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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
View File

@ -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);
}
}

358
unsupported/test/cxx11_tensor_image_patch.cpp
View File

@ -17,32 +17,69 @@ static void test_simple_patch()
{
Tensor<float, 4> tensor(2,3,5,7);
tensor.setRandom();
Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));
// Single pixel patch: ColMajor
Tensor<float, 5> single_pixel_patch;
single_pixel_patch = tensor.extract_image_patches<1, 1>();
VERIFY_IS_EQUAL(single_pixel_patch.dimension(0), 2);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(1), 1);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(2), 1);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(3), 3*5);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(4), 7);
// Single pixel patch: RowMajor
Tensor<float, 5, RowMajor> single_pixel_patch_row_major;
single_pixel_patch_row_major = tensor_row_major.extract_image_patches<1, 1>();
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(0), 7);
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(1), 3*5);
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(2), 1);
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(3), 1);
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(4), 2);
for (int i = 0; i < tensor.size(); ++i) {
// ColMajor
if (tensor.data()[i] != single_pixel_patch.data()[i]) {
std::cout << "Mismatch detected at index " << i << " : " << tensor.data()[i] << " vs " << single_pixel_patch.data()[i] << std::endl;
std::cout << "Mismatch detected at index " << i << " : "
<< tensor.data()[i] << " vs " << single_pixel_patch.data()[i]
<< std::endl;
}
VERIFY_IS_EQUAL(single_pixel_patch.data()[i], tensor.data()[i]);
// RowMajor
if (tensor_row_major.data()[i] != single_pixel_patch_row_major.data()[i]) {
std::cout << "Mismatch detected at index " << i << " : "
<< tensor.data()[i] << " vs "
<< single_pixel_patch_row_major.data()[i] << std::endl;
}
VERIFY_IS_EQUAL(single_pixel_patch_row_major.data()[i],
tensor_row_major.data()[i]);
VERIFY_IS_EQUAL(tensor.data()[i], tensor_row_major.data()[i]);
VERIFY_IS_EQUAL(single_pixel_patch.data()[i],
single_pixel_patch_row_major.data()[i]);
}
// Entire image patch: ColMajor
Tensor<float, 5> entire_image_patch;
entire_image_patch = tensor.extract_image_patches<3, 5>();
VERIFY_IS_EQUAL(entire_image_patch.dimension(0), 2);
VERIFY_IS_EQUAL(entire_image_patch.dimension(1), 3);
VERIFY_IS_EQUAL(entire_image_patch.dimension(2), 5);
VERIFY_IS_EQUAL(entire_image_patch.dimension(3), 3*5);
VERIFY_IS_EQUAL(entire_image_patch.dimension(4), 7);
// Entire image patch: RowMajor
Tensor<float, 5, RowMajor> entire_image_patch_row_major;
entire_image_patch_row_major = tensor_row_major.extract_image_patches<3, 5>();
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(0), 7);
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(1), 3*5);
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(2), 5);
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(3), 3);
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(4), 2);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 5; ++j) {
int patchId = i+3*j;
@ -51,13 +88,27 @@ static void test_simple_patch()
for (int d = 0; d < 2; ++d) {
for (int b = 0; b < 7; ++b) {
float expected = 0.0f;
float expected_row_major = 0.0f;
if (r-1+i >= 0 && c-2+j >= 0 && r-1+i < 3 && c-2+j < 5) {
expected = tensor(d, r-1+i, c-2+j, b);
expected_row_major = tensor_row_major(b, c-2+j, r-1+i, d);
}
// ColMajor
if (entire_image_patch(d, r, c, patchId, b) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(entire_image_patch(d, r, c, patchId, b), expected);
// RowMajor
if (entire_image_patch_row_major(b, patchId, c, r, d) !=
expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j
<< " r=" << r << " c=" << c << " d=" << d << " b=" << b
<< std::endl;
}
VERIFY_IS_EQUAL(entire_image_patch_row_major(b, patchId, c, r, d),
expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -65,15 +116,25 @@ static void test_simple_patch()
}
}
// 2D patch: ColMajor
Tensor<float, 5> twod_patch;
twod_patch = tensor.extract_image_patches<2, 2>();
VERIFY_IS_EQUAL(twod_patch.dimension(0), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(3), 3*5);
VERIFY_IS_EQUAL(twod_patch.dimension(4), 7);
// 2D patch: RowMajor
Tensor<float, 5, RowMajor> twod_patch_row_major;
twod_patch_row_major = tensor_row_major.extract_image_patches<2, 2>();
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(0), 7);
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(1), 3*5);
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(2), 2);
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(3), 2);
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(4), 2);
// Based on the calculation described in TensorTraits.h, padding happens to be 0.
