load onnx model in pytorch

Here's a step-by-step tutorial on how to load an ONNX model in PyTorch with a code example:
Make sure you have PyTorch and ONNX installed. You can install them using the following commands:
Before loading an ONNX model, you need to export a PyTorch model to the ONNX format. Here's a simple example of creating and exporting a PyTorch model:
This code snippet creates a ResNet-18 model from torchvision and exports it to the ONNX format. Adjust the model creation and input shape according to your specific use case.
Now, let's load the exported ONNX model back into PyTorch:
Now, pytorch_model is a PyTorch model that you can use for inference.
This tutorial covers the basic steps to load an ONNX model in PyTorch. Make sure to customize the model creation and input data based on your specific use case. Loading ONNX models in PyTorch is useful for interoperability between different deep learning frameworks.
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