test_PyDataProviderWrapper.cpp 8.0 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Z
zhangjinchao01 已提交
2 3 4 5 6 7 8 9 10 11 12 13 14 15

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. */

#ifndef PADDLE_NO_PYTHON
Y
Yu Yang 已提交
16
#include <DataConfig.pb.h>
Z
zhangjinchao01 已提交
17
#include <gtest/gtest.h>
X
Xin Pan 已提交
18
#include <paddle/legacy/gserver/dataproviders/DataProvider.h>
X
Xin Pan 已提交
19 20
#include <paddle/legacy/math/Matrix.h>
#include <paddle/legacy/parameter/Argument.h>
X
Xin Pan 已提交
21
#include <paddle/legacy/utils/PythonUtil.h>
Y
Yu Yang 已提交
22 23
#include <fstream>
#include <typeinfo>
Z
zhangjinchao01 已提交
24 25 26 27 28
#include <unordered_map>
#include <unordered_set>
#include "picojson.h"

void checkValue(std::vector<paddle::Argument>& arguments, picojson::array& arr);
X
Xin Pan 已提交
29
const std::string kDir = "./legacy/trainer/tests/pydata_provider_wrapper_dir/";
Z
zhangjinchao01 已提交
30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220

TEST(PyDataProviderWrapper, SequenceData) {
  paddle::DataConfig conf;
  conf.set_type("py");
  conf.set_load_data_module("testPyDataWrapper");
  conf.set_load_data_object("processSeqAndGenerateData");
  conf.set_load_data_args(kDir + "test_pydata_provider_wrapper.json");
  conf.clear_files();
  conf.set_files(kDir + "test_pydata_provider_wrapper.list");
  paddle::DataProviderPtr provider(paddle::DataProvider::create(conf, false));
  provider->setSkipShuffle();
  provider->reset();
  paddle::DataBatch batchFromPy;
  provider->getNextBatch(100, &batchFromPy);

  picojson::value val;
  std::fstream fin;
  fin.open(kDir + "test_pydata_provider_wrapper.json", std::ios_base::in);
  EXPECT_TRUE(fin.is_open());
  if (fin.is_open()) {
    std::string err = picojson::parse(val, fin);
    EXPECT_TRUE(err.empty());
    EXPECT_TRUE(val.is<picojson::array>());
    picojson::array& arr = val.get<picojson::array>();
    std::vector<paddle::Argument>& arguments = batchFromPy.getStreams();
    // CHECK Value
    checkValue(arguments, arr);
    // CHECK sequenceStartPositions
    for (size_t i = 0; i < arr.size(); i++) {
      int row_id = arr[i].get<picojson::array>().size();
      EXPECT_EQ(0, arguments[i].sequenceStartPositions->getData(false)[0]);
      EXPECT_EQ((int)row_id,
                arguments[i].sequenceStartPositions->getData(false)[1]);
    }
    fin.close();
  }
}

TEST(PyDataProviderWrapper, HasSubSequenceData) {
  paddle::DataConfig conf;
  conf.set_type("py");
  conf.set_load_data_module("testPyDataWrapper");
  conf.set_load_data_object("processSubSeqAndGenerateData");
  conf.set_load_data_args(kDir + "test_pydata_provider_wrapper.json");
  conf.clear_files();
  conf.set_files(kDir + "test_pydata_provider_wrapper.list");
  paddle::DataProviderPtr provider(paddle::DataProvider::create(conf, false));
  provider->setSkipShuffle();
  provider->reset();
  paddle::DataBatch batchFromPy;
  provider->getNextBatch(1, &batchFromPy);

  picojson::value val;
  std::fstream fin;
  fin.open(kDir + "test_pydata_provider_wrapper.json", std::ios_base::in);
  EXPECT_TRUE(fin.is_open());
  if (fin.is_open()) {
    std::string err = picojson::parse(val, fin);
    EXPECT_TRUE(err.empty());
    EXPECT_TRUE(val.is<picojson::array>());
    picojson::array& arr = val.get<picojson::array>();
    std::vector<paddle::Argument>& arguments = batchFromPy.getStreams();
    // CHECK Value
    checkValue(arguments, arr);
    // CHECK sequenceStartPositions and subSequenceStartPositions
    for (size_t i = 0; i < arr.size(); i++) {
      int row_id = arr[i].get<picojson::array>().size();
      EXPECT_EQ(0, arguments[i].sequenceStartPositions->getData(false)[0]);
      EXPECT_EQ((int)row_id,
                arguments[i].sequenceStartPositions->getData(false)[1]);
      EXPECT_EQ(0, arguments[i].subSequenceStartPositions->getData(false)[0]);
      EXPECT_EQ((int)row_id,
                arguments[i].subSequenceStartPositions->getData(false)[1]);
    }
    fin.close();
  }
}

int main(int argc, char** argv) {
  paddle::initMain(argc, argv);
  paddle::initPython(argc, argv);
  testing::InitGoogleTest(&argc, argv);
  return RUN_ALL_TESTS();
}