int row_padding = 0;
int col_padding = 0;
@ -87,8 +148,10 @@ static void test_simple_patch()
for (int d = 0; d < 2; ++d) {
for (int b = 0; b < 7; ++b) {
float expected = 0.0f;
float expected_row_major = 0.0f;
int row_offset = r*stride + i - row_padding;
int col_offset = c*stride + j - col_padding;
// ColMajor
if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor.dimension(1) && col_offset < tensor.dimension(2)) {
expected = tensor(d, row_offset, col_offset, b);
}
@ -96,6 +159,18 @@ static void test_simple_patch()
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(twod_patch(d, r, c, patchId, b), expected);
// RowMajor
if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor_row_major.dimension(2) && col_offset < tensor_row_major.dimension(1)) {
expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
}
if (twod_patch_row_major(b, patchId, c, r, d) != expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(twod_patch_row_major(b, patchId, c, r, d), expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -118,6 +193,7 @@ static void test_patch_padding_valid()
for (int i = 0; i < tensor.size(); ++i) {
tensor.data()[i] = i + 1;
}
// ColMajor
Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, PADDING_VALID);
VERIFY_IS_EQUAL(result.dimension(0), input_depth); // depth
@ -126,6 +202,20 @@ static void test_patch_padding_valid()
VERIFY_IS_EQUAL(result.dimension(3), 1); // number of patches
VERIFY_IS_EQUAL(result.dimension(4), input_batches); // number of batches
// RowMajor
Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));
Tensor<float, 5, RowMajor> result_row_major = tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, PADDING_VALID);
VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));
// No padding is carried out.
int row_padding = 0;
int col_padding = 0;
@ -138,15 +228,25 @@ static void test_patch_padding_valid()
for (int d = 0; d < input_depth; ++d) { // depth
for (int b = 0; b < input_batches; ++b) { // batch
float expected = 0.0f;
float expected_row_major = 0.0f;
int row_offset = r + i - row_padding;
int col_offset = c + j - col_padding;
if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows && col_offset < input_cols) {
expected = tensor(d, row_offset, col_offset, b);
expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
}
// ColMajor
if (result(d, r, c, patchId, b) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
// RowMajor
if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -164,6 +264,7 @@ static void test_patch_padding_valid_same_value()
int input_batches = 2;
int ksize = 3; // Corresponds to the Rows and Cols for tensor.extract_image_patches<>.
int stride = 2; // Only same stride is supported.
// ColMajor
Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
tensor = tensor.constant(11.0f);
Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, PADDING_VALID);
@ -174,6 +275,20 @@ static void test_patch_padding_valid_same_value()
VERIFY_IS_EQUAL(result.dimension(3), 4); // number of patches
VERIFY_IS_EQUAL(result.dimension(4), input_batches); // number of batches
// RowMajor
Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));
Tensor<float, 5, RowMajor> result_row_major = tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, PADDING_VALID);
VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));
// No padding is carried out.
int row_padding = 0;
int col_padding = 0;
@ -186,15 +301,25 @@ static void test_patch_padding_valid_same_value()
for (int d = 0; d < input_depth; ++d) { // depth
for (int b = 0; b < input_batches; ++b) { // batch
float expected = 0.0f;
float expected_row_major = 0.0f;
int row_offset = r + i - row_padding;
int col_offset = c + j - col_padding;
if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows && col_offset < input_cols) {
expected = tensor(d, row_offset, col_offset, b);
expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
}
// ColMajor
if (result(d, r, c, patchId, b) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
// RowMajor
if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -212,6 +337,7 @@ static void test_patch_padding_same()
int input_batches = 1;
int ksize = 2; // Corresponds to the Rows and Cols for tensor.extract_image_patches<>.
int stride = 2; // Only same stride is supported.
