!1983 Remove inheritance of Sampler from DatasetOp

Merge pull request !1983 from JesseKLee/sampler

mindspore/ccsrc/dataset/engine/datasetops/source/celeba_op.cc

@@ -263,7 +263,7 @@ std::vector<std::string> CelebAOp::Split(const std::string &line) {
 Status CelebAOp::operator()() {
   RETURN_IF_NOT_OK(LaunchThreadsAndInitOp());
   std::unique_ptr<DataBuffer> data_buffer;
-  RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&data_buffer));
+  RETURN_IF_NOT_OK(sampler_->GetNextSample(&data_buffer));
   RETURN_IF_NOT_OK(AddIOBlock(&data_buffer));
   return Status::OK();
 }
@@ -291,7 +291,7 @@ Status CelebAOp::AddIOBlock(std::unique_ptr<DataBuffer> *data_buffer) {
           keys.clear();
         }
       }
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(data_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(data_buffer));
     }
 
     if (!keys.empty()) {
@@ -313,7 +313,7 @@ Status CelebAOp::AddIOBlock(std::unique_ptr<DataBuffer> *data_buffer) {
         io_block_queues_[(buff_count++) % num_workers_]->Add(std::make_unique<IOBlock>(IOBlock::kDeIoBlockFlagEoe)));
       RETURN_IF_NOT_OK(wp_.Wait());  // Master thread goes to sleep after it has made all the IOBlocks
       wp_.Clear();
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(data_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(data_buffer));
     }
   }
 }

mindspore/ccsrc/dataset/engine/datasetops/source/cifar_op.cc

@@ -100,7 +100,7 @@ CifarOp::CifarOp(CifarType type, int32_t num_works, int32_t rows_per_buf, const
 Status CifarOp::operator()() {
   RETURN_IF_NOT_OK(LaunchThreadsAndInitOp());
   std::unique_ptr<DataBuffer> sampler_buffer;
-  RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+  RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
   while (true) {  // each iterator is 1 epoch
     std::vector<int64_t> keys;
     keys.reserve(rows_per_buffer_);
@@ -118,7 +118,7 @@ Status CifarOp::operator()() {
           keys.clear();
         }
       }
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
     }
     if (keys.empty() == false) {
       RETURN_IF_NOT_OK(io_block_queues_[(buf_cnt_++) % num_workers_]->Add(
@@ -139,7 +139,7 @@ Status CifarOp::operator()() {
         io_block_queues_[(buf_cnt_++) % num_workers_]->Add(std::make_unique<IOBlock>(IOBlock::kDeIoBlockFlagEoe)));
       RETURN_IF_NOT_OK(wp_.Wait());  // Master thread goes to sleep after it has made all the IOBlocks
       wp_.Clear();
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
     }
   }
 }

mindspore/ccsrc/dataset/engine/datasetops/source/image_folder_op.cc

@@ -126,7 +126,7 @@ Status ImageFolderOp::PrescanMasterEntry(const std::string &filedir) {
 Status ImageFolderOp::operator()() {
   RETURN_IF_NOT_OK(LaunchThreadsAndInitOp());
   std::unique_ptr<DataBuffer> sampler_buffer;
-  RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+  RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
   while (true) {  // each iterator is 1 epoch
     std::vector<int64_t> keys;
     keys.reserve(rows_per_buffer_);
@@ -145,7 +145,7 @@ Status ImageFolderOp::operator()() {
           keys.clear();
         }
       }
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
     }
     if (keys.empty() == false) {
       RETURN_IF_NOT_OK(
@@ -166,7 +166,7 @@ Status ImageFolderOp::operator()() {
         io_block_queues_[(buf_cnt_++) % num_workers_]->Add(std::make_unique<IOBlock>(IOBlock::kDeIoBlockFlagEoe)));
       RETURN_IF_NOT_OK(wp_.Wait());  // Master thread goes to sleep after it has made all the IOBlocks
       wp_.Clear();
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
     }
   }
 }

mindspore/ccsrc/dataset/engine/datasetops/source/manifest_op.cc

@@ -88,7 +88,7 @@ ManifestOp::ManifestOp(int32_t num_works, int32_t rows_per_buffer, std::string f
 Status ManifestOp::operator()() {
   RETURN_IF_NOT_OK(LaunchThreadsAndInitOp());
   std::unique_ptr<DataBuffer> sampler_buffer;
-  RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+  RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
   return AddIoBlock(&sampler_buffer);
 }
 
