!4696 C++ API Support for CSV Dataset

Merge pull request !4696 from jiangzhiwen/jzw/c_api_csv

mindspore/ccsrc/minddata/dataset/api/datasets.cc

@@ -25,6 +25,7 @@
 #include "minddata/dataset/engine/datasetops/source/cifar_op.h"
 #include "minddata/dataset/engine/datasetops/source/clue_op.h"
 #include "minddata/dataset/engine/datasetops/source/coco_op.h"
+#include "minddata/dataset/engine/datasetops/source/csv_op.h"
 #include "minddata/dataset/engine/datasetops/source/image_folder_op.h"
 #include "minddata/dataset/engine/datasetops/source/manifest_op.h"
 #include "minddata/dataset/engine/datasetops/source/mnist_op.h"
@@ -161,6 +162,18 @@ std::shared_ptr<CocoDataset> Coco(const std::string &dataset_dir, const std::str
   return ds->ValidateParams() ? ds : nullptr;
 }
 
+// Function to create a CSVDataset.
+std::shared_ptr<CSVDataset> CSV(const std::vector<std::string> &dataset_files, char field_delim,
+                                const std::vector<std::shared_ptr<CsvBase>> &column_defaults,
+                                const std::vector<std::string> &column_names, int64_t num_samples, ShuffleMode shuffle,
+                                int32_t num_shards, int32_t shard_id) {
+  auto ds = std::make_shared<CSVDataset>(dataset_files, field_delim, column_defaults, column_names, num_samples,
+                                         shuffle, num_shards, shard_id);
+
+  // Call derived class validation method.
+  return ds->ValidateParams() ? ds : nullptr;
+}
+
 // Function to create a ImageFolderDataset.
 std::shared_ptr<ImageFolderDataset> ImageFolder(const std::string &dataset_dir, bool decode,
                                                 const std::shared_ptr<SamplerObj> &sampler,
@@ -1021,6 +1034,84 @@ std::vector<std::shared_ptr<DatasetOp>> CocoDataset::Build() {
   return node_ops;
 }
 
+// Constructor for CSVDataset
+CSVDataset::CSVDataset(const std::vector<std::string> &csv_files, char field_delim,
+                       const std::vector<std::shared_ptr<CsvBase>> &column_defaults,
+                       const std::vector<std::string> &column_names, int64_t num_samples, ShuffleMode shuffle,
+                       int32_t num_shards, int32_t shard_id)
+    : dataset_files_(csv_files),
+      field_delim_(field_delim),
+      column_defaults_(column_defaults),
+      column_names_(column_names),
+      num_samples_(num_samples),
+      shuffle_(shuffle),
+      num_shards_(num_shards),
+      shard_id_(shard_id) {}
+
+bool CSVDataset::ValidateParams() {
+  if (!ValidateDatasetFilesParam("CSVDataset", dataset_files_)) {
+    return false;
+  }
+
+  if (field_delim_ == '"' || field_delim_ == '\r' || field_delim_ == '\n') {
+    MS_LOG(ERROR) << "CSVDataset: The field delimiter should not be \", \\r, \\n";
+    return false;
+  }
+
+  if (num_samples_ < -1) {
+    MS_LOG(ERROR) << "CSVDataset: Invalid number of samples: " << num_samples_;
+    return false;
+  }
+
+  if (!ValidateDatasetShardParams("CSVDataset", num_shards_, shard_id_)) {
+    return false;
+  }
+
+  return true;
+}
+
+// Function to build CSVDataset
+std::vector<std::shared_ptr<DatasetOp>> CSVDataset::Build() {
+  // A vector containing shared pointer to the Dataset Ops that this object will create
+  std::vector<std::shared_ptr<DatasetOp>> node_ops;
+
+  bool shuffle_files = (shuffle_ == ShuffleMode::kGlobal || shuffle_ == ShuffleMode::kFiles);
+  std::vector<std::shared_ptr<CsvOp::BaseRecord>> column_default_list;
+  for (auto v : column_defaults_) {
+    if (v->type == CsvType::INT) {
+      column_default_list.push_back(
+        std::make_shared<CsvOp::Record<int>>(CsvOp::INT, std::dynamic_pointer_cast<CsvRecord<int>>(v)->value));
+    } else if (v->type == CsvType::FLOAT) {
+      column_default_list.push_back(
+        std::make_shared<CsvOp::Record<float>>(CsvOp::FLOAT, std::dynamic_pointer_cast<CsvRecord<float>>(v)->value));
+    } else if (v->type == CsvType::STRING) {
+      column_default_list.push_back(std::make_shared<CsvOp::Record<std::string>>(
+        CsvOp::STRING, std::dynamic_pointer_cast<CsvRecord<std::string>>(v)->value));
+    }
+  }
+
+  std::shared_ptr<CsvOp> csv_op = std::make_shared<CsvOp>(
+    dataset_files_, field_delim_, column_default_list, column_names_, num_workers_, rows_per_buffer_, num_samples_,
+    worker_connector_size_, connector_que_size_, shuffle_files, num_shards_, shard_id_);
+  RETURN_EMPTY_IF_ERROR(csv_op->Init());
+  if (shuffle_ == ShuffleMode::kGlobal) {
+    // Inject ShuffleOp
+    std::shared_ptr<DatasetOp> shuffle_op = nullptr;
+    int64_t num_rows = 0;
+
+    // First, get the number of rows in the dataset
+    RETURN_EMPTY_IF_ERROR(CsvOp::CountAllFileRows(dataset_files_, column_names_.empty(), &num_rows));
+
+    // Add the shuffle op after this op
+    RETURN_EMPTY_IF_ERROR(AddShuffleOp(dataset_files_.size(), num_shards_, num_rows, 0, connector_que_size_,
+                                       rows_per_buffer_, &shuffle_op));
+    node_ops.push_back(shuffle_op);
+  }
+
+  node_ops.push_back(csv_op);
+  return node_ops;
+}
+
 ImageFolderDataset::ImageFolderDataset(std::string dataset_dir, bool decode, std::shared_ptr<SamplerObj> sampler,
                                        bool recursive, std::set<std::string> extensions,
                                        std::map<std::string, int32_t> class_indexing)

