| import torch | |
| from .Module import Module | |
| class GradientReversal(Module): | |
| def __init__(self, lambd=1): | |
| super(GradientReversal, self).__init__() | |
| self.lambd = lambd | |
| def setLambda(self, lambd): | |
| self.lambd = lambd | |
| def updateOutput(self, input): | |
| self.output.set_(input) | |
| return self.output | |
| def updateGradInput(self, input, gradOutput): | |
| self.gradInput.resizeAs_(gradOutput) | |
| self.gradInput.copy_(gradOutput) | |
| self.gradInput.mul_(-self.lambd) | |
| return self.gradInput | |