
  Stored in directory: /tmp/pip-ephem-wheel-cache-n2zshew_/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+13.g78f1f0b
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git
  Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-woatedhm
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-woatedhm
  Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit 2783231f3aa39dd6acb0e5f6431cc73faacde7fe
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.8.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+21.g2783231) (0.9.0+13.g78f1f0b)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.2.5)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.10.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2022.3.0)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (4.64.1)
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Building wheels for collected packages: merlin-dataloader
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+21.g2783231-py3-none-any.whl size=40305 sha256=9f051c67c062817e0933d309f5818f52fd77e0c19c35f0d6c50de8bdef3d5de6
  Stored in directory: /tmp/pip-ephem-wheel-cache-e4gj55vt/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1
Successfully built merlin-dataloader
Installing collected packages: merlin-dataloader
  Attempting uninstall: merlin-dataloader
    Found existing installation: merlin-dataloader 0.0.3
    Uninstalling merlin-dataloader-0.0.3:
      Successfully uninstalled merlin-dataloader-0.0.3
Successfully installed merlin-dataloader-0.0.2+21.g2783231
py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-bfinszdh
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-bfinszdh
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit ee3b7440eb22fad71ad50a6df978e1fa526f4817
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+11.gee3b7440) (0.9.0+13.g78f1f0b)
Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+11.gee3b7440) (0.0.2+21.g2783231)
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+11.gee3b7440) (1.8.1)
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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (21.3)
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Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (2.4.0)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (65.5.1)
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Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (2022.2.1)
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Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+11.gee3b7440) (6.0.1)
Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+11.gee3b7440-cp38-cp38-linux_x86_64.whl size=257603 sha256=01a70c7fb8d28c5dd4f3f96ac23d0e2d155436738878be057dc322b061858a7b
  Stored in directory: /tmp/pip-ephem-wheel-cache-hd2irsoe/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+11.gee3b7440
py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 877 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 23%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 23%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py F               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 31%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 32%]

tests/unit/tf/inputs/test_base.py .                                      [ 32%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 33%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 44%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

.............................................                            [ 63%]

tests/unit/tf/outputs/test_base.py ......                                [ 64%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 67%]

tests/unit/tf/outputs/test_topk.py .                                     [ 67%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 70%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py ................ERROR: Got SIGTERM, handling it as a KeyboardInterrupt

ERROR: got KeyboardInterrupt signal

Build was aborted

Aborted by �[8mha:////4K4GEn4Qce1FuoxeaQlMDQWh44+blmg3CeEZ3q4W6VxeAAAAmR+LCAAAAAAAAP9b85aBtbiIQTGjNKU4P08vOT+vOD8nVc83PyU1x6OyILUoJzMv2y+/JJUBAhiZGBgqihhk0NSjKDWzXb3RdlLBUSYGJk8GtpzUvPSSDB8G5tKinBIGIZ+sxLJE/ZzEvHT94JKizLx0a6BxUmjGOUNodHsLgAz2EgZe/dLi1CL90rzsvPzyPAATbMabwgAAAA==�[0munknown

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[workspace] $ /bin/bash /tmp/jenkins4718191113958578337.sh

nvidia-merlin-bot · 2022-12-01T06:10:26Z

Click to view CI Results

GitHub pull request #845 of commit 25d61d1a6a9996c526aac030b4397aefa5c30dc0, no merge conflicts.
Running as SYSTEM
Setting status of 25d61d1a6a9996c526aac030b4397aefa5c30dc0 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1980/ and message: 'Pending'
Using context: Jenkins
Building on the built-in node in workspace /var/jenkins_home/jobs/merlin_models/workspace
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 25d61d1a6a9996c526aac030b4397aefa5c30dc0^{commit} # timeout=10
Checking out Revision 25d61d1a6a9996c526aac030b4397aefa5c30dc0 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 25d61d1a6a9996c526aac030b4397aefa5c30dc0 # timeout=10
Commit message: "fix merge"
 > git rev-list --no-walk 84218a039bb97138f9ef89702a981f4b381ba74f # timeout=10
[workspace] $ /bin/bash /tmp/jenkins6021487239597451460.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+86.g25d61d1a.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.20,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.20,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==6.0.0,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.3,merlin-models==0.9.0+86.g25d61d1a,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.3,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.10.0,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==3.0.1,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2324904361'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-dzjzkdia
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-dzjzkdia
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 4f73ff5bd4121c1acaabdc01a123af4f986ffc78
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (2022.5.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (2022.3.0)
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Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (1.10.0)
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Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (3.19.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (4.64.1)
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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (21.3)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (0.55.1)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (5.4.1)
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Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.2.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.0.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (6.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (8.1.3)
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Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (3.1.2)
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Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.4.0)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+14.g4f73ff5) (65.5.1)
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Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+14.g4f73ff5) (3.0.9)
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Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (4.0.0)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+14.g4f73ff5-py3-none-any.whl size=119010 sha256=ea8854e53ca265863da076b0a0b458d6b61001799d755a502568e75280bba800
  Stored in directory: /tmp/pip-ephem-wheel-cache-4l_uo6fx/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+14.g4f73ff5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git
  Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-b0pw07fv
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-b0pw07fv
  Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit 2783231f3aa39dd6acb0e5f6431cc73faacde7fe
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.8.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+21.g2783231) (0.9.0+14.g4f73ff5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2022.5.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2022.3.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2022.3.0)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.10.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.2.5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (3.19.5)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.3.5)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (21.3)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (0.55.1)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (0.12.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2.2.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2.0.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (6.2)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (8.1.3)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (5.8.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (3.1.2)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.0.4)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2.4.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.7.0)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (0.38.1)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.20.3)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (3.0.9)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2022.2.1)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2.8.2)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (1.0.1)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (6.0.2)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (4.1.0)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (2.0.1)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (6.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+21.g2783231) (4.0.0)
Building wheels for collected packages: merlin-dataloader
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+21.g2783231-py3-none-any.whl size=40305 sha256=8bf573ecb33b8ab4767607ae048275b9062d1e8b170e98dba2a629d57dada506
  Stored in directory: /tmp/pip-ephem-wheel-cache-zb04fpm6/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1
Successfully built merlin-dataloader
Installing collected packages: merlin-dataloader
  Attempting uninstall: merlin-dataloader
    Found existing installation: merlin-dataloader 0.0.3
    Uninstalling merlin-dataloader-0.0.3:
      Successfully uninstalled merlin-dataloader-0.0.3
Successfully installed merlin-dataloader-0.0.2+21.g2783231
py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-6qnjfiwj
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-6qnjfiwj
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 3bcd555a7fdc1cdaca47379676c2f111750352a8
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+12.g3bcd555a) (1.8.1)
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Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+12.g3bcd555a-cp38-cp38-linux_x86_64.whl size=257601 sha256=b8a63bc642a3179374ba3548d6e2bfa9d3f8ecfd001bd284a1dff06ce50e5be5
  Stored in directory: /tmp/pip-ephem-wheel-cache-roo8ya07/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+12.g3bcd555a
py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 877 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 23%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 31%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 32%]

tests/unit/tf/inputs/test_base.py .                                      [ 32%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 33%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 44%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

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tests/unit/tf/outputs/test_base.py ......                                [ 64%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 67%]

tests/unit/tf/outputs/test_topk.py .                                     [ 67%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 70%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 75%]

tests/unit/tf/transforms/test_features.py s............................. [ 78%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 83%]

tests/unit/tf/transforms/test_noise.py .....                             [ 83%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 86%]

tests/unit/tf/utils/test_batch.py ....                                   [ 86%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 3 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 8 warnings

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 97 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filef3r5p5gm.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classification_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classification_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           155      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                         16      5    69%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       175     28    84%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         64     20    69%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             131     37    72%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        758    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     45    90%

merlin/models/tf/transforms/negative_sampling.py                        77      4    95%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  165     16    90%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                210     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     23    71%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                10919   2245    79%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 864 passed, 13 skipped, 1470 warnings in 1879.30s (0:31:19) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[workspace] $ /bin/bash /tmp/jenkins10657563034382091898.sh

oliverholworthy · 2022-12-01T18:56:40Z

tests/unit/tf/core/test_prediction.py

@@ -70,5 +70,5 @@ def flip_target(target):
    features, targets = mm.sample_batch(ecommerce_data, batch_size=100)
    outputs, context = model(features, targets=targets, training=True, output_context=True)

-    flipped = np.logical_not(targets["click"].numpy()).astype(np.int)


Why is targets no longer a dict here? This feels like it should be unrelated to the dataloader change.

Dataloader no longer returns a dictionary for targets, and will pick one column and use it if there are multiple target columns. I'm not sure if this is what we want, but it is how dataloader behaves for now.

Following team discussion, it looks like having dataloader output a tensor, not a dictionary, might not work for Models. We might need to change the dataloader's behavior upstream.

nvidia-merlin-bot · 2022-12-01T19:03:46Z

Click to view CI Results

GitHub pull request #845 of commit d6b123af15db859e71344c11e4944b4c262bd146, no merge conflicts.
Running as SYSTEM
Setting status of d6b123af15db859e71344c11e4944b4c262bd146 to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1986/ and message: 'Pending'
Using context: Jenkins
Building on the built-in node in workspace /var/jenkins_home/jobs/merlin_models/workspace
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse d6b123af15db859e71344c11e4944b4c262bd146^{commit} # timeout=10
Checking out Revision d6b123af15db859e71344c11e4944b4c262bd146 (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f d6b123af15db859e71344c11e4944b4c262bd146 # timeout=10
Commit message: "Merge branch 'main' into merlin_dataloader"
 > git rev-list --no-walk 6a5e5820e135c20afea50853526ace50d385f28e # timeout=10
[workspace] $ /bin/bash /tmp/jenkins4868145809954474575.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
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Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+88.gd6b123af.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.20,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.20,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==6.0.0,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.3,merlin-models==0.9.0+88.gd6b123af,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.4,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.10.0,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==3.0.1,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='2168089354'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-n_qi9ftu
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-n_qi9ftu
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 4f73ff5bd4121c1acaabdc01a123af4f986ffc78
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (1.3.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (2022.5.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (1.2.5)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (4.64.1)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (1.10.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (3.19.5)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (0.4.3)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (0.12.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (5.4.1)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.4.0)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.0.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (6.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (5.8.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (3.1.2)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.7.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (8.1.3)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.0.4)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+14.g4f73ff5) (65.5.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+14.g4f73ff5) (1.20.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+14.g4f73ff5) (0.38.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+14.g4f73ff5) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+14.g4f73ff5-py3-none-any.whl size=119010 sha256=2473c818f43db23e5d102e5e33689a2f0a388cdd1348b87a76ccd12e4a79d609
  Stored in directory: /tmp/pip-ephem-wheel-cache-ygkpteb1/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+14.g4f73ff5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git
  Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-niy145cc
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-niy145cc
  Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit 498543d54629216dc09a5854dca4dbeeabcab356
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.8.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+22.g498543d) (0.9.0+14.g4f73ff5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.3.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (2022.5.0)
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Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (21.3)
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Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.10.0)
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Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (6.0.1)
Building wheels for collected packages: merlin-dataloader
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+22.g498543d-py3-none-any.whl size=40350 sha256=0bf682c90e622e9eb8bdfa45abfdd1efe35f7a3ac62ff77c12a81f372600d6b2
  Stored in directory: /tmp/pip-ephem-wheel-cache-slcga253/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1
Successfully built merlin-dataloader
Installing collected packages: merlin-dataloader
  Attempting uninstall: merlin-dataloader
    Found existing installation: merlin-dataloader 0.0.3
    Uninstalling merlin-dataloader-0.0.3:
      Successfully uninstalled merlin-dataloader-0.0.3
Successfully installed merlin-dataloader-0.0.2+22.g498543d
py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-zq_mt4ab
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-zq_mt4ab
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 3bcd555a7fdc1cdaca47379676c2f111750352a8
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: scipy in /usr/local/lib/python3.8/dist-packages (from nvtabular==1.6.0+12.g3bcd555a) (1.8.1)
Requirement already satisfied: merlin-dataloader>=0.0.2 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+12.g3bcd555a) (0.0.2+22.g498543d)
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+12.g3bcd555a) (0.9.0+14.g4f73ff5)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (2022.3.0)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (1.3.5)
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Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (2022.3.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (4.64.1)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (7.0.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (1.10.0)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (0.55.1)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (3.19.5)
Requirement already satisfied: numpy<1.25.0,>=1.17.3 in /var/jenkins_home/.local/lib/python3.8/site-packages (from scipy->nvtabular==1.6.0+12.g3bcd555a) (1.20.3)
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Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (0.4.3)
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Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (2.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (1.2.0)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (2.4.0)
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Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (3.1.2)
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Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (65.5.1)
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Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (2.8.2)
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Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+12.g3bcd555a) (6.0.1)
Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+12.g3bcd555a-cp38-cp38-linux_x86_64.whl size=257601 sha256=01b7710427c6e0b251ea871047659e472643983378a023856f4fe3b5bc131ebc
  Stored in directory: /tmp/pip-ephem-wheel-cache-6p7ak5mr/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+12.g3bcd555a
py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 877 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