mindspore/ccsrc/minddata/dataset/include/datasets.h

@@ -51,6 +51,8 @@ class Cifar10Dataset;
 class Cifar100Dataset;
 class CLUEDataset;
 class CocoDataset;
+class CSVDataset;
+class CsvBase;
 class ImageFolderDataset;
 class ManifestDataset;
 class MnistDataset;
@@ -114,13 +116,13 @@ std::shared_ptr<Cifar100Dataset> Cifar100(const std::string &dataset_dir,
 /// \param[in] usage Be used to "train", "test" or "eval" data (default="train").
 /// \param[in] num_samples The number of samples to be included in the dataset.
 ///    (Default = 0 means all samples.)
-/// \param[in] shuffle The mode for shuffling data every epoch. (Default=ShuffleMode.kGlobal)
+/// \param[in] shuffle The mode for shuffling data every epoch. (Default=ShuffleMode::kGlobal)
 ///    Can be any of:
-///    ShuffleMode.kFalse - No shuffling is performed.
-///    ShuffleMode.kFiles - Shuffle files only.
-///    ShuffleMode.kGlobal - Shuffle both the files and samples.
+///    ShuffleMode::kFalse - No shuffling is performed.
+///    ShuffleMode::kFiles - Shuffle files only.
+///    ShuffleMode::kGlobal - Shuffle both the files and samples.
 /// \param[in] num_shards Number of shards that the dataset should be divided into. (Default = 1)
-/// \param[in] shard_id  The shard ID within num_shards. This argument should be
+/// \param[in] shard_id The shard ID within num_shards. This argument should be
 ///    specified only when num_shards is also specified. (Default = 0)
 /// \return Shared pointer to the current CLUEDataset
 std::shared_ptr<CLUEDataset> CLUE(const std::vector<std::string> &dataset_files, const std::string &task = "AFQMC",
@@ -148,6 +150,32 @@ std::shared_ptr<CocoDataset> Coco(const std::string &dataset_dir, const std::str
                                   const std::string &task = "Detection", const bool &decode = false,
                                   const std::shared_ptr<SamplerObj> &sampler = nullptr);
 
