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[PyTorch](https://github.com/pytorch/pytorch) is an open-source machine learning framework.
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[Intel® oneCCL](https://github.com/oneapi-src/oneCCL) (collective communications library) is a library for efficient distributed deep learning training implementing such collectives like `allreduce`, `allgather`, `alltoall`. For more information on oneCCL, please refer to the [oneCCL documentation](https://spec.oneapi.com/versions/latest/elements/oneCCL/source/index.html).
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[Intel® oneCCL](https://github.com/oneapi-src/oneCCL) (collective communications library) is a library for efficient distributed deep learning training, implementing collectives like `allreduce`, `allgather`, `alltoall`. For more information on oneCCL, please refer to the [oneCCL documentation](https://spec.oneapi.com/versions/latest/elements/oneCCL/source/index.html).
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`oneccl_bindings_for_pytorch` module implements PyTorch C10D ProcessGroup API and can be dynamically loaded as external ProcessGroup and only works on Linux platform now.
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The usage details can be found in the README of corresponding branch. The following part is about the usage of v1.9 tag. if you want to use other version of torch-ccl please checkout to that branch(tag). For pytorch-1.5.0-rc3, the [#PR28068](https://github.com/pytorch/pytorch/pull/28068) and [#PR32361](https://github.com/pytorch/pytorch/pull/32361) are need to dynamicall register external ProcessGroup and enable `alltoall` collective communication primitive. The patch file about these two PRs is in `patches` directory and you can use it directly.
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The usage details can be found in the README of corresponding branch.
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## Requirements
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- Python 3.8 or later and a C++17 compiler
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- PyTorch v2.1.2
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- PyTorch v2.1.0
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## Build Option List
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The following build options are supported in Intel® oneCCL Bindings for PyTorch*.
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