// ColMajor
Tensor<float, 4> tensor(input_depth, input_rows, input_cols, input_batches);
// Initializes tensor with incrementing numbers.
for (int i = 0; i < tensor.size(); ++i) {
@ -225,6 +351,20 @@ static void test_patch_padding_same()
VERIFY_IS_EQUAL(result.dimension(3), 2); // number of patches
VERIFY_IS_EQUAL(result.dimension(4), input_batches); // number of batches
// RowMajor
Tensor<float, 4, RowMajor> tensor_row_major = tensor.swap_layout();
VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(3));
VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(2));
VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(1));
VERIFY_IS_EQUAL(tensor.dimension(3), tensor_row_major.dimension(0));
Tensor<float, 5, RowMajor> result_row_major = tensor_row_major.extract_image_patches(ksize, ksize, stride, stride, PADDING_SAME);
VERIFY_IS_EQUAL(result.dimension(0), result_row_major.dimension(4));
VERIFY_IS_EQUAL(result.dimension(1), result_row_major.dimension(3));
VERIFY_IS_EQUAL(result.dimension(2), result_row_major.dimension(2));
VERIFY_IS_EQUAL(result.dimension(3), result_row_major.dimension(1));
VERIFY_IS_EQUAL(result.dimension(4), result_row_major.dimension(0));
// Based on the calculation described in TensorTraits.h, padding happens to be
// 0.
int row_padding = 0;
@ -238,15 +378,25 @@ static void test_patch_padding_same()
for (int d = 0; d < input_depth; ++d) { // depth
for (int b = 0; b < input_batches; ++b) { // batch
float expected = 0.0f;
float expected_row_major = 0.0f;
int row_offset = r*stride + i - row_padding;
int col_offset = c*stride + j - col_padding;
if (row_offset >= 0 && col_offset >= 0 && row_offset < input_rows && col_offset < input_cols) {
expected = tensor(d, row_offset, col_offset, b);
expected_row_major = tensor_row_major(b, col_offset, row_offset, d);
}
// ColMajor
if (result(d, r, c, patchId, b) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(result(d, r, c, patchId, b), expected);
// RowMajor
if (result_row_major(b, patchId, c, r, d) != expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(result_row_major(b, patchId, c, r, d), expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -259,30 +409,62 @@ static void test_patch_no_extra_dim()
{
Tensor<float, 3> tensor(2,3,5);
tensor.setRandom();
Tensor<float, 3, RowMajor> tensor_row_major = tensor.swap_layout();
VERIFY_IS_EQUAL(tensor.dimension(0), tensor_row_major.dimension(2));
VERIFY_IS_EQUAL(tensor.dimension(1), tensor_row_major.dimension(1));
VERIFY_IS_EQUAL(tensor.dimension(2), tensor_row_major.dimension(0));
// Single pixel patch: ColMajor
Tensor<float, 4> single_pixel_patch;
single_pixel_patch = tensor.extract_image_patches<1, 1>();
VERIFY_IS_EQUAL(single_pixel_patch.dimension(0), 2);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(1), 1);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(2), 1);
VERIFY_IS_EQUAL(single_pixel_patch.dimension(3), 3*5);
// Single pixel patch: RowMajor
Tensor<float, 4, RowMajor> single_pixel_patch_row_major;
single_pixel_patch_row_major = tensor_row_major.extract_image_patches<1, 1>();
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(0), 3*5);
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(1), 1);
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(2), 1);
VERIFY_IS_EQUAL(single_pixel_patch_row_major.dimension(3), 2);
for (int i = 0; i < tensor.size(); ++i) {
// ColMajor
if (tensor.data()[i] != single_pixel_patch.data()[i]) {
std::cout << "Mismatch detected at index " << i << " : " << tensor.data()[i] << " vs " << single_pixel_patch.data()[i] << std::endl;
}
VERIFY_IS_EQUAL(single_pixel_patch.data()[i], tensor.data()[i]);
// RowMajor
if (tensor_row_major.data()[i] != single_pixel_patch_row_major.data()[i]) {
