void ConvBaseOperator::reshapeImageDescriptors() {
hl_tensor_reshape(imageDesc_,
1,
channels_,
imageH_,
imageW_,
channels_ * imageH_ * imageW_,
imageH_ * imageW_,
imageW_,
1);
hl_tensor_reshape(outputDesc_,
1,
numFilters_,
outputH_,
outputW_,
numFilters_ * outputH_ * outputW_,
outputH_ * outputW_,
outputW_,
1);
hl_reset_convolution_descriptor(convDesc_,
imageDesc_,
filterDesc_,
paddingY_,
padding_,
strideY_,
stride_);
}
void ConvBaseProjection::reshapeTensorDesc(int batchSize) {
// The stride between two consecutive samples in the output of ConvProjection
// may not be numFilters_ * outputH_ * outputW_ (conv) or
// channels_ * imageH_ * imageW_ (deconv)
// for example, in the case of layer ConcatenateLayer2 with two
// ConvProjection, the stride is the output_size of layer ConcatenateLayer2.
// So the calculation of nStride is different from CudnnConvLayer.
size_t nStrideImage, nStrideOutput;
if (isDeconv_) {
nStrideImage = out_->value->getStride();
nStrideOutput = numFilters_ * outputH_ * outputW_;
} else {
nStrideImage = channels_ * imageH_ * imageW_;
nStrideOutput = out_->value->getStride();
}
hl_tensor_reshape(imageDesc_,
batchSize,
channels_ / groups_,
imageH_,
imageW_,
nStrideImage,
imageH_ * imageW_,
imageW_,
1);
hl_tensor_reshape(outputDesc_,
batchSize,
numFilters_ / groups_,
outputH_,
outputW_,
nStrideOutput,
outputH_ * outputW_,
outputW_,
1);
hl_reset_convolution_descriptor(convDesc_,
imageDesc_,
filterDesc_,
paddingH_,
paddingW_,
strideH_,
strideW_,
dilationH_,
dilationW_);
}
