forked from mindspore-Ecosystem/mindspore
220 lines
7.0 KiB
C++
220 lines
7.0 KiB
C++
/**
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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 <thread>
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#include "minddata/dataset/core/client.h"
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#include "minddata/dataset/core/constants.h"
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#include "minddata/dataset/engine/datasetops/map_op.h"
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#include "minddata/dataset/engine/datasetops/zip_op.h"
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#include "minddata/dataset/core/tensor.h"
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#include "minddata/dataset/core/config_manager.h"
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#include "common/common.h"
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#include "common/utils.h"
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#include "minddata/dataset/engine/data_buffer.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 "utils/log_adapter.h"
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namespace common = mindspore::common;
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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 MindDataTestZipOp : public UT::DatasetOpTesting {
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};
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TEST_F(MindDataTestZipOp, MindDataTestZipOpDefault) {
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/* Tree:
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*
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*
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* OpId(2) ZipOp
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* / \
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* OpId(0) TFReaderOp OpId(1) TFReaderOp
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* Start with an empty execution tree
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*/
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Status rc;
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MS_LOG(INFO) << "UT test TestZipBasic.";
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auto my_tree = std::make_shared<ExecutionTree>();
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// Creating TFReaderOp
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std::string dataset_path = datasets_root_path_ + "/test_tf_file_3_images/train-0000-of-0001.data";
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std::string dataset_path2 = datasets_root_path_ + "/testBatchDataset/test.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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rc = TFReaderOp::Builder()
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.SetDatasetFilesList({dataset_path})
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.SetRowsPerBuffer(2)
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.SetWorkerConnectorSize(16)
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.SetNumWorkers(1)
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.Build(&my_tfreader_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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EXPECT_TRUE(rc.IsOk());
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std::shared_ptr<TFReaderOp> my_tfreader_op2;
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rc = TFReaderOp::Builder()
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.SetDatasetFilesList({dataset_path2})
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.SetRowsPerBuffer(2)
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.SetWorkerConnectorSize(1)
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.SetNumWorkers(1)
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.Build(&my_tfreader_op2);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op2);
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EXPECT_TRUE(rc.IsOk());
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// Creating DatasetOp
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std::shared_ptr<ZipOp> zip_op;
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rc = ZipOp::Builder().Build(&zip_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(zip_op);
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EXPECT_TRUE(rc.IsOk());
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rc = zip_op->AddChild(std::move(my_tfreader_op));
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EXPECT_TRUE(rc.IsOk());
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rc = zip_op->AddChild(std::move(my_tfreader_op2));
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(zip_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->Prepare();
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EXPECT_TRUE(rc.IsOk());
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// Launch the tree execution to kick off threads and start running the pipeline
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MS_LOG(INFO) << "Launching my tree.";
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rc = my_tree->Launch();
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EXPECT_TRUE(rc.IsOk());
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// Simulate a parse of data from our pipeline.
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std::shared_ptr<DatasetOp> rootNode = my_tree->root();
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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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EXPECT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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MS_LOG(INFO) << "Row display for row #: " << row_count << ".";
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << common::SafeCStr(ss.str()) << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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EXPECT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 3); // Should be 3 rows fetched
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}
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TEST_F(MindDataTestZipOp, MindDataTestZipOpRepeat) {
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/* Tree:
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* OpId(3) Repeat(3)
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*
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* OpId(2) ZipOp
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* / \
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* OpId(0) TFReaderOp OpId(1) TFReaderOp
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*
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* Start with an empty execution tree
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*/
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Status rc;
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MS_LOG(INFO) << "UT test TestZipRepeat.";
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path = datasets_root_path_ + "/test_tf_file_3_images/train-0000-of-0001.data";
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std::string dataset_path2 = datasets_root_path_ + "/testBatchDataset/test.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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rc = TFReaderOp::Builder()
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.SetDatasetFilesList({dataset_path})
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.SetRowsPerBuffer(2)
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.SetWorkerConnectorSize(16)
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.SetNumWorkers(1)
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.Build(&my_tfreader_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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EXPECT_TRUE(rc.IsOk());
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std::shared_ptr<TFReaderOp> my_tfreader_op2;
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rc = TFReaderOp::Builder()
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.SetDatasetFilesList({dataset_path2})
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.SetRowsPerBuffer(2)
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.SetWorkerConnectorSize(1)
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.SetNumWorkers(1)
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.Build(&my_tfreader_op2);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op2);
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EXPECT_TRUE(rc.IsOk());
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// Creating DatasetOp
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std::shared_ptr<ZipOp> zip_op;
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rc = ZipOp::Builder().Build(&zip_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(zip_op);
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EXPECT_TRUE(rc.IsOk());
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rc = zip_op->AddChild(std::move(my_tfreader_op));
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EXPECT_TRUE(rc.IsOk());
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rc = zip_op->AddChild(std::move(my_tfreader_op2));
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EXPECT_TRUE(rc.IsOk());
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// Builder(num_of_repeats)
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std::shared_ptr<RepeatOp> my_repeat_op;
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rc = RepeatOp::Builder(3).Build(&my_repeat_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_repeat_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_repeat_op->AddChild(zip_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(my_repeat_op);
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EXPECT_TRUE(rc.IsOk());
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rc = my_tree->Prepare();
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EXPECT_TRUE(rc.IsOk());
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// Launch the tree execution to kick off threads and start running the pipeline
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MS_LOG(INFO) << "Launching my tree.";
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rc = my_tree->Launch();
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EXPECT_TRUE(rc.IsOk());
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// Simulate a parse of data from our pipeline.
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std::shared_ptr<DatasetOp> rootNode = my_tree->root();
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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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EXPECT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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MS_LOG(INFO) << "Row display for row #: " << row_count << ".";
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << common::SafeCStr(ss.str()) << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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EXPECT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 9); // Should be 9 rows fetched
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}
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