提交 98fb8e58 编写于 作者: T tensor-tang

test infer nlp

上级 406c1dd1
......@@ -117,7 +117,7 @@ std::unique_ptr<framework::ProgramDesc> Load(framework::Executor* executor,
std::string program_desc_str;
VLOG(3) << "loading model from " << model_filename;
ReadBinaryFile(model_filename, &program_desc_str);
// LOG(INFO) << program_desc_str;
std::unique_ptr<framework::ProgramDesc> main_program(
new framework::ProgramDesc(program_desc_str));
......
......@@ -35,6 +35,7 @@ inference_test(image_classification ARGS vgg resnet)
inference_test(label_semantic_roles)
inference_test(recognize_digits ARGS mlp conv)
inference_test(recommender_system)
inference_test(nlp)
#inference_test(rnn_encoder_decoder)
#inference_test(understand_sentiment ARGS conv)
inference_test(word2vec)
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "gflags/gflags.h"
#include "gtest/gtest.h"
#include "paddle/fluid/inference/tests/test_helper.h"
DEFINE_string(dirname, "", "Directory of the inference model.");
TEST(inference, understand_sentiment) {
if (FLAGS_dirname.empty()) {
LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model";
}
LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl;
std::string dirname = FLAGS_dirname;
// 0. Call `paddle::framework::InitDevices()` initialize all the devices
// In unittests, this is done in paddle/testing/paddle_gtest_main.cc
paddle::framework::LoDTensor words;
paddle::framework::LoD lod{{0, 83}};
int64_t word_dict_len = 198392;
SetupLoDTensor(&words, lod, static_cast<int64_t>(0),
static_cast<int64_t>(word_dict_len - 1));
/*
std::vector<int64_t> srcdata{
784, 784, 1550, 6463, 56, 75693, 6189, 784, 784, 1550,
198391, 6463, 42468, 4376, 10251, 10760, 6189, 297, 396, 6463,
6463, 1550, 198391, 6463, 22564, 1612, 291, 68, 164, 784,
784, 1550, 198391, 6463, 13659, 3362, 42468, 6189, 2209,
198391,
6463, 2209, 2209, 198391, 6463, 2209, 1062, 3029, 1831, 3029,
1065, 2281, 100, 11216, 1110, 56, 10869, 9811, 100,
198391,
6463, 100, 9280, 100, 288, 40031, 1680, 1335, 100, 1550,
9280, 7265, 244, 1550, 198391, 6463, 1550, 198391, 6463,
42468,
4376, 10251, 10760};
paddle::framework::LoD lod{{0, srcdata.size()}};
words.set_lod(lod);
int64_t* pdata =
words.mutable_data<int64_t>({static_cast<int64_t>(srcdata.size()), 1},
paddle::platform::CPUPlace());
memcpy(pdata, srcdata.data(), words.numel() * sizeof(int64_t));
*/
LOG(INFO) << "number of input size:" << words.numel();
std::vector<paddle::framework::LoDTensor*> cpu_feeds;
cpu_feeds.push_back(&words);
paddle::framework::LoDTensor output1;
std::vector<paddle::framework::LoDTensor*> cpu_fetchs1;
cpu_fetchs1.push_back(&output1);
int repeat = 100;
// Run inference on CPU
TestInference<paddle::platform::CPUPlace, true, true>(dirname, cpu_feeds,
cpu_fetchs1, repeat);
LOG(INFO) << output1.lod();
LOG(INFO) << output1.dims();
#ifdef PADDLE_WITH_CUDA
paddle::framework::LoDTensor output2;
std::vector<paddle::framework::LoDTensor*> cpu_fetchs2;
cpu_fetchs2.push_back(&output2);
// Run inference on CUDA GPU
TestInference<paddle::platform::CUDAPlace>(dirname, cpu_feeds, cpu_fetchs2);
LOG(INFO) << output2.lod();
LOG(INFO) << output2.dims();
CheckError<float>(output1, output2);
#endif
}
......@@ -182,6 +182,9 @@ void TestInference(const std::string& dirname,
"init_program",
paddle::platform::DeviceContextPool::Instance().Get(place));
inference_program = InitProgram(&executor, scope, dirname, is_combined);
// std::string binary_str;
// inference_program->Proto()->SerializeToString(&binary_str);
// LOG(INFO) << binary_str;
if (use_mkldnn) {
EnableMKLDNN(inference_program);
}
......
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