| // 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; |
| |
| template<int DataLayout> |
| static void test_simple_chip() |
| { |
| Tensor<float, 5, DataLayout> tensor(2,3,5,7,11); |
| tensor.setRandom(); |
| |
| Tensor<float, 4, DataLayout> chip1; |
| chip1 = tensor.template chip<0>(1); |
| |
| VERIFY_IS_EQUAL(chip1.dimension(0), 3); |
| VERIFY_IS_EQUAL(chip1.dimension(1), 5); |
| VERIFY_IS_EQUAL(chip1.dimension(2), 7); |
| VERIFY_IS_EQUAL(chip1.dimension(3), 11); |
| |
| for (int i = 0; i < 3; ++i) { |
| for (int j = 0; j < 5; ++j) { |
| for (int k = 0; k < 7; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| VERIFY_IS_EQUAL(chip1(i,j,k,l), tensor(1,i,j,k,l)); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> chip2 = tensor.template chip<1>(1); |
| VERIFY_IS_EQUAL(chip2.dimension(0), 2); |
| VERIFY_IS_EQUAL(chip2.dimension(1), 5); |
| VERIFY_IS_EQUAL(chip2.dimension(2), 7); |
| VERIFY_IS_EQUAL(chip2.dimension(3), 11); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 5; ++j) { |
| for (int k = 0; k < 7; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| VERIFY_IS_EQUAL(chip2(i,j,k,l), tensor(i,1,j,k,l)); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> chip3 = tensor.template chip<2>(2); |
| VERIFY_IS_EQUAL(chip3.dimension(0), 2); |
| VERIFY_IS_EQUAL(chip3.dimension(1), 3); |
| VERIFY_IS_EQUAL(chip3.dimension(2), 7); |
| VERIFY_IS_EQUAL(chip3.dimension(3), 11); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 7; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| VERIFY_IS_EQUAL(chip3(i,j,k,l), tensor(i,j,2,k,l)); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> chip4(tensor.template chip<3>(5)); |
| VERIFY_IS_EQUAL(chip4.dimension(0), 2); |
| VERIFY_IS_EQUAL(chip4.dimension(1), 3); |
| VERIFY_IS_EQUAL(chip4.dimension(2), 5); |
| VERIFY_IS_EQUAL(chip4.dimension(3), 11); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| VERIFY_IS_EQUAL(chip4(i,j,k,l), tensor(i,j,k,5,l)); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> chip5(tensor.template chip<4>(7)); |
| VERIFY_IS_EQUAL(chip5.dimension(0), 2); |
| VERIFY_IS_EQUAL(chip5.dimension(1), 3); |
| VERIFY_IS_EQUAL(chip5.dimension(2), 5); |
| VERIFY_IS_EQUAL(chip5.dimension(3), 7); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| VERIFY_IS_EQUAL(chip5(i,j,k,l), tensor(i,j,k,l,7)); |
| } |
| } |
| } |
| } |
| } |
| |
| template<int DataLayout> |
| static void test_dynamic_chip() |
| { |
| Tensor<float, 5, DataLayout> tensor(2,3,5,7,11); |
| tensor.setRandom(); |
| |
| Tensor<float, 4, DataLayout> chip1; |
| chip1 = tensor.chip(1, 0); |
| VERIFY_IS_EQUAL(chip1.dimension(0), 3); |
| VERIFY_IS_EQUAL(chip1.dimension(1), 5); |
| VERIFY_IS_EQUAL(chip1.dimension(2), 7); |
| VERIFY_IS_EQUAL(chip1.dimension(3), 11); |
| for (int i = 0; i < 3; ++i) { |
| for (int j = 0; j < 5; ++j) { |
| for (int k = 0; k < 7; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| VERIFY_IS_EQUAL(chip1(i,j,k,l), tensor(1,i,j,k,l)); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> chip2 = tensor.chip(1, 1); |
| VERIFY_IS_EQUAL(chip2.dimension(0), 2); |
| VERIFY_IS_EQUAL(chip2.dimension(1), 5); |
| VERIFY_IS_EQUAL(chip2.dimension(2), 7); |
| VERIFY_IS_EQUAL(chip2.dimension(3), 11); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 5; ++j) { |
| for (int k = 0; k < 7; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| VERIFY_IS_EQUAL(chip2(i,j,k,l), tensor(i,1,j,k,l)); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> chip3 = tensor.chip(2, 2); |
| VERIFY_IS_EQUAL(chip3.dimension(0), 2); |
| VERIFY_IS_EQUAL(chip3.dimension(1), 3); |
| VERIFY_IS_EQUAL(chip3.dimension(2), 7); |
| VERIFY_IS_EQUAL(chip3.dimension(3), 11); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 7; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| VERIFY_IS_EQUAL(chip3(i,j,k,l), tensor(i,j,2,k,l)); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> chip4(tensor.chip(5, 3)); |
| VERIFY_IS_EQUAL(chip4.dimension(0), 2); |
| VERIFY_IS_EQUAL(chip4.dimension(1), 3); |
| VERIFY_IS_EQUAL(chip4.dimension(2), 5); |
| VERIFY_IS_EQUAL(chip4.dimension(3), 11); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| VERIFY_IS_EQUAL(chip4(i,j,k,l), tensor(i,j,k,5,l)); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> chip5(tensor.chip(7, 4)); |
| VERIFY_IS_EQUAL(chip5.dimension(0), 2); |
| VERIFY_IS_EQUAL(chip5.dimension(1), 3); |
| VERIFY_IS_EQUAL(chip5.dimension(2), 5); |
| VERIFY_IS_EQUAL(chip5.dimension(3), 7); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| VERIFY_IS_EQUAL(chip5(i,j,k,l), tensor(i,j,k,l,7)); |
| } |
| } |
| } |
| } |
| } |
| |
| template<int DataLayout> |
| static void test_chip_in_expr() { |
| Tensor<float, 5, DataLayout> input1(2,3,5,7,11); |
| input1.setRandom(); |
| Tensor<float, 4, DataLayout> input2(3,5,7,11); |
| input2.setRandom(); |
| |
| Tensor<float, 4, DataLayout> result = input1.template chip<0>(0) + input2; |
| for (int i = 0; i < 3; ++i) { |
| for (int j = 0; j < 5; ++j) { |
| for (int k = 0; k < 7; ++k) { |
| for (int l = 0; l < 11; ++l) { |
| float expected = input1(0,i,j,k,l) + input2(i,j,k,l); |
| VERIFY_IS_EQUAL(result(i,j,k,l), expected); |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 3, DataLayout> input3(3,7,11); |
| input3.setRandom(); |
| Tensor<float, 3, DataLayout> result2 = input1.template chip<0>(0).template chip<1>(2) + input3; |
| for (int i = 0; i < 3; ++i) { |
| for (int j = 0; j < 7; ++j) { |
| for (int k = 0; k < 11; ++k) { |
| float expected = input1(0,i,2,j,k) + input3(i,j,k); |
| VERIFY_IS_EQUAL(result2(i,j,k), expected); |
| } |
| } |
| } |
| } |
| |
| template<int DataLayout> |
| static void test_chip_as_lvalue() |
| { |
| Tensor<float, 5, DataLayout> input1(2,3,5,7,11); |
| input1.setRandom(); |
| |
| Tensor<float, 4, DataLayout> input2(3,5,7,11); |
| input2.setRandom(); |
| Tensor<float, 5, DataLayout> tensor = input1; |
| tensor.template chip<0>(1) = input2; |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| for (int m = 0; m < 11; ++m) { |
| if (i != 1) { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m)); |
| } else { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input2(j,k,l,m)); |
| } |
| } |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> input3(2,5,7,11); |
| input3.setRandom(); |
| tensor = input1; |
| tensor.template chip<1>(1) = input3; |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| for (int m = 0; m < 11; ++m) { |
| if (j != 1) { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m)); |
| } else { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input3(i,k,l,m)); |
| } |
| } |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> input4(2,3,7,11); |
| input4.setRandom(); |
| tensor = input1; |
| tensor.template chip<2>(3) = input4; |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| for (int m = 0; m < 11; ++m) { |
| if (k != 3) { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m)); |
| } else { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input4(i,j,l,m)); |
| } |
| } |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> input5(2,3,5,11); |
| input5.setRandom(); |
| tensor = input1; |
| tensor.template chip<3>(4) = input5; |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| for (int m = 0; m < 11; ++m) { |
| if (l != 4) { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m)); |
| } else { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input5(i,j,k,m)); |
| } |
| } |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 4, DataLayout> input6(2,3,5,7); |
| input6.setRandom(); |
| tensor = input1; |
| tensor.template chip<4>(5) = input6; |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| for (int m = 0; m < 11; ++m) { |
| if (m != 5) { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m)); |
| } else { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input6(i,j,k,l)); |
| } |
| } |
| } |
| } |
| } |
| } |
| |
| Tensor<float, 5, DataLayout> input7(2,3,5,7,11); |
| input7.setRandom(); |
| tensor = input1; |
| tensor.chip(0, 0) = input7.chip(0, 0); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| for (int m = 0; m < 11; ++m) { |
| if (i != 0) { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input1(i,j,k,l,m)); |
| } else { |
| VERIFY_IS_EQUAL(tensor(i,j,k,l,m), input7(i,j,k,l,m)); |
| } |
| } |
| } |
| } |
| } |
| } |
| } |
| |
| static void test_chip_raw_data_col_major() |
| { |
| Tensor<float, 5, ColMajor> tensor(2,3,5,7,11); |
| tensor.setRandom(); |
| |
| typedef TensorEvaluator<decltype(tensor.chip<4>(3)), DefaultDevice> Evaluator4; |
| auto chip = Evaluator4(tensor.chip<4>(3), DefaultDevice()); |
| for (int i = 0; i < 2; ++i) { |
| for (int j = 0; j < 3; ++j) { |
| for (int k = 0; k < 5; ++k) { |
| for (int l = 0; l < 7; ++l) { |
| int chip_index = i + 2 * (j + 3 * (k + 5 * l)); |
| VERIFY_IS_EQUAL(chip.data()[chip_index], tensor(i,j,k,l,3)); |
| } |
| } |
| } |
| } |
| |
| typedef TensorEvaluator<decltype(tensor.chip<0>(0)), DefaultDevice> Evaluator0; |
| auto chip0 = Evaluator0(tensor.chip<0>(0), DefaultDevice()); |
| VERIFY_IS_EQUAL(chip0.data(), static_cast<float*>(0)); |
| |
| typedef TensorEvaluator<decltype(tensor.chip<1>(0)), DefaultDevice> Evaluator1; |
| auto chip1 = Evaluator1(tensor.chip<1>(0), DefaultDevice()); |
| VERIFY_IS_EQUAL(chip1.data(), static_cast<float*>(0)); |
| |
| typedef TensorEvaluator<decltype(tensor.chip<2>(0)), DefaultDevice> Evaluator2; |
| auto chip2 = Evaluator2(tensor.chip<2>(0), DefaultDevice()); |
| VERIFY_IS_EQUAL(chip2.data(), static_cast<float*>(0)); |
| |
| typedef TensorEvaluator<decltype(tensor.chip<3>(0)), DefaultDevice> Evaluator3; |
| auto chip3 = Evaluator3(tensor.chip<3>(0), DefaultDevice()); |
| VERIFY_IS_EQUAL(chip3.data(), static_cast<float*>(0)); |
| } |
| |
| static void test_chip_raw_data_row_major() |
| { |
| Tensor<float, 5, RowMajor> tensor(11,7,5,3,2); |
| tensor.setRandom(); |
| |
| typedef TensorEvaluator<decltype(tensor.chip<0>(3)), DefaultDevice> Evaluator0; |
| auto chip = Evaluator0(tensor.chip<0>(3), DefaultDevice()); |
| for (int i = 0; i < 7; ++i) { |
| for (int j = 0; j < 5; ++j) { |
| for (int k = 0; k < 3; ++k) { |
| for (int l = 0; l < 2; ++l) { |
| int chip_index = l + 2 * (k + 3 * (j + 5 * i)); |
| VERIFY_IS_EQUAL(chip.data()[chip_index], tensor(3,i,j,k,l)); |
| } |
| } |
| } |
| } |
| |
| typedef TensorEvaluator<decltype(tensor.chip<1>(0)), DefaultDevice> Evaluator1; |
| auto chip1 = Evaluator1(tensor.chip<1>(0), DefaultDevice()); |
| VERIFY_IS_EQUAL(chip1.data(), static_cast<float*>(0)); |
| |
| typedef TensorEvaluator<decltype(tensor.chip<2>(0)), DefaultDevice> Evaluator2; |
| auto chip2 = Evaluator2(tensor.chip<2>(0), DefaultDevice()); |
| VERIFY_IS_EQUAL(chip2.data(), static_cast<float*>(0)); |
| |
| typedef TensorEvaluator<decltype(tensor.chip<3>(0)), DefaultDevice> Evaluator3; |
| auto chip3 = Evaluator3(tensor.chip<3>(0), DefaultDevice()); |
| VERIFY_IS_EQUAL(chip3.data(), static_cast<float*>(0)); |
| |
| typedef TensorEvaluator<decltype(tensor.chip<4>(0)), DefaultDevice> Evaluator4; |
| auto chip4 = Evaluator4(tensor.chip<4>(0), DefaultDevice()); |
| VERIFY_IS_EQUAL(chip4.data(), static_cast<float*>(0)); |
| } |
| |
| EIGEN_DECLARE_TEST(cxx11_tensor_chipping) |
| { |
| CALL_SUBTEST(test_simple_chip<ColMajor>()); |
| CALL_SUBTEST(test_simple_chip<RowMajor>()); |
| CALL_SUBTEST(test_dynamic_chip<ColMajor>()); |
| CALL_SUBTEST(test_dynamic_chip<RowMajor>()); |
| CALL_SUBTEST(test_chip_in_expr<ColMajor>()); |
| CALL_SUBTEST(test_chip_in_expr<RowMajor>()); |
| CALL_SUBTEST(test_chip_as_lvalue<ColMajor>()); |
| CALL_SUBTEST(test_chip_as_lvalue<RowMajor>()); |
| CALL_SUBTEST(test_chip_raw_data_col_major()); |
| CALL_SUBTEST(test_chip_raw_data_row_major()); |
| } |