Installation

Requirements

• Python 3.9+

• pip 23+

Install from PyPI

pip install onnx-ir

Install from source

git clone https://github.com/onnx/ir-py.git
cd ir-py
pip install -e .

Verify installation

python -c "import onnx_ir as ir; print(ir.__version__)"

Optional integrations

Install optional packages only for the workflows that need them:

Package	Purpose
onnx-shape-inference	IR-native symbolic shape inference with SymPy expressions and shape-data propagation
safetensors>=0.7.0	Save model weights with ir.save_safetensors
rich	Syntax-highlighted display() output and paging
torch	PyTorch tensor adapter and dtype conversion utilities

pip install onnx-shape-inference "safetensors>=0.7.0" rich

ONNX IR does not require these packages for its core model, graph, and tensor APIs. See Model I/O, Tensor Representation, and Debugging transformations for integration-specific usage.

Recommended setup for production workflows

1. Use a dedicated virtual environment per project.

2. Pin exact versions in your lockfile (requirements.txt, uv.lock, or similar).

3. Run with a tested ONNX version from your environment matrix.

4. For external tensor loading from untrusted artifacts, always set base_dir.

See Security for details.