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36 lines
903 B
36 lines
903 B
import torch
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import numpy as np
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import os
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def mkdir(path):
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if not os.path.exists(path):
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os.makedirs(path)
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def mkdirs(*paths):
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# print(paths)
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if isinstance(paths, list) or isinstance(paths, tuple):
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for path in paths:
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mkdir(path)
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else:
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raise ValueError
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def to_numpy(input):
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if isinstance(input, torch.Tensor):
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return input.detach().cpu().numpy()
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elif isinstance(input, np.ndarray):
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return input
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else:
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raise TypeError('Unknown type of input, expected torch.Tensor or '\
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'np.ndarray, but got {}'.format(type(input)))
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def module_size(module):
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assert isinstance(module, torch.nn.Module)
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n_params, n_conv_layers = 0, 0
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for name, param in module.named_parameters():
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if 'conv' in name:
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n_conv_layers += 1
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n_params += param.numel()
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return n_params, n_conv_layers
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