!9482 Remove Repeat(1), Take(-1), and Skip(0) in IR optimizer

From: @nsyca
Reviewed-by: 
Signed-off-by:

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

@@ -490,12 +490,6 @@ RenameDataset::RenameDataset(std::shared_ptr<Dataset> input, const std::vector<s
 #endif
 
 RepeatDataset::RepeatDataset(std::shared_ptr<Dataset> input, int32_t count) {
-  // Workaround for repeat == 1, do not inject repeat.
-  if (count == 1) {
-    ir_node_ = input->IRNode();
-    return;
-  }
-
   auto ds = std::make_shared<RepeatNode>(input->IRNode(), count);
 
   ir_node_ = std::static_pointer_cast<DatasetNode>(ds);
@@ -516,13 +510,6 @@ SkipDataset::SkipDataset(std::shared_ptr<Dataset> input, int32_t count) {
 }
 
 TakeDataset::TakeDataset(std::shared_ptr<Dataset> input, int32_t count) {
-  // If count is greater than the number of element in dataset or equal to -1,
-  // all the element in dataset will be taken
-  if (count == -1) {
-    ir_node_ = input->IRNode();
-    return;
-  }
-
   auto ds = std::make_shared<TakeNode>(input->IRNode(), count);
 
   ir_node_ = std::static_pointer_cast<DatasetNode>(ds);

mindspore/ccsrc/minddata/dataset/engine/data_schema.h

@@ -66,7 +66,7 @@ class ColDescriptor {
   ///     an unknown dimension, then the output shape returned shall resolve dimensions as needed.
   /// \param[in] num_elements - The number of elements in the data for a Tensor
   /// \param[inout] out_shape - The materialized output Tensor shape
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status MaterializeTensorShape(int32_t num_elements, TensorShape *out_shape) const;
 
   /// \brief << Stream output operator overload
@@ -124,13 +124,13 @@ class DataSchema {
   /// \brief Parses a schema json file and populates the columns and meta info.
   /// \param[in] schema_file_path - the schema file that has the column's info to load
   /// \param[in] columns_to_load - list of strings for columns to load. if empty, assumes all columns.
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status LoadSchemaFile(const std::string &schema_file_path, const std::vector<std::string> &columns_to_load);
 
   /// \brief Parses a schema JSON string and populates the columns and meta info.
   /// \param[in] schema_json_string - the schema file that has the column's info to load
   /// \param[in] columns_to_load - list of strings for columns to load. if empty, assumes all columns.
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status LoadSchemaString(const std::string &schema_json_string, const std::vector<std::string> &columns_to_load);
 
   /// \brief A print method typically used for debugging
@@ -148,7 +148,7 @@ class DataSchema {
 
   /// \brief Adds a column descriptor to the schema
   /// \param[in] cd - The ColDescriptor to add
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status AddColumn(const ColDescriptor &cd);
 
   /// \brief getter
@@ -169,7 +169,7 @@ class DataSchema {
 
   /// \brief Loops through all columns in the schema and returns a map with the column name to column index number.
   /// \param[inout] out_column_name_map - The output map of columns names to column index
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status GetColumnNameMap(std::unordered_map<std::string, int32_t> *out_column_name_map);
 
  private:
@@ -177,7 +177,7 @@ class DataSchema {
   ///     does not follow any particular order (json standard does not enforce any ordering protocol).
   ///     This one produces a schema that contains all of the columns from the schema file.
   /// \param[in] column_tree - The nlohmann tree from the json file to parse
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status AnyOrderLoad(nlohmann::json column_tree);
 
   /// \brief Internal helper function. For each input column name, perform a lookup to the json document to
@@ -185,18 +185,18 @@ class DataSchema {
   ///     descriptor and add to the schema in the order in which the input column names are given.
   /// \param[in] column_tree - The nlohmann tree from the json file to parse
   /// \param[in] columns_to_load - list of strings for the columns to add to the schema
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status ColumnOrderLoad(nlohmann::json column_tree, const std::vector<std::string> &columns_to_load);
 
   /// \brief Internal helper function. Given the json tree for a given column, load it into our schema.
   /// \param[in] columnTree - The nlohmann child tree for a given column to load.
   /// \param[in] col_name - The string name of the column for that subtree.
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status ColumnLoad(nlohmann::json column_child_tree, const std::string &col_name);
 
   /// \brief Internal helper function. Performs sanity checks on the json file setup.
   /// \param[in] js - The nlohmann tree for the schema file
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status PreLoadExceptionCheck(const nlohmann::json &js);
 
   std::vector<ColDescriptor> col_descs_;  // Vector of column descriptors

mindspore/ccsrc/minddata/dataset/engine/dataset_iterator.h

@@ -53,7 +53,7 @@ class IteratorBase {
   // functionality exists in the derived versions of this function.
   // @param out_row - A TensorRow (vector of shared pointers to Tensors).  If any of the of data
   // messages are encountered (such as eoe or eof), then an empty TensorRow is returned back.
-  // @return Status - The error code return
+  // @return Status The status code returned
   // @note The position of a Tensor/column might be different from the initial column order
   // in corresponding Dataset Op. User must be aware that MapOp, ZipOps, and others might change
   // the column ordering.
@@ -97,17 +97,17 @@ class DatasetIterator : public IteratorBase {
   // from the tree root node directly.
   // @param out_row - A TensorRow (vector of shared pointers to Tensors).  If any of the of data
   // messages are encountered (such as eoe or eof), then an empty TensorRow is returned back.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status FetchNextTensorRow(TensorRow *out_row) override;
 
   // Fetches the next tensor row into device row, and returns it's shape.
   // @param out_shapes - A vector of tensor shapes (one shape per column)
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetOutputShapes(std::vector<TensorShape> *out_shapes);
 
   // Fetches the next tensor row into device row, and returns it's shape.
   // @param outShapes - A vector of tensor shapes (one shape per column)
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetOutputTypes(std::vector<DataType> *out_types);
 