@@ -110,7 +110,7 @@ Status ManifestOp::AddIoBlock(std::unique_ptr<DataBuffer> *sampler_buffer) {
           keys.clear();
         }
       }
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(sampler_buffer));
     }
     if (keys.empty() == false) {
       RETURN_IF_NOT_OK(io_block_queues_[(buf_cnt_++) % num_workers_]->Add(
@@ -131,7 +131,7 @@ Status ManifestOp::AddIoBlock(std::unique_ptr<DataBuffer> *sampler_buffer) {
         io_block_queues_[(buf_cnt_++) % num_workers_]->Add(std::make_unique<IOBlock>(IOBlock::kDeIoBlockFlagEoe)));
       RETURN_IF_NOT_OK(wp_.Wait());  // Master thread goes to sleep after it has made all the IOBlocks
       wp_.Clear();
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(sampler_buffer));
     }
   }
 }

mindspore/ccsrc/dataset/engine/datasetops/source/mnist_op.cc

@@ -98,7 +98,7 @@ Status MnistOp::TraversalSampleIds(const std::shared_ptr<Tensor> &sample_ids, st
 Status MnistOp::operator()() {
   RETURN_IF_NOT_OK(LaunchThreadsAndInitOp());
   std::unique_ptr<DataBuffer> sampler_buffer;
-  RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+  RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
   while (true) {  // each iterator is 1 epoch
     std::vector<int64_t> keys;
     keys.reserve(rows_per_buffer_);
@@ -109,7 +109,7 @@ Status MnistOp::operator()() {
         RETURN_STATUS_UNEXPECTED("Sampler Tensor isn't UINT64");
       }
       RETURN_IF_NOT_OK(TraversalSampleIds(sample_ids, &keys));
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
     }
     if (keys.empty() == false) {
       RETURN_IF_NOT_OK(io_block_queues_[(buf_cnt_++) % num_workers_]->Add(
@@ -130,7 +130,7 @@ Status MnistOp::operator()() {
         io_block_queues_[(buf_cnt_++) % num_workers_]->Add(std::make_unique<IOBlock>(IOBlock::kDeIoBlockFlagEoe)));
       RETURN_IF_NOT_OK(wp_.Wait());  // Master thread goes to sleep after it has made all the IOBlocks
       wp_.Clear();
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
     }
   }
 }

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/distributed_sampler.cc

@@ -55,14 +55,14 @@ Status DistributedSampler::InitSampler() {
   return Status::OK();
 }
 
-Status DistributedSampler::GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) {
+Status DistributedSampler::GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) {
   if (cnt_ > samples_per_buffer_) {
     RETURN_STATUS_UNEXPECTED("Distributed Sampler Error");
   } else if (cnt_ == samples_per_buffer_) {
     (*out_buffer) = std::make_unique<DataBuffer>(0, DataBuffer::kDeBFlagEOE);
   } else {
     if (HasChildSampler()) {
-      RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&child_ids_));
+      RETURN_IF_NOT_OK(child_[0]->GetNextSample(&child_ids_));
     }
 
     (*out_buffer) = std::make_unique<DataBuffer>(cnt_, DataBuffer::kDeBFlagNone);

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/distributed_sampler.h

@@ -40,7 +40,7 @@ class DistributedSampler : public Sampler {
   // @param std::unique_ptr<DataBuffer> * pBuffer
   // @param int32_t workerId
   // @return - The error code return
-  Status GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) override;
+  Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
   // Init sampler, called by base class or python
   Status InitSampler() override;

