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248 lines
6.6 KiB
248 lines
6.6 KiB
// This file is part of Eigen, a lightweight C++ template library |
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// for linear algebra. |
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// |
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// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com> |
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// |
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// This Source Code Form is subject to the terms of the Mozilla |
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// Public License v. 2.0. If a copy of the MPL was not distributed |
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// with this file, You can obtain one at the mozilla.org home page |
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#include "main.h" |
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#include <Eigen/CXX11/Tensor> |
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using Eigen::Tensor; |
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using Eigen::RowMajor; |
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static void test_simple_lvalue_ref() |
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{ |
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Tensor<int, 1> input(6); |
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input.setRandom(); |
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TensorRef<Tensor<int, 1>> ref3(input); |
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TensorRef<Tensor<int, 1>> ref4 = input; |
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VERIFY_IS_EQUAL(ref3.data(), input.data()); |
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VERIFY_IS_EQUAL(ref4.data(), input.data()); |
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for (int i = 0; i < 6; ++i) { |
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VERIFY_IS_EQUAL(ref3(i), input(i)); |
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VERIFY_IS_EQUAL(ref4(i), input(i)); |
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} |
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for (int i = 0; i < 6; ++i) { |
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ref3.coeffRef(i) = i; |
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} |
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for (int i = 0; i < 6; ++i) { |
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VERIFY_IS_EQUAL(input(i), i); |
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} |
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for (int i = 0; i < 6; ++i) { |
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ref4.coeffRef(i) = -i * 2; |
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} |
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for (int i = 0; i < 6; ++i) { |
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VERIFY_IS_EQUAL(input(i), -i*2); |
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} |
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} |
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static void test_simple_rvalue_ref() |
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{ |
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Tensor<int, 1> input1(6); |
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input1.setRandom(); |
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Tensor<int, 1> input2(6); |
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input2.setRandom(); |
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TensorRef<Tensor<int, 1>> ref3(input1 + input2); |
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TensorRef<Tensor<int, 1>> ref4 = input1 + input2; |
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VERIFY_IS_NOT_EQUAL(ref3.data(), input1.data()); |
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VERIFY_IS_NOT_EQUAL(ref4.data(), input1.data()); |
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VERIFY_IS_NOT_EQUAL(ref3.data(), input2.data()); |
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VERIFY_IS_NOT_EQUAL(ref4.data(), input2.data()); |
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for (int i = 0; i < 6; ++i) { |
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VERIFY_IS_EQUAL(ref3(i), input1(i) + input2(i)); |
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VERIFY_IS_EQUAL(ref4(i), input1(i) + input2(i)); |
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} |
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} |
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static void test_multiple_dims() |
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{ |
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Tensor<float, 3> input(3,5,7); |
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input.setRandom(); |
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TensorRef<Tensor<float, 3>> ref(input); |
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VERIFY_IS_EQUAL(ref.data(), input.data()); |
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VERIFY_IS_EQUAL(ref.dimension(0), 3); |
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VERIFY_IS_EQUAL(ref.dimension(1), 5); |
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VERIFY_IS_EQUAL(ref.dimension(2), 7); |
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for (int i = 0; i < 3; ++i) { |
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for (int j = 0; j < 5; ++j) { |
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for (int k = 0; k < 7; ++k) { |
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VERIFY_IS_EQUAL(ref(i,j,k), input(i,j,k)); |
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} |
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} |
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} |
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} |
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static void test_slice() |
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{ |
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Tensor<float, 5> tensor(2,3,5,7,11); |
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tensor.setRandom(); |
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Eigen::DSizes<ptrdiff_t, 5> indices(1,2,3,4,5); |
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Eigen::DSizes<ptrdiff_t, 5> sizes(1,1,1,1,1); |
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TensorRef<Tensor<float, 5>> slice = tensor.slice(indices, sizes); |
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VERIFY_IS_EQUAL(slice(0,0,0,0,0), tensor(1,2,3,4,5)); |
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Eigen::DSizes<ptrdiff_t, 5> indices2(1,1,3,4,5); |
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Eigen::DSizes<ptrdiff_t, 5> sizes2(1,1,2,2,3); |
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slice = tensor.slice(indices2, sizes2); |
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for (int i = 0; i < 2; ++i) { |
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for (int j = 0; j < 2; ++j) { |
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for (int k = 0; k < 3; ++k) { |
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VERIFY_IS_EQUAL(slice(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k)); |
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} |
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} |
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} |
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Eigen::DSizes<ptrdiff_t, 5> indices3(0,0,0,0,0); |
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Eigen::DSizes<ptrdiff_t, 5> sizes3(2,3,1,1,1); |
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slice = tensor.slice(indices3, sizes3); |
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VERIFY_IS_EQUAL(slice.data(), tensor.data()); |
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} |
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static void test_ref_of_ref() |
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{ |
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Tensor<float, 3> input(3,5,7); |
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input.setRandom(); |
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TensorRef<Tensor<float, 3>> ref(input); |
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TensorRef<Tensor<float, 3>> ref_of_ref(ref); |
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TensorRef<Tensor<float, 3>> ref_of_ref2; |
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ref_of_ref2 = ref; |
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VERIFY_IS_EQUAL(ref_of_ref.data(), input.data()); |
