c++ api support for Manifest Dataset

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

@@ -26,6 +26,7 @@
 #include "minddata/dataset/engine/datasetops/source/clue_op.h"
 #include "minddata/dataset/engine/datasetops/source/coco_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"
 #include "minddata/dataset/engine/datasetops/source/text_file_op.h"
 #include "minddata/dataset/engine/datasetops/source/voc_op.h"
@@ -44,6 +45,7 @@
 // Sampler headers (in alphabetical order)
 #include "minddata/dataset/engine/datasetops/source/sampler/sampler.h"
 #include "minddata/dataset/engine/datasetops/source/sampler/random_sampler.h"
+#include "minddata/dataset/engine/datasetops/source/sampler/sequential_sampler.h"
 
 #include "minddata/dataset/core/config_manager.h"
 #include "minddata/dataset/util/random.h"
@@ -164,6 +166,16 @@ std::shared_ptr<ImageFolderDataset> ImageFolder(const std::string &dataset_dir,
   return ds->ValidateParams() ? ds : nullptr;
 }
 
+// Function to create a ManifestDataset.
+std::shared_ptr<ManifestDataset> Manifest(std::string dataset_file, std::string usage,
+                                          std::shared_ptr<SamplerObj> sampler,
+                                          const std::map<std::string, int32_t> &class_indexing, bool decode) {
+  auto ds = std::make_shared<ManifestDataset>(dataset_file, usage, sampler, class_indexing, decode);
+
+  // Call derived class validation method.
+  return ds->ValidateParams() ? ds : nullptr;
+}
+
 // Function to create a MnistDataset.
 std::shared_ptr<MnistDataset> Mnist(const std::string &dataset_dir, const std::shared_ptr<SamplerObj> &sampler) {
   auto ds = std::make_shared<MnistDataset>(dataset_dir, sampler);
@@ -877,6 +889,51 @@ std::vector<std::shared_ptr<DatasetOp>> ImageFolderDataset::Build() {
   return node_ops;
 }
 
+ManifestDataset::ManifestDataset(std::string dataset_file, std::string usage, std::shared_ptr<SamplerObj> sampler,
+                                 const std::map<std::string, int32_t> &class_indexing, bool decode)
+    : dataset_file_(dataset_file), usage_(usage), decode_(decode), class_index_(class_indexing), sampler_(sampler) {}
+
+bool ManifestDataset::ValidateParams() {
+  Path manifest_file(dataset_file_);
+  if (!manifest_file.Exists()) {
+    MS_LOG(ERROR) << "dataset file: [" << dataset_file_ << "] is invalid or not exist";
+    return false;
+  }
+
+  std::vector<std::string> usage_list = {"train", "eval", "inference"};
+  if (find(usage_list.begin(), usage_list.end(), usage_) == usage_list.end()) {
+    MS_LOG(ERROR) << "usage should be train, eval or inference.";
+    return false;
+  }
+
+  return true;
+}
+
+std::vector<std::shared_ptr<DatasetOp>> ManifestDataset::Build() {
+  // A vector containing shared pointer to the Dataset Ops that this object will create
+  std::vector<std::shared_ptr<DatasetOp>> node_ops;
+
+  // If user does not specify Sampler, create a default sampler based on the shuffle variable.
+  if (sampler_ == nullptr) {
+    sampler_ = CreateDefaultSampler();
+  }
+
+  // Do internal Schema generation.
+  auto schema = std::make_unique<DataSchema>();
+  RETURN_EMPTY_IF_ERROR(schema->AddColumn(ColDescriptor("image", DataType(DataType::DE_UINT8), TensorImpl::kCv, 1)));
+  TensorShape scalar = TensorShape::CreateScalar();
+  RETURN_EMPTY_IF_ERROR(
+    schema->AddColumn(ColDescriptor("label", DataType(DataType::DE_UINT32), TensorImpl::kFlexible, 0, &scalar)));
+
+  std::shared_ptr<ManifestOp> manifest_op;
+  manifest_op =
+    std::make_shared<ManifestOp>(num_workers_, rows_per_buffer_, dataset_file_, connector_que_size_, decode_,
+                                 class_index_, std::move(schema), std::move(sampler_->Build()), usage_);
+
+  node_ops.push_back(manifest_op);
+  return node_ops;
+}
+
 MnistDataset::MnistDataset(std::string dataset_dir, std::shared_ptr<SamplerObj> sampler)
     : dataset_dir_(dataset_dir), sampler_(sampler) {}
 

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

@@ -49,6 +49,7 @@ class Cifar100Dataset;
 class CLUEDataset;
 class CocoDataset;
 class ImageFolderDataset;
+class ManifestDataset;
 class MnistDataset;
 class TextFileDataset;
 class VOCDataset;
@@ -154,6 +155,21 @@ std::shared_ptr<ImageFolderDataset> ImageFolder(const std::string &dataset_dir,
                                                 const std::set<std::string> &extensions = {},
                                                 const std::map<std::string, int32_t> &class_indexing = {});
 
