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flatten conv2d when input_width==kernel_width (#1435)

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Tracy Sharpe 2019-07-18 19:11:45 -07:00 committed by Ke Zhang
parent c843c393e4
commit 07ecd59e8f
1 changed files with 46 additions and 7 deletions
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53
onnxruntime/core/mlas/lib/snchwc.cpp
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@ -169,6 +169,7 @@ Return Value:
size_t InputSize = 1;
size_t OutputSize = 1;
bool CanFlattenShape = (Dimensions == 2);
for (size_t dim = 0; dim < Dimensions; dim++) {
@ -193,6 +194,8 @@ Return Value:
WorkBlock->DilationShape[dim] = 1;
}
CanFlattenShape &= (WorkBlock->DilationShape[dim] == 1);
if (Padding != nullptr) {
WorkBlock->Padding[dim] = size_t(Padding[dim]);
WorkBlock->Padding[dim + Dimensions] = size_t(Padding[dim + Dimensions]);
@ -201,21 +204,58 @@ Return Value:
WorkBlock->Padding[dim + Dimensions] = 0;
}
CanFlattenShape &= (WorkBlock->Padding[dim] == 0 && WorkBlock->Padding[dim + Dimensions] == 0);
if (StrideShape != nullptr) {
WorkBlock->StrideShape[dim] = size_t(StrideShape[dim]);
} else {
WorkBlock->StrideShape[dim] = 1;
}
//
// Compute the number of output elements affected by left and right
// padding.
//
CanFlattenShape &= (WorkBlock->StrideShape[dim] == 1);
}
WorkBlock->InputSize = InputSize;
WorkBlock->OutputSize = OutputSize;
//
// Detect operations where the kernel is using the entire input width,
// has strides and dilations set to one, and no padding. These operations
// are transformed from outputting [N][1] to [1][N] by flattening the
// operation to a single line using striding equal to the original width.
//
// With the originally shape, the NCHWc kernels would process a single
// output per output line. After reshaping, the NCHWc kernels are able to
// process multiple outputs per output line which typically performs better,
// despite potentially using fewer threads due to the decreased output
// height.
//
if (CanFlattenShape && (WorkBlock->InputShape[1] == WorkBlock->KernelShape[1])) {
WorkBlock->StrideShape[1] = WorkBlock->InputShape[1];
WorkBlock->InputShape[1] *= WorkBlock->InputShape[0];
WorkBlock->InputShape[0] = 1;
WorkBlock->OutputShape[1] *= WorkBlock->OutputShape[0];
WorkBlock->OutputShape[0] = 1;
WorkBlock->KernelShape[1] *= WorkBlock->KernelShape[0];
WorkBlock->KernelShape[0] = 1;
}
//
// Compute the number of output elements affected by left and right padding.
//
for (size_t dim = 0; dim < Dimensions; dim++) {
const size_t SpanValue =
WorkBlock->DilationShape[dim] * (WorkBlock->KernelShape[dim] - 1) + 1;
const size_t StrideValue = WorkBlock->StrideShape[dim];
const size_t PaddingLeftValue = WorkBlock->Padding[dim];
const size_t InputValue = WorkBlock->InputShape[dim];
size_t OutputCountWithLeftPad;
@ -231,13 +271,12 @@ Return Value:
OutputCountLeftPad = OutputCountWithLeftPad;
}
const size_t OutputValue = WorkBlock->OutputShape[dim];
WorkBlock->OutputCountLeftPad[dim] = OutputCountLeftPad;
WorkBlock->OutputCount[dim] = OutputCountWithLeftPad - OutputCountLeftPad;
WorkBlock->OutputCountRightPad[dim] = OutputValue - OutputCountWithLeftPad;
}
WorkBlock->InputSize = InputSize;
WorkBlock->OutputSize = OutputSize;
}
//