   // Getter
@@ -140,12 +140,12 @@ class ChildIterator : public IteratorBase {
   // only from the child/worker id as given from the constructor.
   // @param out_row - A TensorRow (vector of shared pointers to Tensors).  If any of the of data
   // messages are encountered (such as eoe or eof), then an empty TensorRow is returned back.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status FetchNextTensorRow(TensorRow *out_row) override;
 
   // This function drains buffer until next eoe has been received.
   // It will be a no-op if the previous row returned is empty.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Drain();
 
   // Getter

mindspore/ccsrc/minddata/dataset/engine/datasetops/barrier_op.h

@@ -134,7 +134,7 @@ class BarrierOp : public PipelineOp {
   // Class functor operator () override.
   // All dataset ops operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Handles preprocessing of the main loop, used when starting new epoch

mindspore/ccsrc/minddata/dataset/engine/datasetops/batch_op.h

@@ -112,12 +112,12 @@ class BatchOp : public ParallelOp {
 #endif
 
     // @param std::shared_ptr<BatchOp>  *ptr pointer to shared_ptr, actual return arg
-    // @return Status - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<BatchOp> *);
 
    private:
     // Sanity check for builder class args
-    // @return Status - The error code return
+    // @return Status The status code returned
     Status SanityCheck();
 
     bool builder_drop_;
@@ -167,11 +167,11 @@ class BatchOp : public ParallelOp {
   ~BatchOp() {}
 
   // @param int32_t workerId
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status EofReceived(int32_t) override;
 
   // @param int32_t workerId
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status EoeReceived(int32_t) override;
 
   // A print method typically used for debugging
@@ -190,7 +190,7 @@ class BatchOp : public ParallelOp {
   }
 
   // Main loop of batch
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Base-class override for NodePass visitor acceptor.
@@ -214,14 +214,14 @@ class BatchOp : public ParallelOp {
   // @param const std::unique_ptr<TensorQTable> *dest - dest_table to hold batched rows
   // @param int32_t size - batch_size
   // @param const std::unordered_map<std::string, int32_t>& column_name_id_map - column names to index mapping
-  // @return Status - The error code return
+  // @return Status The status code returned
   static Status BatchRows(const std::unique_ptr<TensorQTable> *src, const std::unique_ptr<TensorQTable> *dest,
                           dsize_t batch_size);
 
   // @param table
   // @param const PadInfo &pad_info pad info
   // @param const std::unordered_map<std::string, int32_t>& column_name_id_map - column names to index mapping
-  // @return Status - The error code return
+  // @return Status The status code returned
   static Status PadColumns(std::unique_ptr<TensorQTable> *table, const PadInfo &pad_info,
                            const std::unordered_map<std::string, int32_t> &column_name_id_map);
 
@@ -233,18 +233,18 @@ class BatchOp : public ParallelOp {
  private:
   // Worker thread for doing the memcpy of batch
   // @param int32_t param workerId
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // Generate buffer with batched tensors
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status MakeBatchedBuffer(std::pair<std::unique_ptr<TensorQTable>, CBatchInfo> table_pair,
                            std::unique_ptr<DataBuffer> *db);
 
 #ifdef ENABLE_PYTHON
   // Function that calls pyfunc to perform map on batch
   // @param (std::pair<std::unique_ptr<TensorQTable>, batch_stats> *table_pair - contains un-batched tensor
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status MapColumns(std::pair<std::unique_ptr<TensorQTable>, CBatchInfo> *table_pair);
 #endif
 
@@ -253,7 +253,7 @@ class BatchOp : public ParallelOp {
   // @param std::set<int32_t> *cols, col ids to perform pad on
   // @param std::vector<float> *vals, default padding value for each column
   // @param std::vector<std::vector<dsize_t>> *shapes, padding shape specified by user
-  // @return Status - The error code return
+  // @return Status The status code returned
   static Status UnpackPadInfo(const PadInfo &pad_info,
                               const std::unordered_map<std::string, int32_t> &column_name_id_map,
                               std::set<int32_t> *pad_cols, std::vector<std::shared_ptr<Tensor>> *pad_vals,
@@ -264,20 +264,20 @@ class BatchOp : public ParallelOp {
   int32_t num_consumers() const override { return 1; }
 
   // get the batch size for next batch
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetBatchSize(int32_t *batch_size, CBatchInfo info);
 
   // Do the initialization of all queues then start all worker threads
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LaunchThreadsAndInitOp();
 
 #ifdef ENABLE_PYTHON
   // Invoke batch size function with current BatchInfo to generate batch size.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InvokeBatchSizeFunc(int32_t *batch_size, CBatchInfo info);
 
   // Invoke batch map function with current BatchInfo to generate tensors to batch.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InvokeBatchMapFunc(TensorTable *input, TensorTable *output, CBatchInfo info);
 #endif
 

mindspore/ccsrc/minddata/dataset/engine/datasetops/bucket_batch_by_length_op.h

@@ -107,7 +107,7 @@ class BucketBatchByLengthOp : public PipelineOp {
 
   // Might need to batch remaining buckets after receiving eoe, so override this method.
   // @param int32_t workerId
-  // @return Status - The error code returned
+  // @return Status The status code returned
   Status EoeReceived(int32_t) override;
 
   std::string Name() const override { return kBucketBatchByLengthOp; }
@@ -123,7 +123,7 @@ class BucketBatchByLengthOp : public PipelineOp {
   }
 
   // Main loop of batch
-  // @return Status - The error code returned
+  // @return Status The status code returned
   Status operator()() override;
 
  private:

mindspore/ccsrc/minddata/dataset/engine/datasetops/build_sentence_piece_vocab_op.h

