torch.onnx diagnostics

Overview

NOTE: This feature is underdevelopment and is subject to change.

The goal is to improve the diagnostics to help users debug and improve their model export to ONNX.

• The diagnostics are emitted in machine parsable Static Analysis Results Interchange Format (SARIF).

• A new clearer, structured way to add new and keep track of diagnostic rules.

• Serve as foundation for more future improvements consuming the diagnostics.

Diagnostic Rules

• DIAGSYS0001:arg-format-too-verbose
• FXE0001:fx-tracer-success
• FXE0002:fx-tracer-failure
• FXE0003:fx-frontend-aotautograd
• FXE0004:fx-pass-convert-neg-to-sigmoid
• FXE0005:fx-ir-add-node
• FXE0006:atenlib-symbolic-function
• FXE0007:atenlib-fx-to-onnx
• FXE0008:fx-node-to-onnx
• FXE0009:fx-frontend-dynamo-make-fx
• FXE0010:fx-pass
• FXE0011:no-symbolic-function-for-call-function
• FXE0012:unsupported-fx-node-analysis
• POE0001:node-missing-onnx-shape-inference
• POE0002:missing-custom-symbolic-function
• POE0003:missing-standard-symbolic-function
• POE0004:operator-supported-in-newer-opset-version

API Reference

class torch.onnx._internal.diagnostics.ExportDiagnostic(*args, frames_to_skip=1, cpp_stack=False, **kwargs)

Base class for all export diagnostics.

This class is used to represent all export diagnostics. It is a subclass of infra.Diagnostic, and adds additional methods to add more information to the diagnostic.

record_cpp_call_stack(frames_to_skip)

Records the current C++ call stack in the diagnostic.

Return type

Stack