| import torch |
| from .Criterion import Criterion |
| |
| |
| class SoftMarginCriterion(Criterion): |
| |
| def __init__(self, ): |
| super(SoftMarginCriterion, self).__init__() |
| self.sizeAverage = True |
| self.output_tensor = None |
| |
| def updateOutput(self, input, target): |
| if self.output_tensor is None: |
| self.output_tensor = input.new(1) |
| self._backend.SoftMarginCriterion_updateOutput( |
| self._backend.library_state, |
| input, |
| target, |
| self.output_tensor, |
| self.sizeAverage |
| ) |
| self.output = self.output_tensor[0] |
| return self.output |
| |
| def updateGradInput(self, input, target): |
| self._backend.SoftMarginCriterion_updateGradInput( |
| self._backend.library_state, |
| input, |
| target, |
| self.gradInput, |
| self.sizeAverage |
| ) |
| return self.gradInput |