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/pk_sampler.cc

@@ -59,14 +59,14 @@ Status PKSampler::InitSampler() {
   return Status::OK();
 }
 
-Status PKSampler::GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) {
+Status PKSampler::GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) {
   if (next_id_ > num_samples_ || num_samples_ == 0) {
     RETURN_STATUS_UNEXPECTED("Index out of bound in PKSampler");
   } else if (next_id_ == num_samples_) {
     (*out_buffer) = std::make_unique<DataBuffer>(0, DataBuffer::kDeBFlagEOE);
   } else {
     if (HasChildSampler()) {
-      RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&child_ids_));
+      RETURN_IF_NOT_OK(child_[0]->GetNextSample(&child_ids_));
     }
 
     (*out_buffer) = std::make_unique<DataBuffer>(next_id_, DataBuffer::kDeBFlagNone);

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/pk_sampler.h

@@ -41,7 +41,7 @@ class PKSampler : public Sampler {  // NOT YET FINISHED
   // @param std::unique_ptr<DataBuffer pBuffer
   // @param int32_t workerId
   // @return - The error code return
-  Status GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) override;
+  Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
   // first handshake between leaf source op and Sampler. This func will determine the amount of data
   // in the dataset that we can sample from.

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/python_sampler.cc

@@ -23,12 +23,12 @@ namespace dataset {
 PythonSampler::PythonSampler(int64_t num_samples, py::object py_sampler_instance, int64_t samples_per_buffer)
     : Sampler(num_samples, samples_per_buffer), py_sampler_instance(py_sampler_instance), need_to_reset_(false) {}
 
-Status PythonSampler::GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) {
+Status PythonSampler::GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) {
   if (need_to_reset_) {
     (*out_buffer) = std::make_unique<DataBuffer>(0, DataBuffer::kDeBFlagEOE);
   } else {
     if (HasChildSampler()) {
-      RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&child_ids_));
+      RETURN_IF_NOT_OK(child_[0]->GetNextSample(&child_ids_));
     }
 
     std::shared_ptr<Tensor> sample_ids;

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/python_sampler.h

@@ -48,7 +48,7 @@ class PythonSampler : public Sampler {
   // @param std::unique_ptr<DataBuffer> pBuffer - Buffer to be returned to StorageOp
   // @param int32_t workerId - not meant to be used
   // @return - The error code return
-  Status GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) override;
+  Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
  private:
   bool need_to_reset_;  // Whether Reset() should be called before calling GetNextBuffer()

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/random_sampler.cc

@@ -31,14 +31,14 @@ RandomSampler::RandomSampler(int64_t num_samples, bool replacement, bool reshuff
       reshuffle_each_epoch_(reshuffle_each_epoch),
       dist(nullptr) {}
 
-Status RandomSampler::GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) {
+Status RandomSampler::GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) {
   if (next_id_ > num_samples_) {
     RETURN_STATUS_UNEXPECTED("RandomSampler Internal Error");
   } else if (next_id_ == num_samples_) {
     (*out_buffer) = std::make_unique<DataBuffer>(0, DataBuffer::kDeBFlagEOE);
   } else {
     if (HasChildSampler()) {
-      RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&child_ids_));
+      RETURN_IF_NOT_OK(child_[0]->GetNextSample(&child_ids_));
     }
     (*out_buffer) = std::make_unique<DataBuffer>(next_id_, DataBuffer::kDeBFlagNone);
 

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/random_sampler.h

@@ -41,7 +41,7 @@ class RandomSampler : public Sampler {
   // @param std::unique_ptr<DataBuffer> pBuffer - Buffer to be returned to StorageOp
   // @param int32_t workerId - not meant to be used
   // @return - The error code return
-  Status GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) override;
+  Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
   // meant to be called by base class or python
   Status InitSampler() override;

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/sampler.cc

@@ -33,11 +33,7 @@ Status RandomAccessOp::GetNumRowsInDataset(int64_t *num) const {
 }
 