+/// \brief Function to create a CSVDataset
+/// \notes The generated dataset has a variable number of columns
+/// \param[in] dataset_files List of files to be read to search for a pattern of files. The list
+///    will be sorted in a lexicographical order.
+/// \param[in] field_delim A char that indicates the delimiter to separate fields (default=',').
+/// \param[in] column_defaults List of default values for the CSV field (default={}). Each item in the list is
+///    either a valid type (float, int, or string). If this is not provided, treats all columns as string type.
+/// \param[in] column_names List of column names of the dataset (default={}). If this is not provided, infers the
+///    column_names from the first row of CSV file.
+/// \param[in] num_samples The number of samples to be included in the dataset.
+///    (Default = -1 means all samples.)
+/// \param[in] shuffle The mode for shuffling data every epoch. (Default=ShuffleMode::kGlobal)
+///    Can be any of:
+///    ShuffleMode::kFalse - No shuffling is performed.
+///    ShuffleMode::kFiles - Shuffle files only.
+///    ShuffleMode::kGlobal - Shuffle both the files and samples.
+/// \param[in] num_shards Number of shards that the dataset should be divided into. (Default = 1)
+/// \param[in] shard_id The shard ID within num_shards. This argument should be
+///    specified only when num_shards is also specified. (Default = 0)
+/// \return Shared pointer to the current Dataset
+std::shared_ptr<CSVDataset> CSV(const std::vector<std::string> &dataset_files, char field_delim = ',',
+                                const std::vector<std::shared_ptr<CsvBase>> &column_defaults = {},
+                                const std::vector<std::string> &column_names = {}, int64_t num_samples = -1,
+                                ShuffleMode shuffle = ShuffleMode::kGlobal, int32_t num_shards = 1,
+                                int32_t shard_id = 0);
+
 /// \brief Function to create an ImageFolderDataset
 /// \notes A source dataset that reads images from a tree of directories
 ///    All images within one folder have the same label
@@ -217,13 +245,13 @@ std::shared_ptr<RandomDataset> RandomData(const int32_t &total_rows = 0, T schem
 ///    will be sorted in a lexicographical order.
 /// \param[in] num_samples The number of samples to be included in the dataset.
 ///    (Default = 0 means all samples.)
-/// \param[in] shuffle The mode for shuffling data every epoch. (Default=ShuffleMode.kGlobal)
+/// \param[in] shuffle The mode for shuffling data every epoch. (Default=ShuffleMode::kGlobal)
 ///    Can be any of:
-///    ShuffleMode.kFalse - No shuffling is performed.
-///    ShuffleMode.kFiles - Shuffle files only.
-///    ShuffleMode.kGlobal - Shuffle both the files and samples.
+///    ShuffleMode::kFalse - No shuffling is performed.
+///    ShuffleMode::kFiles - Shuffle files only.
+///    ShuffleMode::kGlobal - Shuffle both the files and samples.
 /// \param[in] num_shards Number of shards that the dataset should be divided into. (Default = 1)
-/// \param[in] shard_id  The shard ID within num_shards. This argument should be
+/// \param[in] shard_id The shard ID within num_shards. This argument should be
 ///    specified only when num_shards is also specified. (Default = 0)
 /// \return Shared pointer to the current TextFileDataset
 std::shared_ptr<TextFileDataset> TextFile(const std::vector<std::string> &dataset_files, int32_t num_samples = 0,
@@ -572,6 +600,57 @@ class CocoDataset : public Dataset {
   std::shared_ptr<SamplerObj> sampler_;
 };
 
