| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2024 Tobias Wood tobias@spinicist.org.uk |
| // |
| // 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::array; |
| using Eigen::Tensor; |
| |
| template <int DataLayout> |
| static void test_simple_roll() { |
| Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7); |
| tensor.setRandom(); |
| |
| array<Index, 4> dim_roll; |
| dim_roll[0] = 0; |
| dim_roll[1] = 1; |
| dim_roll[2] = 4; |
| dim_roll[3] = 8; |
| |
| Tensor<float, 4, DataLayout> rolled_tensor; |
| rolled_tensor = tensor.roll(dim_roll); |
| |
| VERIFY_IS_EQUAL(rolled_tensor.dimension(0), 2); |
| VERIFY_IS_EQUAL(rolled_tensor.dimension(1), 3); |
| VERIFY_IS_EQUAL(rolled_tensor.dimension(2), 5); |
| VERIFY_IS_EQUAL(rolled_tensor.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(tensor(i, (j + 1) % 3, (k + 4) % 5, (l + 8) % 7), rolled_tensor(i, j, k, l)); |
| } |
| } |
| } |
| } |
| |
| dim_roll[0] = -3; |
| dim_roll[1] = -2; |
| dim_roll[2] = -1; |
| dim_roll[3] = 0; |
| |
| rolled_tensor = tensor.roll(dim_roll); |
| |
| VERIFY_IS_EQUAL(rolled_tensor.dimension(0), 2); |
| VERIFY_IS_EQUAL(rolled_tensor.dimension(1), 3); |
| VERIFY_IS_EQUAL(rolled_tensor.dimension(2), 5); |
| VERIFY_IS_EQUAL(rolled_tensor.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(tensor((i + 1) % 2, (j + 1) % 3, (k + 4) % 5, l), rolled_tensor(i, j, k, l)); |
| } |
| } |
| } |
| } |
| } |
| |
| template <int DataLayout> |
| static void test_expr_roll(bool LValue) { |
| Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7); |
| tensor.setRandom(); |
| |
| array<bool, 4> dim_roll; |
| dim_roll[0] = 2; |
| dim_roll[1] = 1; |
| dim_roll[2] = 0; |
| dim_roll[3] = 3; |
| |
| Tensor<float, 4, DataLayout> expected(tensor.dimensions()); |
| if (LValue) { |
| expected.roll(dim_roll) = tensor; |
| } else { |
| expected = tensor.roll(dim_roll); |
| } |
| |
| Tensor<float, 4, DataLayout> result(tensor.dimensions()); |
| |
| array<ptrdiff_t, 4> src_slice_dim; |
| src_slice_dim[0] = tensor.dimension(0); |
| src_slice_dim[1] = tensor.dimension(1); |
| src_slice_dim[2] = 1; |
| src_slice_dim[3] = tensor.dimension(3); |
| array<ptrdiff_t, 4> src_slice_start; |
| src_slice_start[0] = 0; |
| src_slice_start[1] = 0; |
| src_slice_start[2] = 0; |
| src_slice_start[3] = 0; |
| array<ptrdiff_t, 4> dst_slice_dim = src_slice_dim; |
| array<ptrdiff_t, 4> dst_slice_start = src_slice_start; |
| |
| for (int i = 0; i < tensor.dimension(2); ++i) { |
| if (LValue) { |
| result.slice(dst_slice_start, dst_slice_dim).roll(dim_roll) = tensor.slice(src_slice_start, src_slice_dim); |
| } else { |
| result.slice(dst_slice_start, dst_slice_dim) = tensor.slice(src_slice_start, src_slice_dim).roll(dim_roll); |
| } |
| src_slice_start[2] += 1; |
| dst_slice_start[2] += 1; |
| } |
| |
| VERIFY_IS_EQUAL(result.dimension(0), tensor.dimension(0)); |
| VERIFY_IS_EQUAL(result.dimension(1), tensor.dimension(1)); |
| VERIFY_IS_EQUAL(result.dimension(2), tensor.dimension(2)); |
| VERIFY_IS_EQUAL(result.dimension(3), tensor.dimension(3)); |
| |
| for (int i = 0; i < expected.dimension(0); ++i) { |
| for (int j = 0; j < expected.dimension(1); ++j) { |
| for (int k = 0; k < expected.dimension(2); ++k) { |
| for (int l = 0; l < expected.dimension(3); ++l) { |
| VERIFY_IS_EQUAL(result(i, j, k, l), expected(i, j, k, l)); |
| } |
| } |
| } |
| } |
| |
| dst_slice_start[2] = 0; |
| result.setRandom(); |
| for (int i = 0; i < tensor.dimension(2); ++i) { |
| if (LValue) { |
| result.slice(dst_slice_start, dst_slice_dim).roll(dim_roll) = tensor.slice(dst_slice_start, dst_slice_dim); |
| } else { |
| result.slice(dst_slice_start, dst_slice_dim) = tensor.roll(dim_roll).slice(dst_slice_start, dst_slice_dim); |
| } |
| dst_slice_start[2] += 1; |
| } |
| |
| for (int i = 0; i < expected.dimension(0); ++i) { |
| for (int j = 0; j < expected.dimension(1); ++j) { |
| for (int k = 0; k < expected.dimension(2); ++k) { |
| for (int l = 0; l < expected.dimension(3); ++l) { |
| VERIFY_IS_EQUAL(result(i, j, k, l), expected(i, j, k, l)); |
| } |
| } |
| } |
| } |
| } |
| |
| EIGEN_DECLARE_TEST(cxx11_tensor_roll) { |
| CALL_SUBTEST(test_simple_roll<ColMajor>()); |
| CALL_SUBTEST(test_simple_roll<RowMajor>()); |
| CALL_SUBTEST(test_expr_roll<ColMajor>(true)); |
| CALL_SUBTEST(test_expr_roll<RowMajor>(true)); |
| CALL_SUBTEST(test_expr_roll<ColMajor>(false)); |
| CALL_SUBTEST(test_expr_roll<RowMajor>(false)); |
| } |