Class NonCausalConv1d

tokenizer.py:21–60

1D noncausal convolution w/ 2-sides padding.

class NonCausalConv1d(nn.Module):
    """1D noncausal convolution w/ 2-sides padding."""

    def __init__(
            self, 
            in_channels, 
            out_channels, 
            kernel_size, 
            stride=1, 
            padding=-1, 
            dilation=1,
            groups=1,
            bias=True):
        super().__init__()
        self.in_channels = in_channels
        self.out_channels = out_channels
        self.kernel_size = kernel_size
        if padding < 0:
            padding = (kernel_size - 1) // 2 * dilation
        self.dilation = dilation
        self.conv = nn.Conv1d(
            in_channels=in_channels, 
            out_channels=out_channels, 
            kernel_size=kernel_size,
            stride=stride, 
            padding=padding, 
            dilation=dilation, 
            groups=groups,
            bias=bias,
        )

    def forward(self, x):
        """
        Args:
            x (Tensor): Float tensor variable with the shape  (B, C, T).
        Returns:
            Tensor: Float tensor variable with the shape (B, C, T).
        """
        x = self.conv(x)
        return x
    

class NonCausalConvTranspose1d(nn.Module):