+/// \brief Record type for CSV
+enum CsvType : uint8_t { INT = 0, FLOAT, STRING };
+
+/// \brief Base class of CSV Record
+struct CsvBase {
+ public:
+  CsvBase() = default;
+  explicit CsvBase(CsvType t) : type(t) {}
+  virtual ~CsvBase() {}
+  CsvType type;
+};
+
+/// \brief CSV Record that can represent integer, float and string.
+template <typename T>
+class CsvRecord : public CsvBase {
+ public:
+  CsvRecord() = default;
+  CsvRecord(CsvType t, T v) : CsvBase(t), value(v) {}
+  ~CsvRecord() {}
+  T value;
+};
+
+class CSVDataset : public Dataset {
+ public:
+  /// \brief Constructor
+  CSVDataset(const std::vector<std::string> &dataset_files, char field_delim,
+             const std::vector<std::shared_ptr<CsvBase>> &column_defaults, const std::vector<std::string> &column_names,
+             int64_t num_samples, ShuffleMode shuffle, int32_t num_shards, int32_t shard_id);
+
+  /// \brief Destructor
+  ~CSVDataset() = default;
+
+  /// \brief a base class override function to create the required runtime dataset op objects for this class
+  /// \return shared pointer to the list of newly created DatasetOps
+  std::vector<std::shared_ptr<DatasetOp>> Build() override;
+
+  /// \brief Parameters validation
+  /// \return bool true if all the params are valid
+  bool ValidateParams() override;
+
+ private:
+  std::vector<std::string> dataset_files_;
+  char field_delim_;
+  std::vector<std::shared_ptr<CsvBase>> column_defaults_;
+  std::vector<std::string> column_names_;
+  int64_t num_samples_;
+  ShuffleMode shuffle_;
+  int32_t num_shards_;
+  int32_t shard_id_;
+};
+
 /// \class ImageFolderDataset
 /// \brief A Dataset derived class to represent ImageFolder dataset
 class ImageFolderDataset : public Dataset {

tests/ut/cpp/dataset/CMakeLists.txt

@@ -103,7 +103,9 @@ SET(DE_UT_SRCS
         c_api_dataset_cifar_test.cc
         c_api_dataset_clue_test.cc
         c_api_dataset_coco_test.cc
+        c_api_dataset_csv_test.cc
         c_api_dataset_filetext_test.cc
+        c_api_dataset_manifest_test.cc
         c_api_dataset_randomdata_test.cc
         c_api_dataset_voc_test.cc
         c_api_datasets_test.cc