@@ -104,7 +104,7 @@ class BuildSentencePieceVocabOp : public PipelineOp {
 
     // The builder "build" method creates the final object.
     // @param std::shared_ptr<BuildVocabOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<BuildSentencePieceVocabOp> *op);
 
    private:

mindspore/ccsrc/minddata/dataset/engine/datasetops/build_vocab_op.h

@@ -110,7 +110,7 @@ class BuildVocabOp : public ParallelOp {
 
     // The builder "build" method creates the final object.
     // @param std::shared_ptr<BuildVocabOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<BuildVocabOp> *op);
 
    private:

mindspore/ccsrc/minddata/dataset/engine/datasetops/cache_base_op.h

@@ -53,7 +53,7 @@ class CacheBase : public ParallelOp {
   /// \brief Overrides base class reset method.  When an operator does a reset, it cleans up any state
   /// info from it's previous execution and then initializes itself so that it can be executed
   /// again.
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status Reset() override;
 
   /// \brief A print method typically used for debugging

mindspore/ccsrc/minddata/dataset/engine/datasetops/cache_lookup_op.h

@@ -80,7 +80,7 @@ class CacheLookupOp : public CacheBase, public SamplerRT {
     std::shared_ptr<SamplerRT> build_sampler_;
 
     // Check if the required parameters are set by the builder.
-    // \return Status The error code return
+    // \return Status The status code returned
     Status SanityCheck() const;
   };
   /// \brief Constructor

mindspore/ccsrc/minddata/dataset/engine/datasetops/cache_merge_op.h

@@ -136,7 +136,7 @@ class CacheMergeOp : public ParallelOp {
     std::shared_ptr<SamplerRT> build_sampler_;
 
     /// Check if the required parameters are set by the builder.
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status SanityCheck() const;
   };
 
@@ -189,7 +189,7 @@ class CacheMergeOp : public ParallelOp {
 
   /// \brief Base-class override for handling cases when an eof is received.
   /// \param worker_id - The worker id
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status EofReceived(int32_t worker_id) override;
 
  protected:

mindspore/ccsrc/minddata/dataset/engine/datasetops/cache_op.h

@@ -99,7 +99,7 @@ class CacheOp : public CacheBase, public RandomAccessOp {
     std::shared_ptr<SamplerRT> build_sampler_;
 
     /// \brief Check if the required parameters are set by the builder.
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status SanityCheck() const;
   };
 
@@ -119,7 +119,7 @@ class CacheOp : public CacheBase, public RandomAccessOp {
   /// \brief Base-class override for special eoe handler.
   /// CacheOp must override this because it shall not perform default handling of eoe. Instead
   /// the CacheOp manages actions related to the end of the epoch.
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status EoeReceived(int32_t worker_id) override;
   /// \brief Base-class override for NodePass pre-visit acceptor
   /// \param[in] p The node to visit
@@ -133,7 +133,7 @@ class CacheOp : public CacheBase, public RandomAccessOp {
   Status Accept(NodePass *p, bool *modified) override;
   /// \brief Base-class override for handling cases when an eof is received.
   /// \param worker_id - The worker id
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status EofReceived(int32_t worker_id) override;
   Status operator()() override;
   Status WorkerEntry(int32_t worker_id) override;
@@ -159,7 +159,7 @@ class CacheOp : public CacheBase, public RandomAccessOp {
   Status CacheAllRows(int32_t worker_id);
   Status RegisterResources() override;
   /// \brief Private function for cache setup/init work just after construction
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status InitCache();
 };
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/engine/datasetops/concat_op.h

@@ -94,7 +94,7 @@ class ConcatOp : public PipelineOp {
 
   // All dataset ops operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Op name getter

mindspore/ccsrc/minddata/dataset/engine/datasetops/dataset_op.h

@@ -146,14 +146,14 @@ class DatasetOp : public std::enable_shared_from_this<DatasetOp> {
   /// DatasetOps operate by launching a thread (see ExecutionTree).
   /// This pure virtual version makes the requirement that derived classes must provide a functor
   /// that will execute their main runtime loop code.
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   virtual Status operator()() = 0;
 
   /// \brief Gets the next buffer from the given child
   /// \notes See GetNextInput for similar function that has built-in message handling
   /// \param p_buffer - The shared pointer for the fetched buffer to return (by reference)
   /// \param worker_id - The worker id
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   virtual Status GetNextBuffer(std::unique_ptr<DataBuffer> *p_buffer, int32_t worker_id) {
     return GetNextBuffer(p_buffer, worker_id, false);
   }
@@ -161,7 +161,7 @@ class DatasetOp : public std::enable_shared_from_this<DatasetOp> {
   /// \brief Gets the next buffer from the given child
   /// \notes See GetNextInput for similar function that has built-in message handling
   /// \param p_buffer - The shared pointer for the fetched buffer to return (by reference)
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   virtual Status GetNextBuffer(std::unique_ptr<DataBuffer> *p_buffer) { return GetNextBuffer(p_buffer, 0, false); }
 
   /// \brief Gets the next buffer from the given child
@@ -169,7 +169,7 @@ class DatasetOp : public std::enable_shared_from_this<DatasetOp> {
   /// \param p_buffer - The shared pointer for the fetched buffer to return (by reference)
   /// \param worker_id - The worker id
   /// \param retry_if_eoe Set this flag to true to allow calling pop() again after the first pop() returns EOE.
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   virtual Status GetNextBuffer(std::unique_ptr<DataBuffer> *p_buffer, int32_t worker_id, bool retry_if_eoe);
 
   /// \brief Gets the next buffer from the given child .  This function also has built-in eoe and eof
@@ -177,7 +177,7 @@ class DatasetOp : public std::enable_shared_from_this<DatasetOp> {
   /// those messages are received.
   /// \param p_buffer - The shared pointer for the fetched buffer to return (by reference)
   /// \param worker_id - The worker id
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   Status GetNextInput(std::unique_ptr<DataBuffer> *p_buffer, int32_t worker_id = 0, int32_t child_index = 0);
 
