| import torch |
| from .Criterion import Criterion |
| |
| |
| class SmoothL1Criterion(Criterion): |
| |
| def __init__(self, sizeAverage=True): |
| super(SmoothL1Criterion, self).__init__() |
| self.sizeAverage = sizeAverage |
| self.output_tensor = None |
| |
| def updateOutput(self, input, target): |
| if self.output_tensor is None: |
| self.output_tensor = input.new(1) |
| self._backend.SmoothL1Criterion_updateOutput( |
| self._backend.library_state, |
| input, |
| target, |
| self.output_tensor, |
| self.sizeAverage, |
| True, # reduce |
| ) |
| self.output = self.output_tensor[0].item() |
| return self.output |
| |
| def updateGradInput(self, input, target): |
| implicit_gradOutput = torch.ones(1).type_as(input) |
| self._backend.SmoothL1Criterion_updateGradInput( |
| self._backend.library_state, |
| input, |
| target, |
| implicit_gradOutput, |
| self.gradInput, |
| self.sizeAverage, |
| True, # reduce |
| ) |
| return self.gradInput |
