| import math |
| import torch |
| from .Module import Module |
| |
| |
| class Mul(Module): |
| |
| def __init__(self): |
| super(Mul, self).__init__() |
| self.weight = torch.Tensor(1) |
| self.gradWeight = torch.Tensor(1) |
| self.reset() |
| |
| def reset(self, stdv=None): |
| if stdv is not None: |
| stdv = stdv * math.sqrt(3) |
| else: |
| stdv = 1. / math.sqrt(self.weight.size(0)) |
| self.weight.uniform_(-stdv, stdv) |
| |
| def updateOutput(self, input): |
| self.output.resize_as_(input).copy_(input) |
| self.output.mul_(self.weight[0]) |
| return self.output |
| |
| def updateGradInput(self, input, gradOutput): |
| self.gradInput.resize_as_(input).zero_() |
| self.gradInput.add_(self.weight[0], gradOutput) |
| return self.gradInput |
| |
| def accGradParameters(self, input, gradOutput, scale=1): |
| self.gradWeight[0] = (self.gradWeight[0] + |
| scale * input.contiguous().view(-1).dot(gradOutput.contiguous().view(-1))) |
