(self, channels, kernel_size=3, dilation=(1, 3))
| 319 | |
| 320 | class ResBlock2(torch.nn.Module): |
| 321 | def __init__(self, channels, kernel_size=3, dilation=(1, 3)): |
| 322 | super(ResBlock2, self).__init__() |
| 323 | self.convs = nn.ModuleList( |
| 324 | [ |
| 325 | weight_norm( |
| 326 | Conv1d( |
| 327 | channels, |
| 328 | channels, |
| 329 | kernel_size, |
| 330 | 1, |
| 331 | dilation=dilation[0], |
| 332 | padding=get_padding(kernel_size, dilation[0]), |
| 333 | ) |
| 334 | ), |
| 335 | weight_norm( |
| 336 | Conv1d( |
| 337 | channels, |
| 338 | channels, |
| 339 | kernel_size, |
| 340 | 1, |
| 341 | dilation=dilation[1], |
| 342 | padding=get_padding(kernel_size, dilation[1]), |
| 343 | ) |
| 344 | ), |
| 345 | ] |
| 346 | ) |
| 347 | self.convs.apply(init_weights) |
| 348 | |
| 349 | def forward(self, x, x_mask=None): |
| 350 | for c in self.convs: |
nothing calls this directly
no test coverage detected