Apply gaussian filter to input. Arguments: input (torch.Tensor): Input to apply gaussian filter on. Returns: filtered (torch.Tensor): Filtered output.
(self, input)
| 61 | ) |
| 62 | |
| 63 | def forward(self, input): |
| 64 | """ |
| 65 | Apply gaussian filter to input. |
| 66 | Arguments: |
| 67 | input (torch.Tensor): Input to apply gaussian filter on. |
| 68 | Returns: |
| 69 | filtered (torch.Tensor): Filtered output. |
| 70 | """ |
| 71 | return self.conv(input, weight=self.weight.to(input.dtype), groups=self.groups) |
| 72 | |
| 73 | |
| 74 | class AverageSmoothing(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected