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Diffstat (limited to 'unsupported/test/cxx11_tensor_chipping.cpp')
-rw-r--r-- | unsupported/test/cxx11_tensor_chipping.cpp | 425 |
1 files changed, 425 insertions, 0 deletions
diff --git a/unsupported/test/cxx11_tensor_chipping.cpp b/unsupported/test/cxx11_tensor_chipping.cpp new file mode 100644 index 000000000..1832dec8b --- /dev/null +++ b/unsupported/test/cxx11_tensor_chipping.cpp @@ -0,0 +1,425 @@ +// 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 < 3; ++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 < 7; ++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 < 3; ++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 < 7; ++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)); +} + +void 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()); +} |