............................                                             [ 16%]

tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

.....................                                                    [ 23%]

tests/unit/tf/blocks/retrieval/test_base.py .                            [ 23%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 31%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py F [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py F [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 32%]

tests/unit/tf/inputs/test_base.py .                                      [ 32%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 33%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

........                                                                 [ 37%]

tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 44%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

.............................................                            [ 63%]

tests/unit/tf/outputs/test_base.py ......                                [ 64%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 67%]

tests/unit/tf/outputs/test_topk.py .                                     [ 67%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 70%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 75%]

tests/unit/tf/transforms/test_features.py s............................. [ 78%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 83%]

tests/unit/tf/transforms/test_noise.py .....                             [ 83%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 86%]

tests/unit/tf/utils/test_batch.py ....                                   [ 86%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=================================== FAILURES ===================================

_________________ test_usecase_accelerate_training_by_lazyadam _________________
tb = <testbook.client.TestbookNotebookClient object at 0x7efc63e1faf0>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
@pytest.mark.skipif(not HAS_GPU, reason="No GPU available")
def test_usecase_accelerate_training_by_lazyadam(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py:25:

../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7efc63e1faf0>

cell = {'cell_type': 'code', 'execution_count': 7, 'id': '0500ad25-29e0-40c8-85bc-6e3864107c6a', 'metadata': {'execution': {'...e_train_function_3863]']}], 'source': 'model1.compile(optimizer="adam")\nmodel1.fit(train, batch_size=1024, epochs=1)'}

cell_index = 12

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': '4ac94e...e, 'engine': '4ac94e46-25fd-4785-bae3-0c39858bf3f2', 'started': '2022-12-01T18:41:13.799746Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model1.compile(optimizer="adam")

E           model1.fit(train, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [7], line 2�[0m

E           �[1;32m      1�[0m model1�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39m�[38;5;124m"�[39m�[38;5;124madam�[39m�[38;5;124m"�[39m)

E           �[0;32m----> 2�[0m �[43mmodel1�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mtrain�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:943�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    940�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    941�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 943�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    945�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    946�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

E           �[0;32m---> 54�[0m   tensors �[38;5;241m=�[39m pywrap_tfe�[38;5;241m.�[39mTFE_Py_Execute(ctx�[38;5;241m.�[39m_handle, device_name, op_name,

E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

E           �[1;32m     56�[0m �[38;5;28;01mexcept�[39;00m core�[38;5;241m.�[39m_NotOkStatusException �[38;5;28;01mas�[39;00m e:

E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

E

E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_21522/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 943, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 757, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_21522/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 943, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 757, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_3863]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_21522/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 943, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 757, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           Detected at node 'Adam/Adam/update_17/mul_1' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_21522/3741080137.py", line 2, in 

E                 model1.fit(train, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 943, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 757, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 206, in _resource_apply_sparse

E                 m_t = tf.compat.v1.assign(m, m * coefficients['beta_1_t'],

E           Node: 'Adam/Adam/update_17/mul_1'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_17/mul_1}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_3863]
../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-12-01 18:41:06.954228: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-12-01 18:41:11.064031: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-12-01 18:41:11.064133: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-12-01 18:41:11.065016: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-12-01 18:41:11.065077: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-12-01 18:41:11.065676: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-12-01 18:41:11.065725: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-12-01 18:41:11.066345: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-12-01 18:41:11.066395: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-12-01 18:41:27.895398: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 3735552/17069309952

2022-12-01 18:41:27.895466: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4153091748

MaxInUse:                   4153194148

NumAllocs:                         249

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-12-01 18:41:27.895485: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-12-01 18:41:27.895493: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-12-01 18:41:27.895504: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 33

2022-12-01 18:41:27.895515: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 9

2022-12-01 18:41:27.895526: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-12-01 18:41:27.895537: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 7

2022-12-01 18:41:27.895545: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 7

2022-12-01 18:41:27.895551: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-12-01 18:41:27.895556: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-12-01 18:41:27.895562: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-12-01 18:41:27.895568: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 3

2022-12-01 18:41:27.895573: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-12-01 18:41:27.895579: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-12-01 18:41:27.895613: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 6400, 26

2022-12-01 18:41:27.895621: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-12-01 18:41:27.895627: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-12-01 18:41:27.895632: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 1

2022-12-01 18:41:27.895638: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-12-01 18:41:27.895644: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-12-01 18:41:27.895649: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 3

2022-12-01 18:41:27.895656: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 4

2022-12-01 18:41:27.895666: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 3

2022-12-01 18:41:27.895677: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-12-01 18:41:27.895688: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-12-01 18:41:27.895698: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-12-01 18:41:27.895704: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3

2022-12-01 18:41:27.895709: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-12-01 18:41:27.896434: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-12-01 18:41:27.899841: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 3735552/17069309952

2022-12-01 18:41:27.899866: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4172600495

MaxInUse:                   4172951655

NumAllocs:                         491

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-12-01 18:41:27.899885: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-12-01 18:41:27.899892: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-12-01 18:41:27.899898: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-12-01 18:41:27.899904: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 10

2022-12-01 18:41:27.899910: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 16, 1

2022-12-01 18:41:27.899916: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 24, 1

2022-12-01 18:41:27.899921: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-12-01 18:41:27.899927: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 48, 1

2022-12-01 18:41:27.899933: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 10

2022-12-01 18:41:27.899939: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 9

2022-12-01 18:41:27.899944: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 5

2022-12-01 18:41:27.899950: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-12-01 18:41:27.899956: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 5

2022-12-01 18:41:27.899961: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 352, 1

2022-12-01 18:41:27.899967: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-12-01 18:41:27.899994: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1008, 3

2022-12-01 18:41:27.900002: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1024, 4

2022-12-01 18:41:27.900007: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-12-01 18:41:27.900013: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-12-01 18:41:27.900021: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3200, 25

2022-12-01 18:41:27.900041: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 6400, 7

2022-12-01 18:41:27.900048: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 25600, 2

2022-12-01 18:41:27.900054: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 61440, 3

2022-12-01 18:41:27.900060: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 65536, 3

2022-12-01 18:41:27.900065: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 102400, 1

2022-12-01 18:41:27.900071: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128000, 1

2022-12-01 18:41:27.900076: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 153600, 1

2022-12-01 18:41:27.900082: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 204800, 2

2022-12-01 18:41:27.900088: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 4

2022-12-01 18:41:27.900093: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 640000, 1

2022-12-01 18:41:27.900099: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 768000, 1

2022-12-01 18:41:27.900105: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 819200, 1

2022-12-01 18:41:27.900110: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-12-01 18:41:27.900116: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-12-01 18:41:27.900122: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-12-01 18:41:27.900127: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 3

2022-12-01 18:41:27.900133: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-12-01 18:41:27.900139: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-12-01 18:41:27.900144: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-12-01 18:41:27.900150: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3

2022-12-01 18:41:27.900156: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-12-01 18:41:27.900169: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

_______________ test_usecase_incremental_training_layer_freezing _______________
tb = <testbook.client.TestbookNotebookClient object at 0x7efcc8029400>
@testbook(
    REPO_ROOT / p,
    timeout=180,
    execute=False,
)
def test_usecase_incremental_training_layer_freezing(tb):
    tb.inject(
        """
        import os
        os.environ["NUM_ROWS"] = "1000"
        """
    )


  tb.execute()


tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py:22:

../../../.local/lib/python3.8/site-packages/testbook/client.py:147: in execute

super().execute_cell(cell, index)

../../../.local/lib/python3.8/site-packages/nbclient/util.py:84: in wrapped

return just_run(coro(*args, **kwargs))

../../../.local/lib/python3.8/site-packages/nbclient/util.py:62: in just_run

return loop.run_until_complete(coro)

/usr/lib/python3.8/asyncio/base_events.py:616: in run_until_complete

return future.result()

../../../.local/lib/python3.8/site-packages/nbclient/client.py:965: in async_execute_cell

await self._check_raise_for_error(cell, cell_index, exec_reply)

self = <testbook.client.TestbookNotebookClient object at 0x7efcc8029400>

cell = {'cell_type': 'code', 'execution_count': 8, 'id': '791e06ec-c0cb-4c0f-9e41-7e5c8fa1dc4e', 'metadata': {'execution': {'...: 'model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))\nmodel.fit(day_1, batch_size=1024, epochs=1)'}

cell_index = 13

exec_reply = {'buffers': [], 'content': {'ename': 'ResourceExhaustedError', 'engine_info': {'engine_id': -1, 'engine_uuid': 'f65bd0...e, 'engine': 'f65bd0a4-ce52-4d19-aa0b-847af279e27a', 'started': '2022-12-01T18:43:36.894087Z', 'status': 'error'}, ...}
async def _check_raise_for_error(
    self, cell: NotebookNode, cell_index: int, exec_reply: t.Optional[t.Dict]
) -> None:

    if exec_reply is None:
        return None

    exec_reply_content = exec_reply['content']
    if exec_reply_content['status'] != 'error':
        return None

    cell_allows_errors = (not self.force_raise_errors) and (
        self.allow_errors
        or exec_reply_content.get('ename') in self.allow_error_names
        or "raises-exception" in cell.metadata.get("tags", [])
    )
    await run_hook(self.on_cell_error, cell=cell, cell_index=cell_index)
    if not cell_allows_errors:


      raise CellExecutionError.from_cell_and_msg(cell, exec_reply_content)


E           nbclient.exceptions.CellExecutionError: An error occurred while executing the following cell:

E           ------------------

E           model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.01))

E           model.fit(day_1, batch_size=1024, epochs=1)

E           ------------------

E

E           �[0;31m---------------------------------------------------------------------------�[0m

E           �[0;31mResourceExhaustedError�[0m                    Traceback (most recent call last)

E           Cell �[0;32mIn [8], line 2�[0m

E           �[1;32m      1�[0m model�[38;5;241m.�[39mcompile(optimizer�[38;5;241m=�[39mtf�[38;5;241m.�[39mkeras�[38;5;241m.�[39moptimizers�[38;5;241m.�[39mAdam(learning_rate�[38;5;241m=�[39m�[38;5;241m0.01�[39m))

E           �[0;32m----> 2�[0m �[43mmodel�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[43mday_1�[49m�[43m,�[49m�[43m �[49m�[43mbatch_size�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1024�[39;49m�[43m,�[49m�[43m �[49m�[43mepochs�[49m�[38;5;241;43m=�[39;49m�[38;5;241;43m1�[39;49m�[43m)�[49m

E

E           File �[0;32m~/workspace/merlin_models/models/merlin/models/tf/models/base.py:943�[0m, in �[0;36mBaseModel.fit�[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)�[0m

E           �[1;32m    940�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39m_reset_compile_cache()

E           �[1;32m    941�[0m     �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre �[38;5;241m=�[39m pre

E           �[0;32m--> 943�[0m out �[38;5;241m=�[39m �[38;5;28;43msuper�[39;49m�[43m(�[49m�[43m)�[49m�[38;5;241;43m.�[39;49m�[43mfit�[49m�[43m(�[49m�[38;5;241;43m�[39;49m�[38;5;241;43m�[39;49m�[43mfit_kwargs�[49m�[43m)�[49m

E           �[1;32m    945�[0m �[38;5;28;01mif�[39;00m pre:

E           �[1;32m    946�[0m     �[38;5;28;01mdel�[39;00m �[38;5;28mself�[39m�[38;5;241m.�[39mtrain_pre

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67�[0m, in �[0;36mfilter_traceback..error_handler�[0;34m(*args, **kwargs)�[0m

E           �[1;32m     65�[0m �[38;5;28;01mexcept�[39;00m �[38;5;167;01mException�[39;00m �[38;5;28;01mas�[39;00m e:  �[38;5;66;03m# pylint: disable=broad-except�[39;00m

E           �[1;32m     66�[0m   filtered_tb �[38;5;241m=�[39m process_traceback_frames(e�[38;5;241m.�[39m__traceback_)

E           �[0;32m---> 67�[0m   �[38;5;28;01mraise�[39;00m e�[38;5;241m.�[39mwith_traceback(filtered_tb) �[38;5;28;01mfrom�[39;00m �[38;5;28mNone�[39m

E           �[1;32m     68�[0m �[38;5;28;01mfinally�[39;00m:

E           �[1;32m     69�[0m   �[38;5;28;01mdel�[39;00m filtered_tb

E

E           File �[0;32m~/.local/lib/python3.8/site-packages/tensorflow/python/eager/execute.py:54�[0m, in �[0;36mquick_execute�[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)�[0m

E           �[1;32m     52�[0m �[38;5;28;01mtry�[39;00m:

E           �[1;32m     53�[0m   ctx�[38;5;241m.�[39mensure_initialized()

