Class NonCausalConvTranspose1d

tokenizer.py:63–101

1D noncausal transpose convolution.

    

class NonCausalConvTranspose1d(nn.Module):
    """1D noncausal transpose convolution."""

    def __init__(
        self,
        in_channels,
        out_channels,
        kernel_size,
        stride,
        padding=-1,
        output_padding=-1,
        groups=1,
        bias=True,
    ):
        super().__init__()
        if padding < 0:
            padding = (stride+1) // 2
        if output_padding < 0:
            output_padding = 1 if stride % 2 else 0
        self.deconv = nn.ConvTranspose1d(
            in_channels=in_channels,
            out_channels=out_channels,
            kernel_size=kernel_size,
            stride=stride,
            padding=padding,
            output_padding=output_padding,
            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.deconv(x)
        return x


class CausalConv1d(NonCausalConv1d):