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Update README.md for PyTorch/XLA 2.6 release (#8647)
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README.md

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To install PyTorch/XLA stable build in a new TPU VM:
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```sh
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pip install torch~=2.5.0 'torch_xla[tpu]~=2.5.0' \
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pip install torch~=2.6.0 'torch_xla[tpu]~=2.6.0' \
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-f https://storage.googleapis.com/libtpu-releases/index.html \
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-f https://storage.googleapis.com/libtpu-wheels/index.html
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-f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
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```
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### C++11 ABI builds
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Starting from Pytorch/XLA 2.6, we'll provide wheels and docker images built with
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two C++ ABI flavors: C++11 and pre-C++11. Pre-C++11 is the default to align with
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PyTorch upstream, but C++11 ABI wheels and docker images have better lazy tensor
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tracing performance.
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To install C++11 ABI flavored 2.6 wheels:
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```sh
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pip install torch==2.6.0+cpu.cxx11.abi torch_xla[tpu]==2.6.0+cxx11 \
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-f https://storage.googleapis.com/libtpu-releases/index.html \
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-f https://storage.googleapis.com/libtpu-wheels/index.html \
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-f https://download.pytorch.org/whl/torch
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```
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To access C++11 ABI flavored docker image:
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```
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us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.6.0_3.10_tpuvm_cxx11
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```
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If your model is tracing bound (e.g. you see that the host CPU is busy tracing
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the model while TPUs are idle), switching to the C++11 ABI wheels/docker images
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can improve performance. Mixtral 8x7B benchmarking results on v5p-256, global
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batch size 1024:
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- Pre-C++11 ABI MFU: 33%
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- C++ ABI MFU: 39%
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### GPU Plugin
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PyTorch/XLA now provides GPU support through a plugin package similar to `libtpu`:
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pip install torch~=2.5.0 torch_xla~=2.5.0 https://storage.googleapis.com/pytorch-xla-releases/wheels/cuda/12.1/torch_xla_cuda_plugin-2.5.0-py3-none-any.whl
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```
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The newest stable version where PyTorch/XLA:GPU wheel is available is `torch_xla`
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2.5. We do not offer a PyTorch/XLA:GPU wheel in the PyTorch/XLA 2.6 release. We
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understand this is important and plan to [reinstate GPU support](https://github.com/pytorch/xla/issues/8577) by the 2.7 release.
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PyTorch/XLA remains an open-source project and we welcome contributions from the
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community to help maintain and improve the project. To contribute, please start
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with the [contributors guide](https://github.com/pytorch/xla/blob/master/CONTRIBUTING.md).
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## Getting Started
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To update your existing training loop, make the following changes:
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| Version | Cloud TPU VMs Wheel |
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|---------|-------------------|
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| 2.5 (Python 3.10) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.5.0-cp310-cp310-manylinux_2_28_x86_64.whl` |
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| 2.4 (Python 3.10) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.4.0-cp310-cp310-manylinux_2_28_x86_64.whl` |
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| 2.3 (Python 3.10) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.3.0-cp310-cp310-manylinux_2_28_x86_64.whl` |
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| 2.2 (Python 3.10) | `https://storage.googleapis.com/pytorch-xla-releases/wheels/tpuvm/torch_xla-2.2.0-cp310-cp310-manylinux_2_28_x86_64.whl` |
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| Version | Cloud TPU VMs Docker |
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| --- | ----------- |
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| 2.6 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.6.0_3.10_tpuvm` |
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| 2.5 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.5.0_3.10_tpuvm` |
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| 2.4 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.4.0_3.10_tpuvm` |
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| 2.3 | `us-central1-docker.pkg.dev/tpu-pytorch-releases/docker/xla:r2.3.0_3.10_tpuvm` |

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