   /// \brief Gets the batch size
@@ -200,19 +200,19 @@ class DatasetOp : public std::enable_shared_from_this<DatasetOp> {
   /// The base class implementation simply flows the eoe message to output. Derived classes
   /// may override if they need to perform special eoe handling.
   /// \param worker_id - The worker id
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   virtual Status EoeReceived(int32_t worker_id);
 
   /// \brief Performs handling for when an eof message is received.
   /// The base class implementation simply flows the eof message to output. Derived classes
   /// may override if they need to perform special eof handling.
   /// \param worker_id - The worker id
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   virtual Status EofReceived(int32_t worker_id);
 
   /// \brief Derived classes may implement the reset function if the operator is stateful and needs
   /// specific reset handling that is not contained in this common code version of the reset
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   virtual Status Reset();
 
   /// \brief During tree prepare phase, operators may have specific pre-operations to perform depending on

mindspore/ccsrc/minddata/dataset/engine/datasetops/filter_op.h

@@ -79,7 +79,7 @@ class FilterOp : public ParallelOp {
 
    private:
     // Sanity check for builder class args.
-    // @return Status - The error code return.
+    // @return Status The status code returned.
     Status SanityCheck();
     std::vector<std::string> build_in_col_names_;
     std::shared_ptr<TensorOp> builder_predicate_func_;
@@ -105,15 +105,15 @@ class FilterOp : public ParallelOp {
   // Class functor operator () override.
   // All dataset ops operate by launching a thread (see ExecutionTree),This class functor will
   // provide the master loop that drives the logic for performing the work.
-  // @return Status The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // @param int32_t workerId.
-  // @return Status - The error code return.
+  // @return Status The status code returned.
   Status EofReceived(int32_t) override;
 
   // @param int32_t workerId.
-  // @return Status - The error code return.
+  // @return Status The status code returned.
   Status EoeReceived(int32_t) override;
 
   // A print method typically used for debugging.
@@ -151,34 +151,34 @@ class FilterOp : public ParallelOp {
   // logic of FilterOp, getting the data from previous Op, validating user specified column names,
   // applying predicate to each of the data, filter the data when predicate result is false.
   // @param worker_id The id assigned to this thread/worker upon creation.
-  // @return Status The error code return.
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;  //  In: workerId assigned by tree_
 
   // Filter the data by  predicate function .
   // @param in_buffer input data buffer.
   // @param to_proess_indices Indices of columns to be processed.
   // @param out data buffer that are filtered by predicate.
-  // @return Status The error code return.
+  // @return Status The status code returned
   Status WorkerCompute(DataBuffer *in_buffer, std::unique_ptr<TensorQTable> *out);
 
   // Collector databuffer.
-  // @return Status The error code return.
+  // @return Status The status code returned
   Status Collector();
 
   // @param input tensor vector.
-  // @return Status - The error code return.
+  // @return Status The status code returned.
   Status CheckInput(const TensorRow &input) const;
 
   // Invoke python func.
   // @param input tensor vector.
   // @param the result of predicate.
-  // @return Status - The error code return.
+  // @return Status The status code returned.
   Status InvokePredicateFunc(const TensorRow &input, bool *out_predicate);
 
   // Private function for validating if each of the user specified input column names
   // exist in the DataBuffer.
   // @param input_columns The vector of input column names used in the current thread.
-  // @return Status The error code return.
+  // @return Status The status code returned
   Status ValidateInColumns(const std::vector<std::string> *input_columns);
 
   // Private function for checking the column legality

mindspore/ccsrc/minddata/dataset/engine/datasetops/map_op/map_op.h

@@ -133,7 +133,7 @@ class MapOp : public ParallelOp {
     int32_t build_op_connector_size_;
 
     // Check if the required parameters are set by the builder.
-    // @return Status The error code return
+    // @return Status The status code returned
     Status sanityCheck() const;
   };
 
@@ -170,7 +170,7 @@ class MapOp : public ParallelOp {
   // provide the master loop that drives the logic for performing the work
   // This main thread creates local queues, pulls databuffers from the previous
   // op's Connector and distributes them to the local queues. Workers pull from the local queues.
-  // @return Status The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Getter
@@ -239,7 +239,7 @@ class MapOp : public ParallelOp {
   // applying a list of TensorOps to each of the data, process the results and then
   // pushing them back to MapOp's output Connector to be fetched by the next Op.
   // @param worker_id The id assigned to this thread/worker upon creation.
-  // @return Status The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;  //  In: workerId assigned by tree_
 
   // Private function for worker thread to perform TensorOp's compute function and get the result.

mindspore/ccsrc/minddata/dataset/engine/datasetops/parallel_op.h

@@ -89,7 +89,7 @@ class ParallelOp : public DatasetOp {
   }
 
   // Override base class reset to provide reset actions specific to the ParallelOp class.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Getter
@@ -115,7 +115,7 @@ class ParallelOp : public DatasetOp {
  protected:
   // Interface for derived classes to implement. All derived classes must provide the entry
   // function with the main execution loop for worker threads.
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status WorkerEntry(int32_t workerId) = 0;
 
   /// This function is only intended to be called by CallbackManager within the master thread of ParallelOp

mindspore/ccsrc/minddata/dataset/engine/datasetops/project_op.h

@@ -75,7 +75,7 @@ class ProjectOp : public PipelineOp {
   // However, the ProjectOp is defined as a inlined operator, so it is invalid to launch the
   // functor since this op runs inlined inside another operator. The function is overloaded to
   // ensure that it is not called by mistake (it will generate an error).
-  // @return Status - The error code returned.
+  // @return Status The status code returned
   Status operator()() override;
 
   // Gets a buffer from the child node and projects that buffer. The caller is typically our parent node.
@@ -93,12 +93,12 @@ class ProjectOp : public PipelineOp {
 
