!17486 [assistant][ops] Add new dataset operator Flickr.

Merge pull request !17486 from Rainfor/wangkc

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

@@ -94,6 +94,7 @@
 #include "minddata/dataset/engine/ir/datasetops/source/clue_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/coco_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/csv_node.h"
+#include "minddata/dataset/engine/ir/datasetops/source/flickr_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/image_folder_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/random_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/text_file_node.h"
@@ -927,6 +928,32 @@ CSVDataset::CSVDataset(const std::vector<std::vector<char>> &dataset_files, char
   ir_node_ = std::static_pointer_cast<DatasetNode>(ds);
 }
 
+FlickrDataset::FlickrDataset(const std::vector<char> &dataset_dir, const std::vector<char> &annotation_file,
+                             bool decode, const std::shared_ptr<Sampler> &sampler,
+                             const std::shared_ptr<DatasetCache> &cache) {
+  auto sampler_obj = sampler ? sampler->Parse() : nullptr;
+  auto ds =
+    std::make_shared<FlickrNode>(CharToString(dataset_dir), CharToString(annotation_file), decode, sampler_obj, cache);
+  ir_node_ = std::static_pointer_cast<DatasetNode>(ds);
+}
+
+FlickrDataset::FlickrDataset(const std::vector<char> &dataset_dir, const std::vector<char> &annotation_file,
+                             bool decode, const Sampler *sampler, const std::shared_ptr<DatasetCache> &cache) {
+  auto sampler_obj = sampler ? sampler->Parse() : nullptr;
+  auto ds =
+    std::make_shared<FlickrNode>(CharToString(dataset_dir), CharToString(annotation_file), decode, sampler_obj, cache);
+  ir_node_ = std::static_pointer_cast<DatasetNode>(ds);
+}
+
+FlickrDataset::FlickrDataset(const std::vector<char> &dataset_dir, const std::vector<char> &annotation_file,
+                             bool decode, const std::reference_wrapper<Sampler> sampler,
+                             const std::shared_ptr<DatasetCache> &cache) {
+  auto sampler_obj = sampler.get().Parse();
+  auto ds =
+    std::make_shared<FlickrNode>(CharToString(dataset_dir), CharToString(annotation_file), decode, sampler_obj, cache);
+  ir_node_ = std::static_pointer_cast<DatasetNode>(ds);
+}
+
 ImageFolderDataset::ImageFolderDataset(const std::vector<char> &dataset_dir, bool decode,
                                        const std::shared_ptr<Sampler> &sampler,
                                        const std::set<std::vector<char>> &extensions,

mindspore/ccsrc/minddata/dataset/api/python/bindings/dataset/engine/ir/datasetops/source/bindings.cc

@@ -31,6 +31,7 @@
 #include "minddata/dataset/engine/ir/datasetops/source/clue_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/coco_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/csv_node.h"
+#include "minddata/dataset/engine/ir/datasetops/source/flickr_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/generator_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/image_folder_node.h"
 #include "minddata/dataset/engine/ir/datasetops/source/mnist_node.h"
@@ -122,6 +123,17 @@ PYBIND_REGISTER(CSVNode, 2, ([](const py::module *m) {
                     }));
                 }));
 
+PYBIND_REGISTER(
+  FlickrNode, 2, ([](const py::module *m) {
+    (void)py::class_<FlickrNode, DatasetNode, std::shared_ptr<FlickrNode>>(*m, "FlickrNode", "to create a FlickrNode")
+      .def(py::init([](std::string dataset_dir, std::string annotation_file, bool decode, py::handle sampler) {
+        auto flickr =
+          std::make_shared<FlickrNode>(dataset_dir, annotation_file, decode, toSamplerObj(sampler), nullptr);
+        THROW_IF_ERROR(flickr->ValidateParams());
+        return flickr;
+      }));
+  }));
+
 PYBIND_REGISTER(GeneratorNode, 2, ([](const py::module *m) {
                   (void)py::class_<GeneratorNode, DatasetNode, std::shared_ptr<GeneratorNode>>(
                     *m, "GeneratorNode", "to create a GeneratorNode")

mindspore/ccsrc/minddata/dataset/engine/datasetops/source/CMakeLists.txt

@@ -16,6 +16,7 @@ set(DATASET_ENGINE_DATASETOPS_SOURCE_SRC_FILES
     album_op.cc
     mappable_leaf_op.cc
     nonmappable_leaf_op.cc
+    flickr_op.cc
     )
 