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VERIFY_IS_EQUAL(ref_of_ref.dimension(0), 3); |
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VERIFY_IS_EQUAL(ref_of_ref.dimension(1), 5); |
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VERIFY_IS_EQUAL(ref_of_ref.dimension(2), 7); |
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VERIFY_IS_EQUAL(ref_of_ref2.data(), input.data()); |
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VERIFY_IS_EQUAL(ref_of_ref2.dimension(0), 3); |
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VERIFY_IS_EQUAL(ref_of_ref2.dimension(1), 5); |
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VERIFY_IS_EQUAL(ref_of_ref2.dimension(2), 7); |
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for (int i = 0; i < 3; ++i) { |
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for (int j = 0; j < 5; ++j) { |
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for (int k = 0; k < 7; ++k) { |
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VERIFY_IS_EQUAL(ref_of_ref(i,j,k), input(i,j,k)); |
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VERIFY_IS_EQUAL(ref_of_ref2(i,j,k), input(i,j,k)); |
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} |
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} |
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} |
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} |
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static void test_ref_in_expr() |
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{ |
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Tensor<float, 3> input(3,5,7); |
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input.setRandom(); |
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TensorRef<Tensor<float, 3>> input_ref(input); |
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Tensor<float, 3> result(3,5,7); |
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result.setRandom(); |
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TensorRef<Tensor<float, 3>> result_ref(result); |
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Tensor<float, 3> bias(3,5,7); |
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bias.setRandom(); |
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result_ref = input_ref + bias; |
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for (int i = 0; i < 3; ++i) { |
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for (int j = 0; j < 5; ++j) { |
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for (int k = 0; k < 7; ++k) { |
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VERIFY_IS_EQUAL(result_ref(i,j,k), input(i,j,k) + bias(i,j,k)); |
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VERIFY_IS_NOT_EQUAL(result(i,j,k), input(i,j,k) + bias(i,j,k)); |
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} |
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} |
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} |
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result = result_ref; |
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for (int i = 0; i < 3; ++i) { |
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for (int j = 0; j < 5; ++j) { |
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for (int k = 0; k < 7; ++k) { |
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VERIFY_IS_EQUAL(result(i,j,k), input(i,j,k) + bias(i,j,k)); |
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} |
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} |
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} |
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} |
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static void test_coeff_ref() |
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{ |
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Tensor<float, 5> tensor(2,3,5,7,11); |
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tensor.setRandom(); |
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Tensor<float, 5> original = tensor; |
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TensorRef<Tensor<float, 4>> slice = tensor.chip(7, 4); |
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slice.coeffRef(0, 0, 0, 0) = 1.0f; |
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slice.coeffRef(1, 0, 0, 0) += 2.0f; |
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VERIFY_IS_EQUAL(tensor(0,0,0,0,7), 1.0f); |
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VERIFY_IS_EQUAL(tensor(1,0,0,0,7), original(1,0,0,0,7) + 2.0f); |
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} |
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static void test_nested_ops_with_ref() |
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{ |
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Tensor<float, 4> t(2, 3, 5, 7); |
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t.setRandom(); |
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TensorMap<Tensor<const float, 4> > m(t.data(), 2, 3, 5, 7); |
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array<std::pair<ptrdiff_t, ptrdiff_t>, 4> paddings; |
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paddings[0] = std::make_pair(0, 0); |
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paddings[1] = std::make_pair(2, 1); |
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paddings[2] = std::make_pair(3, 4); |
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paddings[3] = std::make_pair(0, 0); |
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DSizes<Eigen::DenseIndex, 4> shuffle_dims(0, 1, 2, 3); |
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TensorRef<Tensor<const float, 4> > ref(m.pad(paddings)); |
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array<std::pair<ptrdiff_t, ptrdiff_t>, 4> trivial; |
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trivial[0] = std::make_pair(0, 0); |
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trivial[1] = std::make_pair(0, 0); |
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trivial[2] = std::make_pair(0, 0); |
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trivial[3] = std::make_pair(0, 0); |
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Tensor<float, 4> padded = ref.shuffle(shuffle_dims).pad(trivial); |
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VERIFY_IS_EQUAL(padded.dimension(0), 2+0); |
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VERIFY_IS_EQUAL(padded.dimension(1), 3+3); |
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VERIFY_IS_EQUAL(padded.dimension(2), 5+7); |
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VERIFY_IS_EQUAL(padded.dimension(3), 7+0); |
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for (int i = 0; i < 2; ++i) { |
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for (int j = 0; j < 6; ++j) { |
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for (int k = 0; k < 12; ++k) { |
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for (int l = 0; l < 7; ++l) { |
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if (j >= 2 && j < 5 && k >= 3 && k < 8) { |
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VERIFY_IS_EQUAL(padded(i,j,k,l), t(i,j-2,k-3,l)); |
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} else { |
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VERIFY_IS_EQUAL(padded(i,j,k,l), 0.0f); |
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} |
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} |
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} |
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} |
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} |
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} |
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EIGEN_DECLARE_TEST(cxx11_tensor_ref) |
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{ |
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CALL_SUBTEST(test_simple_lvalue_ref()); |
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CALL_SUBTEST(test_simple_rvalue_ref()); |
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CALL_SUBTEST(test_multiple_dims()); |
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CALL_SUBTEST(test_slice()); |
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CALL_SUBTEST(test_ref_of_ref()); |
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CALL_SUBTEST(test_ref_in_expr()); |
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CALL_SUBTEST(test_coeff_ref()); |
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CALL_SUBTEST(test_nested_ops_with_ref()); |
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}
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