   // Base-class override for special eoe handler.
   // Inline operators must override this because there is no connector to push eoe onto.
-  // @return Status - The error code returned.
+  // @return Status The status code returned
   Status EoeReceived(int32_t worker_id) override;
 
   // Base-class override for special eof handler.
   // Inline operators must override this because there is no connector to push eof onto.
-  // @return Status - The error code returned.
+  // @return Status The status code returned
   Status EofReceived(int32_t worker_id) override;
 
   // Base-class override for NodePass visitor acceptor.

mindspore/ccsrc/minddata/dataset/engine/datasetops/rename_op.h

@@ -107,7 +107,7 @@ class RenameOp : public PipelineOp {
   // Class functor operator () override.
   // All dataset ops operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Base-class override for NodePass visitor acceptor.

mindspore/ccsrc/minddata/dataset/engine/datasetops/repeat_op.h

@@ -78,7 +78,7 @@ class RepeatOp : public PipelineOp {
   // However, the RepeatOp is defined as a inlined operator, so it is invalid to launch the
   // functor since this op runs inlined inside another operator.  The function is overloaded to
   // ensure that it is not called by mistake (it will generate an error).
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // This function returns the buffer that is at the top of our output connector. The caller is
@@ -90,7 +90,7 @@ class RepeatOp : public PipelineOp {
   // @param p_buffer - output pointer to the buffer that it will fetch.
   // @param worker_id - The worker id
   // @param retry_if_eoe Set this flag to true to allow calling pop() again after the first pop() returns EOE.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNextBuffer(std::unique_ptr<DataBuffer> *p_buffer, int32_t worker_id, bool retry_if_eoe) override;
 
   // Base-class override for handling cases when an eoe is received.
@@ -130,7 +130,7 @@ class RepeatOp : public PipelineOp {
   int32_t num_repeats() { return num_repeats_; }
 
   /// \brief reset Op
-  /// \@return Status - The error code return
+  /// \@return Status The status code returned
   Status Reset() override;
 
   int64_t GetTreeRepeatCount() override;

mindspore/ccsrc/minddata/dataset/engine/datasetops/shuffle_op.h

@@ -146,13 +146,13 @@ class ShuffleOp : public PipelineOp {
   // Class functor operator () override.
   // All dataset ops operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Base-class override for special eoe handler.
   // ShuffleOp must override this because it shall not perform default handling of eoe. Instead
   // the ShuffleOp needs to manage actions related to the end of the epoch itself.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status EoeReceived(int32_t worker_id) override;
 
   // Base-class override for NodePass visitor acceptor.
@@ -167,17 +167,17 @@ class ShuffleOp : public PipelineOp {
 
  private:
   // Private function to add a new row to the shuffle buffer.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status AddRowToShuffleBuffer(TensorRow new_shuffle_row);
 
   // Private function to populate the shuffle buffer initially by fetching from the child output
   // connector until the shuffle buffer is full (or there is no more data coming).
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InitShuffleBuffer();
 
   // Private function to re-init the shuffle op for another epoch.  Shuffle op calls this by
   // itself rather than waiting for the reset driven from operators above it in the pipeline.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status SelfReset();
 
   int32_t shuffle_size_;  // User config for the size of the shuffle buffer (number of rows)

mindspore/ccsrc/minddata/dataset/engine/datasetops/skip_op.h

@@ -63,7 +63,7 @@ class SkipOp : public PipelineOp {
   // Class functor operator () override.
   // All dataset ops operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Base-class override for handling cases when an eoe is received.

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

@@ -130,12 +130,12 @@ class AlbumOp : public ParallelOp, public RandomAccessOp {
     }
 
     /// \brief Check validity of input args
-    /// \return - The error code returned
+    /// \return Status The status code returned
     Status SanityCheck();
 
     /// \brief The builder "build" method creates the final object.
     /// \param[inout] std::shared_ptr<AlbumOp> *op - DatasetOp
-    /// \return - The error code returned
+    /// \return Status The status code returned
     Status Build(std::shared_ptr<AlbumOp> *op);
 
    private:
@@ -168,18 +168,18 @@ class AlbumOp : public ParallelOp, public RandomAccessOp {
   ~AlbumOp() = default;
 
   /// \brief Initialize AlbumOp related var, calls the function to walk all files
-  /// \return - The error code returned
+  /// \return Status The status code returned
   Status PrescanEntry();
 
   /// \brief Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   /// \param[in] int32_t workerId - id of each worker
-  /// \return Status - The error code returned
+  /// \return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   /// \brief Main Loop of AlbumOp
   ///     Master thread: Fill IOBlockQueue, then goes to sleep
   ///     Worker thread: pulls IOBlock from IOBlockQueue, work on it then put buffer to mOutConnector
-  /// \return Status - The error code returned
+  /// \return Status The status code returned
   Status operator()() override;
 
   /// \brief A print method typically used for debugging
@@ -204,93 +204,93 @@ class AlbumOp : public ParallelOp, public RandomAccessOp {
 
  private:
   /// \brief Initialize Sampler, calls sampler->Init() within
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status InitSampler();
 
   /// \brief Load image to tensor row
   /// \param[in] image_file Image name of file
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadImageTensor(const std::string &image_file, uint32_t col_num, TensorRow *row);
 
   /// \brief Load vector of ints to tensor, append tensor to tensor row
   /// \param[in] json_obj Json object containing multi-dimensional label
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadIntArrayTensor(const nlohmann::json &json_obj, uint32_t col_num, TensorRow *row);
 
   /// \brief Load vector of floatss to tensor, append tensor to tensor row
   /// \param[in] json_obj Json object containing array data
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadFloatArrayTensor(const nlohmann::json &json_obj, uint32_t col_num, TensorRow *row);
 
   /// \brief Load string array into a tensor, append tensor to tensor row
   /// \param[in] json_obj Json object containing string tensor
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadStringArrayTensor(const nlohmann::json &json_obj, uint32_t col_num, TensorRow *row);
 
