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69 lines
2.5 KiB
69 lines
2.5 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#include "gflags/gflags.h"
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#include "gtest/gtest.h"
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#include "paddle/fluid/inference/tests/test_helper.h"
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DEFINE_string(dirname, "", "Directory of the inference model.");
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TEST(inference, word2vec) {
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if (FLAGS_dirname.empty()) {
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LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model";
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}
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LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl;
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std::string dirname = FLAGS_dirname;
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// 0. Call `paddle::framework::InitDevices()` initialize all the devices
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// In unittests, this is done in paddle/testing/paddle_gtest_main.cc
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paddle::framework::LoDTensor first_word, second_word, third_word, fourth_word;
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paddle::framework::LoD lod{{0, 1}};
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int64_t dict_size = 2073; // The size of dictionary
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SetupLoDTensor(&first_word, lod, static_cast<int64_t>(0), dict_size - 1);
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SetupLoDTensor(&second_word, lod, static_cast<int64_t>(0), dict_size - 1);
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SetupLoDTensor(&third_word, lod, static_cast<int64_t>(0), dict_size - 1);
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SetupLoDTensor(&fourth_word, lod, static_cast<int64_t>(0), dict_size - 1);
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std::vector<paddle::framework::LoDTensor*> cpu_feeds;
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cpu_feeds.push_back(&first_word);
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cpu_feeds.push_back(&second_word);
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cpu_feeds.push_back(&third_word);
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cpu_feeds.push_back(&fourth_word);
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paddle::framework::LoDTensor output1;
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std::vector<paddle::framework::LoDTensor*> cpu_fetchs1;
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cpu_fetchs1.push_back(&output1);
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// Run inference on CPU
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TestInference<paddle::platform::CPUPlace>(dirname, cpu_feeds, cpu_fetchs1);
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LOG(INFO) << output1.lod();
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LOG(INFO) << output1.dims();
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#ifdef PADDLE_WITH_CUDA
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paddle::framework::LoDTensor output2;
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std::vector<paddle::framework::LoDTensor*> cpu_fetchs2;
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cpu_fetchs2.push_back(&output2);
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// Run inference on CUDA GPU
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TestInference<paddle::platform::CUDAPlace>(dirname, cpu_feeds, cpu_fetchs2);
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LOG(INFO) << output2.lod();
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LOG(INFO) << output2.dims();
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CheckError<float>(output1, output2);
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#endif
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}
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