E           �[0;32m---> 54�[0m   tensors �[38;5;241m=�[39m pywrap_tfe�[38;5;241m.�[39mTFE_Py_Execute(ctx�[38;5;241m.�[39m_handle, device_name, op_name,

E           �[1;32m     55�[0m                                       inputs, attrs, num_outputs)

E           �[1;32m     56�[0m �[38;5;28;01mexcept�[39;00m core�[38;5;241m.�[39m_NotOkStatusException �[38;5;28;01mas�[39;00m e:

E           �[1;32m     57�[0m   �[38;5;28;01mif�[39;00m name �[38;5;129;01mis�[39;00m �[38;5;129;01mnot�[39;00m �[38;5;28;01mNone�[39;00m:

E

E           �[0;31mResourceExhaustedError�[0m: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_19/mul_4' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_22282/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 943, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 757, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 214, in _resource_apply_sparse

E                 v_t = tf.compat.v1.assign(v, v * coefficients['beta_2_t'],

E           Node: 'Adam/Adam/update_19/mul_4'

E           Detected at node 'Adam/Adam/update_19/mul_4' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_22282/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 943, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 757, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 214, in _resource_apply_sparse

E                 v_t = tf.compat.v1.assign(v, v * coefficients['beta_2_t'],

E           Node: 'Adam/Adam/update_19/mul_4'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_4}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_4}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_4009]

E           ResourceExhaustedError: Graph execution error:

E

E           Detected at node 'Adam/Adam/update_19/mul_4' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_22282/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 943, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 757, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 214, in _resource_apply_sparse

E                 v_t = tf.compat.v1.assign(v, v * coefficients['beta_2_t'],

E           Node: 'Adam/Adam/update_19/mul_4'

E           Detected at node 'Adam/Adam/update_19/mul_4' defined at (most recent call last):

E               File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main

E                 return _run_code(code, main_globals, None,

E               File "/usr/lib/python3.8/runpy.py", line 87, in _run_code

E                 exec(code, run_globals)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 17, in 

E                 app.launch_new_instance()

E               File "/usr/local/lib/python3.8/dist-packages/traitlets/config/application.py", line 978, in launch_instance

E                 app.start()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 712, in start

E                 self.io_loop.start()

E               File "/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 215, in start

E                 self.asyncio_loop.run_forever()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever

E                 self._run_once()

E               File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once

E                 handle._run()

E               File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run

E                 self._context.run(self._callback, *self._args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 510, in dispatch_queue

E                 await self.process_one()

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 499, in process_one

E                 await dispatch(*args)

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 406, in dispatch_shell

E                 await result

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 730, in execute_request

E                 reply_content = await reply_content

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 383, in do_execute

E                 res = shell.run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 528, in run_cell

E                 return super().run_cell(*args, **kwargs)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_cell

E                 result = self._run_cell(

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 2940, in _run_cell

E                 return runner(coro)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py", line 129, in pseudo_sync_runner

E                 coro.send(None)

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3139, in run_cell_async

E                 has_raised = await self.run_ast_nodes(code_ast.body, cell_name,

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3318, in run_ast_nodes

E                 if await self.run_code(code, result, async=asy):

E               File "/usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py", line 3378, in run_code

E                 exec(code_obj, self.user_global_ns, self.user_ns)

E               File "/tmp/ipykernel_22282/2071866865.py", line 2, in 

E                 model.fit(day_1, batch_size=1024, epochs=1)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 943, in fit

E                 out = super().fit(**fit_kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/traceback_utils.py", line 64, in error_handler

E                 return fn(*args, **kwargs)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1409, in fit

E                 tmp_logs = self.train_function(iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1051, in train_function

E                 return step_function(self, iterator)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1040, in step_function

E                 outputs = model.distribute_strategy.run(run_step, args=(data,))

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/engine/training.py", line 1030, in run_step

E                 outputs = model.train_step(data)

E               File "/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/models/base.py", line 757, in train_step

E                 self.optimizer.minimize(loss, self.trainable_variables, tape=tape)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 539, in minimize

E                 return self.apply_gradients(grads_and_vars, name=name)

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 678, in apply_gradients

E                 return tf.internal.distribute.interim.maybe_merge_call(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 723, in _distributed_apply

E                 update_op = distribution.extended.update(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 701, in apply_grad_to_update_var

E                 return self._resource_apply_sparse_duplicate_indices(

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/optimizer_v2.py", line 1326, in _resource_apply_sparse_duplicate_indices

E                 return self._resource_apply_sparse(summed_grad, handle, unique_indices,

E               File "/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/adam.py", line 214, in _resource_apply_sparse

E                 v_t = tf.compat.v1.assign(v, v * coefficients['beta_2_t'],

E           Node: 'Adam/Adam/update_19/mul_4'

E           2 root error(s) found.

E             (0) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_4}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           	 [[StatefulPartitionedCall/cond/pivot_t/_131/_53]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E             (1) RESOURCE_EXHAUSTED:  failed to allocate memory

E           	 [[{{node Adam/Adam/update_19/mul_4}}]]

E           Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info. This isn't available when running in Eager mode.

E

E           0 successful operations.

E           0 derived errors ignored. [Op:__inference_train_function_4009]
../../../.local/lib/python3.8/site-packages/nbclient/client.py:862: CellExecutionError

----------------------------- Captured stderr call -----------------------------

2022-12-01 18:43:29.969986: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA

To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.

2022-12-01 18:43:34.084250: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 0

2022-12-01 18:43:34.084361: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 8139 MB memory:  -> device: 0, name: Tesla P100-DGXS-16GB, pci bus id: 0000:07:00.0, compute capability: 6.0

2022-12-01 18:43:34.085125: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 1

2022-12-01 18:43:34.085185: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 13875 MB memory:  -> device: 1, name: Tesla P100-DGXS-16GB, pci bus id: 0000:08:00.0, compute capability: 6.0

2022-12-01 18:43:34.085879: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 2

2022-12-01 18:43:34.085931: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 13875 MB memory:  -> device: 2, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0e:00.0, compute capability: 6.0

2022-12-01 18:43:34.086517: I tensorflow/core/common_runtime/gpu/gpu_process_state.cc:222] Using CUDA malloc Async allocator for GPU: 3

2022-12-01 18:43:34.086567: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 13875 MB memory:  -> device: 3, name: Tesla P100-DGXS-16GB, pci bus id: 0000:0f:00.0, compute capability: 6.0

2022-12-01 18:43:51.353202: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 3735552/17069309952

2022-12-01 18:43:51.353259: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4146924084

MaxInUse:                   4147102620

NumAllocs:                         530

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-12-01 18:43:51.353280: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-12-01 18:43:51.353288: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-12-01 18:43:51.353295: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 34

2022-12-01 18:43:51.353302: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 9

2022-12-01 18:43:51.353308: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 16, 1

2022-12-01 18:43:51.353314: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 24, 2

2022-12-01 18:43:51.353320: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32, 1

2022-12-01 18:43:51.353327: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-12-01 18:43:51.353333: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 48, 1

2022-12-01 18:43:51.353339: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 64, 1

2022-12-01 18:43:51.353345: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 6

2022-12-01 18:43:51.353351: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 7

2022-12-01 18:43:51.353357: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 3

2022-12-01 18:43:51.353389: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-12-01 18:43:51.353397: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-12-01 18:43:51.353403: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 3

2022-12-01 18:43:51.353409: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6

2022-12-01 18:43:51.353416: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 672, 5

2022-12-01 18:43:51.353422: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 720, 5

2022-12-01 18:43:51.353428: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-12-01 18:43:51.353434: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1320, 18

2022-12-01 18:43:51.353440: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 2640, 2

2022-12-01 18:43:51.353446: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 3

2022-12-01 18:43:51.353453: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 10560, 7

2022-12-01 18:43:51.353459: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 31680, 1

2022-12-01 18:43:51.353465: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6

2022-12-01 18:43:51.353471: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 42240, 2

2022-12-01 18:43:51.353477: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 52800, 1

2022-12-01 18:43:51.353483: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 63360, 1

2022-12-01 18:43:51.353489: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 84480, 1

2022-12-01 18:43:51.353495: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 108900, 1

2022-12-01 18:43:51.353501: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3

2022-12-01 18:43:51.353507: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3

2022-12-01 18:43:51.353513: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 168960, 1

2022-12-01 18:43:51.353519: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 337920, 1

2022-12-01 18:43:51.353526: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 3

2022-12-01 18:43:51.353533: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 3

2022-12-01 18:43:51.353539: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 3

2022-12-01 18:43:51.353546: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 3

2022-12-01 18:43:51.353552: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 3

2022-12-01 18:43:51.353558: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 3

2022-12-01 18:43:51.353564: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-12-01 18:43:51.353570: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 4

2022-12-01 18:43:51.353576: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3

2022-12-01 18:43:51.353583: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-12-01 18:43:51.353610: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

2022-12-01 18:43:51.356532: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:288] gpu_async_0 cuMemAllocAsync failed to allocate 1083564064 bytes: CUDA error: out of memory (CUDA_ERROR_OUT_OF_MEMORY)

Reported by CUDA: Free memory/Total memory: 3735552/17069309952

2022-12-01 18:43:51.356558: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:293] Stats: Limit:                      8534360064

InUse:                      4284251828

MaxInUse:                   4284251828

NumAllocs:                         590

MaxAllocSize:               1083564064

Reserved:                            0

PeakReserved:                        0

LargestFreeBlock:                    0
2022-12-01 18:43:51.356595: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:56] Histogram of current allocation: (allocation_size_in_bytes, nb_allocation_of_that_sizes), ...;

2022-12-01 18:43:51.356606: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1, 4

2022-12-01 18:43:51.356613: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4, 36

2022-12-01 18:43:51.356619: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 8, 9

2022-12-01 18:43:51.356626: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 16, 2

2022-12-01 18:43:51.356632: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 24, 2

2022-12-01 18:43:51.356638: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32, 1

2022-12-01 18:43:51.356644: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 40, 2

2022-12-01 18:43:51.356651: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 48, 1

2022-12-01 18:43:51.356657: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 64, 1

2022-12-01 18:43:51.356663: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 128, 9

2022-12-01 18:43:51.356669: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 160, 8

2022-12-01 18:43:51.356675: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 192, 4

2022-12-01 18:43:51.356682: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 256, 6

2022-12-01 18:43:51.356688: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 288, 3

2022-12-01 18:43:51.356694: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 328, 1

2022-12-01 18:43:51.356701: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 480, 4

2022-12-01 18:43:51.356707: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 512, 6

2022-12-01 18:43:51.356713: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 672, 5

2022-12-01 18:43:51.356719: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 720, 5

2022-12-01 18:43:51.356726: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1028, 1

2022-12-01 18:43:51.356732: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1320, 20

2022-12-01 18:43:51.356738: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 3168, 4

2022-12-01 18:43:51.356745: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 32768, 6

2022-12-01 18:43:51.356751: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 84480, 3

2022-12-01 18:43:51.356757: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 108900, 1

2022-12-01 18:43:51.356763: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 122880, 3

2022-12-01 18:43:51.356770: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 131072, 3

2022-12-01 18:43:51.356776: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 168960, 2

2022-12-01 18:43:51.356782: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 316800, 1

2022-12-01 18:43:51.356788: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 337920, 1

2022-12-01 18:43:51.356795: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 436920, 3

2022-12-01 18:43:51.356801: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 584352, 5

2022-12-01 18:43:51.356807: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 823872, 5

2022-12-01 18:43:51.356821: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 4324736, 5

2022-12-01 18:43:51.356829: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 7426048, 5

2022-12-01 18:43:51.356835: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 15401440, 4

2022-12-01 18:43:51.356841: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 18678720, 5

2022-12-01 18:43:51.356848: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 39970560, 3

2022-12-01 18:43:51.356854: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 56589504, 5

2022-12-01 18:43:51.356860: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 135407776, 3

2022-12-01 18:43:51.356866: E tensorflow/core/common_runtime/gpu/gpu_cudamallocasync_allocator.cc:59] 1083564064, 3

2022-12-01 18:43:51.356881: W tensorflow/core/framework/op_kernel.cc:1733] RESOURCE_EXHAUSTED: failed to allocate memory

Error in atexit._run_exitfuncs:

Traceback (most recent call last):

File "/usr/lib/python3.8/logging/init.py", line 2127, in shutdown

h.close()

File "/usr/local/lib/python3.8/dist-packages/absl/logging/init.py", line 934, in close

self.stream.close()

File "/usr/local/lib/python3.8/dist-packages/ipykernel/iostream.py", line 438, in close

self.watch_fd_thread.join()

AttributeError: 'OutStream' object has no attribute 'watch_fd_thread'

=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 6 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 8 warnings

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 99 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 10 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filenksw5cxy.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classification_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classification_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           155      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                         16      5    69%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     54    87%

merlin/models/tf/core/encoder.py                                       182     28    85%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     32    89%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         64     20    69%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             131     37    72%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        772    103    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     45    90%

merlin/models/tf/transforms/negative_sampling.py                        77      4    95%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  165     16    90%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      7    90%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                210     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     23    71%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                10940   2254    79%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

