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113 lines
2.8 KiB
113 lines
2.8 KiB
/*
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Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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#include "paddle/framework/eigen.h"
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#include <gtest/gtest.h>
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namespace paddle {
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namespace framework {
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TEST(EigenDim, From) {
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EigenDim<3>::Type ed = EigenDim<3>::From(make_ddim({1, 2, 3}));
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ASSERT_EQ(1, ed[0]);
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ASSERT_EQ(2, ed[1]);
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ASSERT_EQ(3, ed[2]);
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}
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TEST(Eigen, Tensor) {
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Tensor t;
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float* p = t.mutable_data<float>(make_ddim({1, 2, 3}), platform::CPUPlace());
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for (int i = 0; i < 1 * 2 * 3; i++) {
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p[i] = static_cast<float>(i);
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}
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EigenTensor<float, 3>::Type et = EigenTensor<float, 3>::From(t);
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ASSERT_EQ(1, et.dimension(0));
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ASSERT_EQ(2, et.dimension(1));
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ASSERT_EQ(3, et.dimension(2));
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for (int i = 0; i < 1; 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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ASSERT_NEAR((i * 2 + j) * 3 + k, et(i, j, k), 1e-6f);
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}
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}
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}
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}
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TEST(Eigen, ScalarFrom) {
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Tensor t;
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int* p = t.mutable_data<int>(make_ddim({1}), platform::CPUPlace());
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*p = static_cast<int>(100);
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EigenScalar<int>::Type es = EigenScalar<int>::From(t);
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ASSERT_EQ(0, es.dimension(0));
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ASSERT_EQ(100, es(0));
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}
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TEST(Eigen, VectorFrom) {
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Tensor t;
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float* p = t.mutable_data<float>(make_ddim({6}), platform::CPUPlace());
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for (int i = 0; i < 6; i++) {
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p[i] = static_cast<float>(i);
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}
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EigenVector<float>::Type ev = EigenVector<float>::From(t);
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ASSERT_EQ(6, ev.dimension(0));
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for (int i = 0; i < 6; i++) {
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ASSERT_NEAR(i, ev(i), 1e-6f);
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}
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}
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TEST(Eigen, VectorFlatten) {
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Tensor t;
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float* p = t.mutable_data<float>(make_ddim({1, 2, 3}), platform::CPUPlace());
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for (int i = 0; i < 1 * 2 * 3; i++) {
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p[i] = static_cast<float>(i);
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}
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EigenVector<float>::Type ev = EigenVector<float>::Flatten(t);
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ASSERT_EQ(1 * 2 * 3, ev.dimension(0));
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for (int i = 0; i < 1 * 2 * 3; i++) {
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ASSERT_NEAR(i, ev(i), 1e-6f);
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}
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}
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TEST(Eigen, Matrix) {
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Tensor t;
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float* p = t.mutable_data<float>(make_ddim({2, 3}), platform::CPUPlace());
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for (int i = 0; i < 2 * 3; i++) {
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p[i] = static_cast<float>(i);
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}
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EigenMatrix<float>::Type em = EigenMatrix<float>::From(t);
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ASSERT_EQ(2, em.dimension(0));
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ASSERT_EQ(3, em.dimension(1));
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for (int i = 0; i < 2; i++) {
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for (int j = 0; j < 3; j++) {
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ASSERT_NEAR(i * 3 + j, em(i, j), 1e-6f);
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}
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}
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}
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} // namespace framework
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} // namespace paddle
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