test_PyDataProvider2.cpp 11.8 KB
Newer Older
Z
zhangjinchao01 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
/* Copyright (c) 2016 Baidu, Inc. All Rights Reserve.

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
#include <gtest/gtest.h>
#include <fstream>
#include "paddle/utils/Util.h"
#include "paddle/utils/PythonUtil.h"
#include "paddle/gserver/dataproviders/DataProvider.h"

P_DEFINE_string(train_list, "unittest.list", "file list for unittest");
23 24 25 26 27 28 29 30 31 32 33 34

namespace paddle {
namespace unittest {
namespace pydp2 {
extern void setOnPoolFilledHook(const std::function<void(size_t)>& func);
extern void clearOnPoolFilledHook();

}  // namespace pydp2
}  // namespace unittest
}  // namespace paddle


Z
zhangjinchao01 已提交
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249
const paddle::real epsilon = 1e-5;

static inline int64_t readDataBatch(
    paddle::DataBatch* batch,
    const std::string& funcName,
    int64_t batchSize = 65535) {

  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object(funcName);
  std::unique_ptr<paddle::DataProvider> provider(
      paddle::DataProvider::create(config, false));
  provider->setSkipShuffle();
  provider->reset();
  return provider->getNextBatchInternal(batchSize, batch);
}

TEST(PyDataProvider2, dense_no_seq) {
  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object("test_dense_no_seq");

  std::unique_ptr<paddle::DataProvider> provider(
      paddle::DataProvider::create(config, false));

  provider->setSkipShuffle();  // skip shuffle for unittest.

  paddle::DataBatch batch;
  for (size_t pass=0; pass < 2; ++pass) {  // read 2 passes
    provider->reset();
    int64_t num = provider->getNextBatchInternal(100, &batch);
    ASSERT_NE(num, 0);
    ASSERT_EQ((size_t)batch.getStreams().size(), (size_t)1);
    ASSERT_EQ((size_t)batch.getSize(), (size_t)100);
    // Check batch data.
    for (size_t i=0; i < 100; ++i) {
      for (size_t j=0; j < 200; ++j) {
        paddle::real tmp = (paddle::real)((j-100.0) * (i+1) / 200.0);
        ASSERT_NEAR(batch.getStreams()[0].value->getData()[i*200 + j],
                    tmp, epsilon);}
    }

    num = provider->getNextBatchInternal(100, &batch);
    ASSERT_NE(num, 0);
    ASSERT_EQ(batch.getStreams().size(), (size_t)1);
    ASSERT_EQ((size_t)batch.getSize(), (size_t)100);
    // Check batch data.
    for (size_t i=0; i < 100; ++i) {
      size_t ii = i + 100;
      for (size_t j=0; j < 200; ++j) {
        paddle::real tmp = (paddle::real)((j-100.0) * (ii+1) / 200.0);
        ASSERT_NEAR(batch.getStreams()[0].value->getData()[i*200 + j],
                    tmp, epsilon);}
    }
    num = provider->getNextBatchInternal(100, &batch);
    ASSERT_EQ(num, 0);
  }
}

TEST(PyDataProvider2, index_no_seq) {
  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object("test_index_no_seq");
  std::unique_ptr<paddle::DataProvider> provider(
      paddle::DataProvider::create(config, false));

  provider->setSkipShuffle();  // skip shuffle for unittest.
  paddle::DataBatch batch;
  for (size_t pass=0; pass < 2; ++pass) {
    provider->reset();
    int64_t num = provider->getNextBatchInternal(10000, &batch);
    CHECK_EQ(num, 200);
    for (int i=0; i < 200; ++i) {
      CHECK_EQ(i, batch.getStreams()[0].ids->getData()[i]);
    }
  }
}

TEST(PyDataProvider2, init_hook) {
  paddle::PyObjectPtr pickle(PyImport_ImportModule("pickle"));
  paddle::PyObjectPtr globals(
      PyModule_GetDict(PyImport_AddModule("__main__")));
  PyDict_SetItemString(globals.get(), "pickle", pickle.get());
  paddle::PyObjectPtr locals(PyDict_New());
  paddle::PyObjectPtr mdl(PyRun_String(
      "dumps = pickle.dumps({'value':[float(x) for x in xrange(20)]})",
      Py_file_input, globals.get(), locals.get()));
  CHECK_PY(mdl) << "Error!";
  paddle::PyObjectPtr dps(PyDict_GetItemString(locals.get(), "dumps"));
  CHECK_PY(dps) << "Error!";

