// 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 "paddle/fluid/operators/reader/ctr_reader.h" #include #include #include #include #include #include #include #include "gtest/gtest.h" #include "paddle/fluid/framework/lod_tensor.h" #include "paddle/fluid/operators/reader/blocking_queue.h" using paddle::operators::reader::LoDTensorBlockingQueue; using paddle::operators::reader::LoDTensorBlockingQueueHolder; using paddle::operators::reader::CTRReader; using paddle::framework::LoDTensor; using paddle::framework::LoD; using paddle::framework::DDim; using paddle::platform::CPUPlace; using paddle::framework::make_ddim; using paddle::operators::reader::DataDesc; static void generatedata(const std::vector& data, const std::string& file_name) { std::ifstream in(file_name.c_str()); if (in.good()) { VLOG(3) << "file " << file_name << " exist, delete it first!"; remove(file_name.c_str()); } else { in.close(); } ogzstream out(file_name.c_str()); PADDLE_ENFORCE(out.good(), "open file %s failed!", file_name); for (auto& c : data) { out << c; } out.close(); PADDLE_ENFORCE(out.good(), "save file %s failed!", file_name); } static inline void check_all_data( const std::vector& ctr_data, const std::vector& slots, const std::vector& label_dims, const std::vector& label_value, const std::vector>>& data_slot_6002, const std::vector>>& data_slot_6003, size_t batch_num, size_t batch_size, std::shared_ptr queue, CTRReader* reader) { std::vector out; for (size_t i = 0; i < batch_num; ++i) { reader->ReadNext(&out); ASSERT_EQ(out.size(), slots.size() + 1); auto& label_tensor = out.back(); ASSERT_EQ(label_tensor.dims(), label_dims[i]); for (size_t j = 0; j < batch_size && i * batch_num + j < ctr_data.size(); ++j) { auto& label = label_tensor.data()[j]; ASSERT_TRUE(label == 0 || label == 1); ASSERT_EQ(label, label_value[i * batch_size + j]); } auto& tensor_6002 = out[0]; ASSERT_EQ(std::get<0>(data_slot_6002[i]), tensor_6002.lod()); ASSERT_EQ(std::memcmp(std::get<1>(data_slot_6002[i]).data(), tensor_6002.data(), tensor_6002.dims()[1] * sizeof(int64_t)), 0); } reader->ReadNext(&out); ASSERT_EQ(out.size(), 0); ASSERT_EQ(queue->Size(), 0); } TEST(CTR_READER, read_data) { const std::vector ctr_data = { "aaaa 1 0 0:6002 1:6003 2:6004 3:6005 4:6006 -1\n", "bbbb 1 0 5:6003 6:6003 7:6003 8:6004 9:6004 -1\n", "cccc 1 1 10:6002 11:6002 12:6002 13:6002 14:6002 -2\n", "dddd 1 0 15:6003 16:6003 17:6003 18:6003 19:6004 -3\n", "1111 1 1 20:6001 21:6001 22:6001 23:6001 24:6001 12\n", "2222 1 1 25:6004 26:6004 27:6004 28:6005 29:6005 aa\n", "3333 1 0 30:6002 31:6003 32:6004 33:6004 34:6005 er\n", "eeee 1 1 35:6003 36:6003 37:6005 38:6005 39:6005 dd\n", "ffff 1 1 40:6002 41:6003 42:6004 43:6004 44:6005 66\n", "gggg 1 1 46:6006 45:6006 47:6003 48:6003 49:6003 ba\n", }; std::string gz_file_name = "test_ctr_reader_data.gz"; generatedata(ctr_data, gz_file_name); std::vector label_value = {0, 0, 1, 0, 1, 1, 0, 1, 1, 1}; std::tuple> a1({{0, 1, 2, 7}}, {0, 0, 10, 11, 12, 13, 14}); std::tuple> a2({{0, 1, 2, 3}}, {0, 0, 0}); std::tuple> a3({{0, 1, 2, 3}}, {30, 0, 40}); std::tuple> a4({{0, 1}}, {0}); std::vector>> data_slot_6002{a1, a2, a3, a4}; std::tuple> b1({{0, 1, 4, 5}}, {1, 5, 6, 7, 0}); std::tuple> b2({{0, 4, 5, 6}}, {15, 16, 17, 18, 0, 0}); std::tuple> b3({{0, 1, 3, 4}}, {31, 35, 36, 41}); std::tuple> b4({{0, 3}}, {47, 48, 49}); std::vector>> data_slot_6003{b1, b2, b3, b4}; std::vector label_dims = {{1, 3}, {1, 3}, {1, 3}, {1, 1}}; LoDTensorBlockingQueueHolder queue_holder; int capacity = 64; queue_holder.InitOnce(capacity, false); std::shared_ptr queue = queue_holder.GetQueue(); int batch_size = 3; int thread_num = 1; std::vector sparse_slots = {"6002", "6003"}; std::vector file_list; for (int i = 0; i < thread_num; ++i) { file_list.push_back(gz_file_name); } DataDesc data_desc(batch_size, file_list, "gzip", "svm", {}, {}, sparse_slots); CTRReader reader(queue, thread_num, data_desc); reader.Start(); size_t batch_num = std::ceil(static_cast(ctr_data.size()) / batch_size) * thread_num; check_all_data(ctr_data, sparse_slots, label_dims, label_value, data_slot_6002, data_slot_6003, batch_num, batch_size, queue, &reader); reader.Shutdown(); reader.Start(); check_all_data(ctr_data, sparse_slots, label_dims, label_value, data_slot_6002, data_slot_6003, batch_num, batch_size, queue, &reader); reader.Shutdown(); }