tests/ut/cpp/dataset/c_api_dataset_csv_test.cc

+/**
+ * Copyright 2020 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 "common/common.h"
+#include "minddata/dataset/core/config_manager.h"
+#include "minddata/dataset/core/global_context.h"
+#include "minddata/dataset/include/datasets.h"
+
+using namespace mindspore::dataset::api;
+using mindspore::dataset::ShuffleMode;
+using mindspore::dataset::Tensor;
+using mindspore::dataset::GlobalContext;
+
+class MindDataTestPipeline : public UT::DatasetOpTesting {
+ protected:
+};
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetBasic) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetBasic.";
+
+  // Create a CSVDataset, with single CSV file
+  std::string train_file = datasets_root_path_ + "/testCSV/1.csv";
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+  std::shared_ptr<Dataset> ds = CSV({train_file}, ',', {}, column_names, -1, ShuffleMode::kFalse);
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  // This will trigger the creation of the Execution Tree and launch it.
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+  EXPECT_NE(row.find("col1"), row.end());
+  std::vector<std::vector<std::string>> expected_result = {
+    {"1", "2", "3", "4"},
+    {"5", "6", "7", "8"},
+    {"9", "10", "11", "12"},
+  };
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    for (int j = 0; j < column_names.size(); j++) {
+      auto text = row[column_names[j]];
+      std::string_view sv;
+      text->GetItemAt(&sv, {0});
+      std::string ss(sv);
+      EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str());
+    }
+    iter->GetNextRow(&row);
+    i++;
+  }
+
+  // Expect 3 samples
+  EXPECT_EQ(i, 3);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetMultiFiles) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetMultiFiles.";
+
+  // Set configuration
+  uint32_t original_seed = GlobalContext::config_manager()->seed();
+  uint32_t original_num_parallel_workers = GlobalContext::config_manager()->num_parallel_workers();
+  MS_LOG(DEBUG) << "ORIGINAL seed: " << original_seed << ", num_parallel_workers: " << original_num_parallel_workers;
+  GlobalContext::config_manager()->set_seed(111);
+  GlobalContext::config_manager()->set_num_parallel_workers(4);
+
+  // Create a CSVDataset, with single CSV file
+  std::string file1 = datasets_root_path_ + "/testCSV/1.csv";
+  std::string file2 = datasets_root_path_ + "/testCSV/append.csv";
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+  std::shared_ptr<Dataset> ds = CSV({file1, file2}, ',', {}, column_names, -1, ShuffleMode::kGlobal);
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  // This will trigger the creation of the Execution Tree and launch it.
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+  EXPECT_NE(row.find("col1"), row.end());
+  std::vector<std::vector<std::string>> expected_result = {
+    {"17", "18", "19", "20"},
+    {"1", "2", "3", "4"},
+    {"5", "6", "7", "8"},
+    {"13", "14", "15", "16"},
+    {"21", "22", "23", "24"},
+    {"9", "10", "11", "12"},
+  };
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    for (int j = 0; j < column_names.size(); j++) {
+      auto text = row[column_names[j]];
+      std::string_view sv;
+      text->GetItemAt(&sv, {0});
+      std::string ss(sv);
+      EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str());
+    }
+    iter->GetNextRow(&row);
+    i++;
+  }
+
+  // Expect 6 samples
+  EXPECT_EQ(i, 6);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+
+  // Restore configuration
+  GlobalContext::config_manager()->set_seed(original_seed);
+  GlobalContext::config_manager()->set_num_parallel_workers(original_num_parallel_workers);
+}
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetNumSamples) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetNumSamples.";
+
+  // Create a CSVDataset, with single CSV file
+  std::string file = datasets_root_path_ + "/testCSV/1.csv";
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+  std::shared_ptr<Dataset> ds = CSV({file}, ',', {}, column_names, 2, ShuffleMode::kFalse);
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  // This will trigger the creation of the Execution Tree and launch it.
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+  EXPECT_NE(row.find("col1"), row.end());
+  std::vector<std::vector<std::string>> expected_result = {
+    {"1", "2", "3", "4"},
+    {"5", "6", "7", "8"}
+  };
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    for (int j = 0; j < column_names.size(); j++) {
+      auto text = row[column_names[j]];
+      std::string_view sv;
+      text->GetItemAt(&sv, {0});
+      std::string ss(sv);
+      EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str());
+    }
+    iter->GetNextRow(&row);
+    i++;
+  }
+
+  // Expect 2 samples
+  EXPECT_EQ(i, 2);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetDistribution) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetDistribution.";
