onnx-ir 0.21.0

ONNX-IR is a pure Rust library for parsing ONNX models into an intermediate representation that can be used to generate code for various ML/DL frameworks
Documentation 
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#!/usr/bin/env -S uv run
# /// script
# dependencies = [
#   "onnx>=1.15.0",
#   "numpy>=1.24.0",
# ]
# ///

"""Generate ONNX model with no initializers (all runtime inputs)."""

import onnx
from onnx import helper, TensorProto


def create_model():
    input1 = helper.make_tensor_value_info("input1", TensorProto.FLOAT, [1, 3])
    input2 = helper.make_tensor_value_info("input2", TensorProto.FLOAT, [1, 3])
    output = helper.make_tensor_value_info("output", TensorProto.FLOAT, [1, 3])

    nodes = [
        helper.make_node("Add", ["input1", "input2"], ["temp"], name="add"),
        helper.make_node("Relu", ["temp"], ["output"], name="relu"),
    ]

    graph = helper.make_graph(nodes, "no_initializers", [input1, input2], [output])
    model = helper.make_model(
        graph, producer_name="onnx-ir-test", opset_imports=[helper.make_opsetid("", 16)]
    )
    onnx.checker.check_model(model)
    return model


if __name__ == "__main__":
    model = create_model()
    onnx.save(model, "../fixtures/no_initializers.onnx")
    print("Model saved to ../fixtures/no_initializers.onnx")
    print("  No initializers - all inputs are runtime")