14 lines
499 B
Python
14 lines
499 B
Python
import torch
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from pathlib import Path
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model = torch.load('cloud_removal_model/cloud_removal_unet_best.pth', map_location='cpu')
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print(type(model))
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print("hasattr inc:", hasattr(model, 'inc'))
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if hasattr(model, 'inc'):
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print("hasattr double_conv:", hasattr(model.inc, 'double_conv'))
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if hasattr(model.inc, 'double_conv'):
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print("in_channels:", model.inc.double_conv[0].in_channels)
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else:
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for name, param in model.named_parameters():
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print(name, param.shape)
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break
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