 set(DATASET_ENGINE_DATASETOPS_SOURCE_SRC_FILES

mindspore/ccsrc/minddata/dataset/engine/datasetops/source/flickr_op.cc

@@ -0,0 +1,235 @@
+/**
+ * Copyright 2021 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 "minddata/dataset/engine/datasetops/source/flickr_op.h"
+
+#include <algorithm>
+#include <fstream>
+#include <iomanip>
+#include <set>
+#include <utility>
+
+#include "minddata/dataset/core/config_manager.h"
+#include "minddata/dataset/core/tensor_shape.h"
+#include "minddata/dataset/engine/datasetops/source/sampler/sequential_sampler.h"
+#include "minddata/dataset/engine/db_connector.h"
+#include "minddata/dataset/engine/execution_tree.h"
+#include "utils/ms_utils.h"
+
+namespace mindspore {
+namespace dataset {
+FlickrOp::FlickrOp(int32_t num_workers, const std::string &dataset_dir, const std::string &file_path, bool decode,
+                   int32_t queue_size, std::unique_ptr<DataSchema> data_schema, std::shared_ptr<SamplerRT> sampler)
+    : MappableLeafOp(num_workers, queue_size, std::move(sampler)),
+      dataset_dir_(dataset_dir),
+      file_path_(file_path),
+      decode_(decode),
+      data_schema_(std::move(data_schema)) {
+  io_block_queues_.Init(num_workers_, queue_size);
+}
+
+Status FlickrOp::LaunchThreadsAndInitOp() {
+  if (tree_ == nullptr) {
+    RETURN_STATUS_UNEXPECTED("Pipeline init failed, Execution tree not set.");
+  }
+
+  RETURN_IF_NOT_OK(io_block_queues_.Register(tree_->AllTasks()));
+  RETURN_IF_NOT_OK(wait_for_workers_post_.Register(tree_->AllTasks()));
+  RETURN_IF_NOT_OK(
+    tree_->LaunchWorkers(num_workers_, std::bind(&FlickrOp::WorkerEntry, this, std::placeholders::_1), "", id()));
+  TaskManager::FindMe()->Post();
+  // The order of the following 2 functions must not be changed!
+  RETURN_IF_NOT_OK(ParseFlickrData());   // Parse Flickr data and get num rows, blocking
+  RETURN_IF_NOT_OK(CountDatasetInfo());  // Count the total rows
+  RETURN_IF_NOT_OK(InitSampler());       // Pass numRows to Sampler
+  return Status::OK();
+}
+
+// Load 1 TensorRow (image, annotations) using 1 ImageLabelPair. 1 function call produces 1 TensorTow
+Status FlickrOp::LoadTensorRow(row_id_type row_id, TensorRow *trow) {
+  std::pair<std::string, std::vector<std::string>> data = image_annotation_pairs_[static_cast<size_t>(row_id)];
+  std::shared_ptr<Tensor> image;
+  std::shared_ptr<Tensor> annotations;
+  RETURN_IF_NOT_OK(Tensor::CreateFromFile(data.first, &image));
+  RETURN_IF_NOT_OK(Tensor::CreateFromVector(data.second, &annotations));
+
+  if (decode_ == true) {
+    Status rc = Decode(image, &image);
+    if (rc.IsError()) {
+      std::string err = "Invalid data, failed to decode image: " + data.first;
+      RETURN_STATUS_UNEXPECTED(err);
+    }
+  }
+
+  (*trow) = TensorRow(row_id, {std::move(image), std::move(annotations)});
+  trow->setPath({data.first, file_path_});
+  return Status::OK();
+}
+
+void FlickrOp::Print(std::ostream &out, bool show_all) const {
+  if (!show_all) {
+    // Call the super class for displaying any common 1-liner info
+    ParallelOp::Print(out, show_all);
+    // Then show any custom derived-internal 1-liner info for this op
+    out << "\n";
+  } else {
+    // Call the super class for displaying any common detailed info
+    ParallelOp::Print(out, show_all);
+    // Then show any custom derived-internal stuff
+    out << "\nNumber of rows:" << num_rows_ << "\nFlickr DatasetDir: " << dataset_dir_
+        << "\nAnnotationFile: " << file_path_ << "\nDecode: " << (decode_ ? "yes" : "no") << "\n\n";
+  }
+}
+
+Status FlickrOp::ParseFlickrData() {
+  std::ifstream file_handle(file_path_);
+  if (!file_handle.is_open()) {
+    RETURN_STATUS_UNEXPECTED("Invalid file, failed to open Flickr annotation file: " + file_path_);
+  }
+
+  std::string line;
+  int32_t flag_idx;
+  std::string sub_str_flag = "\t";
+  std::string image_file_path;
+  std::string image_name;
+  std::map<std::string, std::vector<std::string>> image_annotation_map_;
+  Path dataset_dir(dataset_dir_);
+  while (getline(file_handle, line)) {
+    try {
+      if (line.empty()) {
+        continue;
+      }
+
+      flag_idx = line.find_first_of(sub_str_flag);
+      image_name = line.substr(0, flag_idx - 2);  // -2 because "#[0-4]\t"
+      if (image_name.empty()) {
+        file_handle.close();
+        RETURN_STATUS_UNEXPECTED("Invalid data, image_name is not found in Flickr annotation file: " + file_path_ +
+                                 "; line: " + line);
+      }
+
+      image_file_path = (dataset_dir / image_name).toString();
+      std::string annotation = line.substr(flag_idx + 1);
+      if (annotation.empty()) {
+        file_handle.close();
+        RETURN_STATUS_UNEXPECTED("Invalid data, annotation is not found in Flickr annotation file: " + file_path_ +
+                                 "; line: " + line);
+      }
+
+      bool valid = false;
+      RETURN_IF_NOT_OK(CheckImageType(image_file_path, &valid));
+      if (!valid) {
+        continue;
+      }
+
+      image_annotation_map_[image_file_path].emplace_back(annotation);
+    } catch (const std::exception &err) {
+      file_handle.close();
+      RETURN_STATUS_UNEXPECTED("Invalid file, failed to open Flickr annotation file: " + file_path_);
+    }
+  }
+
+  for (auto item : image_annotation_map_) {
+    image_annotation_pairs_.emplace_back(std::make_pair(item.first, item.second));
+  }
+
+  file_handle.close();
+  return Status::OK();
+}
+
+// Only support JPEG/PNG/GIF/BMP
+// Optimization: Could take in a tensor
+// This function does not return status because we want to just skip bad input, not crash
+Status FlickrOp::CheckImageType(const std::string &file_name, bool *valid) {
+  std::ifstream file_handle;
+  constexpr int read_num = 3;
+  *valid = false;
+  file_handle.open(file_name, std::ios::binary | std::ios::in);
+  if (!file_handle.is_open()) {
+    RETURN_STATUS_UNEXPECTED("Invalid file, failed to open image file: " + file_name);
+  }
+  unsigned char file_type[read_num];
+  (void)file_handle.read(reinterpret_cast<char *>(file_type), read_num);
+
+  if (file_handle.fail()) {
+    file_handle.close();
+    RETURN_STATUS_UNEXPECTED("Invalid data, failed to read image file: " + file_name);
+  }
+  file_handle.close();
+  if (file_type[0] == 0xff && file_type[1] == 0xd8 && file_type[2] == 0xff) {
+    // Normal JPEGs start with \xff\xd8\xff\xe0
+    // JPEG with EXIF stats with \xff\xd8\xff\xe1
+    // Use \xff\xd8\xff to cover both.
+    *valid = true;
+  } else if (file_type[0] == 0x89 && file_type[1] == 0x50 && file_type[2] == 0x4e) {
+    // It's a PNG
+    *valid = true;
+  } else if (file_type[0] == 0x47 && file_type[1] == 0x49 && file_type[2] == 0x46) {
+    // It's a GIF
+    *valid = true;
+  } else if (file_type[0] == 0x42 && file_type[1] == 0x4d) {
+    // It's a BMP
+    *valid = true;
+  }
+  return Status::OK();
+}
+
+Status FlickrOp::CountDatasetInfo() {
+  num_rows_ = static_cast<int64_t>(image_annotation_pairs_.size());
+  if (num_rows_ == 0) {
+    RETURN_STATUS_UNEXPECTED(
+      "Invalid data, no valid data matching the dataset API FlickrDataset. Please check file path or dataset API.");
+  }
+  return Status::OK();
+}
+
+Status FlickrOp::CountTotalRows(const std::string &dir, const std::string &file, int64_t *count) {
+  // the logic of counting the number of samples is copied from ParseFlickrData()
+  *count = 0;
+  const int64_t num_samples = 0;
+  const int64_t start_index = 0;
+  auto new_sampler = std::make_shared<SequentialSamplerRT>(start_index, num_samples);
+
+  // build a new unique schema object
+  auto new_schema = std::make_unique<DataSchema>();
+  TensorShape scalar = TensorShape::CreateScalar();
+  RETURN_IF_NOT_OK(
+    new_schema->AddColumn(ColDescriptor("image", DataType(DataType::DE_UINT8), TensorImpl::kFlexible, 1)));
+  RETURN_IF_NOT_OK(new_schema->AddColumn(
+    ColDescriptor("annotation", DataType(DataType::DE_STRING), TensorImpl::kFlexible, 0, &scalar)));
+  std::shared_ptr<ConfigManager> cfg = GlobalContext::config_manager();
+  int32_t num_workers = cfg->num_parallel_workers();
+  int32_t op_connect_size = cfg->op_connector_size();
+  std::shared_ptr<FlickrOp> op = std::make_shared<FlickrOp>(num_workers, dir, file, false, op_connect_size,
+                                                            std::move(new_schema), std::move(new_sampler));
+
+  RETURN_IF_NOT_OK(op->ParseFlickrData());
+  *count = static_cast<int64_t>(op->image_annotation_pairs_.size());
+  return Status::OK();
+}
+
+Status FlickrOp::ComputeColMap() {
+  // Set the column name map (base class field)
+  if (column_name_id_map_.empty()) {
+    for (int32_t i = 0; i < data_schema_->NumColumns(); ++i) {
+      column_name_id_map_[data_schema_->column(i).name()] = i;
+    }
+  } else {
+    MS_LOG(WARNING) << "Column name map is already set!";
+  }
+  return Status::OK();
+}
+}  // namespace dataset
+}  // namespace mindspore