 Sampler::Sampler(int64_t num_samples, int64_t samples_per_buffer)
-    : DatasetOp(0),
-      num_rows_(0),
-      num_samples_(num_samples),
-      samples_per_buffer_(samples_per_buffer),
-      col_desc_(nullptr) {}
+    : num_rows_(0), num_samples_(num_samples), samples_per_buffer_(samples_per_buffer), col_desc_(nullptr) {}
 
 Status Sampler::HandshakeRandomAccessOp(const RandomAccessOp *op) {
   std::shared_ptr<Sampler> child_sampler;
@@ -97,7 +93,7 @@ Status Sampler::GetAllIdsThenReset(py::array *data) {
   std::shared_ptr<Tensor> sample_ids;
 
   // A call to derived class to get sample ids wrapped inside a buffer
-  RETURN_IF_NOT_OK(GetNextBuffer(&db));
+  RETURN_IF_NOT_OK(GetNextSample(&db));
   // Get the only tensor inside the buffer that contains the actual SampleIds for the entire epoch
   RETURN_IF_NOT_OK(db->GetTensor(&sample_ids, 0, 0));
   // check this buffer is not a ctrl buffer
@@ -114,7 +110,7 @@ Status Sampler::GetAllIdsThenReset(py::array *data) {
     }
   }
   // perform error checking! Next buffer supposed to be EOE since last one already contains all ids for current epoch
-  RETURN_IF_NOT_OK(GetNextBuffer(&db));
+  RETURN_IF_NOT_OK(GetNextSample(&db));
   CHECK_FAIL_RETURN_UNEXPECTED(db->eoe(), "ERROR Non EOE received");
   // Reset Sampler since this is the end of the epoch
   RETURN_IF_NOT_OK(Reset());
@@ -133,17 +129,7 @@ Status Sampler::SetNumRowsInDataset(int64_t num_rows) {
   return Status::OK();
 }
 
-// inline op doesn't have it's own consumer, it's assigned from parent
-int32_t Sampler::num_consumers() const {
-  if (parent_.empty() || parent_[0] == nullptr) {
-    MS_LOG(WARNING) << "Sampler with no parent.  num_consumers is 0.";
-    return 0;
-  } else {
-    return parent_[0]->num_consumers();
-  }
-}
-
-Status Sampler::AddChild(std::shared_ptr<DatasetOp> child) {
+Status Sampler::AddChild(std::shared_ptr<Sampler> child) {
   if (child == nullptr) {
     return Status::OK();
   }
@@ -182,14 +168,5 @@ Status Sampler::GetAssociatedChildId(int64_t *out_associated_id, int64_t id) {
   return Status::OK();
 }
 
-// inline op doesn't have it's own producers, it's assigned from child
-int32_t Sampler::num_producers() const {
-  if (child_.empty() || child_[0] == nullptr) {
-    MS_LOG(WARNING) << "Sampler with no child, num_producers is 0.";
-    return 0;
-  } else {
-    return child_[0]->num_producers();
-  }
-}
 }  // namespace dataset
 }  // namespace mindspore

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/sampler.h

@@ -54,7 +54,7 @@ class RandomAccessOp {
   int64_t num_rows_;
 };
 
-class Sampler : public DatasetOp {
+class Sampler {
  public:
   // Constructor
   // @param int64_t num_samples: the user-requested number of samples ids to generate. A value of 0
@@ -70,14 +70,14 @@ class Sampler : public DatasetOp {
   // @param std::unique_ptr<DataBuffer> pBuffer - Buffer to be returned to StorageOp
   // @param int32_t workerId - not meant to be used
   // @return - The error code return
-  Status GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) override = 0;
+  virtual Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) = 0;
 
   // return all ids in one epoch as a numpy array, then call reset
   Status GetAllIdsThenReset(py::array *data);
 
   // for next epoch of sampleIds
   // @return - The error code return
-  Status Reset() override = 0;
+  virtual Status Reset() = 0;
 
