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Added support for RowMajor layout to the image patch extraction code

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Speeded up the unsupported_cxx11_tensor_image_patch test and reduced its memory footprint
This commit is contained in:
Benoit Steiner
2015-02-25 09:48:54 -08:00
parent 531fa9de77
commit 8afce86e64
2 changed files with 421 additions and 59 deletions
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122
unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h
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@@ -106,7 +106,8 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
{
typedef TensorImagePatchOp<Rows, Cols, ArgType> XprType;
typedef typename XprType::Index Index;
static const int NumDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value + 1;
static const int NumInputDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
static const int NumDims = NumInputDims + 1;
typedef DSizes<Index, NumDims> Dimensions;
typedef typename XprType::Scalar Scalar;
@@ -120,16 +121,18 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
: m_impl(op.expression(), device)
{
// Only column major tensors are supported for now.
EIGEN_STATIC_ASSERT((static_cast<int>(Layout) == static_cast<int>(ColMajor)), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT(NumDims >= 4, YOU_MADE_A_PROGRAMMING_MISTAKE);
const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
// Caches a few variables.
m_inputRows = input_dims[1];
m_inputCols = input_dims[2];
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
m_inputRows = input_dims[1];
m_inputCols = input_dims[2];
} else {
m_inputRows = input_dims[NumInputDims-2];
m_inputCols = input_dims[NumInputDims-3];
}
m_row_strides = op.row_strides();
m_col_strides = op.col_strides();
@@ -157,28 +160,57 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
}
// Dimensions for result of extraction.
// 0: depth
// 1: patch_rows
// 2: patch_cols
// 3: number of patches
// 4 and beyond: anything else (such as batch).
m_dimensions[0] = input_dims[0];
m_dimensions[1] = op.patch_rows();
m_dimensions[2] = op.patch_cols();
m_dimensions[3] = m_outputRows * m_outputCols;
for (int i = 4; i < NumDims; ++i) {
m_dimensions[i] = input_dims[i-1];
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
// ColMajor
// 0: depth
// 1: patch_rows
// 2: patch_cols
// 3: number of patches
// 4 and beyond: anything else (such as batch).
m_dimensions[0] = input_dims[0];
m_dimensions[1] = op.patch_rows();
m_dimensions[2] = op.patch_cols();
m_dimensions[3] = m_outputRows * m_outputCols;
for (int i = 4; i < NumDims; ++i) {
m_dimensions[i] = input_dims[i-1];
}
} else {
// RowMajor
// NumDims-1: depth
// NumDims-2: patch_rows
// NumDims-3: patch_cols
// NumDims-4: number of patches
// NumDims-5 and beyond: anything else (such as batch).
m_dimensions[NumDims-1] = input_dims[NumInputDims-1];
m_dimensions[NumDims-2] = op.patch_rows();
m_dimensions[NumDims-3] = op.patch_cols();
m_dimensions[NumDims-4] = m_outputRows * m_outputCols;
for (int i = NumDims-5; i >= 0; --i) {
m_dimensions[i] = input_dims[i];
}
}
// Strides for moving the patch in various dimensions.
m_colStride = m_dimensions[1];
m_patchStride = m_colStride * m_dimensions[2] * m_dimensions[0];
m_otherStride = m_patchStride * m_dimensions[3];
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
m_colStride = m_dimensions[1];
m_patchStride = m_colStride * m_dimensions[2] * m_dimensions[0];
m_otherStride = m_patchStride * m_dimensions[3];
} else {
m_colStride = m_dimensions[NumDims-2];
m_patchStride = m_colStride * m_dimensions[NumDims-3] * m_dimensions[NumDims-1];
m_otherStride = m_patchStride * m_dimensions[NumDims-4];
}
// Strides for navigating through the input tensor.
m_rowInputStride = input_dims[0];
m_colInputStride = input_dims[0] * input_dims[1];
m_patchInputStride = input_dims[0] * input_dims[1] * input_dims[2];
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
m_rowInputStride = input_dims[0];
m_colInputStride = input_dims[0] * input_dims[1];
m_patchInputStride = input_dims[0] * input_dims[1] * input_dims[2];
} else {
m_rowInputStride = input_dims[NumInputDims-1];
m_colInputStride = input_dims[NumInputDims-1] * input_dims[NumInputDims-2];
m_patchInputStride = input_dims[NumInputDims-1] * input_dims[NumInputDims-2] * input_dims[NumInputDims-3];
}
// Fast representations of different variables.