==== 2 failed, 862 passed, 13 skipped, 1475 warnings in 1872.77s (0:31:12) =====

ERROR: InvocationError for command /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/bin/python -m pytest --cov-report term --cov merlin -rxs tests/unit (exited with code 1)

___________________________________ summary ____________________________________

ERROR:   py38-gpu: commands failed

Build step 'Execute shell' marked build as failure

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[workspace] $ /bin/bash /tmp/jenkins15043942844261333430.sh

nvidia-merlin-bot · 2022-12-01T23:49:54Z

Click to view CI Results

GitHub pull request #845 of commit 93706b6be396c2951b7d02f13ea456eb5f9ce10d, no merge conflicts.
Running as SYSTEM
Setting status of 93706b6be396c2951b7d02f13ea456eb5f9ce10d to PENDING with url http://merlin-infra1.nvidia.com:8080/job/merlin_models/1991/ and message: 'Pending'
Using context: Jenkins
Building on the built-in node in workspace /var/jenkins_home/jobs/merlin_models/workspace
using credential nvidia-merlin-bot
 > git rev-parse --is-inside-work-tree # timeout=10
Fetching changes from the remote Git repository
 > git config remote.origin.url https://github.com/NVIDIA-Merlin/models/ # timeout=10
Fetching upstream changes from https://github.com/NVIDIA-Merlin/models/
 > git --version # timeout=10
using GIT_ASKPASS to set credentials This is the bot credentials for our CI/CD
 > git fetch --tags --force --progress -- https://github.com/NVIDIA-Merlin/models/ +refs/pull/845/*:refs/remotes/origin/pr/845/* # timeout=10
 > git rev-parse 93706b6be396c2951b7d02f13ea456eb5f9ce10d^{commit} # timeout=10
Checking out Revision 93706b6be396c2951b7d02f13ea456eb5f9ce10d (detached)
 > git config core.sparsecheckout # timeout=10
 > git checkout -f 93706b6be396c2951b7d02f13ea456eb5f9ce10d # timeout=10
Commit message: "use loader context mananger"
 > git rev-list --no-walk 7a363efc7b692bd8d5a6f72b6c9ebf90e79285af # timeout=10
[workspace] $ /bin/bash /tmp/jenkins12763940742759809375.sh
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Requirement already satisfied: testbook in /usr/local/lib/python3.8/dist-packages (0.4.2)
Requirement already satisfied: nbformat>=5.0.4 in /usr/local/lib/python3.8/dist-packages (from testbook) (5.5.0)
Requirement already satisfied: nbclient>=0.4.0 in /usr/local/lib/python3.8/dist-packages (from testbook) (0.6.8)
Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (1.5.5)
Requirement already satisfied: jupyter-client>=6.1.5 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (7.3.5)
Requirement already satisfied: traitlets>=5.2.2 in /usr/local/lib/python3.8/dist-packages (from nbclient>=0.4.0->testbook) (5.4.0)
Requirement already satisfied: jsonschema>=2.6 in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.16.0)
Requirement already satisfied: fastjsonschema in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (2.16.1)
Requirement already satisfied: jupyter_core in /usr/local/lib/python3.8/dist-packages (from nbformat>=5.0.4->testbook) (4.11.1)
Requirement already satisfied: importlib-resources>=1.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (5.9.0)
Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (0.18.1)
Requirement already satisfied: pkgutil-resolve-name>=1.3.10 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (1.3.10)
Requirement already satisfied: attrs>=17.4.0 in /usr/local/lib/python3.8/dist-packages (from jsonschema>=2.6->nbformat>=5.0.4->testbook) (22.1.0)
Requirement already satisfied: entrypoints in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (0.4)
Requirement already satisfied: pyzmq>=23.0 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (24.0.0)
Requirement already satisfied: tornado>=6.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (6.2)
Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.8/dist-packages (from jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (2.8.2)
Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from importlib-resources>=1.4.0->jsonschema>=2.6->nbformat>=5.0.4->testbook) (3.8.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter-client>=6.1.5->nbclient>=0.4.0->testbook) (1.15.0)
GLOB sdist-make: /var/jenkins_home/workspace/merlin_models/models/setup.py
py38-gpu recreate: /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
py38-gpu installdeps: -rrequirements/dev.txt, tensorflow<2.10
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu inst: /var/jenkins_home/workspace/merlin_models/models/.tox/.tmp/package/4/merlin-models-0.9.0+90.g93706b6b.zip
WARNING: Discarding $PYTHONPATH from environment, to override specify PYTHONPATH in 'passenv' in your configuration.
py38-gpu installed: absl-py==1.2.0,aiohttp==3.8.1,aiosignal==1.2.0,alabaster==0.7.12,alembic==1.8.1,anyio==3.6.1,appdirs==1.4.4,argon2-cffi==21.3.0,argon2-cffi-bindings==21.2.0,astroid==2.5.6,asttokens==2.0.8,astunparse==1.6.3,asv==0.5.1,asvdb==0.4.2,async-timeout==4.0.2,attrs==22.1.0,autopage==0.5.1,awscli==1.27.20,Babel==2.10.3,backcall==0.2.0,beautifulsoup4==4.11.1,betterproto==1.2.5,black==20.8b1,bleach==5.0.1,bokeh==3.0.2,boto3==1.24.75,botocore==1.29.20,Brotli==1.0.9,build==0.9.0,cachetools==5.2.0,certifi==2019.11.28,cffi==1.15.1,chardet==3.0.4,charset-normalizer==2.1.1,check-manifest==0.48,clang==5.0,click==8.1.3,cliff==4.1.0,cloudpickle==2.2.0,cmaes==0.9.0,cmake==3.24.1.1,cmd2==2.4.2,colorama==0.4.4,colorlog==6.7.0,contourpy==1.0.5,coverage==6.5.0,cuda-python==11.7.1,cupy-cuda117==10.6.0,cycler==0.11.0,Cython==0.29.32,dask==2022.1.1,dbus-python==1.2.16,debugpy==1.6.3,decorator==5.1.1,defusedxml==0.7.1,dill==0.3.5.1,distlib==0.3.6,distributed==2022.5.1,distro==1.7.0,dm-tree==0.1.6,docker-pycreds==0.4.0,docutils==0.16,emoji==1.7.0,entrypoints==0.4,execnet==1.9.0,executing==1.0.0,faiss==1.7.2,faiss-gpu==1.7.2,fastai==2.7.9,fastapi==0.85.0,fastavro==1.6.1,fastcore==1.5.27,fastdownload==0.0.7,fastjsonschema==2.16.1,fastprogress==1.0.3,fastrlock==0.8,feast==0.19.4,fiddle==0.2.2,filelock==3.8.0,flake8==6.0.0,flatbuffers==1.12,fonttools==4.37.3,frozenlist==1.3.1,fsspec==2022.5.0,gast==0.4.0,gevent==21.12.0,geventhttpclient==2.0.2,gitdb==4.0.9,GitPython==3.1.27,google==3.0.0,google-api-core==2.10.1,google-auth==2.11.1,google-auth-oauthlib==0.4.6,google-pasta==0.2.0,googleapis-common-protos==1.52.0,graphviz==0.20.1,greenlet==1.1.3,grpcio==1.41.0,grpcio-channelz==1.49.0,grpcio-reflection==1.48.1,grpclib==0.4.3,h11==0.13.0,h2==4.1.0,h5py==3.7.0,HeapDict==1.0.1,horovod==0.26.1,hpack==4.0.0,httptools==0.5.0,hugectr2onnx==0.0.0,huggingface-hub==0.9.1,hyperframe==6.0.1,idna==2.8,imagesize==1.4.1,implicit==0.6.1,importlib-metadata==4.12.0,importlib-resources==5.9.0,iniconfig==1.1.1,interrogate==1.5.0,ipykernel==6.15.3,ipython==8.5.0,ipython-genutils==0.2.0,ipywidgets==7.7.0,isort==5.10.1,jedi==0.18.1,Jinja2==3.1.2,jmespath==1.0.1,joblib==1.2.0,json5==0.9.10,jsonschema==4.16.0,jupyter==1.0.0,jupyter-cache==0.4.3,jupyter-console==6.4.4,jupyter-core==4.11.1,jupyter-server==1.18.1,jupyter-server-mathjax==0.2.5,jupyter-sphinx==0.3.2,jupyter_client==7.3.5,jupyterlab==3.4.7,jupyterlab-pygments==0.2.2,jupyterlab-widgets==1.1.0,jupyterlab_server==2.15.1,keras==2.9.0,Keras-Preprocessing==1.1.2,kiwisolver==1.4.4,lazy-object-proxy==1.8.0,libclang==14.0.6,libcst==0.4.7,lightfm==1.16,lightgbm==3.3.2,linkify-it-py==1.0.3,llvmlite==0.39.1,locket==1.0.0,lxml==4.9.1,Mako==1.2.4,Markdown==3.4.1,markdown-it-py==1.1.0,MarkupSafe==2.1.1,matplotlib==3.6.0,matplotlib-inline==0.1.6,mccabe==0.7.0,mdit-py-plugins==0.2.8,merlin-core==0.6.0+1.g5926fcf,merlin-dataloader==0.0.3,merlin-models==0.9.0+90.g93706b6b,merlin-systems==0.5.0+4.g15074ad,mistune==2.0.4,mmh3==3.0.0,mpi4py==3.1.3,msgpack==1.0.4,multidict==6.0.2,mypy==0.991,mypy-extensions==0.4.3,myst-nb==0.13.2,myst-parser==0.15.2,natsort==8.1.0,nbclassic==0.4.3,nbclient==0.6.8,nbconvert==7.0.0,nbdime==3.1.1,nbformat==5.5.0,nest-asyncio==1.5.5,ninja==1.10.2.3,notebook==6.4.12,notebook-shim==0.1.0,numba==0.56.2,numpy==1.22.4,nvidia-pyindex==1.0.9,# Editable install with no version control (nvtabular==1.4.0+8.g95e12d347),-e /usr/local/lib/python3.8/dist-packages,nvtx==0.2.5,oauthlib==3.2.1,oldest-supported-numpy==2022.8.16,onnx==1.12.0,onnxruntime==1.11.1,opt-einsum==3.3.0,optuna==3.0.4,packaging==21.3,pandas==1.3.5,pandavro==1.5.2,pandocfilters==1.5.0,parso==0.8.3,partd==1.3.0,pathspec==0.10.2,pathtools==0.1.2,pbr==5.11.0,pep517==0.13.0,pexpect==4.8.0,pickleshare==0.7.5,Pillow==9.2.0,pkgutil_resolve_name==1.3.10,platformdirs==2.5.2,plotly==5.11.0,pluggy==1.0.0,prettytable==3.5.0,prometheus-client==0.14.1,promise==2.3,prompt-toolkit==3.0.31,proto-plus==1.19.6,protobuf==3.19.5,psutil==5.9.2,ptyprocess==0.7.0,pure-eval==0.2.2,py==1.11.0,pyarrow==7.0.0,pyasn1==0.4.8,pyasn1-modules==0.2.8,pybind11==2.10.0,pycodestyle==2.10.0,pycparser==2.21,pydantic==1.10.2,pydot==1.4.2,pyflakes==3.0.1,Pygments==2.13.0,PyGObject==3.36.0,pynvml==11.4.1,pyparsing==3.0.9,pyperclip==1.8.2,pyrsistent==0.18.1,pytest==7.1.3,pytest-cov==4.0.0,pytest-xdist==3.0.2,python-apt==2.0.0+ubuntu0.20.4.8,python-dateutil==2.8.2,python-dotenv==0.21.0,python-rapidjson==1.8,pytz==2022.2.1,PyYAML==5.4.1,pyzmq==24.0.0,qtconsole==5.4.0,QtPy==2.3.0,regex==2022.9.13,requests==2.22.0,requests-oauthlib==1.3.1,requests-unixsocket==0.2.0,rsa==4.7.2,s3fs==2022.2.0,s3transfer==0.6.0,sacremoses==0.0.53,scikit-build==0.15.0,scikit-learn==1.1.2,scipy==1.8.1,seedir==0.3.0,Send2Trash==1.8.0,sentry-sdk==1.9.8,setproctitle==1.3.2,setuptools-scm==7.0.5,shortuuid==1.0.9,six==1.15.0,sklearn==0.0,smmap==5.0.0,sniffio==1.3.0,snowballstemmer==2.2.0,sortedcontainers==2.4.0,soupsieve==2.3.2.post1,Sphinx==5.3.0,sphinx-multiversion==0.2.4,sphinx-togglebutton==0.3.1,sphinx_external_toc==0.3.0,sphinxcontrib-applehelp==1.0.2,sphinxcontrib-copydirs @ git+https://github.com/mikemckiernan/sphinxcontrib-copydirs.git@bd8c5d79b3f91cf5f1bb0d6995aeca3fe84b670e,sphinxcontrib-devhelp==1.0.2,sphinxcontrib-htmlhelp==2.0.0,sphinxcontrib-jsmath==1.0.1,sphinxcontrib-qthelp==1.0.3,sphinxcontrib-serializinghtml==1.1.5,SQLAlchemy==1.4.44,stack-data==0.5.0,starlette==0.20.4,stevedore==4.1.1,stringcase==1.2.0,supervisor==4.1.0,tabulate==0.8.10,tblib==1.7.0,tdqm==0.0.1,tenacity==8.0.1,tensorboard==2.9.1,tensorboard-data-server==0.6.1,tensorboard-plugin-wit==1.8.1,tensorflow==2.9.2,tensorflow-estimator==2.9.0,tensorflow-gpu==2.9.2,tensorflow-io-gcs-filesystem==0.27.0,tensorflow-metadata==1.10.0,termcolor==2.0.1,terminado==0.15.0,testbook==0.4.2,threadpoolctl==3.1.0,tinycss2==1.1.1,tokenizers==0.10.3,toml==0.10.2,tomli==2.0.1,toolz==0.12.0,torch==1.12.1+cu113,torchmetrics==0.3.2,tornado==6.2,tox==3.26.0,tqdm==4.64.1,traitlets==5.4.0,transformers==4.12.0,transformers4rec==0.1.12+2.gbcc939255,treelite==2.3.0,treelite-runtime==2.3.0,tritonclient==2.25.0,typed-ast==1.5.4,typing-inspect==0.8.0,typing_extensions==4.3.0,uc-micro-py==1.0.1,urllib3==1.26.12,uvicorn==0.18.3,uvloop==0.17.0,versioneer==0.20,virtualenv==20.16.5,wandb==0.13.3,watchfiles==0.17.0,wcwidth==0.2.5,webencodings==0.5.1,websocket-client==1.4.1,websockets==10.3,Werkzeug==2.2.2,widgetsnbextension==3.6.0,wrapt==1.12.1,xgboost==1.6.2,xyzservices==2022.9.0,yarl==1.8.1,zict==2.2.0,zipp==3.8.1,zope.event==4.5.0,zope.interface==5.4.0
py38-gpu run-test-pre: PYTHONHASHSEED='3225772755'
py38-gpu run-test: commands[0] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/core.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/core.git
  Cloning https://github.com/NVIDIA-Merlin/core.git to /tmp/pip-req-build-vnl6f4ur
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/core.git /tmp/pip-req-build-vnl6f4ur
  Resolved https://github.com/NVIDIA-Merlin/core.git to commit 4f73ff5bd4121c1acaabdc01a123af4f986ffc78
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (3.19.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (7.0.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (2022.3.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (1.10.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (2022.5.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core==0.9.0+14.g4f73ff5) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (1.3.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core==0.9.0+14.g4f73ff5) (0.55.1)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (0.12.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (3.1.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.0.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.0.4)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (6.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (5.8.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (8.1.3)
