| import torch |
| from .Module import Module |
| |
| |
| class Copy(Module): |
| |
| def __init__(self, intype, outtype, dontCast=False): |
| self.dontCast = dontCast |
| super(Copy, self).__init__() |
| self.gradInput = intype() |
| self.output = outtype() |
| |
| def updateOutput(self, input): |
| self.output.resize_(input.size()).copy_(input) |
| return self.output |
| |
| def updateGradInput(self, input, gradOutput): |
| self.gradInput.resize_(gradOutput.size()).copy_(gradOutput) |
| return self.gradInput |
| |
| def type(self, type=None, tensorCache=None): |
| if type and self.dontCast: |
| return self |
| |
| return super(Copy, self).type(self, type, tensorCache) |
