zxros10
20 lines
544 B
Python
20 lines
544 B
Python
import torch
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from efficientnet_pytorch import EfficientNet
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# Specify which model to use
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model_name = 'efficientnet-b3'
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image_size = EfficientNet.get_image_size(model_name)
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print('Image size: ', image_size)
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# Load model
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model = EfficientNet.from_pretrained(model_name)
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model.set_swish(memory_efficient=False)
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model.eval()
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print('Model image size: ', model._global_params.image_size)
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# Dummy input for ONNX
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dummy_input = torch.randn(1, 3, 300, 300)
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# Export with ONNX
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torch.onnx.export(model, dummy_input, f"{model_name}.onnx", verbose=True)
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