save pytorch model as onnx

Open Neural Network Exchange (ONNX) is an open-source format designed to represent machine learning models. It allows models trained in one framework (like PyTorch) to be transferred and used in another framework (like TensorFlow, MXNet, etc.). Here's a step-by-step guide on how to save a PyTorch model as an ONNX file.
Make sure you have PyTorch and ONNX installed. If not, install them using pip:
For demonstration purposes, let's create a simple model and train it:
Now that you have saved your PyTorch model as an ONNX file, you can load it in other frameworks or use it for inference:
Remember, not all PyTorch operations can be directly converted to ONNX, so complex or custom operations might need adjustments or extensions in ONNX. Additionally, ensure that the input shapes and data types match your model's requirements when using the ONNX model for inference.
That's it! You've learned how to save a PyTorch model as an ONNX file and utilize it for inference in another framework using ONNX Runtime.
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