mindspore/ccsrc/minddata/dataset/engine/datasetops/source/flickr_op.h

@@ -0,0 +1,107 @@
+/**
+ * Copyright 2021 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.
+ */
+
+#ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_DATASETOPS_SOURCE_FLICKR_OP_H_
+#define MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_DATASETOPS_SOURCE_FLICKR_OP_H_
+
+#include <map>
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "minddata/dataset/core/tensor.h"
+#include "minddata/dataset/engine/data_schema.h"
+#include "minddata/dataset/engine/datasetops/parallel_op.h"
+#include "minddata/dataset/engine/datasetops/source/mappable_leaf_op.h"
+#include "minddata/dataset/engine/datasetops/source/sampler/sampler.h"
+#include "minddata/dataset/util/path.h"
+#include "minddata/dataset/util/queue.h"
+#include "minddata/dataset/util/services.h"
+#include "minddata/dataset/util/status.h"
+#include "minddata/dataset/util/wait_post.h"
+
+namespace mindspore {
+namespace dataset {
+class FlickrOp : public MappableLeafOp {
+ public:
+  /// \brief Constructor.
+  /// \param[in] int32_t num_workers - Num of workers reading images in parallel
+  /// \param[in] std::string dataset_dir - dir directory of Flickr dataset
+  /// \param[in] std::string annotation_file - dir directory of annotation file
+  /// \param[in] int32_t queue_size - connector queue size
+  /// \param[in] std::unique_ptr<Sampler> sampler - sampler tells ImageFolderOp what to read
+  FlickrOp(int32_t num_workers, const std::string &dataset_dir, const std::string &annotation_file, bool decode,
+           int32_t queue_size, std::unique_ptr<DataSchema> data_schema, std::shared_ptr<SamplerRT> sampler);
+
+  /// \brief Destructor.
+  ~FlickrOp() = default;
+
+  /// \brief A print method typically used for debugging
+  /// \param[out] out
+  /// \param[in] show_all
+  void Print(std::ostream &out, bool show_all) const override;
+
+  /// \brief Function to count the number of samples in the Flickr dataset
+  /// \param[in] dir - path to the Flickr directory
+  /// \param[in] file - path to the annotation file
+  /// \param[out] count - output arg that will hold the actual dataset size
+  /// \return Status - The status code returned
+  static Status CountTotalRows(const std::string &dir, const std::string &file, int64_t *count);
+
+  /// \brief Op name getter
+  /// \return Name of the current Op
+  std::string Name() const override { return "FlickrOp"; }
+
+ private:
+  /// \brief Load a tensor row according to a pair
+  /// \param[in] uint64_t index - index need to load
+  /// \param[out] TensorRow row - image & annotation read into this tensor row
+  /// \return Status - The status code returned
+  Status LoadTensorRow(row_id_type index, TensorRow *trow) override;
+
+  /// \brief Called first when function is called
+  /// \return Status - The status code returned
+  Status LaunchThreadsAndInitOp() override;
+
+  /// \brief Parse Flickr data
+  /// \return Status - The status code returned
+  Status ParseFlickrData();
+
+  /// \brief Check if image ia valid.Only support JPEG/PNG/GIF/BMP
+  /// \param[in] std::string file_name - image file name need to be checked
+  /// \param[out] bool valid - whether the image type is valid
+  /// \return Status - The status code returned
+  Status CheckImageType(const std::string &file_name, bool *valid);
+
+  /// \brief Count annotation index,num rows and num samples
+  /// \return Status - The status code returned
+  Status CountDatasetInfo();
+
+  /// \brief Private function for computing the assignment of the column name map.
+  /// \return Status - The status code returned
+  Status ComputeColMap() override;
+
+  std::string dataset_dir_;
+  std::string file_path_;
+  bool decode_;
+  std::unique_ptr<DataSchema> data_schema_;
+
+  std::vector<std::pair<std::string, std::vector<std::string>>> image_annotation_pairs_;
+};
+}  // namespace dataset
+}  // namespace mindspore
+#endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_DATASETOPS_SOURCE_FLICKR_OP_H_

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/dataset_node.h

@@ -81,6 +81,7 @@ constexpr char kCifar10Node[] = "Cifar10Dataset";
 constexpr char kCLUENode[] = "CLUEDataset";
 constexpr char kCocoNode[] = "CocoDataset";
 constexpr char kCSVNode[] = "CSVDataset";
+constexpr char kFlickrNode[] = "FlickrDataset";
 constexpr char kGeneratorNode[] = "GeneratorDataset";
 constexpr char kImageFolderNode[] = "ImageFolderDataset";
 constexpr char kManifestNode[] = "ManifestDataset";

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/CMakeLists.txt

@@ -10,6 +10,7 @@ set(DATASET_ENGINE_IR_DATASETOPS_SOURCE_SRC_FILES
         clue_node.cc
         coco_node.cc
         csv_node.cc
+        flickr_node.cc
         image_folder_node.cc
         manifest_node.cc
         minddata_node.cc

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/flickr_node.cc

@@ -0,0 +1,152 @@
+/**
+ * Copyright 2021 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 "minddata/dataset/engine/ir/datasetops/source/flickr_node.h"
+
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "minddata/dataset/engine/datasetops/source/flickr_op.h"
+#include "minddata/dataset/util/status.h"
+
+namespace mindspore {
+namespace dataset {
+
+// Constructor for FlickrNode
+FlickrNode::FlickrNode(const std::string &dataset_dir, const std::string &annotation_file, bool decode,
+                       std::shared_ptr<SamplerObj> sampler, std::shared_ptr<DatasetCache> cache)
+    : MappableSourceNode(std::move(cache)),
+      dataset_dir_(dataset_dir),
+      annotation_file_(annotation_file),
+      decode_(decode),
+      sampler_(sampler) {}
+
+std::shared_ptr<DatasetNode> FlickrNode::Copy() {
+  std::shared_ptr<SamplerObj> sampler = (sampler_ == nullptr) ? nullptr : sampler_->SamplerCopy();
+  auto node = std::make_shared<FlickrNode>(dataset_dir_, annotation_file_, decode_, sampler, cache_);
+  return node;
+}
+
+void FlickrNode::Print(std::ostream &out) const {
+  out << Name() + "(dataset dir:" + dataset_dir_;
+  out << ", annotation file:" + annotation_file_;
+  if (sampler_ != nullptr) {
+    out << ", sampler";
+  }
+  if (cache_ != nullptr) {
+    out << ", cache";
+  }
+  out << ")";
+}
+
+Status FlickrNode::ValidateParams() {
+  RETURN_IF_NOT_OK(DatasetNode::ValidateParams());
+  RETURN_IF_NOT_OK(ValidateDatasetDirParam("FlickrNode", dataset_dir_));
+
+  if (annotation_file_.empty()) {
+    std::string err_msg = "FlickrNode: annotation_file is not specified.";
+    MS_LOG(ERROR) << err_msg;
+    RETURN_STATUS_SYNTAX_ERROR(err_msg);
+  }
+
+  std::vector<char> forbidden_symbols = {':', '*', '?', '"', '<', '>', '|', '`', '&', '\'', ';'};
+  for (char c : annotation_file_) {
+    auto p = std::find(forbidden_symbols.begin(), forbidden_symbols.end(), c);
+    if (p != forbidden_symbols.end()) {
+      std::string err_msg = "FlickrNode: annotation_file: [" + annotation_file_ + "] should not contain :*?\"<>|`&;\'.";
+      MS_LOG(ERROR) << err_msg;
+      RETURN_STATUS_SYNTAX_ERROR(err_msg);
+    }
+  }
+  Path annotation_file(annotation_file_);
+  if (!annotation_file.Exists()) {
+    std::string err_msg = "FlickrNode: annotation_file: [" + annotation_file_ + "] is invalid or not exist.";
+    MS_LOG(ERROR) << err_msg;
+    RETURN_STATUS_SYNTAX_ERROR(err_msg);
+  }
+
+  RETURN_IF_NOT_OK(ValidateDatasetSampler("FlickrNode", sampler_));
+  return Status::OK();
+}
+
+// Function to build FlickrOp for Flickr
+Status FlickrNode::Build(std::vector<std::shared_ptr<DatasetOp>> *const node_ops) {
+  // Do internal Schema generation.
+  auto schema = std::make_unique<DataSchema>();
+  RETURN_IF_NOT_OK(schema->AddColumn(ColDescriptor("image", DataType(DataType::DE_UINT8), TensorImpl::kCv, 1)));
+  TensorShape scalar = TensorShape::CreateScalar();
+  RETURN_IF_NOT_OK(
+    schema->AddColumn(ColDescriptor("annotation", DataType(DataType::DE_STRING), TensorImpl::kFlexible, 0, &scalar)));
+  std::shared_ptr<SamplerRT> sampler_rt = nullptr;
+  RETURN_IF_NOT_OK(sampler_->SamplerBuild(&sampler_rt));
+
+  auto flickr_op = std::make_shared<FlickrOp>(num_workers_, dataset_dir_, annotation_file_, decode_,
+                                              connector_que_size_, std::move(schema), std::move(sampler_rt));
+  flickr_op->set_total_repeats(GetTotalRepeats());
+  flickr_op->set_num_repeats_per_epoch(GetNumRepeatsPerEpoch());
+  node_ops->push_back(flickr_op);
+  return Status::OK();
+}
+
+// Get the shard id of node
+Status FlickrNode::GetShardId(int32_t *shard_id) {
+  *shard_id = sampler_->ShardId();
+  return Status::OK();
+}
+
+// Get Dataset size
+Status FlickrNode::GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &size_getter, bool estimate,
+                                  int64_t *dataset_size) {
+  if (dataset_size_ > 0) {
+    *dataset_size = dataset_size_;
+    return Status::OK();
+  }
+
+  int64_t num_rows, sample_size;
+  RETURN_IF_NOT_OK(FlickrOp::CountTotalRows(dataset_dir_, annotation_file_, &num_rows));
+  std::shared_ptr<SamplerRT> sampler_rt = nullptr;
+  RETURN_IF_NOT_OK(sampler_->SamplerBuild(&sampler_rt));
+  sample_size = sampler_rt->CalculateNumSamples(num_rows);
+
+  if (sample_size == -1) {
+    RETURN_IF_NOT_OK(size_getter->DryRun(shared_from_this(), &sample_size));
+  }
+
+  *dataset_size = sample_size;
+  dataset_size_ = *dataset_size;
+  return Status::OK();
+}
+
+Status FlickrNode::to_json(nlohmann::json *out_json) {
+  nlohmann::json args, sampler_args;
+  RETURN_IF_NOT_OK(sampler_->to_json(&sampler_args));
+  args["sampler"] = sampler_args;
+  args["num_parallel_workers"] = num_workers_;
+  args["dataset_dir"] = dataset_dir_;
+  args["annotation_file"] = annotation_file_;
+  args["decode"] = decode_;
+  if (cache_ != nullptr) {
+    nlohmann::json cache_args;
+    RETURN_IF_NOT_OK(cache_->to_json(&cache_args));
+    args["cache"] = cache_args;
+  }
+  *out_json = args;
+  return Status::OK();
+}
+}  // namespace dataset
+}  // namespace mindspore

