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author | Stanislaw Halik <sthalik@misaki.pl> | 2017-03-25 14:17:07 +0100 |
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committer | Stanislaw Halik <sthalik@misaki.pl> | 2017-03-25 14:17:07 +0100 |
commit | 35f7829af10c61e33dd2e2a7a015058e11a11ea0 (patch) | |
tree | 7135010dcf8fd0a49f3020d52112709bcb883bd6 /eigen/unsupported/test/cxx11_tensor_ref.cpp | |
parent | 6e8724193e40a932faf9064b664b529e7301c578 (diff) |
update
Diffstat (limited to 'eigen/unsupported/test/cxx11_tensor_ref.cpp')
-rw-r--r-- | eigen/unsupported/test/cxx11_tensor_ref.cpp | 248 |
1 files changed, 248 insertions, 0 deletions
diff --git a/eigen/unsupported/test/cxx11_tensor_ref.cpp b/eigen/unsupported/test/cxx11_tensor_ref.cpp new file mode 100644 index 0000000..c8f105e --- /dev/null +++ b/eigen/unsupported/test/cxx11_tensor_ref.cpp @@ -0,0 +1,248 @@ +// 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; +using Eigen::RowMajor; + +static void test_simple_lvalue_ref() +{ + Tensor<int, 1> input(6); + input.setRandom(); + + TensorRef<Tensor<int, 1>> ref3(input); + TensorRef<Tensor<int, 1>> ref4 = input; + + VERIFY_IS_EQUAL(ref3.data(), input.data()); + VERIFY_IS_EQUAL(ref4.data(), input.data()); + + for (int i = 0; i < 6; ++i) { + VERIFY_IS_EQUAL(ref3(i), input(i)); + VERIFY_IS_EQUAL(ref4(i), input(i)); + } + + for (int i = 0; i < 6; ++i) { + ref3.coeffRef(i) = i; + } + for (int i = 0; i < 6; ++i) { + VERIFY_IS_EQUAL(input(i), i); + } + for (int i = 0; i < 6; ++i) { + ref4.coeffRef(i) = -i * 2; + } + for (int i = 0; i < 6; ++i) { + VERIFY_IS_EQUAL(input(i), -i*2); + } +} + + +static void test_simple_rvalue_ref() +{ + Tensor<int, 1> input1(6); + input1.setRandom(); + Tensor<int, 1> input2(6); + input2.setRandom(); + + TensorRef<Tensor<int, 1>> ref3(input1 + input2); + TensorRef<Tensor<int, 1>> ref4 = input1 + input2; + + VERIFY_IS_NOT_EQUAL(ref3.data(), input1.data()); + VERIFY_IS_NOT_EQUAL(ref4.data(), input1.data()); + VERIFY_IS_NOT_EQUAL(ref3.data(), input2.data()); + VERIFY_IS_NOT_EQUAL(ref4.data(), input2.data()); + + for (int i = 0; i < 6; ++i) { + VERIFY_IS_EQUAL(ref3(i), input1(i) + input2(i)); + VERIFY_IS_EQUAL(ref4(i), input1(i) + input2(i)); + } +} + + +static void test_multiple_dims() +{ + Tensor<float, 3> input(3,5,7); + input.setRandom(); + + TensorRef<Tensor<float, 3>> ref(input); + VERIFY_IS_EQUAL(ref.data(), input.data()); + VERIFY_IS_EQUAL(ref.dimension(0), 3); + VERIFY_IS_EQUAL(ref.dimension(1), 5); + VERIFY_IS_EQUAL(ref.dimension(2), 7); + + for (int i = 0; i < 3; ++i) { + for (int j = 0; j < 5; ++j) { + for (int k = 0; k < 7; ++k) { + VERIFY_IS_EQUAL(ref(i,j,k), input(i,j,k)); + } + } + } +} + + +static void test_slice() +{ + Tensor<float, 5> tensor(2,3,5,7,11); + tensor.setRandom(); + + Eigen::DSizes<ptrdiff_t, 5> indices(1,2,3,4,5); + Eigen::DSizes<ptrdiff_t, 5> sizes(1,1,1,1,1); + TensorRef<Tensor<float, 5>> slice = tensor.slice(indices, sizes); + VERIFY_IS_EQUAL(slice(0,0,0,0,0), tensor(1,2,3,4,5)); + + Eigen::DSizes<ptrdiff_t, 5> indices2(1,1,3,4,5); + Eigen::DSizes<ptrdiff_t, 5> sizes2(1,1,2,2,3); + slice = tensor.slice(indices2, sizes2); + for (int i = 0; i < 2; ++i) { + for (int j = 0; j < 2; ++j) { + for (int k = 0; k < 3; ++k) { + VERIFY_IS_EQUAL(slice(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k)); + } + } + } + + Eigen::DSizes<ptrdiff_t, 5> indices3(0,0,0,0,0); + Eigen::DSizes<ptrdiff_t, 5> sizes3(2,3,1,1,1); + slice = tensor.slice(indices3, sizes3); + VERIFY_IS_EQUAL(slice.data(), tensor.data()); +} + + +static void test_ref_of_ref() +{ + Tensor<float, 3> input(3,5,7); + input.setRandom(); + + TensorRef<Tensor<float, 3>> ref(input); + TensorRef<Tensor<float, 3>> ref_of_ref(ref); + TensorRef<Tensor<float, 3>> ref_of_ref2; + ref_of_ref2 = ref; + + VERIFY_IS_EQUAL(ref_of_ref.data(), input.data()); + VERIFY_IS_EQUAL(ref_of_ref.dimension(0), 3); + VERIFY_IS_EQUAL(ref_of_ref.dimension(1), 5); + VERIFY_IS_EQUAL(ref_of_ref.dimension(2), 7); + + VERIFY_IS_EQUAL(ref_of_ref2.data(), input.data()); + VERIFY_IS_EQUAL(ref_of_ref2.dimension(0), 3); + VERIFY_IS_EQUAL(ref_of_ref2.dimension(1), 5); + VERIFY_IS_EQUAL(ref_of_ref2.dimension(2), 7); + + for (int i = 0; i < 3; ++i) { + for (int j = 0; j < 5; ++j) { + for (int k = 0; k < 7; ++k) { + VERIFY_IS_EQUAL(ref_of_ref(i,j,k), input(i,j,k)); + VERIFY_IS_EQUAL(ref_of_ref2(i,j,k), input(i,j,k)); + } + } + } +} + + +static void test_ref_in_expr() +{ + Tensor<float, 3> input(3,5,7); + input.setRandom(); + TensorRef<Tensor<float, 3>> input_ref(input); + + Tensor<float, 3> result(3,5,7); + result.setRandom(); + TensorRef<Tensor<float, 3>> result_ref(result); + + Tensor<float, 3> bias(3,5,7); + bias.setRandom(); + + result_ref = input_ref + bias; + for (int i = 0; i < 3; ++i) { + for (int j = 0; j < 5; ++j) { + for (int k = 0; k < 7; ++k) { + VERIFY_IS_EQUAL(result_ref(i,j,k), input(i,j,k) + bias(i,j,k)); + VERIFY_IS_NOT_EQUAL(result(i,j,k), input(i,j,k) + bias(i,j,k)); + } + } + } + + result = result_ref; + for (int i = 0; i < 3; ++i) { + for (int j = 0; j < 5; ++j) { + for (int k = 0; k < 7; ++k) { + VERIFY_IS_EQUAL(result(i,j,k), input(i,j,k) + bias(i,j,k)); + } + } + } +} + + +static void test_coeff_ref() +{ + Tensor<float, 5> tensor(2,3,5,7,11); + tensor.setRandom(); + Tensor<float, 5> original = tensor; + + TensorRef<Tensor<float, 4>> slice = tensor.chip(7, 4); + slice.coeffRef(0, 0, 0, 0) = 1.0f; + slice.coeffRef(1, 0, 0, 0) += 2.0f; + + VERIFY_IS_EQUAL(tensor(0,0,0,0,7), 1.0f); + VERIFY_IS_EQUAL(tensor(1,0,0,0,7), original(1,0,0,0,7) + 2.0f); +} + + +static void test_nested_ops_with_ref() +{ + Tensor<float, 4> t(2, 3, 5, 7); + t.setRandom(); + TensorMap<Tensor<const float, 4> > m(t.data(), 2, 3, 5, 7); + array<std::pair<ptrdiff_t, ptrdiff_t>, 4> paddings; + paddings[0] = std::make_pair(0, 0); + paddings[1] = std::make_pair(2, 1); + paddings[2] = std::make_pair(3, 4); + paddings[3] = std::make_pair(0, 0); + DSizes<Eigen::DenseIndex, 4> shuffle_dims(0, 1, 2, 3); + TensorRef<Tensor<const float, 4> > ref(m.pad(paddings)); + array<std::pair<ptrdiff_t, ptrdiff_t>, 4> trivial; + trivial[0] = std::make_pair(0, 0); + trivial[1] = std::make_pair(0, 0); + trivial[2] = std::make_pair(0, 0); + trivial[3] = std::make_pair(0, 0); + Tensor<float, 4> padded = ref.shuffle(shuffle_dims).pad(trivial); + VERIFY_IS_EQUAL(padded.dimension(0), 2+0); + VERIFY_IS_EQUAL(padded.dimension(1), 3+3); + VERIFY_IS_EQUAL(padded.dimension(2), 5+7); + VERIFY_IS_EQUAL(padded.dimension(3), 7+0); + + for (int i = 0; i < 2; ++i) { + for (int j = 0; j < 6; ++j) { + for (int k = 0; k < 12; ++k) { + for (int l = 0; l < 7; ++l) { + if (j >= 2 && j < 5 && k >= 3 && k < 8) { + VERIFY_IS_EQUAL(padded(i,j,k,l), t(i,j-2,k-3,l)); + } else { + VERIFY_IS_EQUAL(padded(i,j,k,l), 0.0f); + } + } + } + } + } +} + + +void test_cxx11_tensor_ref() +{ + CALL_SUBTEST(test_simple_lvalue_ref()); + CALL_SUBTEST(test_simple_rvalue_ref()); + CALL_SUBTEST(test_multiple_dims()); + CALL_SUBTEST(test_slice()); + CALL_SUBTEST(test_ref_of_ref()); + CALL_SUBTEST(test_ref_in_expr()); + CALL_SUBTEST(test_coeff_ref()); + CALL_SUBTEST(test_nested_ops_with_ref()); +} |