   // first handshake between leaf source op and Sampler. This func will determine the amount of data
   // in the dataset that we can sample from.
@@ -98,26 +98,10 @@ class Sampler : public DatasetOp {
   // @return status error code
   Status SetNumRowsInDataset(int64_t num_rows);
 
-  // Sampler is an inlined op and has no workers.  Producers and consumers are computed.
-  // @return
-  int32_t num_workers() const final { return 0; }
-
-  // Identify num consumers (inlined op)
-  // @return
-  int32_t num_consumers() const final;
-
-  // Identify num producers (inlined op)
-  // @return
-  int32_t num_producers() const final;
-
-  // Not meant to be called!
-  // @return - The error code return
-  Status operator()() final { RETURN_STATUS_UNEXPECTED("Functor not supported in Sampler"); }
-
   // Adds a sampler to become our child.
   // @param std::shared_ptr<DatasetOp> - The sampler to add as a child.
   // @return - The error code returned.
-  Status AddChild(std::shared_ptr<DatasetOp> child);
+  Status AddChild(std::shared_ptr<Sampler> child);
 
   // A helper function to create a int64_t 1-D Tensor specifically used to hold sampleIds for Sampler
   // @param std::shared_ptr<Tensor>* sampleIds
@@ -125,7 +109,7 @@ class Sampler : public DatasetOp {
   // @return - The error code returned.
   Status CreateSamplerTensor(std::shared_ptr<Tensor> *sample_ids, int64_t num_elements);
 
-  void Print(std::ostream &out, bool show_all) const override;
+  virtual void Print(std::ostream &out, bool show_all) const;
 
   friend std::ostream &operator<<(std::ostream &out, const Sampler &sampler) {
     sampler.Print(out, false);
@@ -156,6 +140,7 @@ class Sampler : public DatasetOp {
 
   int64_t samples_per_buffer_;
   std::unique_ptr<ColDescriptor> col_desc_;
+  std::vector<std::shared_ptr<Sampler>> child_;  // Child nodes
   std::unique_ptr<DataBuffer> child_ids_;
 };
 }  // namespace dataset

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/sequential_sampler.cc

@@ -23,14 +23,14 @@ namespace dataset {
 SequentialSampler::SequentialSampler(int64_t num_samples, int64_t start_index, int64_t samples_per_buffer)
     : Sampler(num_samples, samples_per_buffer), start_index_(start_index), current_id_(start_index), id_count_(0) {}
 
-Status SequentialSampler::GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) {
+Status SequentialSampler::GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) {
   if (id_count_ > num_samples_) {
     RETURN_STATUS_UNEXPECTED("SequentialSampler Internal Error");
   } else if (id_count_ == num_samples_) {
     (*out_buffer) = std::make_unique<DataBuffer>(0, DataBuffer::kDeBFlagEOE);
   } else {
     if (HasChildSampler()) {
-      RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&child_ids_));
+      RETURN_IF_NOT_OK(child_[0]->GetNextSample(&child_ids_));
     }
 
     (*out_buffer) = std::make_unique<DataBuffer>(current_id_, DataBuffer::kDeBFlagNone);

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/sequential_sampler.h

@@ -47,7 +47,7 @@ class SequentialSampler : public Sampler {
   // @param std::unique_ptr<DataBuffer> pBuffer - Buffer to be returned to StorageOp
   // @param int32_t workerId - not meant to be used
   // @return - The error code return
-  Status GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) override;
+  Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
   void Print(std::ostream &out, bool show_all) const override;
 

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/subset_random_sampler.cc

@@ -72,13 +72,13 @@ Status SubsetRandomSampler::Reset() {
 }
 
 // Get the sample ids.
-Status SubsetRandomSampler::GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) {
+Status SubsetRandomSampler::GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) {
   // All samples have been drawn
   if (sample_id_ == num_samples_) {
     (*out_buffer) = std::make_unique<DataBuffer>(buffer_id_++, DataBuffer::kDeBFlagEOE);
   } else {
     if (HasChildSampler()) {
-      RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&child_ids_));
+      RETURN_IF_NOT_OK(child_[0]->GetNextSample(&child_ids_));
     }
 