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/flickr_node.h

@@ -0,0 +1,102 @@
+/**
+ * Copyright 2021 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.
+ */
+
+#ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_FLICKR_NODE_H_
+#define MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_FLICKR_NODE_H_
+
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "minddata/dataset/engine/ir/datasetops/dataset_node.h"
+
+namespace mindspore {
+namespace dataset {
+
+class FlickrNode : public MappableSourceNode {
+ public:
+  /// \brief Constructor
+  FlickrNode(const std::string &dataset_dir, const std::string &annotation_file, bool decode,
+             std::shared_ptr<SamplerObj> sampler, std::shared_ptr<DatasetCache> cache);
+
+  /// \brief Destructor
+  ~FlickrNode() = default;
+
+  /// \brief Node name getter
+  /// \return Name of the current node
+  std::string Name() const override { return kFlickrNode; }
+
+  /// \brief Print the description
+  /// \param[out] out - The output stream to write output to
+  void Print(std::ostream &out) const override;
+
+  /// \brief Copy the node to a new object
+  /// \return A shared pointer to the new copy
+  std::shared_ptr<DatasetNode> Copy() override;
+
+  /// \brief a base class override function to create the required runtime dataset op objects for this class
+  /// \param[out] node_ops - A vector containing shared pointer to the Dataset Ops that this object will create
+  /// \return Status Status::OK() if build successfully
+  Status Build(std::vector<std::shared_ptr<DatasetOp>> *const node_ops) override;
+
+  /// \brief Parameters validation
+  /// \return Status Status::OK() if all the parameters are valid
+  Status ValidateParams() override;
+
+  /// \brief Get the shard id of node
+  /// \return Status Status::OK() if get shard id successfully
+  Status GetShardId(int32_t *shard_id) override;
+
+  /// \brief Base-class override for GetDatasetSize
+  /// \param[in] size_getter Shared pointer to DatasetSizeGetter
+  /// \param[in] estimate This is only supported by some of the ops and it's used to speed up the process of getting
+  ///     dataset size at the expense of accuracy.
+  /// \param[out] dataset_size the size of the dataset
+  /// \return Status of the function
+  Status GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &size_getter, bool estimate,
+                        int64_t *dataset_size) override;
+
+  /// \brief Getter functions
+  const std::string &DatasetDir() const { return dataset_dir_; }
+
+  /// \brief Getter functions
+  const std::string &AnnotationFile() const { return annotation_file_; }
+
+  /// \brief Getter functions
+  bool Decode() const { return decode_; }
+
+  /// \brief Get the arguments of node
+  /// \param[out] out_json JSON string of all attributes
+  /// \return Status of the function
+  Status to_json(nlohmann::json *out_json) override;
+
+  /// \brief Sampler getter
+  /// \return SamplerObj of the current node
+  std::shared_ptr<SamplerObj> Sampler() override { return sampler_; }
+
+  /// \brief Sampler setter
+  void SetSampler(std::shared_ptr<SamplerObj> sampler) override { sampler_ = sampler; }
+
+ private:
+  std::string dataset_dir_;
+  std::string annotation_file_;
+  bool decode_;
+  std::shared_ptr<SamplerObj> sampler_;
+};
+
+}  // namespace dataset
+}  // namespace mindspore
+#endif  // MINDSPORE_CCSRC_MINDDATA_DATASET_ENGINE_IR_DATASETOPS_SOURCE_FLICKR_NODE_H_

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

@@ -1091,6 +1091,64 @@ inline std::shared_ptr<CSVDataset> CSV(const std::vector<std::string> &dataset_f
                                       cache);
 }
 
