This is a pure Python implementation of an ONNX model pruning and structure optimization tool with no extra compilation dependencies. By analyzing and rewriting the computational graph, it automatically removes redundant nodes, invalid branches, and excess parameters, reducing the model size and improving inference speed while maintaining model accuracy, suitable for model publishing, inference deployment, and engineering scenarios