std::cout << "Mismatch detected at index " << i << " : "
<< tensor.data()[i] << " vs "
<< single_pixel_patch_row_major.data()[i] << std::endl;
}
VERIFY_IS_EQUAL(single_pixel_patch_row_major.data()[i],
tensor_row_major.data()[i]);
VERIFY_IS_EQUAL(tensor.data()[i], tensor_row_major.data()[i]);
VERIFY_IS_EQUAL(single_pixel_patch.data()[i],
single_pixel_patch_row_major.data()[i]);
}
// Entire image patch: ColMajor
Tensor<float, 4> entire_image_patch;
entire_image_patch = tensor.extract_image_patches<3, 5>();
VERIFY_IS_EQUAL(entire_image_patch.dimension(0), 2);
VERIFY_IS_EQUAL(entire_image_patch.dimension(1), 3);
VERIFY_IS_EQUAL(entire_image_patch.dimension(2), 5);
VERIFY_IS_EQUAL(entire_image_patch.dimension(3), 3*5);
// Entire image patch: RowMajor
Tensor<float, 4, RowMajor> entire_image_patch_row_major;
entire_image_patch_row_major = tensor_row_major.extract_image_patches<3, 5>();
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(0), 3*5);
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(1), 5);
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(2), 3);
VERIFY_IS_EQUAL(entire_image_patch_row_major.dimension(3), 2);
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 5; ++j) {
int patchId = i+3*j;
@ -290,27 +472,47 @@ static void test_patch_no_extra_dim()
for (int c = 0; c < 5; ++c) {
for (int d = 0; d < 2; ++d) {
float expected = 0.0f;
float expected_row_major = 0.0f;
if (r-1+i >= 0 && c-2+j >= 0 && r-1+i < 3 && c-2+j < 5) {
expected = tensor(d, r-1+i, c-2+j);
expected_row_major = tensor_row_major(c-2+j, r-1+i, d);
}
// ColMajor
if (entire_image_patch(d, r, c, patchId) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << std::endl;
}
VERIFY_IS_EQUAL(entire_image_patch(d, r, c, patchId), expected);
// RowMajor
if (entire_image_patch_row_major(patchId, c, r, d) !=
expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << std::endl;
}
VERIFY_IS_EQUAL(entire_image_patch_row_major(patchId, c, r, d),
expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
}
}
// 2D patch: ColMajor
Tensor<float, 4> twod_patch;
twod_patch = tensor.extract_image_patches<2, 2>();
VERIFY_IS_EQUAL(twod_patch.dimension(0), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(1), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(2), 2);
VERIFY_IS_EQUAL(twod_patch.dimension(3), 3*5);
// 2D patch: RowMajor
Tensor<float, 4, RowMajor> twod_patch_row_major;
twod_patch_row_major = tensor_row_major.extract_image_patches<2, 2>();
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(0), 3*5);
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(1), 2);
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(2), 2);
VERIFY_IS_EQUAL(twod_patch_row_major.dimension(3), 2);
// Based on the calculation described in TensorTraits.h, padding happens to be 0.
int row_padding = 0;
int col_padding = 0;
@ -323,8 +525,10 @@ static void test_patch_no_extra_dim()
for (int c = 0; c < 2; ++c) {
for (int d = 0; d < 2; ++d) {
float expected = 0.0f;
float expected_row_major = 0.0f;
int row_offset = r*stride + i - row_padding;
int col_offset = c*stride + j - col_padding;
// ColMajor
if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor.dimension(1) && col_offset < tensor.dimension(2)) {
expected = tensor(d, row_offset, col_offset);
}
@ -332,6 +536,16 @@ static void test_patch_no_extra_dim()
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << std::endl;
}
VERIFY_IS_EQUAL(twod_patch(d, r, c, patchId), expected);
// RowMajor
if (row_offset >= 0 && col_offset >= 0 && row_offset < tensor_row_major.dimension(1) && col_offset < tensor_row_major.dimension(0)) {
expected_row_major = tensor_row_major(col_offset, row_offset, d);
}