+/// \brief Function to create a ManifestDataset
+/// \notes The generated dataset has two columns ['image', 'label']
+/// \param[in] dataset_file The dataset file to be read
+/// \param[in] usage Need "train", "eval" or "inference" data (default="train")
+/// \param[in] decode Decode the images after reading (default=false).
+/// \param[in] class_indexing A str-to-int mapping from label name to index (default={}, the folder
+///    names will be sorted alphabetically and each class will be given a unique index starting from 0).
+/// \param[in] sampler Object used to choose samples from the dataset. If sampler is `nullptr`,
+///    A `RandomSampler` will be used to randomly iterate the entire dataset
+/// \return Shared pointer to the current ManifestDataset
+std::shared_ptr<ManifestDataset> Manifest(std::string dataset_file, std::string usage = "train",
+                                          std::shared_ptr<SamplerObj> sampler = nullptr,
+                                          const std::map<std::string, int32_t> &class_indexing = {},
+                                          bool decode = false);
+
 /// \brief Function to create a MnistDataset
 /// \notes The generated dataset has two columns ['image', 'label']
 /// \param[in] dataset_dir Path to the root directory that contains the dataset
@@ -500,6 +516,31 @@ class ImageFolderDataset : public Dataset {
   std::set<std::string> exts_;
 };
 
+class ManifestDataset : public Dataset {
+ public:
+  /// \brief Constructor
+  ManifestDataset(std::string dataset_file, std::string usage, std::shared_ptr<SamplerObj> sampler,
+                  const std::map<std::string, int32_t> &class_indexing, bool decode);
+
+  /// \brief Destructor
+  ~ManifestDataset() = default;
+
+  /// \brief a base class override function to create the required runtime dataset op objects for this class
+  /// \return The list of shared pointers to the 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::string dataset_file_;
+  std::string usage_;
+  bool decode_;
+  std::map<std::string, int32_t> class_index_;
+  std::shared_ptr<SamplerObj> sampler_;
+};
+
 class MnistDataset : public Dataset {
  public:
   /// \brief Constructor

tests/ut/cpp/dataset/c_api_dataset_manifest_test.cc

@@ -0,0 +1,206 @@
+/**
+ * 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/include/datasets.h"
+
+using namespace mindspore::dataset::api;
+using mindspore::dataset::Tensor;
+
+class MindDataTestPipeline : public UT::DatasetOpTesting {
+ protected:
+};
+
+TEST_F(MindDataTestPipeline, TestManifestBasic) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestManifestBasic.";
+
+  std::string file_path = datasets_root_path_ + "/testManifestData/cpp.json";
+  // Create a Manifest Dataset
+  std::shared_ptr<Dataset> ds = Manifest(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, std::shared_ptr<Tensor>> row;
+  iter->GetNextRow(&row);
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    MS_LOG(INFO) << "Tensor image shape: " << image->shape();
+    iter->GetNextRow(&row);
+  }
+
+  EXPECT_EQ(i, 2);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestManifestDecode) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestManifestDecode.";
+
+  std::string file_path = datasets_root_path_ + "/testManifestData/cpp.json";
+  // Create a Manifest Dataset
+  std::shared_ptr<Dataset> ds = Manifest(file_path, "train", nullptr, {}, true);
+  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);
+
+  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
+    iter->GetNextRow(&row);
+  }
+
+  EXPECT_EQ(i, 2);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestManifestEval) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestManifestEval.";
+
+  std::string file_path = datasets_root_path_ + "/testManifestData/cpp.json";
+  // Create a Manifest Dataset
+  std::shared_ptr<Dataset> ds = Manifest(file_path, "eval");
+  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);
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    MS_LOG(INFO) << "Tensor image shape: " << image->shape();
+    iter->GetNextRow(&row);
+  }
+
+  EXPECT_EQ(i, 1);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestManifestClassIndex) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestManifestClassIndex.";
+
+  std::string file_path = datasets_root_path_ + "/testManifestData/cpp.json";
+  std::map<std::string, int32_t> map;
+  map["cat"] = 111;  // forward slash is not good, but we need to add this somewhere, also in windows, its a '\'
+  map["dog"] = 222;  // forward slash is not good, but we need to add this somewhere, also in windows, its a '\'
+  map["wrong folder name"] = 1234;  // this is skipped
+  std::vector<int> expected_label = {111, 222};
+
+  // Create a Manifest Dataset
+  std::shared_ptr<Dataset> ds = Manifest(file_path, "train", nullptr, map, true);
+  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);
+
+  uint64_t i = 0;
+  int32_t label_idx = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    MS_LOG(INFO) << "Tensor image shape: " << image->shape();
+    row["label"]->GetItemAt<int32_t>(&label_idx, {});
+    MS_LOG(INFO) << "Tensor label value: " << label_idx;
+    auto label_it = std::find(expected_label.begin(), expected_label.end(), label_idx);
+    EXPECT_NE(label_it, expected_label.end());
+    iter->GetNextRow(&row);
+  }
+
+  EXPECT_EQ(i, 2);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestManifestNumSamplers) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestManifestNumSamplers.";
+
+  std::string file_path = datasets_root_path_ + "/testManifestData/cpp.json";
+  // Create a Manifest Dataset
+  std::shared_ptr<Dataset> ds = Manifest(file_path, "train", SequentialSampler(0, 1), {}, true);
+  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);
+
+  uint64_t i = 0;
+  while (row.size() != 0) {
+    i++;
+    auto image = row["image"];
+    MS_LOG(INFO) << "Tensor image shape: " << image->shape();
+    iter->GetNextRow(&row);
+  }
+
+  EXPECT_EQ(i, 1);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
+TEST_F(MindDataTestPipeline, TestManifestError) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestManifestError.";
+
+  std::string file_path = datasets_root_path_ + "/testManifestData/cpp.json";
+  // Create a Manifest Dataset with not exist file
+  std::shared_ptr<Dataset> ds0 = Manifest("NotExistFile", "train");
+  EXPECT_EQ(ds0, nullptr);
+
+  // Create a Manifest Dataset with invalid usage
+  std::shared_ptr<Dataset> ds1 = Manifest(file_path, "invalid_usage");
+  EXPECT_EQ(ds1, nullptr);
+}