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* XLA:
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* MWMS is now compilable with XLA.
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* [oneDNN CPU performance optimizations](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md):
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* **x86 CPUs**: oneDNN bfloat16 auto-mixed precision grappler graph optimization pass has been renamed from `auto_mixed_precision_mkl` to `auto_mixed_precision_onednn_bfloat16`. See example usage [here](https://www.intel.com/content/www/us/en/developer/articles/guide/getting-started-with-automixedprecisionmkl.html).
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* CPU performance optimizations:
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* **x86 CPUs**: [oneDNN](https://github.com/tensorflow/community/blob/master/rfcs/20210930-enable-onednn-ops.md) bfloat16 auto-mixed precision grappler graph optimization pass has been renamed from `auto_mixed_precision_mkl` to `auto_mixed_precision_onednn_bfloat16`. See example usage [here](https://www.intel.com/content/www/us/en/developer/articles/guide/getting-started-with-automixedprecisionmkl.html).
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* **aarch64 CPUs:** Experimental Arm Compute Library (ACL) CPU performance optimizations through oneDNN are available in the default Linux aarch64 package (`pip install tensorflow`).
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* The optimizations are disabled by default.
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* Set the environment variable `TF_ENABLE_ONEDNN_OPTS=1` to enable the optimizations. Setting the variable to 0 or unsetting it will disable the optimizations.
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