if (twod_patch_row_major(patchId, c, r, d) != expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << std::endl;
}
VERIFY_IS_EQUAL(twod_patch_row_major(patchId, c, r, d), expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -339,20 +553,35 @@ static void test_patch_no_extra_dim()
}
}
static void test_imagenet_patches()
{
// Test the code on typical configurations used by the 'imagenet' benchmarks at
// https://github.com/soumith/convnet-benchmarks
Tensor<float, 4> l_in(3, 128, 128, 128);
// ColMajor
Tensor<float, 4> l_in(3, 128, 128, 16);
l_in.setRandom();
Tensor<float, 5> l_out = l_in.extract_image_patches(11, 11);
VERIFY_IS_EQUAL(l_out.dimension(0), 3);
VERIFY_IS_EQUAL(l_out.dimension(1), 11);
VERIFY_IS_EQUAL(l_out.dimension(2), 11);
VERIFY_IS_EQUAL(l_out.dimension(3), 128*128);
VERIFY_IS_EQUAL(l_out.dimension(4), 128);
for (int b = 0; b < 128; ++b) {
VERIFY_IS_EQUAL(l_out.dimension(4), 16);
// RowMajor
Tensor<float, 4, RowMajor> l_in_row_major = l_in.swap_layout();
VERIFY_IS_EQUAL(l_in.dimension(0), l_in_row_major.dimension(3));
VERIFY_IS_EQUAL(l_in.dimension(1), l_in_row_major.dimension(2));
VERIFY_IS_EQUAL(l_in.dimension(2), l_in_row_major.dimension(1));
VERIFY_IS_EQUAL(l_in.dimension(3), l_in_row_major.dimension(0));
Tensor<float, 5, RowMajor> l_out_row_major = l_in_row_major.extract_image_patches(11, 11);
VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 16);
VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 128*128);
VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 11);
VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 11);
VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 3);
for (int b = 0; b < 16; ++b) {
for (int i = 0; i < 128; ++i) {
for (int j = 0; j < 128; ++j) {
int patchId = i+128*j;
@ -360,13 +589,27 @@ static void test_imagenet_patches()
for (int r = 0; r < 11; ++r) {
for (int d = 0; d < 3; ++d) {
float expected = 0.0f;
float expected_row_major = 0.0f;
if (r-5+i >= 0 && c-5+j >= 0 && r-5+i < 128 && c-5+j < 128) {
expected = l_in(d, r-5+i, c-5+j, b);
expected_row_major = l_in_row_major(b, c-5+j, r-5+i, d);
}
// ColMajor
if (l_out(d, r, c, patchId, b) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
// RowMajor
if (l_out_row_major(b, patchId, c, r, d) !=
expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j
<< " r=" << r << " c=" << c << " d=" << d << " b=" << b
<< std::endl;
}
VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d),
expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -374,29 +617,50 @@ static void test_imagenet_patches()
}
}
l_in.resize(64, 64, 64, 128);
// ColMajor
l_in.resize(16, 64, 64, 32);
l_in.setRandom();
l_out = l_in.extract_image_patches(9, 9);
VERIFY_IS_EQUAL(l_out.dimension(0), 64);
VERIFY_IS_EQUAL(l_out.dimension(0), 16);
VERIFY_IS_EQUAL(l_out.dimension(1), 9);
VERIFY_IS_EQUAL(l_out.dimension(2), 9);
VERIFY_IS_EQUAL(l_out.dimension(3), 64*64);
VERIFY_IS_EQUAL(l_out.dimension(4), 128);
for (int b = 0; b < 128; ++b) {
VERIFY_IS_EQUAL(l_out.dimension(4), 32);
// RowMajor
l_in_row_major = l_in.swap_layout();
l_out_row_major = l_in_row_major.extract_image_patches(9, 9);
VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 64*64);
VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 9);
VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 9);
VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 16);
for (int b = 0; b < 32; ++b) {
for (int i = 0; i < 64; ++i) {
for (int j = 0; j < 64; ++j) {
int patchId = i+64*j;
for (int c = 0; c < 9; ++c) {
for (int r = 0; r < 9; ++r) {
for (int d = 0; d < 64; ++d) {
for (int d = 0; d < 16; ++d) {
float expected = 0.0f;
float expected_row_major = 0.0f;
if (r-4+i >= 0 && c-4+j >= 0 && r-4+i < 64 && c-4+j < 64) {
