onnx-mlir/docs/DebuggingNumericalError.md

Debugging Numerical Error

Use util/debug.py python script to debug numerical errors, when onnx-mlir-compiled inference executable produces numerical results that are inconsistent with those produced by the training framework. This python script will run the model through onnx-mlir and a reference backend, and compare the intermediate results produced by these two backends layer by layer.

Rrerequisite

• Set ONNX_MLIR_HOME environment variable to be the path to the HOME directory for onnx-mlir. The HOME directory for onnx-mlir refers to the parent folder containing the bin, lib, etc sub-folders in which ONNX-MLIR executables and libraries can be found.
• Install an ONNX backend, by default onnx-runtime is used as testing backend. Install by running pip install onnxruntime. To use a different testing backend, simply replace code importing onnxruntime to some other ONNX-compliant backend.

Usage

util/debug.py supports the following command-line options:

usage: debug.py [-h] model_path

positional arguments:
  model_path  Path to the model to debug.