+
+  // Create a CSVDataset, with single CSV file
+  std::string file = datasets_root_path_ + "/testCSV/1.csv";
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+  std::shared_ptr<Dataset> ds = CSV({file}, ',', {}, column_names, -1, ShuffleMode::kFalse, 2, 0);
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  // This will trigger the creation of the Execution Tree and launch it.
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+  EXPECT_NE(row.find("col1"), row.end());
+  std::vector<std::vector<std::string>> expected_result = {
+    {"1", "2", "3", "4"},
+    {"5", "6", "7", "8"}
+  };
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    for (int j = 0; j < column_names.size(); j++) {
+      auto text = row[column_names[j]];
+      std::string_view sv;
+      text->GetItemAt(&sv, {0});
+      std::string ss(sv);
+      EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str());
+    }
+    iter->GetNextRow(&row);
+    i++;
+  }
+
+  // Expect 2 samples
+  EXPECT_EQ(i, 2);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetType) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetType.";
+
+  // Create a CSVDataset, with single CSV file
+  std::string file = datasets_root_path_ + "/testCSV/default.csv";
+  std::vector<std::shared_ptr<CsvBase>> colum_type = {
+    std::make_shared<CsvRecord<std::string>>(CsvType::STRING, ""),
+    std::make_shared<CsvRecord<int>>(CsvType::INT, 0),
+    std::make_shared<CsvRecord<float>>(CsvType::FLOAT, 0.0),
+    std::make_shared<CsvRecord<std::string>>(CsvType::STRING, ""),
+  };
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+  std::shared_ptr<Dataset> ds = CSV({file}, ',', colum_type, column_names, -1, ShuffleMode::kFalse);
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  // This will trigger the creation of the Execution Tree and launch it.
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+  std::vector<std::vector<std::shared_ptr<CsvBase>>> expected = {
+    {
+      std::make_shared<CsvRecord<std::string>>(CsvType::STRING, ""),
+      std::make_shared<CsvRecord<int>>(CsvType::INT, 2),
+      std::make_shared<CsvRecord<float>>(CsvType::FLOAT, 3.0),
+      std::make_shared<CsvRecord<std::string>>(CsvType::STRING, ""),
+    },
+    {
+      std::make_shared<CsvRecord<std::string>>(CsvType::STRING, "a"),
+      std::make_shared<CsvRecord<int>>(CsvType::INT, 4),
+      std::make_shared<CsvRecord<float>>(CsvType::FLOAT, 5.0),
+      std::make_shared<CsvRecord<std::string>>(CsvType::STRING, "b"),
+    },
+  };
+  EXPECT_NE(row.find("col1"), row.end());
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    for (int j = 0; j < column_names.size(); j++) {
+      auto text = row[column_names[j]];
+      if (colum_type[j]->type == CsvType::INT) {
+        int val;
+        text->GetItemAt(&val, {0});
+        EXPECT_EQ(val, std::dynamic_pointer_cast<CsvRecord<int>>(expected[i][j])->value);
+      } else if (colum_type[j]->type == CsvType::FLOAT) {
+        float val;
+        text->GetItemAt(&val, {0});
+        EXPECT_EQ(val, std::dynamic_pointer_cast<CsvRecord<float>>(expected[i][j])->value);
+      } else if (colum_type[j]->type == CsvType::STRING) {
+        std::string_view sv;
+        text->GetItemAt(&sv, {0});
+        std::string ss(sv);
+        EXPECT_STREQ(ss.c_str(), std::dynamic_pointer_cast<CsvRecord<std::string>>(expected[i][j])->value.c_str());
+      }
+    }
+    iter->GetNextRow(&row);
+    i++;
+  }
+
+  // Expect 2 samples
+  EXPECT_EQ(i, 2);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetHeader) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetHeader.";
+
+  // Create a CSVDataset, with single CSV file
+  std::string train_file = datasets_root_path_ + "/testCSV/header.csv";
+  std::shared_ptr<Dataset> ds = CSV({train_file}, ',', {}, {});
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  // This will trigger the creation of the Execution Tree and launch it.
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+  EXPECT_NE(row.find("col1"), row.end());
+  std::vector<std::vector<std::string>> expected_result = {
+    {"a", "b", "c", "d"},
+  };
+
+  uint64_t i = 0;
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+  while (row.size() != 0) {
+    for (int j = 0; j < column_names.size(); j++) {
+      auto text = row[column_names[j]];
+      std::string_view sv;
+      text->GetItemAt(&sv, {0});
+      std::string ss(sv);
+      EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str());
+    }
+    iter->GetNextRow(&row);
+    i++;
+  }
+
+  // Expect 3 samples
+  EXPECT_EQ(i, 1);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetException) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetException.";
+  // Create a CSV Dataset
+  std::string file = datasets_root_path_ + "/testCSV/1.csv";
+  std::string invalid_csv_file = "./NotExistFile";
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+
