1 /** 2 * Copyright 2020 Huawei Technologies Co., Ltd 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 #include "minddata/dataset/util/circular_pool.h" 17 #include "minddata/dataset/core/client.h" 18 #include "minddata/dataset/engine/jagged_connector.h" 19 #include "common/common.h" 20 #include "gtest/gtest.h" 21 #include "utils/log_adapter.h" 22 23 using namespace mindspore::dataset; 24 using mindspore::LogStream; 25 using mindspore::ExceptionType::NoExceptionType; 26 using mindspore::MsLogLevel::INFO; 27 28 class MindDataTestSkipOp : public UT::DatasetOpTesting {}; 29 30 TEST_F(MindDataTestSkipOp, TestSkipOpFuntions) { 31 // Start with an empty execution tree 32 auto my_tree = std::make_shared<ExecutionTree>(); 33 Status rc; 34 std::string dataset_path; 35 dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data"; 36 37 std::shared_ptr<ConfigManager> config_manager = GlobalContext::config_manager(); 38 int32_t op_connector_size = config_manager->op_connector_size(); 39 int32_t num_workers = config_manager->num_parallel_workers(); 40 int32_t worker_connector_size = 16; 41 std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>(); 42 schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {}); 43 std::vector<std::string> columns_to_load = {}; 44 std::vector<std::string> files = {dataset_path}; 45 std::shared_ptr<TFReaderOp> my_tfreader_op = 46 std::make_shared<TFReaderOp>(num_workers, worker_connector_size, 0, files, std::move(schema), op_connector_size, 47 columns_to_load, false, 1, 0, false); 48 rc = my_tfreader_op->Init(); 49 ASSERT_TRUE(rc.IsOk()); 50 rc = my_tree->AssociateNode(my_tfreader_op); 51 ASSERT_TRUE(rc.IsOk()); 52 53 // SkipOp 54 std::shared_ptr<SkipOp> skip_op = std::make_shared<SkipOp>(5); 55 rc = my_tree->AssociateNode(skip_op); 56 ASSERT_TRUE(rc.IsOk()); 57 58 // Set children/root layout. 59 rc = skip_op->AddChild(my_tfreader_op); 60 ASSERT_TRUE(rc.IsOk()); 61 rc = my_tree->AssignRoot(skip_op); 62 ASSERT_TRUE(rc.IsOk()); 63 64 MS_LOG(INFO) << "Launching tree and begin iteration."; 65 rc = my_tree->Prepare(); 66 67 ASSERT_TRUE(rc.IsOk()); 68 69 rc = my_tree->Launch(); 70 ASSERT_TRUE(rc.IsOk()); 71 72 // Start the loop of reading tensors from our pipeline 73 DatasetIterator di(my_tree); 74 TensorRow tensor_list; 75 rc = di.FetchNextTensorRow(&tensor_list); 76 ASSERT_TRUE(rc.IsOk()); 77 78 int row_count = 0; 79 while (!tensor_list.empty()) { 80 MS_LOG(INFO) << "Row display for row #: " << row_count << "."; 81 82 // Display the tensor by calling the printer on it 83 for (int i = 0; i < tensor_list.size(); i++) { 84 std::ostringstream ss; 85 ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl; 86 MS_LOG(INFO) << "Tensor print: " << ss.str() << "."; 87 } 88 89 rc = di.FetchNextTensorRow(&tensor_list); 90 ASSERT_TRUE(rc.IsOk()); 91 row_count++; 92 } 93 94 ASSERT_EQ(row_count, 7); 95 } 96