void checkValue(std::vector<paddle::Argument>& arguments,
                picojson::array& arr) {
  // CHECK SLOT 0, Sparse Value.
  paddle::Argument& sparse_values_seq = arguments[0];
  paddle::MatrixPtr& sparse_values_seq_rawmatrix = sparse_values_seq.value;
  EXPECT_TRUE(sparse_values_seq_rawmatrix != nullptr);
  paddle::CpuSparseMatrix* sparse_val_seq_sparse_mat =
      dynamic_cast<paddle::CpuSparseMatrix*>(sparse_values_seq_rawmatrix.get());
  EXPECT_TRUE(sparse_val_seq_sparse_mat != nullptr);
  EXPECT_EQ(arr.size(), arguments.size());
  EXPECT_TRUE(arr[0].is<picojson::array>());
  size_t row_id = 0;
  for (picojson::value& sparse_val_seq : arr[0].get<picojson::array>()) {
    std::unordered_map<int, real> cols;
    for (picojson::value& kv : sparse_val_seq.get<picojson::array>()) {
      EXPECT_TRUE(kv.get(0).is<double>());
      EXPECT_TRUE(kv.get(1).is<double>());
      int col = (int)(kv.get(0).get<double>());
      real val = (real)(kv.get(1).get<double>());
      cols.insert({col, val});
    }
    size_t colNum = sparse_val_seq_sparse_mat->getColNum(row_id);
    EXPECT_EQ(cols.size(), colNum);
    int* rowIds = sparse_val_seq_sparse_mat->getRowCols(row_id);
    real* rowBuf = sparse_val_seq_sparse_mat->getRowValues(row_id);
    for (size_t i = 0; i < colNum; ++i) {
      int id = rowIds[i];
      auto it = cols.find(id);
      EXPECT_NE(cols.end(), it);
      real expect = it->second;
      EXPECT_NEAR(expect, *rowBuf, 1e-5);
      ++rowBuf;
    }
    ++row_id;
  }

  // CHECK SLOT 1, Dense Value.
  paddle::Argument& dense_arg = arguments[1];
  paddle::MatrixPtr& dense_mat = dense_arg.value;
  EXPECT_NE(nullptr, dense_mat);
  EXPECT_TRUE(arr[1].is<picojson::array>());
  row_id = 0;
  for (picojson::value& dense_seq : arr[1].get<picojson::array>()) {
    EXPECT_TRUE(dense_seq.is<picojson::array>());
    picojson::array& row = dense_seq.get<picojson::array>();
    EXPECT_EQ(row.size(), dense_mat->getWidth());
    real* rowBuf = dense_mat->getRowBuf(row_id++);

    for (picojson::value& val : row) {
      EXPECT_TRUE(val.is<double>());
      real expect = val.get<double>();
      EXPECT_NEAR(expect, *rowBuf++, 1e-5);
    }
  }

  // CHECK SLOT 2, Sparse Non Value.
  paddle::Argument& sparse_non_val_arg = arguments[2];
  paddle::MatrixPtr& sparse_non_val_rawm = sparse_non_val_arg.value;
  EXPECT_NE(nullptr, sparse_non_val_rawm);
  paddle::CpuSparseMatrix* sparse_non_val_m =
      dynamic_cast<paddle::CpuSparseMatrix*>(sparse_non_val_rawm.get());
  EXPECT_NE(nullptr, sparse_non_val_m);
  row_id = 0;
  for (picojson::value& row : arr[2].get<picojson::array>()) {
    EXPECT_TRUE(row.is<picojson::array>());
    std::unordered_set<int> ids;
    for (picojson::value& id : row.get<picojson::array>()) {
      EXPECT_TRUE(id.is<double>());
      ids.insert((int)(id.get<double>()));
    }
    size_t colNum = sparse_non_val_m->getColNum(row_id);
    EXPECT_EQ(ids.size(), colNum);
    for (size_t i = 0; i < colNum; ++i) {
      int col = sparse_non_val_m->getRowCols(row_id)[i];
      EXPECT_TRUE(ids.find(col) != ids.end());
    }
    ++row_id;
  }

  // CHECK SLOT 3, Index.
  paddle::Argument& index_arg = arguments[3];
  paddle::IVectorPtr indices = index_arg.ids;
  EXPECT_NE(nullptr, indices);
  int* idPtr = indices->getData();
  for (picojson::value& id : arr[3].get<picojson::array>()) {
    EXPECT_TRUE(id.is<double>());
    int _id = (int)(id.get<double>());
    EXPECT_EQ(_id, *idPtr++);
  }

  // CHECK SLOT 4, String.
  paddle::Argument& strArg = arguments[4];
  std::vector<std::string>* strPtr = strArg.strs.get();
  EXPECT_NE(nullptr, strPtr);
  size_t vecIndex = 0;
  for (picojson::value& str : arr[4].get<picojson::array>()) {
    EXPECT_TRUE(str.is<std::string>());
    std::string _str = str.get<std::string>();
    EXPECT_EQ(_str, (*strPtr)[vecIndex++]);
  }
}

#else
int main() { return 0; }

#endif