     (*out_buffer) = std::make_unique<DataBuffer>(buffer_id_++, DataBuffer::kDeBFlagNone);

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/subset_random_sampler.h

@@ -49,7 +49,7 @@ class SubsetRandomSampler : public Sampler {
   // Get the sample ids.
   // @param[out] out_buffer The address of a unique_ptr to DataBuffer where the sample ids will be placed.
   // @note the sample ids (int64_t) will be placed in one Tensor and be placed into pBuffer.
-  Status GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) override;
+  Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
  private:
   // A list of indices (already randomized in constructor).

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/weighted_random_sampler.cc

@@ -95,7 +95,7 @@ Status WeightedRandomSampler::Reset() {
 }
 
 // Get the sample ids.
-Status WeightedRandomSampler::GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) {
+Status WeightedRandomSampler::GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) {
   if (weights_.size() > static_cast<size_t>(num_rows_)) {
     return Status(StatusCode::kUnexpectedError, __LINE__, __FILE__,
                   "number of samples weights is more than num of rows. Might generate id out of bound OR other errors");
@@ -109,7 +109,7 @@ Status WeightedRandomSampler::GetNextBuffer(std::unique_ptr<DataBuffer> *out_buf
     (*out_buffer) = std::make_unique<DataBuffer>(buffer_id_++, DataBuffer::kDeBFlagEOE);
   } else {
     if (HasChildSampler()) {
-      RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&child_ids_));
+      RETURN_IF_NOT_OK(child_[0]->GetNextSample(&child_ids_));
     }
 
     (*out_buffer) = std::make_unique<DataBuffer>(buffer_id_++, DataBuffer::kDeBFlagNone);

mindspore/ccsrc/dataset/engine/datasetops/source/sampler/weighted_random_sampler.h

@@ -51,7 +51,7 @@ class WeightedRandomSampler : public Sampler {
   // Get the sample ids.
   // @param[out] out_buffer The address of a unique_ptr to DataBuffer where the sample ids will be placed.
   // @note the sample ids (int64_t) will be placed in one Tensor and be placed into pBuffer.
-  Status GetNextBuffer(std::unique_ptr<DataBuffer> *out_buffer) override;
+  Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
  private:
   // A list of weights for each sample.

mindspore/ccsrc/dataset/engine/datasetops/source/voc_op.cc

@@ -123,7 +123,7 @@ Status VOCOp::TraverseSampleIds(const std::shared_ptr<Tensor> &sample_ids, std::
 Status VOCOp::operator()() {
   RETURN_IF_NOT_OK(LaunchThreadsAndInitOp());
   std::unique_ptr<DataBuffer> sampler_buffer;
-  RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+  RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
   while (true) {
     std::vector<int64_t> keys;
     keys.reserve(rows_per_buffer_);
@@ -134,7 +134,7 @@ Status VOCOp::operator()() {
         RETURN_STATUS_UNEXPECTED("Sampler Tensor isn't int64");
       }
       RETURN_IF_NOT_OK(TraverseSampleIds(sample_ids, &keys));
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
     }
     if (keys.empty() == false) {
       RETURN_IF_NOT_OK(io_block_queues_[(buf_cnt_++) % num_workers_]->Add(
@@ -155,7 +155,7 @@ Status VOCOp::operator()() {
         io_block_queues_[(buf_cnt_++) % num_workers_]->Add(std::make_unique<IOBlock>(IOBlock::kDeIoBlockFlagEoe)));
       RETURN_IF_NOT_OK(wp_.Wait());
       wp_.Clear();
-      RETURN_IF_NOT_OK(sampler_->GetNextBuffer(&sampler_buffer));
+      RETURN_IF_NOT_OK(sampler_->GetNextSample(&sampler_buffer));
     }
   }
 }

