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import os |
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import torch |
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from torch.nn.utils import weight_norm |
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def init_weights(m, mean=0.0, std=0.01): |
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classname = m.__class__.__name__ |
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if classname.find("Conv") != -1: |
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m.weight.data.normal_(mean, std) |
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def apply_weight_norm(m): |
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classname = m.__class__.__name__ |
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if classname.find("Conv") != -1: |
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weight_norm(m) |
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def get_padding(kernel_size, dilation=1): |
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return int((kernel_size * dilation - dilation) / 2) |
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def load_checkpoint(filepath, device): |
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assert os.path.isfile(filepath) |
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print(f"Loading '{filepath}'") |
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checkpoint_dict = torch.load(filepath, map_location=device) |
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print("Complete.") |
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return checkpoint_dict |
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