Calculate forward propagation. Args: x (Tensor): Input tensor (B, C, F, T). Returns: Tensor: Interpolated tensor (B, C, F * y_scale, T * x_scale),
(self, x)
| 31 | self.mode = mode |
| 32 | |
| 33 | def forward(self, x): |
| 34 | """Calculate forward propagation. |
| 35 | |
| 36 | Args: |
| 37 | x (Tensor): Input tensor (B, C, F, T). |
| 38 | |
| 39 | Returns: |
| 40 | Tensor: Interpolated tensor (B, C, F * y_scale, T * x_scale), |
| 41 | |
| 42 | """ |
| 43 | return F.interpolate( |
| 44 | x, scale_factor=(self.y_scale, self.x_scale), mode=self.mode) |
| 45 | |
| 46 | |
| 47 | class Conv2d(torch.nn.Conv2d): |
nothing calls this directly
no outgoing calls
no test coverage detected