/* 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 #include #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"); 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 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 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 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 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 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( 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( 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); } } 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