Merge pull request #53 from ShopRunner/remove_deprecated_test

Fix deprecated PyTorch Lightning test

CHANGELOG.md

@@ -3,6 +3,10 @@ All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/) and this project uses [Semantic Versioning](http://semver.org/).
 
+# [1.2.1] - 2022-7-12
+### Fixed
+ - Deprecated PyTorch Lightning unit test
+
 # [1.2.0] - 2022-1-18
 ### Added
  - option to ``force_split`` to ``stratified_split``

Dockerfile

@@ -1,12 +1,15 @@
 FROM pytorch/pytorch:1.10.0-cuda11.3-cudnn8-devel
-MAINTAINER data-science@shoprunner.com
+LABEL maintainer="data-science@shoprunner.com"
+
+# Nvidia fix based on Nate's recommendation
+RUN apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/3bf863cc.pub
 
 RUN apt-get update \
-    && apt-get install -y tmux \
-    && apt-get install -y vim \
-    && apt-get install -y libpq-dev \
-    && apt-get install -y gcc \
-    && apt-get clean
+  && apt-get install -y tmux \
+  && apt-get install -y vim \
+  && apt-get install -y libpq-dev \
+  && apt-get install -y gcc \
+  && apt-get clean
 
 # first remove PyYAML from conda or else pip gives us an error that a distutils library cannot be
 # uninstalled

collie/_version.py

@@ -1 +1 @@
-__version__ = '1.2.0'
+__version__ = '1.2.1'

tests/test_model.py

@@ -57,19 +57,6 @@ def test_CollieTrainer_no_gpu(is_available_mock, untrained_implicit_model, capfd
     assert 'Detected GPU. Setting ``gpus`` to 1.' in out
 
 
-@mock.patch('torch.cuda.is_available')
-def test_CollieTrainer_on_cpu(is_available_mock, untrained_implicit_model):
-    is_available_mock.return_value = True
-
-    with pytest.warns(UserWarning):
-        trainer = CollieTrainer(model=untrained_implicit_model,
-                                logger=False,
-                                enable_checkpointing=False,
-                                gpus=0)
-
-    assert trainer.gpus == 0
-
-
 def test_basepipeline_does_not_initialize(train_val_implicit_data):
     train, val = train_val_implicit_data