onnx/onnx-mlir

The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.

ONNX-TensorRT: TensorRT backend for ONNX

Machine learning compiler based on MLIR for Sophgo TPU.

A retargetable MLIR-based machine learning compiler and runtime toolkit.

ONNX Script enables developers to naturally author ONNX functions and models using a subset of Python.

ONNX Optimizer

Lightweight inference library for ONNX files, written in C++. It can run Stable Diffusion XL 1.0 on a RPI Zero 2 (or in 298MB of RAM) but also Mistral 7B on desktops and servers. ARM, x86, WASM, RISC-V supported. Accelerated by XNNPACK. Python, C# and JS(WASM) bindings available.

Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX

A tool for converting ONNX files to LiteRT/TFLite/TensorFlow, PyTorch native code (nn.Module), TorchScript (.pt), state_dict (.pt), Exported Program (.pt2), and Dynamo ONNX. It also supports direct conversion from LiteRT to PyTorch.