Requirement already satisfied: llvmlite<0.39,>=0.38.0rc1 in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+14.g4f73ff5) (0.38.1)
Requirement already satisfied: numpy<1.22,>=1.18 in /var/jenkins_home/.local/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+14.g4f73ff5) (1.20.3)
Requirement already satisfied: setuptools in ./.tox/py38-gpu/lib/python3.8/site-packages (from numba>=0.54->merlin-core==0.9.0+14.g4f73ff5) (65.5.1)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging->merlin-core==0.9.0+14.g4f73ff5) (3.0.9)
Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (2.8.2)
Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (2022.2.1)
Requirement already satisfied: googleapis-common-protos<2,>=1.52.0 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.52.0)
Requirement already satisfied: absl-py<2.0.0,>=0.9 in /usr/local/lib/python3.8/dist-packages (from tensorflow-metadata>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.2.0)
Requirement already satisfied: locket in /var/jenkins_home/.local/lib/python3.8/site-packages/locket-0.2.1-py3.8.egg (from partd>=0.3.10->dask>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (0.2.1)
Requirement already satisfied: six>=1.5 in /var/jenkins_home/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas<1.4.0dev0,>=1.2.0->merlin-core==0.9.0+14.g4f73ff5) (1.15.0)
Requirement already satisfied: heapdict in /var/jenkins_home/.local/lib/python3.8/site-packages/HeapDict-1.0.1-py3.8.egg (from zict>=0.1.3->distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (1.0.1)
Requirement already satisfied: h2<5,>=3.1.0 in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (4.1.0)
Requirement already satisfied: multidict in /usr/local/lib/python3.8/dist-packages (from grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (6.0.2)
Requirement already satisfied: MarkupSafe>=2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from jinja2->distributed>=2022.3.0->merlin-core==0.9.0+14.g4f73ff5) (2.0.1)
Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core==0.9.0+14.g4f73ff5) (6.0.1)
Building wheels for collected packages: merlin-core
  Building wheel for merlin-core (pyproject.toml): started
  Building wheel for merlin-core (pyproject.toml): finished with status 'done'
  Created wheel for merlin-core: filename=merlin_core-0.9.0+14.g4f73ff5-py3-none-any.whl size=119010 sha256=67dc16b10f6e558c634002ee44bd147cf2eab9c4084bc0c26c70d8635706056a
  Stored in directory: /tmp/pip-ephem-wheel-cache-no27gw5f/wheels/c8/38/16/a6968787eafcec5fa772148af8408b089562f71af0752e8e84
Successfully built merlin-core
Installing collected packages: merlin-core
  Attempting uninstall: merlin-core
    Found existing installation: merlin-core 0.3.0+12.g78ecddd
    Not uninstalling merlin-core at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'merlin-core'. No files were found to uninstall.
Successfully installed merlin-core-0.9.0+14.g4f73ff5
py38-gpu run-test: commands[1] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/dataloader.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/dataloader.git
  Cloning https://github.com/NVIDIA-Merlin/dataloader.git to /tmp/pip-req-build-05efha0z
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/dataloader.git /tmp/pip-req-build-05efha0z
  Resolved https://github.com/NVIDIA-Merlin/dataloader.git to commit 498543d54629216dc09a5854dca4dbeeabcab356
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.8.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from merlin-dataloader==0.0.2+22.g498543d) (0.9.0+14.g4f73ff5)
Requirement already satisfied: protobuf>=3.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (3.19.5)
Requirement already satisfied: pyarrow>=5.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (7.0.0)
Requirement already satisfied: dask>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (2022.3.0)
Requirement already satisfied: tensorflow-metadata>=1.2.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.10.0)
Requirement already satisfied: distributed>=2022.3.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (2022.3.0)
Requirement already satisfied: betterproto<2.0.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.2.5)
Requirement already satisfied: fsspec==2022.5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (2022.5.0)
Requirement already satisfied: packaging in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (21.3)
Requirement already satisfied: tqdm>=4.0 in /usr/local/lib/python3.8/dist-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (4.64.1)
Requirement already satisfied: pandas<1.4.0dev0,>=1.2.0 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.3.5)
Requirement already satisfied: numba>=0.54 in /var/jenkins_home/.local/lib/python3.8/site-packages (from merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (0.55.1)
Requirement already satisfied: grpclib in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (0.4.3)
Requirement already satisfied: stringcase in /usr/local/lib/python3.8/dist-packages (from betterproto<2.0.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.2.0)
Requirement already satisfied: partd>=0.3.10 in /var/jenkins_home/.local/lib/python3.8/site-packages/partd-1.2.0-py3.8.egg (from dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.2.0)
Requirement already satisfied: cloudpickle>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (2.2.0)
Requirement already satisfied: pyyaml>=5.3.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/PyYAML-5.4.1-py3.8-linux-x86_64.egg (from dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (5.4.1)
Requirement already satisfied: toolz>=0.8.2 in /usr/local/lib/python3.8/dist-packages (from dask>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (0.12.0)
Requirement already satisfied: tblib>=1.6.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/tblib-1.7.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.7.0)
Requirement already satisfied: jinja2 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (3.1.2)
Requirement already satisfied: zict>=0.1.3 in /var/jenkins_home/.local/lib/python3.8/site-packages/zict-2.0.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (2.0.0)
Requirement already satisfied: msgpack>=0.6.0 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (1.0.4)
Requirement already satisfied: sortedcontainers!=2.0.0,!=2.0.1 in /var/jenkins_home/.local/lib/python3.8/site-packages/sortedcontainers-2.4.0-py3.8.egg (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (2.4.0)
Requirement already satisfied: tornado>=6.0.3 in ./.tox/py38-gpu/lib/python3.8/site-packages (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (6.2)
Requirement already satisfied: psutil>=5.0 in /var/jenkins_home/.local/lib/python3.8/site-packages/psutil-5.8.0-py3.8-linux-x86_64.egg (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (5.8.0)
Requirement already satisfied: click>=6.6 in /usr/local/lib/python3.8/dist-packages (from distributed>=2022.3.0->merlin-core>=0.8.0->merlin-dataloader==0.0.2+22.g498543d) (8.1.3)
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Building wheels for collected packages: merlin-dataloader
  Building wheel for merlin-dataloader (pyproject.toml): started
  Building wheel for merlin-dataloader (pyproject.toml): finished with status 'done'
  Created wheel for merlin-dataloader: filename=merlin_dataloader-0.0.2+22.g498543d-py3-none-any.whl size=40350 sha256=426320f4fbdb6ff4c055a1d5f47ef62ae6bceafc061af03c0e12880fd191fc65
  Stored in directory: /tmp/pip-ephem-wheel-cache-c7vlzoys/wheels/de/f5/d9/251909f4627d2920fb15548f5ffd6daf1bf24c3c56bb4977b1
Successfully built merlin-dataloader
Installing collected packages: merlin-dataloader
  Attempting uninstall: merlin-dataloader
    Found existing installation: merlin-dataloader 0.0.3
    Uninstalling merlin-dataloader-0.0.3:
      Successfully uninstalled merlin-dataloader-0.0.3
Successfully installed merlin-dataloader-0.0.2+22.g498543d
py38-gpu run-test: commands[2] | python -m pip install --upgrade git+https://github.com/NVIDIA-Merlin/nvtabular.git
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com
Collecting git+https://github.com/NVIDIA-Merlin/nvtabular.git
  Cloning https://github.com/NVIDIA-Merlin/nvtabular.git to /tmp/pip-req-build-_dci65eu
  Running command git clone --filter=blob:none --quiet https://github.com/NVIDIA-Merlin/nvtabular.git /tmp/pip-req-build-_dci65eu
  Resolved https://github.com/NVIDIA-Merlin/nvtabular.git to commit 51af616069689b3ba57e8842a6f4a20377795df7
  Installing build dependencies: started
  Installing build dependencies: finished with status 'done'
  Getting requirements to build wheel: started
  Getting requirements to build wheel: finished with status 'done'
  Preparing metadata (pyproject.toml): started
  Preparing metadata (pyproject.toml): finished with status 'done'
Requirement already satisfied: merlin-core>=0.2.0 in ./.tox/py38-gpu/lib/python3.8/site-packages (from nvtabular==1.6.0+13.g51af6160) (0.9.0+14.g4f73ff5)
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Requirement already satisfied: hpack<5,>=4.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+13.g51af6160) (4.0.0)
Requirement already satisfied: hyperframe<7,>=6.0 in /usr/local/lib/python3.8/dist-packages (from h2<5,>=3.1.0->grpclib->betterproto<2.0.0->merlin-core>=0.2.0->nvtabular==1.6.0+13.g51af6160) (6.0.1)
Building wheels for collected packages: nvtabular
  Building wheel for nvtabular (pyproject.toml): started
  Building wheel for nvtabular (pyproject.toml): finished with status 'done'
  Created wheel for nvtabular: filename=nvtabular-1.6.0+13.g51af6160-cp38-cp38-linux_x86_64.whl size=257601 sha256=aa43fcc21e470c2da24c6cafdfed99e18ff16fa20edfbff2ecac83b02b580d12
  Stored in directory: /tmp/pip-ephem-wheel-cache-a9rfiktp/wheels/8f/d9/f9/30f2cdc5bf8787fae6fdfe55afd6e1b493e619ec32c32ec40b
Successfully built nvtabular
Installing collected packages: nvtabular
  Attempting uninstall: nvtabular
    Found existing installation: nvtabular 1.1.1
    Not uninstalling nvtabular at /var/jenkins_home/.local/lib/python3.8/site-packages, outside environment /var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu
    Can't uninstall 'nvtabular'. No files were found to uninstall.
Successfully installed nvtabular-1.6.0+13.g51af6160
py38-gpu run-test: commands[3] | python -m pytest --cov-report term --cov merlin -rxs tests/unit
============================= test session starts ==============================
platform linux -- Python 3.8.10, pytest-7.1.3, pluggy-1.0.0
cachedir: .tox/py38-gpu/.pytest_cache
rootdir: /var/jenkins_home/workspace/merlin_models/models, configfile: pyproject.toml
plugins: anyio-3.5.0, xdist-3.0.2, cov-4.0.0
collected 877 items
tests/unit/config/test_schema.py ....                                    [  0%]

tests/unit/datasets/test_advertising.py .s                               [  0%]

tests/unit/datasets/test_ecommerce.py ..sss.s                            [  1%]

tests/unit/datasets/test_entertainment.py ....sss.                       [  2%]

tests/unit/datasets/test_social.py .                                     [  2%]

tests/unit/datasets/test_synthetic.py ..........                         [  3%]

tests/unit/implicit/test_implicit.py .                                   [  3%]

tests/unit/lightfm/test_lightfm.py .                                     [  3%]

tests/unit/tf/test_core.py ......                                        [  4%]

tests/unit/tf/test_loader.py ................                            [  6%]

tests/unit/tf/test_public_api.py .                                       [  6%]

tests/unit/tf/blocks/test_cross.py ...........                           [  7%]

tests/unit/tf/blocks/test_dlrm.py ..........                             [  8%]

tests/unit/tf/blocks/test_interactions.py ...                            [  9%]

tests/unit/tf/blocks/test_mlp.py ....................................... [ 13%]

