mindspore/tests/ut/cpp/dataset/tfReader_op_test.cc

/**
 * Copyright 2019 Huawei Technologies Co., Ltd
 *
 * 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 <iostream>
#include <memory>
#include <vector>

#include "dataset/core/client.h"
#include "dataset/engine/data_schema.h"
#include "common/common.h"
#include "common/utils.h"
#include "gtest/gtest.h"
#include "utils/log_adapter.h"

namespace common = mindspore::common;

using namespace mindspore::dataset;
using mindspore::MsLogLevel::INFO;
using mindspore::ExceptionType::NoExceptionType;
using mindspore::LogStream;

class MindDataTestTFReaderOp : public UT::DatasetOpTesting {

};

TEST_F(MindDataTestTFReaderOp, TestTFReaderBasic1) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";


  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path})
      .SetRowsPerBuffer(16)
      .SetNumWorkers(16);
  std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
  builder.SetDataSchema(std::move(schema));
  Status rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 12);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderLargeRowsPerBuffer) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";

  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path})
      .SetRowsPerBuffer(500)
      .SetNumWorkers(16);
   std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
  builder.SetDataSchema(std::move(schema));
  Status rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 12);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderSmallRowsPerBuffer) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";

  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path})
      .SetRowsPerBuffer(1)
      .SetNumWorkers(16);
   std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
  builder.SetDataSchema(std::move(schema));
  Status rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 12);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderLargeQueueSize) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";

  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path})
      .SetWorkerConnectorSize(1)
      .SetRowsPerBuffer(16)
      .SetNumWorkers(16);
   std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
  builder.SetDataSchema(std::move(schema));
  Status rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 12);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderOneThread) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";

  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path})
      .SetRowsPerBuffer(16)
      .SetNumWorkers(1);
   std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
  builder.SetDataSchema(std::move(schema));
  Status rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 12);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderRepeat) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";

  // TFReaderOp
  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path})
    .SetRowsPerBuffer(16)
    .SetWorkerConnectorSize(16)
    .SetNumWorkers(16);
  std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
  builder.SetDataSchema(std::move(schema));
  Status rc= builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());
  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  // RepeatOp
  std::shared_ptr<RepeatOp> my_repeat_op = std::make_shared<RepeatOp>(3);
  rc = my_tree->AssociateNode(my_repeat_op);
  ASSERT_TRUE(rc.IsOk());

  // Set children/root layout.
  rc = my_repeat_op->AddChild(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());
  rc = my_tree->AssignRoot(my_repeat_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(INFO) << "Row display for row #: " << row_count << ".";

    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 12 * 3);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderSchemaConstructor) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes";

  std::unique_ptr<DataSchema> data_schema = std::make_unique<DataSchema>();
  std::vector<std::string> columns_to_load;
  columns_to_load.push_back("col_sint32");
  columns_to_load.push_back("col_binary");
  data_schema->LoadSchemaFile(dataset_path + "/datasetSchema.json", columns_to_load);

  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path+"/test.data"})
    .SetRowsPerBuffer(16)
    .SetNumWorkers(16)
    .SetDataSchema(std::move(data_schema));
  Status rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    // Display the tensor by calling the printer on it
    ASSERT_EQ(tensor_list.size(), columns_to_load.size());

    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 12);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderTake1Row) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes";

  std::string data_schema_filepath = dataset_path + "/datasetSchema1Row.json";

  // TFReaderOp
  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path + "/test.data"}).SetRowsPerBuffer(5).SetNumWorkers(16);
  std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema1Row.json", {});
  builder.SetDataSchema(std::move(schema));

  Status rc= builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(INFO) << "Row display for row #: " << row_count << ".";

    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 1);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderTake1Buffer) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes";

  std::string data_schema_filepath = dataset_path + "/datasetSchema5Rows.json";

  // TFReaderOp
  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path + "/test.data"}).SetRowsPerBuffer(5).SetNumWorkers(16);
  std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema5Rows.json", {});
  builder.SetDataSchema(std::move(schema));