  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object("test_init_hook");
  config.set_load_data_args(PyString_AsString(dps.get()));

  std::unique_ptr<paddle::DataProvider> provider(
      paddle::DataProvider::create(config, false));
  provider->setSkipShuffle();  // skip shuffle for unittest.
  provider->reset();
  paddle::DataBatch batch;
  int64_t num = provider->getNextBatchInternal(100000, &batch);
  ASSERT_EQ(num, 200);
  auto& mat = batch.getStreams()[0].value;
  ASSERT_EQ((size_t)mat->getWidth(), (size_t)20);
  for (size_t i=0; i < 200; ++i) {
    for (size_t j=0; j < 20; ++j) {
      ASSERT_NEAR((paddle::real)j, mat->getData()[i*20 + j], epsilon);
    }
  }
}

TEST(PyDataProvider2, sparse_no_value_no_seq) {
  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object("test_sparse_non_value_no_seq");
  std::unique_ptr<paddle::DataProvider> provider(
      paddle::DataProvider::create(config, false));
  provider->setSkipShuffle();
  provider->reset();
  paddle::DataBatch batch;
  int64_t num = provider->getNextBatchInternal(10000, &batch);
  CHECK_EQ(num, 200);
  auto csm = std::dynamic_pointer_cast<paddle::CpuSparseMatrix>(
      batch.getStreams()[0].value);
  CHECK(csm != nullptr);
  for (int i=0; i < 200; ++i) {
    CHECK_EQ(csm->getColNum(i), (size_t)10);
    int* cols = csm->getRowCols(i);
    for (int j=0; j < 10; ++j) {
      CHECK_EQ(cols[j], (i+1)*(j+1));
    }
  }
}

TEST(PyDataProvider2, sparse_value_no_seq) {
  paddle::DataBatch batch;
  CHECK_EQ(readDataBatch(&batch, "test_sparse_value_no_seq"), 200);
  auto csm = std::dynamic_pointer_cast<paddle::CpuSparseMatrix>(
      batch.getStreams()[0].value);
  CHECK(csm != nullptr);
  for (int i=0; i < 200; ++i) {
    CHECK_EQ(csm->getColNum(i), (size_t)10);
    int* cols = csm->getRowCols(i);
    real* dat = csm->getRowValues(i);
    for (int j=0; j < 10; ++j) {
      EXPECT_EQ(cols[j], (i+1)*(j+1));
      EXPECT_EQ(dat[j], real(j)/real(i+1));
    }
  }
}

TEST(PyDataProvider2, index_seq) {
  paddle::DataBatch batch;
  CHECK_EQ(readDataBatch(&batch, "test_index_seq"), 200);
  auto& arg = batch.getStreams()[0];
  CHECK_EQ((int)arg.ids->getSize(), (200 + 1) * 200 /2);
  size_t tmp = 0;
  for (size_t i=0; i < 200; ++i) {  // CHECK DATA CORRECT
    for (size_t j=0; j < i+1; ++j) {
      ASSERT_EQ((size_t)arg.ids->getData()[tmp], j);
      ++tmp;
    }
  }
  ASSERT_EQ(arg.sequenceStartPositions->getSize(), (size_t)201);
  tmp = 0;
  for (size_t i = 0; i < 200; ++i) {
    tmp += i;
    ASSERT_EQ((size_t)arg.sequenceStartPositions->getData(false)[i], tmp);
  }
  tmp += 200;
  ASSERT_EQ((size_t)arg.sequenceStartPositions->getData(false)[200], tmp);
}

TEST(PyDataProvider2, index_sub_seq) {
  paddle::DataBatch batch;
  ASSERT_EQ(readDataBatch(&batch, "test_index_sub_seq"), 200);
  auto& arg = batch.getStreams()[0];
  size_t tmp = 0;
  for (size_t i=0; i < 200; ++i) {
    for (size_t j=0; j < i+1; ++j) {
      for (size_t k=0; k < j+1; ++k) {
        CHECK_EQ((size_t)arg.ids->getData()[tmp++], k);
      }
    }
  }

  CHECK_EQ(tmp, arg.ids->getSize());