+class FlickrDataset : public Dataset {
+ public:
+  explicit FlickrDataset(const std::vector<char> &dataset_dir, const std::vector<char> &annotation_file, bool decode,
+                         const std::shared_ptr<Sampler> &sampler, const std::shared_ptr<DatasetCache> &cache);
+  explicit FlickrDataset(const std::vector<char> &dataset_dir, const std::vector<char> &annotation_file, bool decode,
+                         const Sampler *sampler, const std::shared_ptr<DatasetCache> &cache);
+  explicit FlickrDataset(const std::vector<char> &dataset_dir, const std::vector<char> &annotation_file, bool decode,
+                         const std::reference_wrapper<Sampler> sampler, const std::shared_ptr<DatasetCache> &cache);
+  ~FlickrDataset() = default;
+};
+
+/// \brief Function to create a FlickrDataset
+/// \notes The generated dataset has two columns ["image", "annotation"]
+/// \param[in] dataset_dir The dataset dir to be read
+/// \param[in] annotation_file The annotation file to be read
+/// \param[in] decode Decode the images after reading (default=false).
+/// \param[in] sampler Shared pointer to a sampler object used to choose samples from the dataset. If sampler is not
+///     given, a `RandomSampler` will be used to randomly iterate the entire dataset (default = RandomSampler()).
+/// \param[in] cache Tensor cache to use. (default=nullptr which means no cache is used).
+/// \return Shared pointer to the current FlickrDataset
+inline std::shared_ptr<FlickrDataset> Flickr(
+  const std::string &dataset_dir, const std::string &annotation_file, bool decode = false,
+  const std::shared_ptr<Sampler> &sampler = std::make_shared<RandomSampler>(),
+  const std::shared_ptr<DatasetCache> &cache = nullptr) {
+  return std::make_shared<FlickrDataset>(StringToChar(dataset_dir), StringToChar(annotation_file), decode, sampler,
+                                         cache);
+}
+
+/// \brief Function to create a FlickrDataset
+/// \notes The generated dataset has two columns ["image", "annotation"]
+/// \param[in] dataset_dir The dataset dir to be read
+/// \param[in] annotation_file The annotation file to be read
+/// \param[in] decode Decode the images after reading.
+/// \param[in] sampler Raw pointer to a sampler object used to choose samples from the dataset.
+/// \param[in] cache Tensor cache to use. (default=nullptr which means no cache is used).
+/// \return Shared pointer to the current FlickrDataset
+inline std::shared_ptr<FlickrDataset> Flickr(const std::string &dataset_dir, const std::string &annotation_file,
+                                             bool decode, const Sampler *sampler,
+                                             const std::shared_ptr<DatasetCache> &cache = nullptr) {
+  return std::make_shared<FlickrDataset>(StringToChar(dataset_dir), StringToChar(annotation_file), decode, sampler,
+                                         cache);
+}
+
+/// \brief Function to create a FlickrDataset
+/// \notes The generated dataset has two columns ["image", "annotation"]
+/// \param[in] dataset_dir The dataset dir to be read
+/// \param[in] annotation_file The annotation file to be read
+/// \param[in] decode Decode the images after reading.
+/// \param[in] sampler Sampler object used to choose samples from the dataset.
+/// \param[in] cache Tensor cache to use. (default=nullptr which means no cache is used).
+/// \return Shared pointer to the current FlickrDataset
+inline std::shared_ptr<FlickrDataset> Flickr(const std::string &dataset_dir, const std::string &annotation_file,
+                                             bool decode, const std::reference_wrapper<Sampler> sampler,
+                                             const std::shared_ptr<DatasetCache> &cache = nullptr) {
+  return std::make_shared<FlickrDataset>(StringToChar(dataset_dir), StringToChar(annotation_file), decode, sampler,
+                                         cache);
+}
+
 class ImageFolderDataset : public Dataset {
  public:
   explicit ImageFolderDataset(const std::vector<char> &dataset_dir, bool decode,

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

@@ -37,6 +37,7 @@ class Sampler : std::enable_shared_from_this<Sampler> {
   friend class CLUEDataset;
   friend class CocoDataset;
   friend class CSVDataset;
+  friend class FlickrDataset;
   friend class ImageFolderDataset;
   friend class ManifestDataset;
   friend class MindDataDataset;

mindspore/dataset/engine/datasets.py

@@ -63,7 +63,8 @@ from .validators import check_batch, check_shuffle, check_map, check_filter, che
     check_celebadataset, check_minddataset, check_generatordataset, check_sync_wait, check_zip_dataset, \
     check_add_column, check_textfiledataset, check_concat, check_random_dataset, check_split, \
     check_bucket_batch_by_length, check_cluedataset, check_save, check_csvdataset, check_paddeddataset, \
-    check_tuple_iterator, check_dict_iterator, check_schema, check_to_device_send, check_sb_dataset
+    check_tuple_iterator, check_dict_iterator, check_schema, check_to_device_send, check_flickr_dataset, \
+    check_sb_dataset
 from ..core.config import get_callback_timeout, _init_device_info, get_enable_shared_mem, get_num_parallel_workers, \
     get_prefetch_size
 from ..core.datatypes import mstype_to_detype, mstypelist_to_detypelist
@@ -5675,6 +5676,154 @@ class PaddedDataset(GeneratorDataset):
         self.padded_samples = padded_samples
 
 
+class FlickrDataset(MappableDataset):
+    """
+    A source dataset for reading and parsing Flickr8k and Flickr30k dataset.
+
+    The generated dataset has two columns :py:obj:`[image, annotation]`.
+    The tensor of column :py:obj:`image` is of the uint8 type.
+    The tensor of column :py:obj:`annotation` is a tensor which contains 5 annotations string,
+    such as ["a", "b", "c", "d", "e"].
+
+    Args:
+        dataset_dir (str): Path to the root directory that contains the dataset.
+        annotation_file (str): Path to the root directory that contains the annotation.
+        num_samples (int, optional): The number of images to be included in the dataset.
+            (default=None, all images).
+        num_parallel_workers (int, optional): Number of workers to read the data
+            (default=None, number set in the config).
+        shuffle (bool, optional): Whether to perform shuffle on the dataset (default=None, expected
+            order behavior shown in the table).
+        decode (bool, optional): Decode the images after reading (default=False).
+        sampler (Sampler, optional): Object used to choose samples from the
+            dataset (default=None, expected order behavior shown in the table).
+        num_shards (int, optional): Number of shards that the dataset will be divided
+            into (default=None). When this argument is specified, `num_samples` reflects
+            the max sample number of per shard.
+        shard_id (int, optional): The shard ID within num_shards (default=None). This
+            argument can only be specified when num_shards is also specified.
+        cache (DatasetCache, optional): Use tensor caching service to speed up dataset processing.
+            (default=None, which means no cache is used).
+
+    Raises:
+        RuntimeError: If dataset_dir is not valid or does not contain data files.
+        RuntimeError: If num_parallel_workers exceeds the max thread numbers.
+        RuntimeError: If sampler and shuffle are specified at the same time.
+        RuntimeError: If sampler and sharding are specified at the same time.
+        RuntimeError: If num_shards is specified but shard_id is None.
+        RuntimeError: If shard_id is specified but num_shards is None.
+        ValueError: If dataset_dir is not exist.
+        ValueError: If annotation_file is not exist.
+        ValueError: If shard_id is invalid (< 0 or >= num_shards).
+
+    Note:
+        - This dataset can take in a `sampler`. `sampler` and `shuffle` are mutually exclusive.
+          The table below shows what input arguments are allowed and their expected behavior.
+
+    .. list-table:: Expected Order Behavior of Using `sampler` and `shuffle`
+       :widths: 25 25 50
+       :header-rows: 1
+
+       * - Parameter `sampler`
+         - Parameter `shuffle`
+         - Expected Order Behavior
+       * - None
+         - None
+         - random order
+       * - None
+         - True
+         - random order
+       * - None
+         - False
+         - sequential order
+       * - Sampler object
+         - None
+         - order defined by sampler
+       * - Sampler object
+         - True
+         - not allowed
+       * - Sampler object
+         - False
+         - not allowed
+
+    Examples:
+        >>> flickr_dataset_dir = "/path/to/flickr_dataset_directory"
+        >>> annotation_file = "/path/to/flickr_annotation_file"
+        >>>
+        >>> # 1) Get all samples from FLICKR dataset in sequence
+        >>> dataset = ds.FlickrDataset(dataset_dir=flickr_dataset_dir,
+        ...                            annotation_file=annotation_file,
+        ...                            shuffle=False)
+        >>>
+        >>> # 2) Randomly select 350 samples from FLICKR dataset
+        >>> dataset = ds.FlickrDataset(dataset_dir=flickr_dataset_dir,
+        ...                            annotation_file=annotation_file,
+        ...                            num_samples=350,
+        ...                            shuffle=True)
+        >>>
+        >>> # 3) Get samples from FLICKR dataset for shard 0 in a 2-way distributed training
+        >>> dataset = ds.FlickrDataset(dataset_dir=flickr_dataset_dir,
+        ...                            annotation_file=annotation_file,
+        ...                            num_shards=2,
+        ...                            shard_id=0)
+        >>>
+        >>> # In FLICKR dataset, each dictionary has keys "image" and "annotation"
+
+    About Flickr8k dataset:
+        | The Flickr8k dataset consists of 8092 colour images. There are 40460 annotations in the Flickr8k.token.txt,
+          each image has 5 annotations.
+
+        | You can unzip the dataset files into the following directory structure and read by MindSpore's API.
+        | .
+        | └── Flickr8k
+        |      ├── Flickr8k_Dataset
+        |      |    ├── 1000268201_693b08cb0e.jpg
+        |      |    ├── 1001773457_577c3a7d70.jpg
+        |      |    ├── ...
+        |      └── Flickr8k.token.txt
+
+        .. code-block::
+
+            M. Hodosh, P. Young and J. Hockenmaier (2013)
+            "Framing Image Description as a Ranking Task: Data, Models and Evaluation Metrics"
+            Journal of Artificial Intellegence Research, Volume 47, pages 853-899
+            http://www.jair.org/papers/paper3994.html
+
+    About Flickr30k dataset:
+        | The Flickr30k dataset consists of 31783 colour images. There are 158915 annotations in
+          the results_20130124.token, each image has 5 annotations.
+
+        | You can unzip the dataset files into the following directory structure and read by MindSpore's API.
+        | .
+        | └── Flickr30k
+        |      ├── flickr30k-images
+        |      |    ├── 1000092795.jpg
+        |      |    ├── 10002456.jpg
+        |      |    ├── ...
+        |      └── results_20130124.token
+
+        .. code-block::
+
+            P. Young, A. Lai, M. Hodosh, and J. Hockenmaier.
+            From image description to visual denotations:
+            New similarity metrics for semantic inference over event descriptions.
+            Transactions of the Association for Computational Linguistics (to appear).
+    """
+
+    @check_flickr_dataset
+    def __init__(self, dataset_dir, annotation_file, num_samples=None, num_parallel_workers=None, shuffle=None,
+                 decode=None, sampler=None, num_shards=None, shard_id=None, cache=None):
+        super().__init__(num_parallel_workers=num_parallel_workers, sampler=sampler, num_samples=num_samples,
+                         shuffle=shuffle, num_shards=num_shards, shard_id=shard_id, cache=cache)
+
+        self.dataset_dir = dataset_dir
+        self.annotation_file = annotation_file
+        self.decode = replace_none(decode, False)
+
+    def parse(self, children=None):
+        return cde.FlickrNode(self.dataset_dir, self.annotation_file, self.decode, self.sampler)
+
+
 class SBDataset(GeneratorDataset):
     """
     A source dataset for reading and parsing Semantic Boundaries Dataset.