tests/ut/cpp/dataset/stand_alone_samplers_test.cc

@@ -68,7 +68,7 @@ TEST_F(MindDataTestStandAloneSampler, TestDistributedSampler) {
   for (int i = 0; i < 6; i++) {
     std::shared_ptr<Sampler> sampler = std::make_shared<DistributedSampler>(num_samples, 3, i % 3, (i < 3 ? false : true));
     sampler->HandshakeRandomAccessOp(&mock);
-    sampler->GetNextBuffer(&db);
+    sampler->GetNextSample(&db);
     db->GetTensor(&tensor, 0, 0);
     MS_LOG(DEBUG) << (*tensor);
     if(i < 3) {  // This is added due to std::shuffle()
@@ -90,17 +90,17 @@ TEST_F(MindDataTestStandAloneSampler, TestStandAoneSequentialSampler) {
   std::unique_ptr<DataBuffer> db;
   std::shared_ptr<Tensor> tensor;
   sampler->HandshakeRandomAccessOp(&mock);
-  sampler->GetNextBuffer(&db);
+  sampler->GetNextSample(&db);
   db->GetTensor(&tensor, 0, 0);
   EXPECT_TRUE((*tensor) == (*label1));
-  sampler->GetNextBuffer(&db);
+  sampler->GetNextSample(&db);
   db->GetTensor(&tensor, 0, 0);
   EXPECT_TRUE((*tensor) == (*label2));
   sampler->Reset();
-  sampler->GetNextBuffer(&db);
+  sampler->GetNextSample(&db);
   db->GetTensor(&tensor, 0, 0);
   EXPECT_TRUE((*tensor) == (*label1));
-  sampler->GetNextBuffer(&db);
+  sampler->GetNextSample(&db);
   db->GetTensor(&tensor, 0, 0);
   EXPECT_TRUE((*tensor) == (*label2));
 }

tests/ut/cpp/dataset/subset_random_sampler_test.cc

@@ -49,7 +49,7 @@ TEST_F(MindDataTestSubsetRandomSampler, TestAllAtOnce) {
   std::unique_ptr<DataBuffer> db;
   TensorRow row;
   std::vector<int64_t> out;
-  ASSERT_EQ(sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(sampler.GetNextSample(&db), Status::OK());
   db->PopRow(&row);
   for (const auto &t : row) {
     for (auto it = t->begin<int64_t>(); it != t->end<int64_t>(); it++) {
@@ -61,7 +61,7 @@ TEST_F(MindDataTestSubsetRandomSampler, TestAllAtOnce) {
     ASSERT_NE(in_set.find(out[i]), in_set.end());
   }
 
-  ASSERT_EQ(sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), true);
 }
 
@@ -79,7 +79,7 @@ TEST_F(MindDataTestSubsetRandomSampler, TestGetNextBuffer) {
   TensorRow row;
   std::vector<int64_t> out;
 
-  ASSERT_EQ(sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(sampler.GetNextSample(&db), Status::OK());
   int epoch = 0;
   while (!db->eoe()) {
     epoch++;
@@ -91,7 +91,7 @@ TEST_F(MindDataTestSubsetRandomSampler, TestGetNextBuffer) {
     }
     db.reset();
 
-    ASSERT_EQ(sampler.GetNextBuffer(&db), Status::OK());
+    ASSERT_EQ(sampler.GetNextSample(&db), Status::OK());
   }
 
   ASSERT_EQ(epoch, (total_samples + samples_per_buffer - 1) / samples_per_buffer);
@@ -111,7 +111,7 @@ TEST_F(MindDataTestSubsetRandomSampler, TestReset) {
   TensorRow row;
   std::vector<int64_t> out;
 
-  ASSERT_EQ(sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(sampler.GetNextSample(&db), Status::OK());
   db->PopRow(&row);
   for (const auto &t : row) {
     for (auto it = t->begin<int64_t>(); it != t->end<int64_t>(); it++) {
@@ -125,7 +125,7 @@ TEST_F(MindDataTestSubsetRandomSampler, TestReset) {
 
   sampler.Reset();
 
