Created
August 4, 2020 07:07
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Masked Conv1d
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| class Conv1dWithMask(nn.Module): | |
| def __init__(self, in_channels, out_channels, kernel_size=3, bias=True, w_init_gain='linear'): | |
| super(Conv1dWithMask, self).__init__() | |
| assert kernel_size > 1, f"Conv1dWithMask kernel size must greater than 1" | |
| self.kernel_size = kernel_size | |
| self.out_channels = out_channels | |
| self.conv = torch.nn.Conv1d(in_channels, out_channels, kernel_size=kernel_size, bias=bias) | |
| torch.nn.init.xavier_uniform_( | |
| self.conv.weight, gain=torch.nn.init.calculate_gain(w_init_gain)) | |
| def forward(self, x, mask=None): | |
| """ | |
| :param x: [B, H, T] | |
| :param mask: [B, T, T], e.g.: | |
| tensor([[[1., 1., 0., 0., 0., 0., 0., 0.], | |
| [1., 1., 0., 0., 0., 0., 0., 0.], | |
| [1., 1., 1., 1., 0., 0., 0., 0.], | |
| [1., 1., 1., 1., 0., 0., 0., 0.], | |
| [1., 1., 1., 1., 1., 1., 1., 1.], | |
| [1., 1., 1., 1., 1., 1., 1., 1.], | |
| [1., 1., 1., 1., 1., 1., 1., 1.], | |
| [1., 1., 1., 1., 1., 1., 1., 1.]], ...]) | |
| :return: [B, H', T] | |
| """ | |
| if isinstance(x, list): | |
| assert len(x) == 2 | |
| x, mask = x[0], x[1] | |
| assert mask is not None | |
| x = x.permute(0, 2, 1) # [B, H, T] -> [B, T, H] | |
| kernel_size = self.kernel_size | |
| B, T, H = x.shape | |
| mask_pad = F.pad(mask, [kernel_size // 2, kernel_size // 2]) | |
| mask_pad_shift = torch.cat([mask_pad[:, :, :-1].reshape(B, -1), mask_pad[:, :, -1]], -1) | |
| mask_pad_shift = mask_pad_shift.reshape(B, T, -1)[:, :, :kernel_size] | |
| mask_pad_shift = mask_pad_shift.reshape(-1, 1, kernel_size).float() # [B*T, 1, K] | |
| x_pad = F.pad(x, [0, 0, kernel_size // 2, kernel_size // 2], value=0) # [B, T+K-1, H] | |
| x_unfold = x_pad.unfold(1, kernel_size, 1) # [B, T, H, K] | |
| x_unfold = x_unfold.reshape(-1, H, kernel_size) # [B*T, H, K] | |
| x_conv = self.conv(x_unfold * mask_pad_shift) # [B*T, H', 1] | |
| x_conv = x_conv.reshape(B, T, self.out_channels) # [B, T, H'] | |
| x_conv = x_conv.permute(0, 2, 1) # [B, H', T] | |
| return x_conv |
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