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732175e245
Add example for distributed pytorch geometric (graph learning) with Ray AIR This only showcases distributed training, but with data small enough that it can be loaded in by each training worker individually. Distributed data ingest is out of scope for this PR. Co-authored-by: matthewdeng <matthew.j.deng@gmail.com>
15 lines
665 B
Text
15 lines
665 B
Text
# These requirements are used for the CI and CPU-only Docker images so we install CPU only versions of torch.
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# For GPU Docker images, you should install requirements_ml_docker.txt afterwards.
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tensorflow==2.6.2
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tensorflow-probability==0.14.1
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# If you make changes to the torch versions below, please also make the corresponding changes to `requirements_ml_docker.txt`!
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torch==1.9.0;sys_platform=="darwin"
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torchvision==0.10.0;sys_platform=="darwin"
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# On non-OSX machines only install CPU version of torch and torchvision
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-f https://download.pytorch.org/whl/torch_stable.html
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torch==1.9.0+cpu;sys_platform!="darwin"
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torchvision==0.10.0+cpu;sys_platform!="darwin"
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