|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com> | 
|  | // | 
|  | // This Source Code Form is subject to the terms of the Mozilla | 
|  | // Public License v. 2.0. If a copy of the MPL was not distributed | 
|  | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | 
|  |  | 
|  | #include "main.h" | 
|  |  | 
|  | #include <Eigen/CXX11/Tensor> | 
|  |  | 
|  | using Eigen::Tensor; | 
|  |  | 
|  | 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; | 
|  | } | 
|  | 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; | 
|  | for (int r = 0; r < 3; ++r) { | 
|  | for (int c = 0; c < 5; ++c) { | 
|  | 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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | // 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; | 
|  | int stride = 1; | 
|  |  | 
|  | for (int i = 0; i < 3; ++i) { | 
|  | for (int j = 0; j < 5; ++j) { | 
|  | int patchId = i+3*j; | 
|  | for (int r = 0; r < 2; ++r) { | 
|  | for (int c = 0; c < 2; ++c) { | 
|  | 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); | 
|  | } | 
|  | if (twod_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(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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | // Verifies VALID padding (no padding) with incrementing values. | 
|  | static void test_patch_padding_valid() | 
|  | { | 
|  | int input_depth = 3; | 
|  | int input_rows = 3; | 
|  | int input_cols = 3; | 
|  | 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. | 
|  | 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) { | 
|  | tensor.data()[i] = i + 1; | 
|  | } | 
|  | // ColMajor | 
|  | Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, 1, 1, PADDING_VALID); | 
|  |  | 
|  | VERIFY_IS_EQUAL(result.dimension(0), input_depth);  // depth | 
|  | VERIFY_IS_EQUAL(result.dimension(1), ksize);  // kernel rows | 
|  | VERIFY_IS_EQUAL(result.dimension(2), ksize);  // kernel cols | 
|  | 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, 1, 1, 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; | 
|  |  | 
|  | for (int i = 0; (i+stride+ksize-1) < input_rows; i += stride) {  // input rows | 
|  | for (int j = 0; (j+stride+ksize-1) < input_cols; j += stride) {  // input cols | 
|  | int patchId = i+input_rows*j; | 
|  | for (int r = 0; r < ksize; ++r) {  // patch rows | 
|  | for (int c = 0; c < ksize; ++c) {  // patch cols | 
|  | 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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | // Verifies VALID padding (no padding) with the same value. | 
|  | static void test_patch_padding_valid_same_value() | 
|  | { | 
|  | int input_depth = 1; | 
|  | int input_rows = 5; | 
|  | int input_cols = 5; | 
|  | 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, 1, 1, PADDING_VALID); | 
|  |  | 
|  | VERIFY_IS_EQUAL(result.dimension(0), input_depth);  // depth | 
|  | VERIFY_IS_EQUAL(result.dimension(1), ksize);  // kernel rows | 
|  | VERIFY_IS_EQUAL(result.dimension(2), ksize);  // kernel cols | 
|  | 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, 1, 1, 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; | 
|  |  | 
|  | for (int i = 0; (i+stride+ksize-1) <= input_rows; i += stride) {  // input rows | 
|  | for (int j = 0; (j+stride+ksize-1) <= input_cols; j += stride) {  // input cols | 
|  | int patchId = i+input_rows*j; | 
|  | for (int r = 0; r < ksize; ++r) {  // patch rows | 
|  | for (int c = 0; c < ksize; ++c) {  // patch cols | 
|  | 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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | // Verifies SAME padding. | 
|  | static void test_patch_padding_same() | 
|  | { | 
|  | int input_depth = 3; | 
|  | int input_rows = 4; | 
|  | int input_cols = 2; | 
|  | 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) { | 
|  | tensor.data()[i] = i + 1; | 
|  | } | 
|  | Tensor<float, 5> result = tensor.extract_image_patches(ksize, ksize, stride, stride, PADDING_SAME); | 
|  |  | 
|  | VERIFY_IS_EQUAL(result.dimension(0), input_depth);  // depth | 
|  | VERIFY_IS_EQUAL(result.dimension(1), ksize);  // kernel rows | 
|  | VERIFY_IS_EQUAL(result.dimension(2), ksize);  // kernel cols | 
|  | 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; | 
|  | int col_padding = 0; | 
|  |  | 
|  | for (int i = 0; (i+stride+ksize-1) <= input_rows; i += stride) {  // input rows | 
|  | for (int j = 0; (j+stride+ksize-1) <= input_cols; j += stride) {  // input cols | 
|  | int patchId = i+input_rows*j; | 
|  | for (int r = 0; r < ksize; ++r) {  // patch rows | 
|  | for (int c = 0; c < ksize; ++c) {  // patch cols | 
|  | 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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | 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; | 
|  | for (int r = 0; r < 3; ++r) { | 
|  | 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; | 
|  | int stride = 1; | 
|  |  | 
|  | for (int i = 0; i < 3; ++i) { | 
|  | for (int j = 0; j < 5; ++j) { | 
|  | int patchId = i+3*j; | 
|  | for (int r = 0; r < 2; ++r) { | 
|  | 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); | 
|  | } | 
|  | if (twod_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(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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | static void test_imagenet_patches() | 
|  | { | 
|  | // Test the code on typical configurations used by the 'imagenet' benchmarks at | 
|  | // https://github.com/soumith/convnet-benchmarks | 
|  | // 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), 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; | 
|  | for (int c = 0; c < 11; ++c) { | 
|  | 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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | // 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), 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), 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 < 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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | // 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), 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), 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 < 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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | // 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), 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), 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 < 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); | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  | } | 
|  |  | 
|  | void test_cxx11_tensor_image_patch() | 
|  | { | 
|  | CALL_SUBTEST(test_simple_patch()); | 
|  | CALL_SUBTEST(test_patch_no_extra_dim()); | 
|  | CALL_SUBTEST(test_patch_padding_valid()); | 
|  | CALL_SUBTEST(test_patch_padding_valid_same_value()); | 
|  | CALL_SUBTEST(test_patch_padding_same()); | 
|  | CALL_SUBTEST(test_imagenet_patches()); | 
|  | } |