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tests/unit/tf/blocks/test_optimizer.py s................................ [ 20%]

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tests/unit/tf/blocks/retrieval/test_base.py .                            [ 23%]

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py ..           [ 23%]

tests/unit/tf/blocks/retrieval/test_two_tower.py ............            [ 24%]

tests/unit/tf/blocks/sampling/test_cross_batch.py .                      [ 24%]

tests/unit/tf/blocks/sampling/test_in_batch.py .                         [ 24%]

tests/unit/tf/core/test_aggregation.py .........                         [ 25%]

tests/unit/tf/core/test_base.py ..                                       [ 26%]

tests/unit/tf/core/test_combinators.py s.....................            [ 28%]

tests/unit/tf/core/test_encoder.py ..                                    [ 28%]

tests/unit/tf/core/test_index.py ...                                     [ 29%]

tests/unit/tf/core/test_prediction.py ..                                 [ 29%]

tests/unit/tf/core/test_tabular.py ......                                [ 30%]

tests/unit/tf/examples/test_01_getting_started.py .                      [ 30%]

tests/unit/tf/examples/test_02_dataschema.py .                           [ 30%]

tests/unit/tf/examples/test_03_exploring_different_models.py .           [ 30%]

tests/unit/tf/examples/test_04_export_ranking_models.py .                [ 30%]

tests/unit/tf/examples/test_05_export_retrieval_model.py .               [ 30%]

tests/unit/tf/examples/test_06_advanced_own_architecture.py .            [ 30%]

tests/unit/tf/examples/test_07_train_traditional_models.py .             [ 31%]

tests/unit/tf/examples/test_usecase_accelerate_training_by_lazyadam.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_data_parallel.py .                   [ 31%]

tests/unit/tf/examples/test_usecase_ecommerce_session_based.py .         [ 31%]

tests/unit/tf/examples/test_usecase_incremental_training_layer_freezing.py . [ 31%]

[ 31%]

tests/unit/tf/examples/test_usecase_pretrained_embeddings.py .           [ 31%]

tests/unit/tf/examples/test_usecase_retrieval_with_hpo.py .              [ 31%]

tests/unit/tf/examples/test_usecase_transformers_next_item_prediction.py . [ 31%]

[ 31%]

tests/unit/tf/horovod/test_horovod.py ...                                [ 32%]

tests/unit/tf/inputs/test_base.py .                                      [ 32%]

tests/unit/tf/inputs/test_continuous.py ........                         [ 33%]

tests/unit/tf/inputs/test_embedding.py ................................. [ 36%]

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tests/unit/tf/inputs/test_tabular.py ..................                  [ 39%]

tests/unit/tf/layers/test_queue.py ..............                        [ 41%]

tests/unit/tf/losses/test_losses.py .......................              [ 44%]

tests/unit/tf/metrics/test_metrics_popularity.py .....                   [ 44%]

tests/unit/tf/metrics/test_metrics_topk.py .........................     [ 47%]

tests/unit/tf/models/test_base.py s.........................             [ 50%]

tests/unit/tf/models/test_benchmark.py ..                                [ 50%]

tests/unit/tf/models/test_ranking.py ..................................  [ 54%]

tests/unit/tf/models/test_retrieval.py ................................. [ 58%]

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tests/unit/tf/outputs/test_base.py ......                                [ 64%]

tests/unit/tf/outputs/test_classification.py ......                      [ 64%]

tests/unit/tf/outputs/test_contrastive.py ..............                 [ 66%]

tests/unit/tf/outputs/test_regression.py ..                              [ 66%]

tests/unit/tf/outputs/test_sampling.py ....                              [ 67%]

tests/unit/tf/outputs/test_topk.py .                                     [ 67%]

tests/unit/tf/prediction_tasks/test_classification.py ..                 [ 67%]

tests/unit/tf/prediction_tasks/test_multi_task.py ................       [ 69%]

tests/unit/tf/prediction_tasks/test_next_item.py .....                   [ 69%]

tests/unit/tf/prediction_tasks/test_regression.py .....                  [ 70%]

tests/unit/tf/prediction_tasks/test_retrieval.py .                       [ 70%]

tests/unit/tf/prediction_tasks/test_sampling.py ......                   [ 71%]

tests/unit/tf/transformers/test_block.py ......................          [ 73%]

tests/unit/tf/transformers/test_transforms.py ..........                 [ 74%]

tests/unit/tf/transforms/test_bias.py ..                                 [ 75%]

tests/unit/tf/transforms/test_features.py s............................. [ 78%]

.......................s......                                           [ 81%]

tests/unit/tf/transforms/test_negative_sampling.py .........             [ 83%]

tests/unit/tf/transforms/test_noise.py .....                             [ 83%]

tests/unit/tf/transforms/test_sequence.py ....................           [ 85%]

tests/unit/tf/transforms/test_tensor.py ...                              [ 86%]

tests/unit/tf/utils/test_batch.py ....                                   [ 86%]

tests/unit/tf/utils/test_dataset.py ..                                   [ 86%]

tests/unit/tf/utils/test_tf_utils.py .....                               [ 87%]

tests/unit/torch/test_public_api.py .                                    [ 87%]

tests/unit/torch/block/test_base.py ....                                 [ 88%]

tests/unit/torch/block/test_mlp.py .                                     [ 88%]

tests/unit/torch/features/test_continuous.py ..                          [ 88%]

tests/unit/torch/features/test_embedding.py ..............               [ 89%]

tests/unit/torch/features/test_tabular.py ....                           [ 90%]

tests/unit/torch/model/test_head.py ............                         [ 91%]

tests/unit/torch/model/test_model.py ..                                  [ 92%]

tests/unit/torch/tabular/test_aggregation.py ........                    [ 92%]

tests/unit/torch/tabular/test_tabular.py ...                             [ 93%]

tests/unit/torch/tabular/test_transformations.py .......                 [ 94%]

tests/unit/utils/test_schema_utils.py ................................   [ 97%]

tests/unit/xgb/test_xgboost.py ....................                      [100%]
=============================== warnings summary ===============================

../../../../../usr/lib/python3/dist-packages/requests/init.py:89

/usr/lib/python3/dist-packages/requests/init.py:89: RequestsDependencyWarning: urllib3 (1.26.12) or chardet (3.0.4) doesn't match a supported version!

warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
../../../.local/lib/python3.8/site-packages/flatbuffers/compat.py:19

/var/jenkins_home/.local/lib/python3.8/site-packages/flatbuffers/compat.py:19: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses

import imp
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:36: DeprecationWarning: NEAREST is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.NEAREST or Dither.NONE instead.

'nearest': pil_image.NEAREST,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:37: DeprecationWarning: BILINEAR is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BILINEAR instead.

'bilinear': pil_image.BILINEAR,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:38: DeprecationWarning: BICUBIC is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BICUBIC instead.

'bicubic': pil_image.BICUBIC,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:39: DeprecationWarning: HAMMING is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.HAMMING instead.

'hamming': pil_image.HAMMING,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:40: DeprecationWarning: BOX is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.BOX instead.

'box': pil_image.BOX,
../../../.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/utils/image_utils.py:41: DeprecationWarning: LANCZOS is deprecated and will be removed in Pillow 10 (2023-07-01). Use Resampling.LANCZOS instead.

'lanczos': pil_image.LANCZOS,
tests/unit/datasets/test_advertising.py: 1 warning

tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 10 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 6 warnings

tests/unit/tf/core/test_index.py: 8 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 6 warnings

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 38 warnings

tests/unit/tf/models/test_retrieval.py: 123 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/prediction_tasks/test_retrieval.py: 1 warning

tests/unit/tf/transformers/test_block.py: 16 warnings

tests/unit/tf/transforms/test_bias.py: 2 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_noise.py: 1 warning

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 9 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 3 warnings

tests/unit/xgb/test_xgboost.py: 18 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 3 warnings

tests/unit/datasets/test_entertainment.py: 4 warnings

tests/unit/datasets/test_social.py: 1 warning

tests/unit/datasets/test_synthetic.py: 9 warnings

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_core.py: 6 warnings

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/test_cross.py: 5 warnings

tests/unit/tf/blocks/test_dlrm.py: 9 warnings

tests/unit/tf/blocks/test_interactions.py: 2 warnings

tests/unit/tf/blocks/test_mlp.py: 60 warnings

tests/unit/tf/blocks/test_optimizer.py: 30 warnings

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 11 warnings

tests/unit/tf/core/test_aggregation.py: 6 warnings

tests/unit/tf/core/test_base.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 8 warnings

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/core/test_prediction.py: 2 warnings

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_base.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 7 warnings

tests/unit/tf/inputs/test_embedding.py: 20 warnings

tests/unit/tf/inputs/test_tabular.py: 18 warnings

tests/unit/tf/models/test_base.py: 28 warnings

tests/unit/tf/models/test_benchmark.py: 2 warnings

tests/unit/tf/models/test_ranking.py: 36 warnings

tests/unit/tf/models/test_retrieval.py: 99 warnings

tests/unit/tf/outputs/test_base.py: 6 warnings

tests/unit/tf/outputs/test_classification.py: 6 warnings

tests/unit/tf/outputs/test_contrastive.py: 19 warnings

tests/unit/tf/outputs/test_regression.py: 2 warnings

tests/unit/tf/prediction_tasks/test_classification.py: 2 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 5 warnings

tests/unit/tf/transformers/test_block.py: 12 warnings

tests/unit/tf/transforms/test_features.py: 10 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 10 warnings

tests/unit/tf/transforms/test_sequence.py: 15 warnings

tests/unit/tf/utils/test_batch.py: 7 warnings

tests/unit/tf/utils/test_dataset.py: 2 warnings

tests/unit/torch/block/test_base.py: 4 warnings

tests/unit/torch/block/test_mlp.py: 1 warning

tests/unit/torch/features/test_continuous.py: 1 warning

tests/unit/torch/features/test_embedding.py: 4 warnings

tests/unit/torch/features/test_tabular.py: 4 warnings

tests/unit/torch/model/test_head.py: 12 warnings

tests/unit/torch/model/test_model.py: 2 warnings

tests/unit/torch/tabular/test_aggregation.py: 6 warnings

tests/unit/torch/tabular/test_transformations.py: 2 warnings

tests/unit/xgb/test_xgboost.py: 17 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/datasets/test_ecommerce.py: 1 warning

tests/unit/datasets/test_entertainment.py: 1 warning

tests/unit/implicit/test_implicit.py: 1 warning

tests/unit/lightfm/test_lightfm.py: 1 warning

tests/unit/tf/test_loader.py: 1 warning

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py: 2 warnings

tests/unit/tf/blocks/retrieval/test_two_tower.py: 2 warnings

tests/unit/tf/core/test_combinators.py: 11 warnings

tests/unit/tf/core/test_encoder.py: 2 warnings

tests/unit/tf/core/test_prediction.py: 1 warning

tests/unit/tf/horovod/test_horovod.py: 1 warning

tests/unit/tf/inputs/test_continuous.py: 4 warnings

tests/unit/tf/inputs/test_embedding.py: 9 warnings

tests/unit/tf/inputs/test_tabular.py: 8 warnings

tests/unit/tf/models/test_ranking.py: 20 warnings

tests/unit/tf/models/test_retrieval.py: 10 warnings

tests/unit/tf/prediction_tasks/test_multi_task.py: 16 warnings

tests/unit/tf/prediction_tasks/test_regression.py: 3 warnings

tests/unit/tf/transforms/test_negative_sampling.py: 9 warnings

tests/unit/xgb/test_xgboost.py: 12 warnings

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.SESSION_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.SESSION: 'session'>, <Tags.ID: 'id'>].

