18 lines
670 B
Python
18 lines
670 B
Python
import torch
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import torch.onnx
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from basicsr.archs.rrdbnet_arch import RRDBNet
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# An instance of your model
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model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
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model.load_state_dict(torch.load('experiments/pretrained_models/RealESRGAN_x4plus.pth')['params_ema'])
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# set the train mode to false since we will only run the forward pass.
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model.train(False)
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model.cpu().eval()
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# An example input you would normally provide to your model's forward() method
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x = torch.rand(1, 3, 64, 64)
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# Export the model
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with torch.no_grad():
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torch_out = torch.onnx._export(model, x, 'realesrgan-x4.onnx', opset_version=11, export_params=True)
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