mindspore/dataset/engine/validators.py

@@ -1332,6 +1332,34 @@ def check_to_device_send(method):
     return new_method
 
 
+def check_flickr_dataset(method):
+    """A wrapper that wraps a parameter checker around the original Dataset(Flickr8k, Flickr30k)."""
+
+    @wraps(method)
+    def new_method(self, *args, **kwargs):
+        _, param_dict = parse_user_args(method, *args, **kwargs)
+
+        nreq_param_int = ['num_samples', 'num_parallel_workers', 'num_shards', 'shard_id']
+        nreq_param_bool = ['shuffle', 'decode']
+
+        dataset_dir = param_dict.get('dataset_dir')
+        annotation_file = param_dict.get('annotation_file')
+        check_dir(dataset_dir)
+        check_file(annotation_file)
+
+        validate_dataset_param_value(nreq_param_int, param_dict, int)
+        validate_dataset_param_value(nreq_param_bool, param_dict, bool)
+
+        check_sampler_shuffle_shard_options(param_dict)
+
+        cache = param_dict.get('cache')
+        check_cache_option(cache)
+
+        return method(self, *args, **kwargs)
+
+    return new_method
+
+
 def check_sb_dataset(method):
     """A wrapper that wraps a parameter checker around the original Semantic Boundaries Dataset."""
 

tests/ut/cpp/dataset/CMakeLists.txt

@@ -21,6 +21,7 @@ SET(DE_UT_SRCS
         c_api_dataset_coco_test.cc
         c_api_dataset_config_test.cc
         c_api_dataset_csv_test.cc
+        c_api_dataset_flickr_test.cc
         c_api_dataset_iterator_test.cc
         c_api_dataset_manifest_test.cc
         c_api_dataset_minddata_test.cc

