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Open-CE Version 1.8.0
This is release 1.8.0 of Open Cognitive Environment (Open-CE). See #706 for detailed release contents.
Package Versions
A release of Open-CE consists of the environment files within the open-ce repository and a collection of feedstock repositories. The feedstock repositories contain recipes for various python packages. The following packages (among others) are part of this release:
| Package | Version |
|---|---|
| dali | 1.19.0 |
| deepspeed | 0.7.5 |
| liblightgbm | 3.3.3 |
| av | 10.0.0 |
| bazel | 5.1.1 |
| boost_mp11 | 1.76.0 |
| cmdstan | 2.29.2 |
| cmdstanpy | 1.0.7 |
| cudatoolkit | 11.2.2 and 11.4.4 |
| cudatoolkit-dev | 11.2.2 and 11.4.4 |
| cudnn | 8.3.0.98 |
| datasets | 2.7.1 |
| dm-tree | 0.1.5 |
| grpc-cpp | 1.41.0 |
| gtest | 1.10.0 |
| horovod | 0.26.1 |
| jpeg-turbo | 2.1.4 |
| keras | 2.10.0 |
| libdate | 3.0.1 |
| libflac | 1.3.3 |
| libiconv | 1.16 |
| libsndfile | 1.0.31 |
| libsolv | 0.7.19 |
| magma | 2.6.1 |
| mamba | 1.0.0 |
| libmamba | 1.0.0 |
| nccl | 2.12.7 |
| numactl | 2.0.12 |
| onnx | 1.12 |
| onnxconverter-common | 1.13.0 |
| onnxmltools | 1.11.1 |
| onnxruntime | 1.13.1 |
| libopencv | 4.6.0 |
| openblas | 0.3.21 |
| openmpi | 4.1.4 |
| optional-lite | 3.4.0 |
| orbit-ml | 1.1.1 |
| orc | 1.8.0 |
| arrow-cpp | 10.0.0 |
| prophet | 1.1.1 |
| pybind11-abi | 4 |
| pytorch-base | 1.13.0 for CUDA 11.4 and cpu |
| pytorch-base | 1.10.2 for CUDA 11.2 |
| pytorch-lightning | 1.8.2 |
| pyDeprecate | 0.3.2 |
| pytorch_geometric | 2.1.0 |
| pytorch-lightning-bolts | 0.6.0 |
| pytorch_scatter | 2.0.8 |
| pytorch_sparse | 0.6.10 |
| torchmetrics | 0.8.1 |
| ray_all | 2.0.1 |
| ray-tune | 2.0.1 |
| reproc | 14.2.3 |
| safeint | 3.0.26 |
| sentencepiece | 0.1.96 |
| skl2onnx | 1.13 |
| spdlog | 1.9.2 |
| tensorboard-data-server | 0.6.1 |
| tensorboard | 2.10.1 |
| tensorflow-addons | 0.18.0 |
| tensorflow-datasets | 4.7.0 |
| tensorflow-estimator | 2.10.0 |
| tensorflow-base | 2.10.1 |
| tensorflow-hub | 0.12.0 |
| tensorflow-io | 0.27.0 |
| tensorflow-io-gcs-filesystem | 0.27.0 |
| tensorflow-metadata | 1.11.0 |
| tensorflow-model-optimization | 0.7.3 |
| tensorflow-probability | 0.18.0 |
| tensorflow-text | 2.10.0 |
| tensorflow-serving | 2.10.1 |
| termcolor-cpp | 2.0.0 |
| tf2onnx | 1.13.0 |
| torchtext-base | 0.14.0 for CUDA 11.4 and cpu |
| torchtext-base | 0.11.2 for CUDA 11.2 |
| torchvision-base | 0.14.0 for CUDA 11.4 and cpu |
| torchvision-base | 0.11.3 for CUDA 11.2 |
| typeguard | 2.12.0 |
| libxgboost | 1.7.1 |
| xgboost | 1.7.1 |
| yaml-cpp | 0.6.3 |
| apache-beam | 2.42 |
This release of Open-CE supports NVIDIA's CUDA versions 11.2,11.4 as well as Python 3.8,3.9,3.10.
Getting Started
To get started with this release, see the main readme
Notes
- CUDA support
- This is the last major OpenCE release to support CUDA 11.2.
- CUDA 11.2 limitations:
- The OpenCE recipes build CUDA 11.2 packages only for Python 3.8 and 3.9, not for 3.10
- The PyTorch OpenCE recipe builds PyTorch 1.10. PyTorch 1.13 is only built for CPU and CUDA 11.4.
Known Issues
The following pip check failures are known:
deepspeed 0.7.5+06e00f61 requires ninja, which is not installed.
skl2onnx 1.13 has requirement scikit-learn<=1.1.1, but you have scikit-learn 1.1.3.
pyro-ppl 1.8.3 has requirement torch>=1.11.0, but you have torch 1.10.2.
arviz 0.11.2 has requirement typing-extensions<4,>=3.7.4.3, but you have typing-extensions 4.4.0.
multiprocess 0.70.12.2 has requirement dill>=0.3.4, but you have dill 0.3.1.1.