PyTorch

PyTorch and MDF

The current implementation of our PyTorch to MDF conversion functionality is built on top of the TorchScript infrastructure provided by PyTorch. PyTorch models that can be translated to TorchScript (via torch.jit.script or torch.jit.trace) should then be able to be converted to their MDF representation automatically. Below are several working examples of this functionality.

Inception Blocks Model

To run an example of converting a PyTorch InceptionV3 like model written in PyTorch to its MDF representation simply run:

python inception.py

This will define the model in PyTorch, invoke the TorchScript tracing compiler, convert the underlying IR representation of the model to MDF. The MDF for this model is the written to inception.json. The model is then executed via the MDF scheduler and the results are compared to the native execution in PyTorch.

Drift Diffusion Model

A simple example of a Drift Diffusion Model implemented in PyTorch and converted to MDF can be executed with:

python pytorch_ddm.python

This will generate the MDF representation in ddm.json

Multi-Layer Perceptron MDF to PyTorch Conversion

To run an example where a simple Multi-Layer Perceptron (MLP) created using the MDF specification is translated to a PyTorch model and executed using sample digit-recognition data, run:

python mlp.py