tests/ut/cpp/dataset/c_api_dataset_flickr_test.cc

@@ -0,0 +1,308 @@
+/**
+ * Copyright 2021 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/include/dataset/datasets.h"
+
+using namespace mindspore::dataset;
+using mindspore::dataset::Tensor;
+
+class MindDataTestPipeline : public UT::DatasetOpTesting {
+ protected:
+};
+
+TEST_F(MindDataTestPipeline, TestFlickrBasic) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestFlickrBasic.";
+
+  std::string dataset_path = datasets_root_path_ + "/testFlickrData/flickr30k/flickr30k-images";
+  std::string file_path = datasets_root_path_ + "/testFlickrData/flickr30k/test1.token";
+
+  // Create a Flickr30k Dataset
+  std::shared_ptr<Dataset> ds = Flickr(dataset_path, file_path);
+  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, mindspore::MSTensor> row;
+  ASSERT_OK(iter->GetNextRow(&row));
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
+    ASSERT_OK(iter->GetNextRow(&row));
+  }
+
+  EXPECT_EQ(i, 2);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestFlickrBasicWithPipeline) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestFlickrBasicWithPipeline.";
+
+  std::string dataset_path = datasets_root_path_ + "/testFlickrData/flickr30k/flickr30k-images";
+  std::string file_path = datasets_root_path_ + "/testFlickrData/flickr30k/test1.token";
+
+  // Create two Flickr30k Dataset
+  std::shared_ptr<Dataset> ds1 = Flickr(dataset_path, file_path);
+  std::shared_ptr<Dataset> ds2 = Flickr(dataset_path, file_path);
+  EXPECT_NE(ds1, nullptr);
+  EXPECT_NE(ds2, nullptr);
+
+  // Create two Repeat operation on ds
+  int32_t repeat_num = 2;
+  ds1 = ds1->Repeat(repeat_num);
+  EXPECT_NE(ds1, nullptr);
+  repeat_num = 3;
+  ds2 = ds2->Repeat(repeat_num);
+  EXPECT_NE(ds2, nullptr);
+
+  // Create two Project operation on ds
+  std::vector<std::string> column_project = {"image"};
+  ds1 = ds1->Project(column_project);
+  EXPECT_NE(ds1, nullptr);
+  ds2 = ds2->Project(column_project);
+  EXPECT_NE(ds2, nullptr);
+
+  // Create a Concat operation on the ds
+  ds1 = ds1->Concat({ds2});
+  EXPECT_NE(ds1, 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 = ds1->CreateIterator();
+  EXPECT_NE(iter, nullptr);
+
+  // Iterate the dataset and get each row
+  std::unordered_map<std::string, mindspore::MSTensor> row;
+  ASSERT_OK(iter->GetNextRow(&row));
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
+    ASSERT_OK(iter->GetNextRow(&row));
+  }
+
+  EXPECT_EQ(i, 10);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestFlickrGetters) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestFlickrGetters.";
+
+  std::string dataset_path = datasets_root_path_ + "/testFlickrData/flickr30k/flickr30k-images";
+  std::string file_path1 = datasets_root_path_ + "/testFlickrData/flickr30k/test1.token";
+  std::string file_path2 = datasets_root_path_ + "/testFlickrData/flickr30k/test2.token";
+
+  // Create a Flickr30k Dataset
+  std::shared_ptr<Dataset> ds1 = Flickr(dataset_path, file_path1);
+  std::shared_ptr<Dataset> ds2 = Flickr(dataset_path, file_path2);
+  std::vector<std::string> column_names = {"image", "annotation"};
+
+  EXPECT_NE(ds1, nullptr);
+  EXPECT_EQ(ds1->GetDatasetSize(), 2);
+  EXPECT_EQ(ds1->GetColumnNames(), column_names);
+
+  EXPECT_NE(ds2, nullptr);
+  EXPECT_EQ(ds2->GetDatasetSize(), 3);
+  EXPECT_EQ(ds2->GetColumnNames(), column_names);
+}
+
+TEST_F(MindDataTestPipeline, TestFlickrAnnotations) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestFlickrGetters.";
+
+  std::string dataset_path = datasets_root_path_ + "/testFlickrData/flickr30k/flickr30k-images";
+  std::string file_path = datasets_root_path_ + "/testFlickrData/flickr30k/test3.token";
+  std::shared_ptr<Dataset> ds = Flickr(dataset_path, file_path);
+
+  // 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, mindspore::MSTensor> row;
+  ASSERT_OK(iter->GetNextRow(&row));
+
+  std::shared_ptr<Tensor> a_expect_item;
+  std::vector<std::string> annotation_arr;
+  annotation_arr.emplace_back("This is a banana.");
+  annotation_arr.emplace_back("This is a yellow banana.");
+  annotation_arr.emplace_back("This is a banana on the table.");
+  annotation_arr.emplace_back("The banana is yellow.");
+  annotation_arr.emplace_back("The banana is very big.");
+
+  ASSERT_OK(Tensor::CreateFromVector(annotation_arr, &a_expect_item));
+  mindspore::MSTensor expect_item = mindspore::MSTensor(std::make_shared<mindspore::dataset::DETensor>(a_expect_item));
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    auto annotation = row["annotation"];
+    MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
+    MS_LOG(INFO) << "Tensor annotation shape: " << annotation.Shape();
+
+    EXPECT_MSTENSOR_EQ(annotation, expect_item);
+
+    ASSERT_OK(iter->GetNextRow(&row));
+  }
+
+  EXPECT_EQ(i, 1);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestFlickrDecode) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestFlickrDecode.";
+
+  std::string dataset_path = datasets_root_path_ + "/testFlickrData/flickr30k/flickr30k-images";
+  std::string file_path = datasets_root_path_ + "/testFlickrData/flickr30k/test1.token";
+  // Create a Flickr30k Dataset
+  std::shared_ptr<Dataset> ds = Flickr(dataset_path, file_path, true, std::make_shared<RandomSampler>());
+  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, mindspore::MSTensor> row;
+  ASSERT_OK(iter->GetNextRow(&row));
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    auto shape = image.Shape();
+    MS_LOG(INFO) << "Tensor image shape size: " << shape.size();
+    MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
+    EXPECT_GT(shape.size(), 1);  // Verify decode=true took effect
+    ASSERT_OK(iter->GetNextRow(&row));
+  }
+
+  EXPECT_EQ(i, 2);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestFlickrNumSamplers) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestFlickrNumSamplers.";
+
+  std::string dataset_path = datasets_root_path_ + "/testFlickrData/flickr30k/flickr30k-images";
+  std::string file_path = datasets_root_path_ + "/testFlickrData/flickr30k/test1.token";
+  // Create a Flickr30k Dataset
+  std::shared_ptr<Dataset> ds = Flickr(dataset_path, file_path, true, std::make_shared<SequentialSampler>(0, 1));
+  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, mindspore::MSTensor> row;
+  ASSERT_OK(iter->GetNextRow(&row));
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    auto annotation = row["annotation"];
+    MS_LOG(INFO) << "Tensor image shape: " << image.Shape();
+
+    auto a_it = annotation.Shape().begin();
+    for (; a_it != annotation.Shape().end(); ++a_it) {
+      std::cout << "annotation shape " << *a_it << std::endl;
+    }
+    ASSERT_OK(iter->GetNextRow(&row));
+  }
+
+  EXPECT_EQ(i, 1);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestFlickrError) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestFlickrError.";
+
+  std::string dataset_path = datasets_root_path_ + "/testFlickrData/flickr30k/flickr30k-images";
+  std::string file_path = datasets_root_path_ + "/testFlickrData/flickr30k/test1.token";
+  // Create a Flickr30k Dataset with non-existing dataset dir
+  std::shared_ptr<Dataset> ds0 = Flickr("NotExistFile", file_path);
+  EXPECT_NE(ds0, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  std::shared_ptr<Iterator> iter0 = ds0->CreateIterator();
+  // Expect failure: invalid Flickr30k input
+  EXPECT_EQ(iter0, nullptr);
+
+  // Create a Flickr30k Dataset with non-existing annotation file
+  std::shared_ptr<Dataset> ds1 = Flickr(dataset_path, "NotExistFile");
+  EXPECT_NE(ds1, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  std::shared_ptr<Iterator> iter1 = ds1->CreateIterator();
+  // Expect failure: invalid Flickr30k input
+  EXPECT_EQ(iter1, nullptr);
+
+  // Create a Flickr30k Dataset with invalid string of dataset dir
+  std::shared_ptr<Dataset> ds2 = Flickr(":*?\"<>|`&;'", file_path);
+  EXPECT_NE(ds2, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  std::shared_ptr<Iterator> iter2 = ds2->CreateIterator();
+  // Expect failure: invalid Flickr30k input
+  EXPECT_EQ(iter2, nullptr);
+
+  // Create a Flickr30k Dataset with invalid string of annotation file
+  std::shared_ptr<Dataset> ds3 = Flickr(dataset_path, ":*?\"<>|`&;'");
+  EXPECT_NE(ds3, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  std::shared_ptr<Iterator> iter3 = ds3->CreateIterator();
+  // Expect failure: invalid Flickr30k input
+  EXPECT_EQ(iter3, nullptr);
+}
+
+TEST_F(MindDataTestPipeline, TestFlickrWithNullSamplerError) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestFlickrWithNullSamplerError.";
+
+  std::string dataset_path = datasets_root_path_ + "/testFlickrData/flickr30k/flickr30k-images";
+  std::string file_path = datasets_root_path_ + "/testFlickrData/flickr30k/test1.token";
+  // Create a Flickr30k Dataset
+  std::shared_ptr<Dataset> ds = Flickr(dataset_path, file_path, false, nullptr);
+  EXPECT_NE(ds, nullptr);
+
+  // Create an iterator over the result of the above dataset
+  std::shared_ptr<Iterator> iter = ds->CreateIterator();
+  // Expect failure: invalid Flickr30k input, sampler cannot be nullptr
+  EXPECT_EQ(iter, nullptr);
+}

tests/ut/data/dataset/testFlickrData/flickr30k/test1.token

@@ -0,0 +1,10 @@
+000001.jpg#0	This is \*a banana.
+000001.jpg#1	This is a yellow banana.
+000001.jpg#2	This is a banana on the table.
+000001.jpg#3	The banana is yellow.
+000001.jpg#4	The banana is very big.
+000002.jpg#0	This is a pen.
+000002.jpg#1	This is a red and black pen.
+000002.jpg#2	This is a pen on the table.
+000002.jpg#3	The color of the pen is red and black.
+000002.jpg#4	The pen has two colors.

