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Tutorial 6: Exporting a model to ONNX

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves.

Supported Models

So far, our codebase supports onnx exporting from pytorch models trained with MMAction2. The supported models are:

  • I3D
  • TSN
  • TIN
  • TSM
  • R(2+1)D
  • SLOWFAST
  • SLOWONLY
  • BMN
  • BSN(tem, pem)

Usage

For simple exporting, you can use the script here. Note that the package onnx and onnxruntime are required for verification after exporting.

Prerequisite

First, install onnx.

pip install onnx onnxruntime

We provide a python script to export the pytorch model trained by MMAction2 to ONNX.

python tools/pytorch2onnx.py ${CONFIG_FILE} ${CHECKPOINT_FILE} [--shape ${SHAPE}] \
    [--verify] [--show] [--output-file ${OUTPUT_FILE}]  [--is-localizer] [--opset-version ${VERSION}]

Optional arguments:

  • --shape: The shape of input tensor to the model. For 2D recognizer(e.g. TSN), the input should be $batch $clip $channel $height $width(e.g. 1 1 3 224 224); For 3D recognizer(e.g. I3D), the input should be $batch $clip $channel $time $height $width(e.g. 1 1 3 32 224 224); For localizer such as BSN, the input for each module is different, please check the forward function for it. If not specified, it will be set to 1 1 3 224 224.
  • --verify: Determines whether to verify the exported model, runnably and numerically. If not specified, it will be set to False.
  • --show: Determines whether to print the architecture of the exported model. If not specified, it will be set to False.
  • --output-file: The output onnx model name. If not specified, it will be set to tmp.onnx.
  • --is-localizer: Determines whether the model to be exported is a localizer. If not specified, it will be set to False.
  • --opset-version: Determines the operation set version of onnx, we recommend you to use a higher version such as 11 for compatibility. If not specified, it will be set to 11.
  • --softmax: Determines whether to add a softmax layer at the end of recognizers. If not specified, it will be set to False. For now, localizers are not supported.

Recognizers

For recognizers, please run:

python tools/pytorch2onnx.py $CONFIG_PATH $CHECKPOINT_PATH --shape $SHAPE --verify

Localizers

For localizers, please run:

python tools/pytorch2onnx.py $CONFIG_PATH $CHECKPOINT_PATH --is-localizer --shape $SHAPE --verify

Please fire an issue if you discover any checkpoints that are not perfectly exported or suffer some loss in accuracy.