test_inference_recognize_digits.cc 4.0 KB
Newer Older
L
Liu Yiqun 已提交
1
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
2 3 4 5 6 7 8 9 10 11 12 13 14

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. */

15
#include <gtest/gtest.h>
16
#include <time.h>
17
#include <sstream>
18
#include "gflags/gflags.h"
19
#include "paddle/framework/init.h"
20 21
#include "paddle/inference/inference.h"

22 23
DEFINE_string(dirname, "", "Directory of the inference model.");

L
Liu Yiqun 已提交
24 25 26 27
template <typename Place, typename T>
void TestInference(const std::string& dirname,
                   const std::vector<paddle::framework::LoDTensor*>& cpu_feeds,
                   std::vector<paddle::framework::LoDTensor*>& cpu_fetchs) {
28
  // 1. Define place, executor and scope
L
Liu Yiqun 已提交
29
  auto place = Place();
30 31 32 33
  auto executor = paddle::framework::Executor(place);
  auto* scope = new paddle::framework::Scope();

  // 2. Initialize the inference_program and load all parameters from file
34
  paddle::InferenceEngine* engine = new paddle::InferenceEngine();
35 36 37 38 39 40 41
  paddle::framework::ProgramDesc* inference_program =
      engine->LoadInferenceModel(executor, scope, dirname);

  // 3. Get the feed_var_names and fetch_var_names
  const std::vector<std::string>& feed_target_names = engine->GetFeedVarNames();
  const std::vector<std::string>& fetch_target_names =
      engine->GetFetchVarNames();
42

43 44
  // 4. Prepare inputs
  std::map<std::string, const paddle::framework::LoDTensor*> feed_targets;
L
Liu Yiqun 已提交
45 46 47
  for (size_t i = 0; i < feed_target_names.size(); ++i) {
    // Please make sure that cpu_feeds[i] is right for feed_target_names[i]
    feed_targets[feed_target_names[i]] = cpu_feeds[i];
48
  }
49 50 51

  // 5. Define Tensor to get the outputs
  std::map<std::string, paddle::framework::LoDTensor*> fetch_targets;
L
Liu Yiqun 已提交
52 53 54
  for (size_t i = 0; i < fetch_target_names.size(); ++i) {
    fetch_targets[fetch_target_names[i]] = cpu_fetchs[i];
  }
55 56 57

  // 6. Run the inference program
  executor.Run(*inference_program, scope, feed_targets, fetch_targets);
58

59
  delete scope;
60
  delete engine;
61 62
}

L
Liu Yiqun 已提交
63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115
TEST(inference, recognize_digits) {
  if (FLAGS_dirname.empty()) {
    LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model";
  }

  LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl;

  // 0. Initialize all the devices
  paddle::framework::InitDevices();

  paddle::framework::LoDTensor input;
  srand(time(0));
  float* input_ptr =
      input.mutable_data<float>({1, 28, 28}, paddle::platform::CPUPlace());
  for (int i = 0; i < 784; ++i) {
    input_ptr[i] = rand() / (static_cast<float>(RAND_MAX));
  }
  std::vector<paddle::framework::LoDTensor*> cpu_feeds;
  cpu_feeds.push_back(&input);

  paddle::framework::LoDTensor output1;
  std::vector<paddle::framework::LoDTensor*> cpu_fetchs1;
  cpu_fetchs1.push_back(&output1);

  // Run inference on CPU
  TestInference<paddle::platform::CPUPlace, float>(
      FLAGS_dirname, cpu_feeds, cpu_fetchs1);
  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, float>(
      FLAGS_dirname, cpu_feeds, cpu_fetchs2);
  LOG(INFO) << output2.dims();

  EXPECT_EQ(output1.dims(), output2.dims());
  EXPECT_EQ(output1.numel(), output2.numel());

  float err = 1E-3;
  int count = 0;
  for (int64_t i = 0; i < output1.numel(); ++i) {
    if (fabs(output1.data<float>()[i] - output2.data<float>()[i]) > err) {
      count++;
    }
  }
  EXPECT_EQ(count, 0) << "There are " << count << " different elements.";
#endif
}

116 117 118 119
int main(int argc, char** argv) {
  google::ParseCommandLineFlags(&argc, &argv, false);
  testing::InitGoogleTest(&argc, argv);
  return RUN_ALL_TESTS();
120
}