warnings.warn(
tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_matrix_factorization.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/blocks/retrieval/test_two_tower.py::test_matrix_factorization_embedding_export

tests/unit/tf/inputs/test_embedding.py::test_embedding_features_exporting_and_loading_pretrained_initializer

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/inputs/embedding.py:970: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

embeddings_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(embeddings)))
tests/unit/tf/blocks/retrieval/test_two_tower.py: 1 warning

tests/unit/tf/core/test_index.py: 4 warnings

tests/unit/tf/horovod/test_horovod.py: 4 warnings

tests/unit/tf/models/test_retrieval.py: 63 warnings

tests/unit/tf/prediction_tasks/test_next_item.py: 3 warnings

tests/unit/tf/utils/test_batch.py: 2 warnings

/tmp/autograph_generated_filev182y83k.py:8: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead

ag.converted_call(ag__.ld(warnings).warn, ("The 'warn' method is deprecated, use 'warning' instead", ag__.ld(DeprecationWarning), 2), None, fscope)
tests/unit/tf/core/test_combinators.py::test_parallel_block_select_by_tags

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/core/tabular.py:602: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working

elif isinstance(self.feature_names, collections.Sequence):
tests/unit/tf/core/test_index.py: 5 warnings

tests/unit/tf/models/test_retrieval.py: 30 warnings

tests/unit/tf/utils/test_batch.py: 4 warnings

tests/unit/tf/utils/test_dataset.py: 1 warning

/var/jenkins_home/workspace/merlin_models/models/merlin/models/utils/dataset.py:75: DeprecationWarning: unique_rows_by_features is deprecated and will be removed in a future version. Please use unique_by_tag instead.

warnings.warn(
tests/unit/tf/models/test_base.py::test_model_pre_post[True]

tests/unit/tf/models/test_base.py::test_model_pre_post[False]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.1]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.3]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.5]

tests/unit/tf/transforms/test_noise.py::test_stochastic_swap_noise[0.7]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082: UserWarning: tf.keras.backend.random_binomial is deprecated, and will be removed in a future version.Please use tf.keras.backend.random_bernoulli instead.

return dispatch_target(*args, **kwargs)
tests/unit/tf/models/test_base.py::test_freeze_parallel_block[True]

tests/unit/tf/models/test_base.py::test_freeze_sequential_block

tests/unit/tf/models/test_base.py::test_freeze_unfreeze

tests/unit/tf/models/test_base.py::test_unfreeze_all_blocks

/var/jenkins_home/.local/lib/python3.8/site-packages/keras/optimizers/optimizer_v2/gradient_descent.py:108: UserWarning: The lr argument is deprecated, use learning_rate instead.

super(SGD, self).init(name, **kwargs)
tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_base.py::test_retrieval_model_query

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_v2_export_embeddings

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[True]

tests/unit/tf/models/test_retrieval.py::test_youtube_dnn_topk_evaluation[False]

tests/unit/tf/transformers/test_block.py::test_retrieval_transformer[True]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/utils/tf_utils.py:298: DeprecationWarning: This function is deprecated in favor of cupy.from_dlpack

tensor_cupy = cupy.fromDlpack(to_dlpack(tf.convert_to_tensor(tensor)))
tests/unit/tf/models/test_ranking.py::test_deepfm_model_only_categ_feats[False]

tests/unit/tf/models/test_ranking.py::test_deepfm_model_categ_and_continuous_feats[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_3/parallel_block_2/sequential_block_3/sequential_block_2/private__dense_1/dense_1/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_categorical_one_hot[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_model_hashed_cross[False]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_2/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[True]

tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/workspace/merlin_models/models/merlin/models/tf/transforms/features.py:569: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_embedding_custom_inputblock[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py:371: UserWarning: Please make sure input features to be categorical, detect user_age has no categorical tag

return py_builtins.overload_of(f)(*args)
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_onehot_multihot_feature_interaction[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_5/sequential_block_9/sequential_block_8/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/models/test_ranking.py::test_wide_deep_model_wide_feature_interaction_multi_optimizer[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape_1:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Reshape:0", shape=(None, 1), dtype=float32), dense_shape=Tensor("gradient_tape/model/parallel_block_4/sequential_block_6/sequential_block_5/private__dense_3/dense_3/embedding_lookup_sparse/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classification_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_as_classification_model[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_causal_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/prepare_transformer_inputs_1/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/bert_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask_1/GatherV2:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/boolean_mask/GatherV2:0", shape=(None, 48), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/prepare_transformer_inputs_5/RaggedToTensor/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_3:0", shape=(None,), dtype=int64), values=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Reshape_2:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/Cast:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_1:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/tf/transformers/test_block.py::test_transformer_with_masked_language_modeling_check_eval_masked[False]

/var/jenkins_home/.local/lib/python3.8/site-packages/tensorflow/python/framework/indexed_slices.py:444: UserWarning: Converting sparse IndexedSlices(IndexedSlices(indices=Tensor("gradient_tape/model/gpt2_block/replace_masked_embeddings/RaggedWhere/RaggedTile_2/Reshape_3:0", shape=(None,), dtype=int32), values=Tensor("gradient_tape/model/concat_features/RaggedConcat/Slice_3:0", shape=(None, None), dtype=float32), dense_shape=Tensor("gradient_tape/model/concat_features/RaggedConcat/Shape_1:0", shape=(2,), dtype=int32))) to a dense Tensor of unknown shape. This may consume a large amount of memory.

warnings.warn(
tests/unit/torch/block/test_mlp.py::test_mlp_block

/var/jenkins_home/workspace/merlin_models/models/tests/unit/torch/_conftest.py:151: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at  ../torch/csrc/utils/tensor_new.cpp:201.)

return {key: torch.tensor(value) for key, value in data.items()}
tests/unit/xgb/test_xgboost.py::test_without_dask_client

tests/unit/xgb/test_xgboost.py::TestXGBoost::test_music_regression

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs0-DaskDeviceQuantileDMatrix]

tests/unit/xgb/test_xgboost.py::test_gpu_hist_dmatrix[fit_kwargs1-DaskDMatrix]

tests/unit/xgb/test_xgboost.py::TestEvals::test_multiple

tests/unit/xgb/test_xgboost.py::TestEvals::test_default

tests/unit/xgb/test_xgboost.py::TestEvals::test_train_and_valid

tests/unit/xgb/test_xgboost.py::TestEvals::test_invalid_data

/var/jenkins_home/workspace/merlin_models/models/merlin/models/xgb/init.py:344: UserWarning: Ignoring list columns as inputs to XGBoost model: ['item_genres', 'user_genres'].

warnings.warn(f"Ignoring list columns as inputs to XGBoost model: {list_column_names}.")
tests/unit/xgb/test_xgboost.py::TestXGBoost::test_unsupported_objective

/var/jenkins_home/workspace/merlin_models/models/.tox/py38-gpu/lib/python3.8/site-packages/tornado/ioloop.py:350: DeprecationWarning: make_current is deprecated; start the event loop first

self.make_current()
tests/unit/xgb/test_xgboost.py: 14 warnings

/usr/local/lib/python3.8/dist-packages/xgboost/dask.py:884: RuntimeWarning: coroutine 'Client._wait_for_workers' was never awaited

client.wait_for_workers(n_workers)

Enable tracemalloc to get traceback where the object was allocated.

See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info.
tests/unit/xgb/test_xgboost.py: 11 warnings

/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:1183: DeprecationWarning: The default dtype for empty Series will be 'object' instead of 'float64' in a future version. Specify a dtype explicitly to silence this warning.

mask = pd.Series(mask)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
---------- coverage: platform linux, python 3.8.10-final-0 -----------

Name                                                                 Stmts   Miss  Cover
merlin/datasets/init.py                                              2      0   100%

merlin/datasets/advertising/init.py                                  2      0   100%

merlin/datasets/advertising/criteo/init.py                           0      0   100%

merlin/datasets/advertising/criteo/dataset.py                           79     49    38%

merlin/datasets/advertising/criteo/transformed/init.py               0      0   100%

merlin/datasets/ecommerce/init.py                                    4      0   100%

merlin/datasets/ecommerce/aliccp/init.py                             0      0   100%

merlin/datasets/ecommerce/aliccp/dataset.py                            141     87    38%

merlin/datasets/ecommerce/aliccp/raw/init.py                         0      0   100%

merlin/datasets/ecommerce/aliccp/transformed/init.py                 0      0   100%

merlin/datasets/ecommerce/booking/init.py                            0      0   100%

merlin/datasets/ecommerce/booking/dataset.py                           127    100    21%

merlin/datasets/ecommerce/booking/raw/init.py                        0      0   100%

merlin/datasets/ecommerce/booking/transformed/init.py                0      0   100%

merlin/datasets/ecommerce/dressipi/init.py                           0      0   100%

merlin/datasets/ecommerce/dressipi/dataset.py                           45     37    18%

merlin/datasets/ecommerce/dressipi/preprocessed/init.py              0      0   100%

merlin/datasets/ecommerce/large/init.py                              0      0   100%

merlin/datasets/ecommerce/small/init.py                              0      0   100%

merlin/datasets/ecommerce/transactions/init.py                       0      0   100%

merlin/datasets/entertainment/init.py                                2      0   100%

merlin/datasets/entertainment/movielens/1m-raw/init.py               0      0   100%

merlin/datasets/entertainment/movielens/1m-raw/ratings/init.py       0      0   100%

merlin/datasets/entertainment/movielens/1m/init.py                   0      0   100%

merlin/datasets/entertainment/movielens/25m/init.py                  0      0   100%

merlin/datasets/entertainment/movielens/100k/init.py                 0      0   100%

merlin/datasets/entertainment/movielens/init.py                      0      0   100%

merlin/datasets/entertainment/movielens/dataset.py                     152    122    20%

merlin/datasets/entertainment/music_streaming/init.py                0      0   100%

merlin/datasets/social/init.py                                       0      0   100%

merlin/datasets/synthetic.py                                           155      8    95%

merlin/datasets/testing/init.py                                      0      0   100%

merlin/datasets/testing/sequence_testing/init.py                     0      0   100%

merlin/models/init.py                                                2      0   100%

merlin/models/_version.py                                              354    205    42%

merlin/models/api.py                                                    14      5    64%

merlin/models/config/init.py                                         0      0   100%

merlin/models/config/schema.py                                          62      0   100%

merlin/models/implicit/init.py                                      27      4    85%

merlin/models/io.py                                                     15      0   100%

merlin/models/lightfm/init.py                                       23      0   100%

merlin/models/loader/init.py                                         0      0   100%

merlin/models/loader/backend.py                                         16      5    69%

merlin/models/tf/init.py                                            69      0   100%

merlin/models/tf/blocks/init.py                                      0      0   100%

merlin/models/tf/blocks/cross.py                                        44      0   100%

merlin/models/tf/blocks/dlrm.py                                         49      2    96%

merlin/models/tf/blocks/experts.py                                      99     17    83%

merlin/models/tf/blocks/interaction.py                                 108     40    63%

merlin/models/tf/blocks/mlp.py                                         117      7    94%

merlin/models/tf/blocks/optimizer.py                                   173     12    93%

merlin/models/tf/blocks/retrieval/init.py                            0      0   100%

merlin/models/tf/blocks/retrieval/base.py                              175     62    65%

merlin/models/tf/blocks/retrieval/matrix_factorization.py               35      1    97%

merlin/models/tf/blocks/retrieval/two_tower.py                          30      0   100%

merlin/models/tf/blocks/sampling/init.py                             0      0   100%

merlin/models/tf/blocks/sampling/base.py                                29      2    93%

merlin/models/tf/blocks/sampling/cross_batch.py                         46      2    96%

merlin/models/tf/blocks/sampling/in_batch.py                            35      0   100%

merlin/models/tf/blocks/sampling/queue.py                              115     12    90%

merlin/models/tf/core/init.py                                        0      0   100%

merlin/models/tf/core/aggregation.py                                   241     45    81%

merlin/models/tf/core/base.py                                          242     51    79%

merlin/models/tf/core/combinators.py                                   426     53    88%

merlin/models/tf/core/encoder.py                                       182     28    85%

merlin/models/tf/core/index.py                                         106     16    85%

merlin/models/tf/core/prediction.py                                     50      1    98%

merlin/models/tf/core/tabular.py                                       280     29    90%

merlin/models/tf/distributed/init.py                                 0      0   100%

merlin/models/tf/distributed/backend.py                                  9      2    78%

merlin/models/tf/inputs/init.py                                      0      0   100%

merlin/models/tf/inputs/base.py                                         64     20    69%

merlin/models/tf/inputs/continuous.py                                   39      3    92%

merlin/models/tf/inputs/embedding.py                                   458     51    89%

merlin/models/tf/loader.py                                             131     37    72%

merlin/models/tf/losses/init.py                                      4      0   100%

merlin/models/tf/losses/base.py                                          9      0   100%

merlin/models/tf/losses/listwise.py                                     13      0   100%

