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PyTorch Model Conversion to ExecuTorch Format

PyTorch Model Conversion to ExecuTorch Format#

In this guideline we will show how to use the ExecuTorch AoT part to convert a PyTorch model to ExecuTorch format and delegate the model computation to eIQ Neutron NPU using the eIQ Neutron Backend.

First we will start with an example script converting the model. This example shows the CifarNet model preparation. It is the same model which is part of the example_cifarnet.

  1. Run the aot_neutron_compile.py example with the cifar10 model. As the aot_neutron_compile.py is already installed as part of the ExecuTorch installation, we will run it from there

$ python -m examples.nxp.aot_neutron_compile --quantize \
        --delegate --remove-quant-io-ops --use_channels_last_dim_order \
        -m cifar10

  1. This command generates a cifar10_nxp_delegate.pte file, which can be used with the MCUXpresso SDK cifarnet_example project.

The generated PTE file is used in the executorch_cifarnet example application, see example_applications.

NXP eIQ Neutron Kernel Selective Kernel Registration#

The NXP ExecuTorch backend supports selective Neutron kernel registration for Neutron-C targets, which reduces the size of the Neutron Firmware. For more information and example commands, see NXP eIQ Neutron Kernel Selective Kernel Registration.

MCUXpresso SDK build with kernel selection#

The build process of only selected kernels to reduce the size of deployed application is described in MCUXpresso SDK build with kernel selection

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