void AffineReluTrivialConvolution_BackwardPass()

in sparseconvnet/SCN/CPU/AffineReluTrivialConvolution.cpp [30:68]

• 38 lines of code
• 10 McCabe index (conditional complexity)

void AffineReluTrivialConvolution_BackwardPass(
    T *input_features, T *d_input_features, Int input_nPlanes, Int input_stride,
    T *d_output_features, Int output_nPlanes, Int output_stride,
    T *affineWeight, T *dAffineWeight, T *affineBias, T *dAffineBias,
    T *convWeight, T *dConvWeight, Int nActive, bool additiveGrad) {

  for (Int row = 0; row < input_nPlanes; row++) {
    for (Int column = 0; column < output_nPlanes; column++) {
      T sum = 0;
      for (Int j = 0; j < nActive; j++) {
        T i = input_features[j * input_stride + row] * affineWeight[row] +
              affineBias[row];
        i = (i > 0) ? i : 0;
        sum += i * d_output_features[j * output_stride + column];
      }
      dConvWeight[row * output_nPlanes + column] += sum;
    }
  }
  for (Int row = 0; row < nActive; row++) {
    for (Int column = 0; column < input_nPlanes; column++) {
      T sum = 0;
      for (Int j = 0; j < output_nPlanes; j++) {
        sum += d_output_features[row * output_stride + j] *
               convWeight[column * output_nPlanes + j];
      }
      T i = input_features[row * input_stride + column] * affineWeight[column] +
            affineBias[column];
      if (i <= 0) // d_ReLU
        sum = 0;
      dAffineWeight[column] += sum * i;
      dAffineBias[column] += sum;
      sum *= affineWeight[column];
      if (additiveGrad)
        d_input_features[row * input_stride + column] += sum;
      else
        d_input_features[row * input_stride + column] = sum;
    }
  }
}