| 40 | """ |
| 41 | |
| 42 | def __init__( |
| 43 | self, |
| 44 | channels: int, |
| 45 | use_conv: bool = False, |
| 46 | use_conv_transpose: bool = False, |
| 47 | out_channels: Optional[int] = None, |
| 48 | name: str = "conv", |
| 49 | ): |
| 50 | super().__init__() |
| 51 | self.channels = channels |
| 52 | self.out_channels = out_channels or channels |
| 53 | self.use_conv = use_conv |
| 54 | self.use_conv_transpose = use_conv_transpose |
| 55 | self.name = name |
| 56 | |
| 57 | self.conv = None |
| 58 | if use_conv_transpose: |
| 59 | self.conv = nn.ConvTranspose1d(channels, self.out_channels, 4, 2, 1) |
| 60 | elif use_conv: |
| 61 | self.conv = nn.Conv1d(self.channels, self.out_channels, 3, padding=1) |
| 62 | |
| 63 | def forward(self, inputs: torch.Tensor) -> torch.Tensor: |
| 64 | assert inputs.shape[1] == self.channels |