tests/ut/data/dataset/testFlickrData/flickr30k/test2.token

@@ -0,0 +1,15 @@
+000003.jpg#0	This is an orange.
+000003.jpg#1	This is an big orange.
+000003.jpg#2	This is an orange on the pad.
+000003.jpg#3	The orange looks like very delicious.
+000003.jpg#4	The orange is on the black pad.
+000004.jpg#0	This is a key.
+000004.jpg#1	This is a delicate key.
+000004.jpg#2	This is a key on the table.
+000004.jpg#3	The key looks like very old.
+000004.jpg#4	The key can be used to open door.
+000005.jpg#0	This is a cup.
+000005.jpg#1	This is a beautiful and delicate cup.
+000005.jpg#2	This is a cup on the table.
+000005.jpg#3	The cup is white and the pattern is blue.
+000005.jpg#4	The beautiful cup is on the black table.

tests/ut/data/dataset/testFlickrData/flickr30k/test3.token

@@ -0,0 +1,5 @@
+000001.jpg#0	This is a banana.
+000001.jpg#1	This is a yellow banana.
+000001.jpg#2	This is a banana on the table.
+000001.jpg#3	The banana is yellow.
+000001.jpg#4	The banana is very big.

tests/ut/python/dataset/test_datasets_flickr.py

@@ -0,0 +1,154 @@
+# Copyright 2021 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.
+# ==============================================================================
+import numpy as np
+import matplotlib.pyplot as plt
+
+import mindspore.dataset as ds
+import mindspore.dataset.vision.c_transforms as c_vision
+from mindspore import log as logger
+
+FLICKR30K_DATASET_DIR = "../data/dataset/testFlickrData/flickr30k/flickr30k-images"
+FLICKR30K_ANNOTATION_FILE_1 = "../data/dataset/testFlickrData/flickr30k/test1.token"
+FLICKR30K_ANNOTATION_FILE_2 = "../data/dataset/testFlickrData/flickr30k/test2.token"
+
+
+def visualize_dataset(images, labels):
+    """
+    Helper function to visualize the dataset samples
+    """
+    plt.figure(figsize=(10, 10))
+    for i, item in enumerate(zip(images, labels), start=1):
+        plt.imshow(item[0])
+        plt.title('\n'.join([s.decode('utf-8') for s in item[1]]))
+        plt.savefig('./flickr_' + str(i) + '.jpg')
+
+
+def test_flickr30k_dataset_train(plot=False):
+    data = ds.FlickrDataset(FLICKR30K_DATASET_DIR, FLICKR30K_ANNOTATION_FILE_1, decode=True)
+    count = 0
+    images_list = []
+    annotation_list = []
+    for item in data.create_dict_iterator(num_epochs=1, output_numpy=True):
+        logger.info("item[image] is {}".format(item["image"]))
+        images_list.append(item['image'])
+        annotation_list.append(item['annotation'])
+        count = count + 1
+    assert count == 2
+    if plot:
+        visualize_dataset(images_list, annotation_list)
+
+
+def test_flickr30k_dataset_annotation_check():
+    data = ds.FlickrDataset(FLICKR30K_DATASET_DIR, FLICKR30K_ANNOTATION_FILE_1, decode=True, shuffle=False)
+    count = 0
+    expect_annotation_arr = [
+        np.array([
+            r'This is \*a banana.',
+            'This is a yellow banana.',
+            'This is a banana on the table.',
+            'The banana is yellow.',
+            'The banana is very big.',
+        ]),
+        np.array([
+            'This is a pen.',
+            'This is a red and black pen.',
+            'This is a pen on the table.',
+            'The color of the pen is red and black.',
+            'The pen has two colors.',
+        ])
+    ]
+    for item in data.create_dict_iterator(num_epochs=1, output_numpy=True):
+        annotation = [s.decode("utf8") for s in item["annotation"]]
+        np.testing.assert_array_equal(annotation, expect_annotation_arr[count])
+        logger.info("item[image] is {}".format(item["image"]))
+        count = count + 1
+    assert count == 2
+
+
+def test_flickr30k_dataset_basic():
+    # case 1: test num_samples
+    data1 = ds.FlickrDataset(FLICKR30K_DATASET_DIR, FLICKR30K_ANNOTATION_FILE_2, num_samples=2, decode=True)
+    num_iter1 = 0
+    for _ in data1.create_dict_iterator(num_epochs=1, output_numpy=True):
+        num_iter1 += 1
+    assert num_iter1 == 2
+
+    # case 2: test repeat
+    data2 = ds.FlickrDataset(FLICKR30K_DATASET_DIR, FLICKR30K_ANNOTATION_FILE_1, decode=True)
+    data2 = data2.repeat(5)
+    num_iter2 = 0
+    for _ in data2.create_dict_iterator(num_epochs=1, output_numpy=True):
+        num_iter2 += 1
+    assert num_iter2 == 10
+
+    # case 3: test batch with drop_remainder=False
+    data3 = ds.FlickrDataset(FLICKR30K_DATASET_DIR, FLICKR30K_ANNOTATION_FILE_2, decode=True, shuffle=False)
+    resize_op = c_vision.Resize((100, 100))
+    data3 = data3.map(operations=resize_op, input_columns=["image"], num_parallel_workers=1)
+    assert data3.get_dataset_size() == 3
+    assert data3.get_batch_size() == 1
+    data3 = data3.batch(batch_size=2)  # drop_remainder is default to be False
+    assert data3.get_dataset_size() == 2
+    assert data3.get_batch_size() == 2
+    num_iter3 = 0
+    for _ in data3.create_dict_iterator(num_epochs=1, output_numpy=True):
+        num_iter3 += 1
+    assert num_iter3 == 2
+
+    # case 4: test batch with drop_remainder=True
+    data4 = ds.FlickrDataset(FLICKR30K_DATASET_DIR, FLICKR30K_ANNOTATION_FILE_2, decode=True, shuffle=False)
+    resize_op = c_vision.Resize((100, 100))
+    data4 = data4.map(operations=resize_op, input_columns=["image"], num_parallel_workers=1)
+    assert data4.get_dataset_size() == 3
+    assert data4.get_batch_size() == 1
+    data4 = data4.batch(batch_size=2, drop_remainder=True)  # the rest of incomplete batch will be dropped
+    assert data4.get_dataset_size() == 1
+    assert data4.get_batch_size() == 2
+    num_iter4 = 0
+    for _ in data4.create_dict_iterator(num_epochs=1, output_numpy=True):
+        num_iter4 += 1
+    assert num_iter4 == 1
+
+
+def test_flickr30k_dataset_exception():
+    def exception_func(item):
+        raise Exception("Error occur!")
+
+    try:
+        data = ds.FlickrDataset(FLICKR30K_DATASET_DIR, FLICKR30K_ANNOTATION_FILE_1, decode=True)
+        data = data.map(operations=exception_func, input_columns=["image"], num_parallel_workers=1)
+        num_rows = 0
+        for _ in data.create_dict_iterator():
+            num_rows += 1
+        assert False
+    except RuntimeError as e:
+        assert "map operation: [PyFunc] failed. The corresponding data files" in str(e)
+
+    try:
+        data = ds.FlickrDataset(FLICKR30K_DATASET_DIR, FLICKR30K_ANNOTATION_FILE_1, decode=True)
+        data = data.map(operations=exception_func, input_columns=["annotation"], num_parallel_workers=1)
+        num_rows = 0
+        for _ in data.create_dict_iterator():
+            num_rows += 1
+        assert False
+    except RuntimeError as e:
+        assert "map operation: [PyFunc] failed. The corresponding data files" in str(e)
+
+
+if __name__ == "__main__":
+    test_flickr30k_dataset_train(False)
+    test_flickr30k_dataset_annotation_check()
+    test_flickr30k_dataset_basic()
+    test_flickr30k_dataset_exception()