+  // Test empty file list
+  std::shared_ptr<Dataset> ds0 = CSV({});
+  EXPECT_EQ(ds0, nullptr);
+
+  // Test invalid file
+  std::shared_ptr<Dataset> ds1 = CSV({invalid_csv_file});
+  EXPECT_EQ(ds1, nullptr);
+
+  // Test invalid num_samples < -1
+  std::shared_ptr<Dataset> ds2 = CSV({file}, ',', {}, column_names, -2);
+  EXPECT_EQ(ds2, nullptr);
+
+  // Test invalid num_shards < 1
+  std::shared_ptr<Dataset> ds3 = CSV({file}, ',', {}, column_names, -1, ShuffleMode::kFalse, 0);
+  EXPECT_EQ(ds3, nullptr);
+
+  // Test invalid shard_id >= num_shards
+  std::shared_ptr<Dataset> ds4 = CSV({file}, ',', {}, column_names, -1, ShuffleMode::kFalse, 2, 2);
+  EXPECT_EQ(ds4, nullptr);
+
+  // Test invalid field_delim
+  std::shared_ptr<Dataset> ds5 = CSV({file}, '"', {}, column_names);
+  EXPECT_EQ(ds5, nullptr);
+}
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetShuffleFiles) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetShuffleFiles.";
+
+  // Set configuration
+  uint32_t original_seed = GlobalContext::config_manager()->seed();
+  uint32_t original_num_parallel_workers = GlobalContext::config_manager()->num_parallel_workers();
+  MS_LOG(DEBUG) << "ORIGINAL seed: " << original_seed << ", num_parallel_workers: " << original_num_parallel_workers;
+  GlobalContext::config_manager()->set_seed(130);
+  GlobalContext::config_manager()->set_num_parallel_workers(4);
+
+  // Create a CSVDataset, with single CSV file
+  std::string file1 = datasets_root_path_ + "/testCSV/1.csv";
+  std::string file2 = datasets_root_path_ + "/testCSV/append.csv";
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+  std::shared_ptr<Dataset> ds = CSV({file1, file2}, ',', {}, column_names, -1, ShuffleMode::kFiles);
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  // This will trigger the creation of the Execution Tree and launch it.
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+  EXPECT_NE(row.find("col1"), row.end());
+  std::vector<std::vector<std::string>> expected_result = {
+    {"13", "14", "15", "16"},
+    {"1", "2", "3", "4"},
+    {"17", "18", "19", "20"},
+    {"5", "6", "7", "8"},
+    {"21", "22", "23", "24"},
+    {"9", "10", "11", "12"},
+  };
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    for (int j = 0; j < column_names.size(); j++) {
+      auto text = row[column_names[j]];
+      std::string_view sv;
+      text->GetItemAt(&sv, {0});
+      std::string ss(sv);
+      EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str());
+    }
+    iter->GetNextRow(&row);
+    i++;
+  }
+
+  // Expect 6 samples
+  EXPECT_EQ(i, 6);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+
+  // Restore configuration
+  GlobalContext::config_manager()->set_seed(original_seed);
+  GlobalContext::config_manager()->set_num_parallel_workers(original_num_parallel_workers);
+}
+
+TEST_F(MindDataTestPipeline, TestCSVDatasetShuffleGlobal) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestCSVDatasetShuffleGlobal.";
+  // Test CSV Dataset with GLOBLE shuffle
+
+  // Set configuration
+  uint32_t original_seed = GlobalContext::config_manager()->seed();
+  uint32_t original_num_parallel_workers = GlobalContext::config_manager()->num_parallel_workers();
+  MS_LOG(DEBUG) << "ORIGINAL seed: " << original_seed << ", num_parallel_workers: " << original_num_parallel_workers;
+  GlobalContext::config_manager()->set_seed(135);
+  GlobalContext::config_manager()->set_num_parallel_workers(4);
+
+  // Create a CSVFile Dataset, with single CSV file
+  std::string train_file = datasets_root_path_ + "/testCSV/1.csv";
+  std::vector<std::string> column_names = {"col1", "col2", "col3", "col4"};
+  std::shared_ptr<Dataset> ds = CSV({train_file}, ',', {}, column_names, -1, ShuffleMode::kGlobal);
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  // This will trigger the creation of the Execution Tree and launch it.
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+  EXPECT_NE(row.find("col1"), row.end());
+  std::vector<std::vector<std::string>> expected_result = {
+    {"5", "6", "7", "8"},
+    {"9", "10", "11", "12"},
+    {"1", "2", "3", "4"}
+  };
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    for (int j = 0; j < column_names.size(); j++) {
+      auto text = row[column_names[j]];
+      std::string_view sv;
+      text->GetItemAt(&sv, {0});
+      std::string ss(sv);
+      EXPECT_STREQ(ss.c_str(), expected_result[i][j].c_str());
+    }
+    iter->GetNextRow(&row);
+    i++;
+  }
+
+  // Expect 3 samples
+  EXPECT_EQ(i, 3);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+
+  // Restore configuration
+  GlobalContext::config_manager()->set_seed(original_seed);
+  GlobalContext::config_manager()->set_num_parallel_workers(original_num_parallel_workers);
+}

tests/ut/data/dataset/testCSV/append.csv

+13,14,15,16
+17,18,19,20
+21,22,23,24

tests/ut/data/dataset/testCSV/default.csv

+,2,3.0,
+a,4,5,b
\ No newline at end of file