   /// \brief Load string into a tensor, append tensor to tensor row
   /// \param[in] json_obj Json object containing string tensor
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadStringTensor(const nlohmann::json &json_obj, uint32_t col_num, TensorRow *row);
 
   /// \brief Load float value to tensor row
   /// \param[in] json_obj Json object containing float
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadFloatTensor(const nlohmann::json &json_obj, uint32_t col_num, TensorRow *row);
 
   /// \brief Load int value to tensor row
   /// \param[in] json_obj Json object containing int
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadIntTensor(const nlohmann::json &json_obj, uint32_t col_num, TensorRow *row);
 
   /// \brief Load emtpy tensor to tensor row
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadEmptyTensor(uint32_t col_num, TensorRow *row);
 
   /// \brief Load id from file name to tensor row
   /// \param[in] file The file name to get ID from
   /// \param[in] col_num Column num in schema
   /// \param[inout] row Tensor row to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadIDTensor(const std::string &file, uint32_t col_num, TensorRow *row);
 
   /// \brief Load a tensor row according to a json file
   /// \param[in] row_id_type row_id - id for this tensor row
   /// \param[in] ImageColumns file Json file location
   /// \param[inout] TensorRow row Json content stored into a tensor row
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadTensorRow(row_id_type row_id, const std::string &file, TensorRow *row);
 
   /// \param[in] const std::vector<int64_t> &keys Keys in ioblock
   /// \param[inout] std::unique_ptr<DataBuffer> db Databuffer to push to
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LoadBuffer(const std::vector<int64_t> &keys, std::unique_ptr<DataBuffer> *db);
 
   /// \brief Called first when function is called
-  /// \return Status The error code returned
+  /// \return Status The status code returned
   Status LaunchThreadsAndInitOp();
 
   /// \brief reset Op
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Reset() override;
 
   // Private function for computing the assignment of the column name map.
-  // @return Status The error code returned
+  // @return Status The status code returned
   Status ComputeColMap() override;
 
   int32_t rows_per_buffer_;

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

@@ -116,12 +116,12 @@ class CelebAOp : public ParallelOp, RandomAccessOp {
       return *this;
     }
     // Check validity of input args
-    // @return - The error code return
+    // @return Status The status code returned
     Status SanityCheck();
 
     // The builder "build" method creates the final object.
     // @param std::shared_ptr<CelebAOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<CelebAOp> *op);
 
    private:
@@ -151,12 +151,12 @@ class CelebAOp : public ParallelOp, RandomAccessOp {
   // Main Loop of CelebAOp
   // Master thread: Fill IOBlockQueue, then goes to sleep
   // Worker thread: pulls IOBlock from IOBlockQueue, work on it then put buffer to mOutConnector
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param int32_t worker_id - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // A print method typically used for debugging
@@ -166,7 +166,7 @@ class CelebAOp : public ParallelOp, RandomAccessOp {
 
   // Method in operator(), to fill IOBlockQueue
   // @param std::unique_ptr<DataBuffer> sampler_buffer - to fill IOBlockQueue
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status AddIOBlock(std::unique_ptr<DataBuffer> *data_buffer);
 
   /// \brief Base-class override for NodePass visitor acceptor
@@ -199,14 +199,14 @@ class CelebAOp : public ParallelOp, RandomAccessOp {
 
   // @param const std::vector<int64_t> &keys - keys in ioblock
   // @param std::unique_ptr<DataBuffer> db
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadBuffer(const std::vector<int64_t> &keys, std::unique_ptr<DataBuffer> *db);
 
   // Load a tensor row according to a pair
   // @param row_id_type row_id - id for this tensor row
   // @param std::pair - <image_file,<label>>
   // @param TensorRow row - image & label read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadTensorRow(row_id_type row_id, const std::pair<std::string, std::vector<int32_t>> &image_label,
                        TensorRow *row);
 
@@ -215,7 +215,7 @@ class CelebAOp : public ParallelOp, RandomAccessOp {
   bool CheckDatasetTypeValid();
 
   // reset Op
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Private function for computing the assignment of the column name map.

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

@@ -109,12 +109,12 @@ class CifarOp : public ParallelOp, public RandomAccessOp {
     }
 
     // Check validity of input args
-    // @return - The error code return
+    // @return Status The status code returned
     Status SanityCheck();
 
     // The builder "build" method creates the final object.
     // @param std::shared_ptr<CifarOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<CifarOp> *op);
 
    private:
@@ -144,13 +144,13 @@ class CifarOp : public ParallelOp, public RandomAccessOp {
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param uint32_t workerId - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // Main Loop of CifarOp
   // Master thread: Fill IOBlockQueue, then goes to sleep
   // Worker thread: pulls IOBlock from IOBlockQueue, work on it then put buffer to mOutConnector
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // A print method typically used for debugging
@@ -177,18 +177,18 @@ class CifarOp : public ParallelOp, public RandomAccessOp {
 
  private:
   // Initialize Sampler, calls sampler->Init() within
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InitSampler();
 
   // Load a tensor row according to a pair
   // @param uint64_t index - index need to load
   // @param TensorRow row - image & label read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadTensorRow(uint64_t index, TensorRow *row);
 
   // @param const std::vector<uint64_t> &keys - keys in ioblock
   // @param std::unique_ptr<DataBuffer> db
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadBuffer(const std::vector<int64_t> &keys, std::unique_ptr<DataBuffer> *db);
 
   // Read block data from cifar file
@@ -200,7 +200,7 @@ class CifarOp : public ParallelOp, public RandomAccessOp {
   Status LaunchThreadsAndInitOp();
 
   // reset Op
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Get cifar files in dir
@@ -221,7 +221,7 @@ class CifarOp : public ParallelOp, public RandomAccessOp {
 
   // Method derived from RandomAccess Op, enable Sampler to get all ids for each calss
   // @param (std::map<uint64_t, std::vector<uint64_t >> * map - key label, val all ids for this class
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetClassIds(std::map<int32_t, std::vector<int64_t>> *cls_ids) const override;
 
   // Private function for computing the assignment of the column name map.