-  ASSERT_EQ(sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), false);
   db->PopRow(&row);
   out.clear();
@@ -139,6 +139,6 @@ TEST_F(MindDataTestSubsetRandomSampler, TestReset) {
     ASSERT_NE(in_set.find(out[i]), in_set.end());
   }
 
-  ASSERT_EQ(sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), true);
 }

tests/ut/cpp/dataset/weighted_random_sampler_test.cc

@@ -58,7 +58,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestOneshotReplacement) {
   std::unique_ptr<DataBuffer> db;
   TensorRow row;
   std::vector<uint64_t> out;
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   db->PopRow(&row);
   for (const auto &t : row) {
     for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
@@ -69,7 +69,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestOneshotReplacement) {
 
   ASSERT_EQ(num_samples, out.size());
 
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), true);
 }
 
@@ -88,7 +88,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestOneshotNoReplacement) {
   std::unique_ptr<DataBuffer> db;
   TensorRow row;
   std::vector<uint64_t> out;
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   db->PopRow(&row);
   for (const auto &t : row) {
     for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
@@ -105,7 +105,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestOneshotNoReplacement) {
     }
   }
 
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), true);
 }
 
@@ -124,7 +124,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestGetNextBufferReplacement) {
   std::unique_ptr<DataBuffer> db;
   TensorRow row;
   std::vector<uint64_t> out;
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   int epoch = 0;
   while (!db->eoe()) {
     epoch++;
@@ -135,7 +135,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestGetNextBufferReplacement) {
       }
     }
     db.reset();
-    ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+    ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   }
 
   ASSERT_EQ(epoch, (num_samples + samples_per_buffer - 1) / samples_per_buffer);
@@ -160,7 +160,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestGetNextBufferNoReplacement) {
   std::unique_ptr<DataBuffer> db;
   TensorRow row;
   std::vector<uint64_t> out;
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   int epoch = 0;
   while (!db->eoe()) {
     epoch++;
@@ -172,7 +172,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestGetNextBufferNoReplacement) {
       }
     }
     db.reset();
-    ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+    ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   }
 
   // Without replacement, each sample only drawn once.
@@ -201,7 +201,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestResetReplacement) {
   std::unique_ptr<DataBuffer> db;
   TensorRow row;
   std::vector<uint64_t> out;
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   db->PopRow(&row);
   for (const auto &t : row) {
     for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
@@ -211,13 +211,13 @@ TEST_F(MindDataTestWeightedRandomSampler, TestResetReplacement) {
   }
   ASSERT_EQ(num_samples, out.size());
 
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), true);
 
   m_sampler.Reset();
   out.clear();
 
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   db->PopRow(&row);
   for (const auto &t : row) {
     for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
@@ -227,7 +227,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestResetReplacement) {
   }
   ASSERT_EQ(num_samples, out.size());
 
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), true);
 }
 
@@ -246,7 +246,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestResetNoReplacement) {
   std::unique_ptr<DataBuffer> db;
   TensorRow row;
   std::vector<uint64_t> out;
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   db->PopRow(&row);
   for (const auto &t : row) {
     for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
@@ -256,7 +256,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestResetNoReplacement) {
   }
   ASSERT_EQ(num_samples, out.size());
 
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), true);
 
   m_sampler.Reset();
@@ -265,7 +265,7 @@ TEST_F(MindDataTestWeightedRandomSampler, TestResetNoReplacement) {
   freq.resize(total_samples, 0);
   MS_LOG(INFO) << "Resetting sampler";
 
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   db->PopRow(&row);
   for (const auto &t : row) {
     for (auto it = t->begin<uint64_t>(); it != t->end<uint64_t>(); it++) {
@@ -282,6 +282,6 @@ TEST_F(MindDataTestWeightedRandomSampler, TestResetNoReplacement) {
     }
   }
 
-  ASSERT_EQ(m_sampler.GetNextBuffer(&db), Status::OK());
+  ASSERT_EQ(m_sampler.GetNextSample(&db), Status::OK());
   ASSERT_EQ(db->eoe(), true);
 }