(self, x: torch.Tensor)
| 86 | self.causal_padding = (kernel_size - 1, 0) |
| 87 | |
| 88 | def forward(self, x: torch.Tensor): |
| 89 | x = F.pad(x, self.causal_padding) |
| 90 | x = super(CausalConv1d, self).forward(x) |
| 91 | return x |
| 92 | |
| 93 | def forward_chunk(self, x: torch.Tensor, cnn_cache: torch.Tensor = None): |
| 94 | if cnn_cache is None: |