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

@@ -133,12 +133,12 @@ class CocoOp : public ParallelOp, public RandomAccessOp {
     }
 
     // Check validity of input args
-    // @return = The error code return
+    // @return Status The status code returned
     Status SanityCheck();
 
     // The builder "Build" method creates the final object.
     // @param std::shared_ptr<CocoOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<CocoOp> *op);
 
    private:
@@ -173,13 +173,13 @@ class CocoOp : public ParallelOp, public RandomAccessOp {
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param int32_t workerId - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // Main Loop of CocoOp
   // Master thread: Fill IOBlockQueue, then goes to sleep
   // Worker thread: pulls IOBlock from IOBlockQueue, work on it the put buffer to mOutConnector
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // A print method typically used for debugging
@@ -214,19 +214,19 @@ class CocoOp : public ParallelOp, public RandomAccessOp {
   std::string Name() const override { return "CocoOp"; }
 
   /// \brief Gets the class indexing
-  /// \return Status - The status code return
+  /// \return Status The status code returned
   Status GetClassIndexing(std::vector<std::pair<std::string, std::vector<int32_t>>> *output_class_indexing) override;
 
  private:
   // Initialize Sampler, calls sampler->Init() within
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InitSampler();
 
   // Load a tensor row according to image id
   // @param row_id_type row_id - id for this tensor row
   // @param std::string image_id - image id
   // @param TensorRow row - image & target read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadTensorRow(row_id_type row_id, const std::string &image_id, TensorRow *row);
 
   // Load a tensor row with vector which a vector to a tensor
@@ -235,7 +235,7 @@ class CocoOp : public ParallelOp, public RandomAccessOp {
   // @param std::shared_ptr<Tensor> image - image tensor
   // @param std::shared_ptr<Tensor> coordinate - coordinate tensor
   // @param TensorRow row - image & target read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadDetectionTensorRow(row_id_type row_id, const std::string &image_id, std::shared_ptr<Tensor> image,
                                 std::shared_ptr<Tensor> coordinate, TensorRow *trow);
 
@@ -245,7 +245,7 @@ class CocoOp : public ParallelOp, public RandomAccessOp {
   // @param std::shared_ptr<Tensor> image - image tensor
   // @param std::shared_ptr<Tensor> coordinate - coordinate tensor
   // @param TensorRow row - image & target read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadSimpleTensorRow(row_id_type row_id, const std::string &image_id, std::shared_ptr<Tensor> image,
                              std::shared_ptr<Tensor> coordinate, TensorRow *trow);
 
@@ -255,69 +255,69 @@ class CocoOp : public ParallelOp, public RandomAccessOp {
   // @param std::shared_ptr<Tensor> image - image tensor
   // @param std::shared_ptr<Tensor> coordinate - coordinate tensor
   // @param TensorRow row - image & target read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadMixTensorRow(row_id_type row_id, const std::string &image_id, std::shared_ptr<Tensor> image,
                           std::shared_ptr<Tensor> coordinate, TensorRow *trow);
 
   // @param const std::string &path - path to the image file
   // @param const ColDescriptor &col - contains tensor implementation and datatype
   // @param std::shared_ptr<Tensor> tensor - return
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ReadImageToTensor(const std::string &path, const ColDescriptor &col, std::shared_ptr<Tensor> *tensor);
 
   // @param const std::vector<uint64_t> &keys - keys in ioblock
   // @param std::unique_ptr<DataBuffer> db
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadBuffer(const std::vector<int64_t> &keys, std::unique_ptr<DataBuffer> *db);
 
   // Read annotation from Annotation folder
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ParseAnnotationIds();
 
   // @param const std::shared_ptr<Tensor> &sample_ids - sample ids of tensor
   // @param std::vector<int64_t> *keys - image id
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status TraverseSampleIds(const std::shared_ptr<Tensor> &sample_ids, std::vector<int64_t> *keys);
 
   // Called first when function is called
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LaunchThreadsAndInitOp();
 
   // Reset dataset state
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // @param nlohmann::json image_tree - image tree of json
   // @param std::vector<std::string> *image_vec - image id list of json
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ImageColumnLoad(const nlohmann::json &image_tree, std::vector<std::string> *image_vec);
 
   // @param nlohmann::json categories_tree - categories tree of json
-  // return Status - The error code return
+  // @return Status The status code returned
   Status CategoriesColumnLoad(const nlohmann::json &categories_tree);
 
   // @param nlohmann::json categories_tree - categories tree of json
   // @param const std::string &image_file - current image name in annotation
   // @param const int32_t &id - current unique id of annotation
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status DetectionColumnLoad(const nlohmann::json &annotation_tree, const std::string &image_file, const int32_t &id);
 
   // @param nlohmann::json categories_tree - categories tree of json
   // @param const std::string &image_file - current image name in annotation
   // @param const int32_t &id - current unique id of annotation
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status StuffColumnLoad(const nlohmann::json &annotation_tree, const std::string &image_file, const int32_t &id);
 
   // @param nlohmann::json categories_tree - categories tree of json
   // @param const std::string &image_file - current image name in annotation
   // @param const int32_t &id - current unique id of annotation
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status KeypointColumnLoad(const nlohmann::json &annotation_tree, const std::string &image_file, const int32_t &id);
 
   // @param nlohmann::json categories_tree - categories tree of json
   // @param const std::string &image_file - current image name in annotation
   // @param const int32_t &image_id - current unique id of annotation
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status PanopticColumnLoad(const nlohmann::json &annotation_tree, const std::string &image_file,
                             const int32_t &image_id);
 

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

@@ -115,13 +115,13 @@ class GeneratorOp : public PipelineOp {
   // Class functor operator () override.
   // All DatasetOps operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Overrides base class reset method.  When an operator does a reset, it cleans up any state
   // info from it's previous execution and then initializes itself so that it can be executed
   // again.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Base-class override for NodePass visitor acceptor.