  Status rc= builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(INFO) << "Row display for row #: " << row_count << ".";

    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 5);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderTake7Rows) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes";

  std::string data_schema_filepath = dataset_path + "/datasetSchema7Rows.json";

  // TFReaderOp
  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path + "/test.data"}).SetRowsPerBuffer(5).SetNumWorkers(16);
  std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema7Rows.json", {});
  builder.SetDataSchema(std::move(schema));

  Status rc= builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    MS_LOG(INFO) << "Row display for row #: " << row_count << ".";

    // Display the tensor by calling the printer on it
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 7);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderBasicNoSchema) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string dataset_path;
  dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";

  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({dataset_path})
      .SetRowsPerBuffer(16)
      .SetNumWorkers(16);
  Status rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssociateNode(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->AssignRoot(my_tfreader_op);
  ASSERT_TRUE(rc.IsOk());

  MS_LOG(INFO) << "Launching tree and begin iteration.";
  rc = my_tree->Prepare();
  ASSERT_TRUE(rc.IsOk());

  rc = my_tree->Launch();
  ASSERT_TRUE(rc.IsOk());

  // Start the loop of reading tensors from our pipeline
  DatasetIterator di(my_tree);
  TensorRow tensor_list;
  rc = di.FetchNextTensorRow(&tensor_list);
  ASSERT_TRUE(rc.IsOk());

  int row_count = 0;
  while (!tensor_list.empty()) {
    // Display the tensor by calling the printer on it
    ASSERT_EQ(tensor_list.size(), 9);
    for (int i = 0; i < tensor_list.size(); i++) {
      std::ostringstream ss;
      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
    }

    rc = di.FetchNextTensorRow(&tensor_list);
    ASSERT_TRUE(rc.IsOk());
    row_count++;
  }

  ASSERT_EQ(row_count, 12);
}

TEST_F(MindDataTestTFReaderOp, TestTotalRowsBasic) {
  std::string tf_file = datasets_root_path_ + "/testTFTestAllTypes/test.data";

  std::vector<std::string> filenames;

  for (int i = 0; i < 5; i++) {
    filenames.push_back(tf_file);
  }

  int64_t total_rows = 0;
  TFReaderOp::CountTotalRows(&total_rows, filenames, 1);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 2);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 3);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 4);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 5);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 6);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 729);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 1, true);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 2, true);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 3, true);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 4, true);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 5, true);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 6, true);
  ASSERT_EQ(total_rows, 60);
  TFReaderOp::CountTotalRows(&total_rows, filenames, 729, true);
  ASSERT_EQ(total_rows, 60);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderInvalidFiles) {
  // Start with an empty execution tree
  auto my_tree = std::make_shared<ExecutionTree>();

  std::string valid_file = datasets_root_path_ + "/testTFTestAllTypes/test.data";
  std::string schema_file = datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json";
  std::string invalid_file = datasets_root_path_ + "/testTFTestAllTypes/invalidFile.txt";
  std::string nonexistent_file = "this/file/doesnt/exist";

  std::shared_ptr<TFReaderOp> my_tfreader_op;
  TFReaderOp::Builder builder;
  builder.SetDatasetFilesList({invalid_file, valid_file, schema_file})
      .SetRowsPerBuffer(16)
      .SetNumWorkers(16);

  std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(schema_file, {});
  builder.SetDataSchema(std::move(schema));

  Status rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(!rc.IsOk());

  builder.SetDatasetFilesList({invalid_file, valid_file, schema_file, nonexistent_file})
      .SetRowsPerBuffer(16)
      .SetNumWorkers(16);

  schema = std::make_unique<DataSchema>();
  schema->LoadSchemaFile(schema_file, {});
  builder.SetDataSchema(std::move(schema));

  rc = builder.Build(&my_tfreader_op);
  ASSERT_TRUE(!rc.IsOk());
}