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# OpenXLA | ||
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As of June 28th, 2023, PyTorch/XLA now pulls XLA from OpenXLA. | ||
OpenXLA is an [open source machine learning compiler XLA for GPUs, CPUs, and ML accelerators](https://github.com/openxla/xla). | ||
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Previous to OpenXLA, PyTorch/XLA pulled XLA directly from [TensorFlow](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla). With our [XLA to OpenXLA migration](https://github.com/pytorch/xla/pull/5202), PyTorch/XLA now pulls XLA from [OpenXLA](https://github.com/openxla/xla). | ||
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# How to use OpenXLA | ||
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For [PJRT runtime](https://github.com/pytorch/xla/blob/master/docs/pjrt.md) users, there is no change with this migration. For XRT runtime users, there is a separate [XRT branch of PyTorch/XLA](https://github.com/pytorch/xla/tree/xrt) since OpenXLA doesn't support XRT. | ||
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# Performance | ||
Below is a performance visual comparison of throughput for ResNet50 pre and post the migration on different TPU hardwares. | ||
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| | resnet50-pjrt-v2-8 | resnet50-pjrt-v4-8 | resnet50-pjrt-v4-32 | | ||
| :------------ | :------------ | :------------ | :------------ | | ||
| Pre Migration | 18.59 | 20.06 | 27.92 | | ||
| Post Migration | 18.63 | 19.94 | 27.14 | |