m_fastOtherStride = internal::TensorIntDivisor<Index>(m_otherStride);
@@ -186,7 +218,11 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
m_fastColStride = internal::TensorIntDivisor<Index>(m_colStride);
// Number of patches in the width dimension.
m_fastOutputRows = internal::TensorIntDivisor<Index>(m_outputRows);
m_fastDimZero = internal::TensorIntDivisor<Index>(m_dimensions[0]);
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
m_fastDimZero = internal::TensorIntDivisor<Index>(m_dimensions[0]);
} else {
m_fastDimZero = internal::TensorIntDivisor<Index>(m_dimensions[NumDims-1]);
}
}
typedef typename XprType::CoeffReturnType CoeffReturnType;
@@ -207,7 +243,6 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
{
// Patch index corresponding to the passed in index.
const Index patchIndex = index / m_fastPatchStride;
// Find the offset of the element wrt the location of the first element.
const Index patchOffset = (index - patchIndex * m_patchStride) / m_fastDimZero;
@@ -232,7 +267,8 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
return Scalar(0);
}
const Index depth = index - (index / m_fastDimZero) * m_dimensions[0];
const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
const Index depth = index - (index / m_fastDimZero) * m_dimensions[depth_index];
const Index inputIndex = depth + inputRow * m_rowInputStride + inputCol * m_colInputStride + otherIndex * m_patchInputStride;
return m_impl.coeff(inputIndex);
@@ -286,7 +322,8 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
if (inputRows[0] >= 0 && inputRows[1] < m_inputRows) {
// no padding
const Index depth = index - (index / m_fastDimZero) * m_dimensions[0];
const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
const Index depth = index - (index / m_fastDimZero) * m_dimensions[depth_index];
const Index inputIndex = depth + inputRows[0] * m_rowInputStride + inputCols[0] * m_colInputStride + otherIndex * m_patchInputStride;
return m_impl.template packet<Unaligned>(inputIndex);
}
@@ -309,14 +346,24 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(const array<Index, NumDims>& coords) const
{
// Location of the first element of the patch.
// ColMajor
// 0: d, 1: patch_rows, 2: patch_cols, 3: number of patches, 4: number of batches
const Index patchIndex = coords[3];
// RowMajor
// 0: number of batches, 1: number of patches, 2: patch_cols , 3: patch_rows, 4: d
const Index patchIndex = coords[static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 3 : 1];
array<Index, NumDims-1> inputCoords;
inputCoords[0] = coords[0]; // depth
inputCoords[1] = patchIndex / m_inputCols + coords[1] - m_rowPaddingTop;
inputCoords[2] = patchIndex - patchIndex / m_inputCols * m_inputCols + coords[2] - m_colPaddingLeft;
inputCoords[3] = coords[4]; // batch
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
inputCoords[0] = coords[0]; // depth
inputCoords[1] = patchIndex / m_inputCols + coords[1] - m_rowPaddingTop;
inputCoords[2] = patchIndex - patchIndex / m_inputCols * m_inputCols + coords[2] - m_colPaddingLeft;
inputCoords[3] = coords[4]; // batch
} else {
inputCoords[3] = coords[4]; // depth
inputCoords[2] = patchIndex / m_inputCols + coords[3] - m_rowPaddingTop;
inputCoords[1] = patchIndex - patchIndex / m_inputCols * m_inputCols + coords[2] - m_colPaddingLeft;
inputCoords[0] = coords[0]; // batch
}
// If the computed coordinates are outside the original image perimeter, return 0.
if (inputCoords[1] < 0 || inputCoords[1] >= m_inputRows ||
inputCoords[2] < 0 || inputCoords[2] >= m_inputCols) {
@@ -325,11 +372,20 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
if (TensorEvaluator<ArgType, Device>::CoordAccess) {
return m_impl.coeff(inputCoords);
} else {
Index inputIndex =
Index inputIndex;
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
inputIndex =
inputCoords[3] * m_patchInputStride +
inputCoords[2] * m_colInputStride +
inputCoords[1] * m_rowInputStride +
inputCoords[0];
} else {
inputIndex =
inputCoords[1] * m_patchInputStride +
inputCoords[2] * m_colInputStride +
inputCoords[3] * m_rowInputStride +
inputCoords[4];
}
return m_impl.coeff(inputIndex);
}
}