| import torch |
| from .SpatialConvolution import SpatialConvolution |
| |
| |
| class SpatialDilatedConvolution(SpatialConvolution): |
| |
| def __init__(self, nInputPlane, nOutputPlane, kW, kH, dW=1, dH=1, padW=0, padH=None, dilationH=1, dilationW=None): |
| super(SpatialDilatedConvolution, self).__init__(nInputPlane, nOutputPlane, kW, kH, dW, dH, padW, padH) |
| |
| self.dilationH = dilationH |
| self.dilationW = dilationW if dilationW is not None else dilationH |
| |
| def updateOutput(self, input): |
| if self.finput is None: |
| self.finput = self.weight.new() |
| if self.fgradInput is None: |
| self.fgradInput = self.weight.new() |
| input = self._makeContiguous(input) |
| self._backend.SpatialDilatedConvolution_updateOutput( |
| self._backend.library_state, |
| input, |
| self.output, |
| self.weight, |
| self.bias, |
| self.finput, |
| self.fgradInput, |
| self.kW, self.kH, |
| self.dW, self.dH, |
| self.padW, self.padH, |
| self.dilationH, self.dilationW |
| ) |
| return self.output |
| |
| def updateGradInput(self, input, gradOutput): |
| if self.gradInput is None: |
| return |
| |
| input, gradOutput = self._makeContiguous(input, gradOutput) |
| if self.fgradInput is None: |
| self.fgradInput = self.weight.new() |
| self._backend.SpatialDilatedConvolution_updateGradInput( |
| self._backend.library_state, |
| input, |
| gradOutput, |
| self.gradInput, |
| self.weight, |
| self.finput, |
| self.kW, self.kH, |
| self.dW, self.dH, |
| self.padW, self.padH, |
| self.dilationH, self.dilationW |
| ) |
| return self.gradInput |
| |
| def accGradParameters(self, input, gradOutput, scale=1): |
| input, gradOutput = self._makeContiguous(input, gradOutput) |
| if self.fgradInput is None: |
| self.fgradInput = self.weight.new() |
| self._backend.SpatialDilatedConvolution_accGradParameters( |
| self._backend.library_state, |
| input, |
| gradOutput, |
| self.gradWeight, |
| self.gradBias, |
| self.finput, |
| self.fgradInput, |
| self.kW, self.kH, |
| self.dW, self.dH, |
| self.padW, self.padH, |
| self.dilationH, self.dilationW, |
| scale |
| ) |
| |
| def __repr__(self): |
| s = super(SpatialConvolution, self).__repr__() |
| s += '({} -> {}, {}x{}'.format(self.nInputPlane, self.nOutputPlane, self.kW, self.kH) |
| if self.dW != 1 or self.dH != 1 or self.padW != 0 or self.padH != 0: |
| s += ', {}, {}'.format(self.dW, self.dH) |
| |
| if self.padW != 0 or self.padH != 0: |
| s += ', {}, {}'.format(self.padW, self.padH) |
| |
| s += ', {}, {}'.format(self.dilationW, self.dilationH) |
| |
| s += ')' |
| if self.bias is None: |
| s += ' without bias' |
| return s |