  ASSERT_EQ((size_t)arg.sequenceStartPositions->getSize(), (size_t)201);
  ASSERT_EQ(arg.subSequenceStartPositions->getData(false)[0], 0);
  ASSERT_EQ(arg.sequenceStartPositions->getData(false)[0], 0);
  size_t idx = 1;
  tmp = 0;
  for (size_t i=0; i < 200; ++i) {
    for (size_t j=0; j < i+1; ++j) {
      tmp += j+1;
      ASSERT_EQ((size_t)arg.subSequenceStartPositions->getData(false)[idx],
          (size_t)tmp);
      ++idx;
    }
    ASSERT_EQ((size_t)arg.sequenceStartPositions->getData(false)[i+1], tmp);
  }
}

250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323
TEST(PyDataProvider2, min_pool_size) {
  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object("test_min_pool_size");
  config.set_load_data_args("");
  size_t totalData = 1 << 14;
  constexpr size_t batchSize = 100;
  constexpr size_t minPoolSize = 1000;
  paddle::DataBatch batch;
  std::unique_ptr<paddle::DataProvider> provider(
      paddle::DataProvider::create(config, false));
  provider->reset();

  paddle::unittest::pydp2::setOnPoolFilledHook([&](size_t poolSize) {
    if (totalData > batchSize) {
      CHECK_GE(poolSize, std::min(totalData-batchSize, minPoolSize));
    }
  });
  while (true) {
    size_t realBatchSize = provider->getNextBatchInternal(batchSize, &batch);
    if (realBatchSize) {
      totalData -= realBatchSize;
    } else {
      break;
    }
  }
  paddle::unittest::pydp2::clearOnPoolFilledHook();
}

TEST(PyDataProvider2, can_over_batch_size) {
  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object("test_can_over_batch_size");
  config.set_load_data_args("");
  paddle::DataBatch batch;
  std::unique_ptr<paddle::DataProvider> provider(
  paddle::DataProvider::create(config, false));
  provider->reset();
  constexpr size_t batchSize = 100;
  while (true) {
    size_t realBatchSize = provider->getNextBatchInternal(batchSize, &batch);
    if (realBatchSize) {
      CHECK_LE(realBatchSize, batchSize);
    } else {
      break;
    }
  }
}

TEST(PyDataProvider2, input_order) {
  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object("test_input_order");
  config.set_load_data_args("");

  paddle::ModelConfig modelConfig;
  *modelConfig.add_input_layer_names() = "input1";
  *modelConfig.add_input_layer_names() = "input2";
  paddle::DataBatch batch;
  std::unique_ptr<paddle::DataProvider> provider(
  paddle::DataProvider::create(config, modelConfig, false));
  provider->reset();
  constexpr size_t batchSize = 100;
  while (true) {
    size_t realBatchSize = provider->getNextBatchInternal(batchSize, &batch);
    if (!realBatchSize) {
      break;
    }
324
    ASSERT_EQ(batch.getStreams().size(), (size_t)2);
325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355
    for (size_t i = 0; i < realBatchSize; ++i) {
      ASSERT_EQ(batch.getStream(0).ids->getData()[i], 0);
      ASSERT_EQ(batch.getStream(1).ids->getData()[i], 1);
    }
  }
}

TEST(PyDataProvider2, test_check) {
  paddle::DataConfig config;
  config.set_type("py2");
  config.set_files(FLAGS_train_list.c_str());
  config.set_load_data_module("test_PyDataProvider2");
  config.set_load_data_object("test_check");
  config.set_load_data_args("");
  paddle::DataBatch batch;
  std::unique_ptr<paddle::DataProvider> provider(
  paddle::DataProvider::create(config, false));
  provider->reset();
  while (true) {
    size_t realBatchSize = provider->getNextBatchInternal(100, &batch);
    if (!realBatchSize) {
      break;
    } else {
      auto& ivec = batch.getStream(0).ids;
      for (size_t i=0; i < ivec->getSize(); ++i) {
        CHECK_LT(ivec->getData()[i], 10);
      }
    }
  }
}

Z
zhangjinchao01 已提交
356 357 358 359 360 361 362 363 364 365 366 367 368 369
int main(int argc, char** argv) {
  testing::InitGoogleTest(&argc, argv);
  paddle::initMain(argc, argv);
  paddle::initPython(argc, argv);

  std::ofstream fout(FLAGS_train_list);
  CHECK(fout.is_open());
  fout << "stub file name" << std::endl;  // in unittest, filename is not used.
  fout.close();

  return RUN_ALL_TESTS();
}

#endif