31 lines
975 B
Python
31 lines
975 B
Python
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from torch import nn
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class MDNBlock(nn.Module):
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"""Mixture of Density Network implementation
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https://arxiv.org/pdf/2003.01950.pdf
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"""
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def __init__(self, in_channels, out_channels):
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super().__init__()
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self.out_channels = out_channels
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self.conv1 = nn.Conv1d(in_channels, in_channels, 1)
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self.norm = nn.LayerNorm(in_channels)
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self.relu = nn.ReLU()
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self.dropout = nn.Dropout(0.1)
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self.conv2 = nn.Conv1d(in_channels, out_channels, 1)
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def forward(self, x):
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o = self.conv1(x)
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o = o.transpose(1, 2)
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o = self.norm(o)
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o = o.transpose(1, 2)
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o = self.relu(o)
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o = self.dropout(o)
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mu_sigma = self.conv2(o)
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# TODO: check this sigmoid
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# mu = torch.sigmoid(mu_sigma[:, :self.out_channels//2, :])
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mu = mu_sigma[:, : self.out_channels // 2, :]
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log_sigma = mu_sigma[:, self.out_channels // 2 :, :]
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return mu, log_sigma
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