merlin/models/tf/losses/pairwise.py                                    115      1    99%

merlin/models/tf/metrics/init.py                                     2      0   100%

merlin/models/tf/metrics/evaluation.py                                 105     48    54%

merlin/models/tf/metrics/topk.py                                       198     48    76%

merlin/models/tf/models/init.py                                      0      0   100%

merlin/models/tf/models/base.py                                        772    101    87%

merlin/models/tf/models/benchmark.py                                    16      0   100%

merlin/models/tf/models/ranking.py                                      67      3    96%

merlin/models/tf/models/retrieval.py                                    78      4    95%

merlin/models/tf/models/utils.py                                        10      1    90%

merlin/models/tf/outputs/init.py                                     0      0   100%

merlin/models/tf/outputs/base.py                                       123     17    86%

merlin/models/tf/outputs/classification.py                              91      1    99%

merlin/models/tf/outputs/contrastive.py                                147     10    93%

merlin/models/tf/outputs/regression.py                                   9      0   100%

merlin/models/tf/outputs/sampling/init.py                            0      0   100%

merlin/models/tf/outputs/sampling/base.py                               78     21    73%

merlin/models/tf/outputs/sampling/in_batch.py                           37      1    97%

merlin/models/tf/outputs/sampling/popularity.py                         27      1    96%

merlin/models/tf/outputs/topk.py                                        98      6    94%

merlin/models/tf/prediction_tasks/init.py                            0      0   100%

merlin/models/tf/prediction_tasks/base.py                              207     37    82%

merlin/models/tf/prediction_tasks/classification.py                     68     17    75%

merlin/models/tf/prediction_tasks/multi.py                               7      0   100%

merlin/models/tf/prediction_tasks/next_item.py                          59     17    71%

merlin/models/tf/prediction_tasks/regression.py                         35      2    94%

merlin/models/tf/prediction_tasks/retrieval.py                          73      3    96%

merlin/models/tf/transformers/init.py                                0      0   100%

merlin/models/tf/transformers/block.py                                 101      2    98%

merlin/models/tf/transformers/transforms.py                             63      0   100%

merlin/models/tf/transforms/init.py                                  0      0   100%

merlin/models/tf/transforms/bias.py                                    111      9    92%

merlin/models/tf/transforms/features.py                                435     45    90%

merlin/models/tf/transforms/negative_sampling.py                        77      4    95%

merlin/models/tf/transforms/noise.py                                    43      1    98%

merlin/models/tf/transforms/regularization.py                           17      1    94%

merlin/models/tf/transforms/sequence.py                                282     42    85%

merlin/models/tf/transforms/tensor.py                                  165     16    90%

merlin/models/tf/typing.py                                               7      0   100%

merlin/models/tf/utils/init.py                                       0      0   100%

merlin/models/tf/utils/batch_utils.py                                   85      4    95%

merlin/models/tf/utils/repr_utils.py                                    69      4    94%

merlin/models/tf/utils/search_utils.py                                  34     22    35%

merlin/models/tf/utils/testing_utils.py                                210     36    83%

merlin/models/tf/utils/tf_utils.py                                     209     43    79%

merlin/models/torch/init.py                                         12      0   100%

merlin/models/torch/block/init.py                                    0      0   100%

merlin/models/torch/block/base.py                                      167     32    81%

merlin/models/torch/block/mlp.py                                        38      5    87%

merlin/models/torch/features/init.py                                 0      0   100%

merlin/models/torch/features/base.py                                     4      0   100%

merlin/models/torch/features/continuous.py                              22      0   100%

merlin/models/torch/features/embedding.py                              165     12    93%

merlin/models/torch/features/tabular.py                                 65      8    88%

merlin/models/torch/losses.py                                           28     28     0%

merlin/models/torch/model/init.py                                    0      0   100%

merlin/models/torch/model/base.py                                      286     65    77%

merlin/models/torch/model/prediction_task.py                            24      0   100%

merlin/models/torch/tabular/init.py                                  0      0   100%

merlin/models/torch/tabular/aggregation.py                              75      0   100%

merlin/models/torch/tabular/base.py                                    247     39    84%

merlin/models/torch/tabular/transformations.py                          67      3    96%

merlin/models/torch/typing.py                                            6      0   100%

merlin/models/torch/utils/init.py                                    0      0   100%

merlin/models/torch/utils/data_utils.py                                117    117     0%

merlin/models/torch/utils/examples_utils.py                             39     39     0%

merlin/models/torch/utils/torch_utils.py                                80     23    71%

merlin/models/utils/init.py                                          0      0   100%

merlin/models/utils/constants.py                                         3      0   100%

merlin/models/utils/dataset.py                                          38      4    89%

merlin/models/utils/dependencies.py                                     26     19    27%

merlin/models/utils/doc_utils.py                                        10      0   100%

merlin/models/utils/example_utils.py                                    31      2    94%

merlin/models/utils/misc_utils.py                                      118     90    24%

merlin/models/utils/nvt_utils.py                                        27     24    11%

merlin/models/utils/registry.py                                        101     29    71%

merlin/models/utils/schema_utils.py                                     90     19    79%

merlin/models/xgb/init.py                                          124      4    97%
TOTAL                                                                10940   2245    79%
=========================== short test summary info ============================

SKIPPED [1] tests/unit/datasets/test_advertising.py:20: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:64: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:80: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:94: ALI-CCP data is not available, pass it through env variable $DATA_PATH_ALICCP

SKIPPED [1] tests/unit/datasets/test_ecommerce.py:115: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [3] tests/unit/datasets/test_entertainment.py:44: No data-dir available, pass it through env variable $INPUT_DATA_DIR

SKIPPED [5] ../../../.local/lib/python3.8/site-packages/tensorflow/python/framework/test_util.py:2746: Not a test.

========= 864 passed, 13 skipped, 1477 warnings in 1881.35s (0:31:21) ==========

___________________________________ summary ____________________________________

py38-gpu: commands succeeded

congratulations :)

Performing Post build task...

Match found for : : True

Logical operation result is TRUE

Running script  : #!/bin/bash

cd /var/jenkins_home/

CUDA_VISIBLE_DEVICES=1 python test_res_push.py "https://api.GitHub.com/repos/NVIDIA-Merlin/models/issues/$ghprbPullId/comments" "/var/jenkins_home/jobs/$JOB_NAME/builds/$BUILD_NUMBER/log"

[workspace] $ /bin/bash /tmp/jenkins8168264580289142794.sh

tox.ini

edknv · 2022-12-06T16:46:13Z

Note: Dataloader has been updated upstream to return a dictionary of tensors {tensor_name: tensor} for the label columns when there are multiple label columns (NVIDIA-Merlin/dataloader#80). I updated the PR in commit 16adc59 to expect a dictionary of tensors when there are multiple targets.

edknv · 2022-12-06T17:19:26Z

Note: Dataloader was changed to be a generator previously but the change was reverted in NVIDIA-Merlin/dataloader#79 so dataloader is a keras sequence again. Reverted some changes that had to be made due to dataloader being a generator in 705dc6b.

* Use merlin-dataloader package * remove torch.dataset in favor of merlin.loader.torch * update dressipi notebook * minor clean up * Completely removes models DataLoader * Installs merlin-dataloader in github actions * Adds back the stop method * dataloader can produce sparse tensors using value counts * remove data files * fix torch tests * add missing target to dlrm test * use loader.peek() * add some comments to help understand horovod tests * make sparse tensors optional * cleanup * fix spelling * fix merge * replace while loop with for loop in horovod test * use loader context mananger * Update according to dataloader changes #80 * restore tox.ini * restore gh workflow * revert generator changes

…guage modeling (#909) * add the inference fix to ReplaceMaskedEmbeddings * first solution for inference support * updates based on PR comments * Apply suggestions from code review Co-authored-by: Gabriel Moreira <gmoreira@nvidia.com> * Use merlin-dataloader package (#845) * Use merlin-dataloader package * remove torch.dataset in favor of merlin.loader.torch * update dressipi notebook * minor clean up * Completely removes models DataLoader * Installs merlin-dataloader in github actions * Adds back the stop method * dataloader can produce sparse tensors using value counts * remove data files * fix torch tests * add missing target to dlrm test * use loader.peek() * add some comments to help understand horovod tests * make sparse tensors optional * cleanup * fix spelling * fix merge * replace while loop with for loop in horovod test * use loader context mananger * Update according to dataloader changes #80 * restore tox.ini * restore gh workflow * revert generator changes * Restore documentation build (#916) - Change Python 3.9.7 to 3.8. - Update the versions of the GH actions. - Update pre-commit config file to get flake8 from GitHub instead of GitLab. * Support `tuple` return type from model `pre` and update test to use this (#890) * Support `tuple` return typee from `pre` arg to `evaluate`, `predict` * Update CLM transformer test to use `pre` instead of Loader `transform` * Update youtube dnn tests to use transform as model fit pre * Add `pre` to ModelBlock fit/evaluate * Revert "Add `pre` to ModelBlock fit/evaluate" This reverts commit 1eef7b8. * Raise exception if ragged/sparse tensors are passed at training time. * Update model_test helper to avoid passing ragged tensors to `fit` * Handle x and y in model_test * Change process_lists param to False by default * Convert to tuple in test loader * Move order of ragged tensor assertion to before train_pre call * expand dims in test_classification * pass transform as pre in test in batch negatives * Update continuous and retrieval tests * Remove test of sequence predict functions with loader * Update error message about ragged tensors for clarity * Add explanation about why the input types are restricted * Rename dataset to dataloader in model_test Co-authored-by: rnyak <ronayak@hotmail.com> * add assertion check to TransformerInferenceHiddenState Co-authored-by: Gabriel Moreira <gmoreira@nvidia.com> Co-authored-by: edknv <109497216+edknv@users.noreply.github.com> Co-authored-by: mikemckiernan <mmckiernan@nvidia.com> Co-authored-by: Oliver Holworthy <oholworthy@nvidia.com> Co-authored-by: rnyak <ronayak@hotmail.com>

Use merlin-dataloader package

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edknv added area/packaging area/data-loading chore Maintenance for the repository labels Nov 2, 2022

edknv self-assigned this Nov 2, 2022

edknv and others added 2 commits November 2, 2022 15:46

remove torch.dataset in favor of merlin.loader.torch

081331a

Merge branch 'main' into merlin_dataloader

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edknv removed the area/packaging label Nov 2, 2022

Merge branch 'main' into merlin_dataloader

c1c607d

edknv added 2 commits November 7, 2022 19:12

Merge branch 'main' into merlin_dataloader

4e2bb47

update dressipi notebook

315c7d3

Merge branch 'main' into merlin_dataloader

00ca57b

edknv and others added 2 commits November 9, 2022 10:13

Merge branch 'main' into merlin_dataloader

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minor clean up

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edknv force-pushed the merlin_dataloader branch from e51835e to 3e6bf94 Compare November 10, 2022 15:12

Merge branch 'main' into merlin_dataloader

d9f76d5

edknv marked this pull request as ready for review November 10, 2022 18:35

edknv requested a review from jperez999 November 10, 2022 18:35

oliverholworthy reviewed Nov 30, 2022

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edknv and others added 6 commits November 30, 2022 10:07

use loader.peek()

070a8d8

add some comments to help understand horovod tests

1a89c9f

make sparse tensors optional

02a54d8

cleanup

cc5893f

fix spelling

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Merge branch 'main' into merlin_dataloader

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fix merge

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Merge branch 'main' into merlin_dataloader

d6b123a

oliverholworthy reviewed Dec 1, 2022

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edknv added 2 commits December 1, 2022 14:33

replace while loop with for loop in horovod test

d6de79d

use loader context mananger

93706b6

edknv mentioned this pull request Dec 6, 2022

Support multiple label columns NVIDIA-Merlin/dataloader#80

Merged

Update according to dataloader changes NVIDIA-Merlin#80

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edknv commented Dec 6, 2022

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edknv added 2 commits December 6, 2022 07:36

restore tox.ini

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restore gh workflow

fb1285b

revert generator changes

705dc6b

oliverholworthy approved these changes Dec 8, 2022

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edknv merged commit 60a9ca1 into NVIDIA-Merlin:main Dec 9, 2022

edknv mentioned this pull request Dec 21, 2022

remove transform parameter from loader #935

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Use merlin-dataloader package #845

Use merlin-dataloader package #845

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edknv commented Nov 2, 2022 • edited

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nvidia-merlin-bot commented Dec 1, 2022

---------- coverage: platform linux, python 3.8.10-final-0 ----------- Name Stmts Miss Cover

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---------- coverage: platform linux, python 3.8.10-final-0 ----------- Name Stmts Miss Cover

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edknv commented Nov 2, 2022 •

edited

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---------- coverage: platform linux, python 3.8.10-final-0 -----------
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---------- coverage: platform linux, python 3.8.10-final-0 -----------
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---------- coverage: platform linux, python 3.8.10-final-0 -----------
Name Stmts Miss Cover