expected = l_in(d, r-4+i, c-4+j, b);
expected_row_major = l_in_row_major(b, c-4+j, r-4+i, d);
}
// ColMajor
if (l_out(d, r, c, patchId, b) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
// RowMajor
if (l_out_row_major(b, patchId, c, r, d) != expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -404,29 +668,50 @@ static void test_imagenet_patches()
}
}
l_in.resize(128, 16, 16, 128);
// ColMajor
l_in.resize(32, 16, 16, 32);
l_in.setRandom();
l_out = l_in.extract_image_patches(7, 7);
VERIFY_IS_EQUAL(l_out.dimension(0), 128);
VERIFY_IS_EQUAL(l_out.dimension(0), 32);
VERIFY_IS_EQUAL(l_out.dimension(1), 7);
VERIFY_IS_EQUAL(l_out.dimension(2), 7);
VERIFY_IS_EQUAL(l_out.dimension(3), 16*16);
VERIFY_IS_EQUAL(l_out.dimension(4), 128);
for (int b = 0; b < 128; ++b) {
VERIFY_IS_EQUAL(l_out.dimension(4), 32);
// RowMajor
l_in_row_major = l_in.swap_layout();
l_out_row_major = l_in_row_major.extract_image_patches(7, 7);
VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 16*16);
VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 7);
VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 7);
VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 32);
for (int b = 0; b < 32; ++b) {
for (int i = 0; i < 16; ++i) {
for (int j = 0; j < 16; ++j) {
int patchId = i+16*j;
for (int c = 0; c < 7; ++c) {
for (int r = 0; r < 7; ++r) {
for (int d = 0; d < 128; ++d) {
for (int d = 0; d < 32; ++d) {
float expected = 0.0f;
float expected_row_major = 0.0f;
if (r-3+i >= 0 && c-3+j >= 0 && r-3+i < 16 && c-3+j < 16) {
expected = l_in(d, r-3+i, c-3+j, b);
expected_row_major = l_in_row_major(b, c-3+j, r-3+i, d);
}
// ColMajor
if (l_out(d, r, c, patchId, b) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
// RowMajor
if (l_out_row_major(b, patchId, c, r, d) != expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}
@ -434,29 +719,50 @@ static void test_imagenet_patches()
}
}
l_in.resize(384, 13, 13, 128);
// ColMajor
l_in.resize(64, 13, 13, 32);
l_in.setRandom();
l_out = l_in.extract_image_patches(3, 3);
VERIFY_IS_EQUAL(l_out.dimension(0), 384);
VERIFY_IS_EQUAL(l_out.dimension(0), 64);
VERIFY_IS_EQUAL(l_out.dimension(1), 3);
VERIFY_IS_EQUAL(l_out.dimension(2), 3);
VERIFY_IS_EQUAL(l_out.dimension(3), 13*13);
VERIFY_IS_EQUAL(l_out.dimension(4), 128);
for (int b = 0; b < 128; ++b) {
VERIFY_IS_EQUAL(l_out.dimension(4), 32);
// RowMajor
l_in_row_major = l_in.swap_layout();
l_out_row_major = l_in_row_major.extract_image_patches(3, 3);
VERIFY_IS_EQUAL(l_out_row_major.dimension(0), 32);
VERIFY_IS_EQUAL(l_out_row_major.dimension(1), 13*13);
VERIFY_IS_EQUAL(l_out_row_major.dimension(2), 3);
VERIFY_IS_EQUAL(l_out_row_major.dimension(3), 3);
VERIFY_IS_EQUAL(l_out_row_major.dimension(4), 64);
for (int b = 0; b < 32; ++b) {
for (int i = 0; i < 13; ++i) {
for (int j = 0; j < 13; ++j) {
int patchId = i+13*j;
for (int c = 0; c < 3; ++c) {
for (int r = 0; r < 3; ++r) {
for (int d = 0; d < 384; ++d) {
for (int d = 0; d < 64; ++d) {
float expected = 0.0f;
float expected_row_major = 0.0f;
if (r-1+i >= 0 && c-1+j >= 0 && r-1+i < 13 && c-1+j < 13) {
expected = l_in(d, r-1+i, c-1+j, b);
expected_row_major = l_in_row_major(b, c-1+j, r-1+i, d);
}
// ColMajor
if (l_out(d, r, c, patchId, b) != expected) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(l_out(d, r, c, patchId, b), expected);
// RowMajor
if (l_out_row_major(b, patchId, c, r, d) != expected_row_major) {
std::cout << "Mismatch detected at index i=" << i << " j=" << j << " r=" << r << " c=" << c << " d=" << d << " b=" << b << std::endl;
}
VERIFY_IS_EQUAL(l_out_row_major(b, patchId, c, r, d), expected_row_major);
// Check that ColMajor and RowMajor agree.
VERIFY_IS_EQUAL(expected, expected_row_major);
}
}
}