What are the steps to activate Intel Extension for Pytorch (IPEX) within my Python script?

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To activate Intel Extension for PyTorch (IPEX) within your Python script, follow these steps:

1. Install PyTorch with the Intel optimization package using the following command:

pip install torch torchvision torchaudio intel-cmpl-rpl intel-openmp

1. Import the IPEX module at the beginning of your Python script:

import intel_pytorch_extension as ipex

1. Use the ipex.enable_auto_mixed_precision() function to enable the Automatic Mixed Precision (AMP) feature, which uses lower-precision data types to speed up training and inference:

ipex.enable_auto_mixed_precision()

1. Before performing any PyTorch operation, use the ipex.enable_auto_dnnl() function to enable the Intel oneDNN library, which provides optimized deep learning primitives:

ipex.enable_auto_dnnl()

1. In your PyTorch model, wrap the layers that you want to accelerate with the ipex.AmpNetWrapper() function:

model = ipex.AmpNetWrapper(model)

1. Finally, use the ipex.optimize() function to optimize your PyTorch model for better performance:

ipex.optimize(model)

Note: It is important to use the ipex.enable_auto_dnnl() function before the ipex.AmpNetWrapper() function. Also, make sure to optimize your model after wrapping it with ipex.AmpNetWrapper().