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24 lines
555 B
24 lines
555 B
3 years ago
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import torch.nn as nn
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import numpy as np
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class Model(nn.Module):
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def __init__(self):
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super(Model, self).__init__()
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def initialize(self, m):
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if isinstance(m, (nn.Conv1d)):
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# nn.init.xavier_uniform_(m.weight)
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# if m.bias is not None:
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# nn.init.xavier_uniform_(m.bias)
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nn.init.kaiming_uniform_(m.weight, mode="fan_in", nonlinearity="relu")
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class Identity(nn.Module):
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def __init__(self):
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super(Identity, self).__init__()
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def forward(self, x):
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return x
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