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121 lines
3.8 KiB
121 lines
3.8 KiB
/**
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* Copyright 2019 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <chrono>
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#include <cstdlib>
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#include <cstring>
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#include <functional>
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#include <iostream>
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#include <memory>
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#include <string>
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#include "minddata/dataset/core/client.h"
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#include "gtest/gtest.h"
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#include "minddata/dataset/core/global_context.h"
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#include "minddata/dataset/util/status.h"
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#include "minddata/dataset/core/client.h"
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#include "common/common.h"
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#include "gtest/gtest.h"
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#include "utils/log_adapter.h"
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#include <memory>
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#include <vector>
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#include <iostream>
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using namespace mindspore::dataset;
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using mindspore::MsLogLevel::INFO;
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using mindspore::ExceptionType::NoExceptionType;
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using mindspore::LogStream;
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class MindDataTestClientConfig : public UT::DatasetOpTesting {
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protected:
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};
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TEST_F(MindDataTestClientConfig, TestClientConfig1) {
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std::shared_ptr<ConfigManager> my_conf = GlobalContext::config_manager();
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ASSERT_EQ(my_conf->num_parallel_workers(), kCfgParallelWorkers);
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ASSERT_EQ(my_conf->rows_per_buffer(), kCfgRowsPerBuffer);
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ASSERT_EQ(my_conf->worker_connector_size(), kCfgWorkerConnectorSize);
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ASSERT_EQ(my_conf->op_connector_size(), kCfgOpConnectorSize);
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ASSERT_EQ(my_conf->seed(), kCfgDefaultSeed);
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my_conf->set_num_parallel_workers(2);
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my_conf->set_rows_per_buffer(1);
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my_conf->set_worker_connector_size(3);
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my_conf->set_op_connector_size(4);
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my_conf->set_seed(5);
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ASSERT_EQ(my_conf->num_parallel_workers(), 2);
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ASSERT_EQ(my_conf->rows_per_buffer(), 1);
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ASSERT_EQ(my_conf->worker_connector_size(), 3);
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ASSERT_EQ(my_conf->op_connector_size(), 4);
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ASSERT_EQ(my_conf->seed(), 5);
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std::string file = datasets_root_path_ + "/declient.cfg";
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ASSERT_TRUE(my_conf->LoadFile(file));
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ASSERT_EQ(my_conf->num_parallel_workers(), kCfgParallelWorkers);
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ASSERT_EQ(my_conf->rows_per_buffer(), kCfgRowsPerBuffer);
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ASSERT_EQ(my_conf->worker_connector_size(), kCfgWorkerConnectorSize);
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ASSERT_EQ(my_conf->op_connector_size(), kCfgOpConnectorSize);
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ASSERT_EQ(my_conf->seed(), kCfgDefaultSeed);
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}
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TEST_F(MindDataTestClientConfig, TestClientConfig2) {
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std::shared_ptr<ConfigManager> my_conf = GlobalContext::config_manager();
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my_conf->set_num_parallel_workers(8);
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Status rc;
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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// Test info:
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// Dataset from testDataset1 has 10 rows, 2 columns.
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// RowsPerBuffer buffer setting of 2 divides evenly into total rows.
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testDataset1/testDataset1.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path});
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rc = builder.Build(&my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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ASSERT_EQ(my_tfreader_op->num_workers(),1);
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my_tree->AssociateNode(my_tfreader_op);
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// Set children/root layout.
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my_tree->AssignRoot(my_tfreader_op);
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my_tree->Prepare();
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my_tree->Launch();
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 10); // Should be 10 rows fetched
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ASSERT_EQ(my_tfreader_op->num_workers(),1);
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}
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