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

@@ -135,12 +135,12 @@ class ImageFolderOp : public ParallelOp, public RandomAccessOp {
     }
 
     // Check validity of input args
-    // @return - The error code return
+    // @return Status The status code returned
     Status SanityCheck();
 
     // The builder "build" method creates the final object.
     // @param std::shared_ptr<ImageFolderOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<ImageFolderOp> *op);
 
    private:
@@ -172,28 +172,28 @@ class ImageFolderOp : public ParallelOp, public RandomAccessOp {
 
   // Initialize ImageFOlderOp related var, calls the function to walk all files
   // @param - std::string dir file directory to  ImageNetFolder
-  // @return - The error code return
+  // @return Status The status code returned
   Status PrescanMasterEntry(const std::string &dir);
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param int32_t workerId - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param int32_t workerId - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status PrescanWorkerEntry(int32_t worker_id);
 
   // Main Loop of ImageFolderOp
   // Master thread: Fill IOBlockQueue, then goes to sleep
   // Worker thread: pulls IOBlock from IOBlockQueue, work on it then put buffer to mOutConnector
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Method derived from RandomAccess Op, enable Sampler to get all ids for each class
   // @param (std::map<int64_t, std::vector<int64_t >> * map - key label, val all ids for this class
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetClassIds(std::map<int32_t, std::vector<int64_t>> *cls_ids) const override;
 
   // A print method typically used for debugging
@@ -224,19 +224,19 @@ class ImageFolderOp : public ParallelOp, public RandomAccessOp {
 
  private:
   // Initialize Sampler, calls sampler->Init() within
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InitSampler();
 
   // Load a tensor row according to a pair
   // @param row_id_type row_id - id for this tensor row
   // @param ImageLabelPair pair - <imagefile,label>
   // @param TensorRow row - image & label read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadTensorRow(row_id_type row_id, ImageLabelPair pair, TensorRow *row);
 
   // @param const std::vector<int64_t> &keys - keys in ioblock
   // @param std::unique_ptr<DataBuffer> db
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadBuffer(const std::vector<int64_t> &keys, std::unique_ptr<DataBuffer> *db);
 
   // @param std::string & dir - dir to walk all images
@@ -253,7 +253,7 @@ class ImageFolderOp : public ParallelOp, public RandomAccessOp {
   Status LaunchThreadsAndInitOp();
 
   // reset Op
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Private function for computing the assignment of the column name map.

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

@@ -58,12 +58,12 @@ class IOBlock {
   // Fetches the first key from the block.
   // @note Only useful if you know the block only has 1 key.
   // @return  A copy of the first key from the block
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetKey(int64_t *out_key) const;
 
   // Fetches the list of keys from this block.
   // @param out_keys - A copy of the vector of keys from the block.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetKeys(std::vector<int64_t> *out_keys) const;
 
   // Does this block have the eoe flag turned on?
@@ -110,7 +110,7 @@ class FilenameBlock : public IOBlock {
   // Gets the filename from the block using the provided index container
   // @param out_filename - The filename to add to the block
   // @param index - The index to perform lookup against
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetFilename(std::string *out_filename, const AutoIndexObj<std::string> &index) const;
 
   // Get the start offset of file

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

@@ -110,12 +110,12 @@ class ManifestOp : public ParallelOp, public RandomAccessOp {
     }
 
     // Check validity of input args
-    // @return Status - The error code return
+    // @return Status The status code returned
     Status SanityCheck();
 
     // The builder "build" method creates the final object.
     // @param std::shared_ptr<ManifestOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<ManifestOp> *op);
 
    private:
@@ -145,18 +145,18 @@ class ManifestOp : public ParallelOp, public RandomAccessOp {
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param int32_t worker_id - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // Main Loop of ManifestOp
   // Master thread: Fill IOBlockQueue, then goes to sleep
   // Worker thread: pulls IOBlock from IOBlockQueue, work on it then put buffer to mOutConnector
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Method derived from RandomAccess Op, enable Sampler to get all ids for each class
   // @param (std::map<int64_t, std::vector<int64_t >> * map - key label, val all ids for this class
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetClassIds(std::map<int32_t, std::vector<int64_t>> *cls_ids) const override;
 
   // A print method typically used for debugging
@@ -201,37 +201,37 @@ class ManifestOp : public ParallelOp, public RandomAccessOp {
 
  private:
   // Initialize Sampler, calls sampler->Init() within
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InitSampler();
 
   // Method in operator(), to fill IOBlockQueue
   // @param std::unique_ptr<DataBuffer> sampler_buffer - to fill IOBlockQueue
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status AddIoBlock(std::unique_ptr<DataBuffer> *sampler_buffer);
 
   // Load a tensor row according to a pair
   // @param row_id_type row_id - id for this tensor row
   // @param std::pair<std::string, std::vector<std::string>> - <imagefile, <label1, label2...>>
   // @param TensorRow row - image & label read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadTensorRow(row_id_type row_id, const std::pair<std::string, std::vector<std::string>> &data,
                        TensorRow *row);
 
   // @param const std::vector<int64_t> &keys - keys in ioblock
   // @param std::unique_ptr<DataBuffer> db
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadBuffer(const std::vector<int64_t> &keys, std::unique_ptr<DataBuffer> *db);
 
   // Parse manifest file to get image path and label and so on.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ParseManifestFile();
 
   // Called first when function is called
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LaunchThreadsAndInitOp();
 
   // reset Op
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Check if image ia valid.Only support JPEG/PNG/GIF/BMP
@@ -239,7 +239,7 @@ class ManifestOp : public ParallelOp, public RandomAccessOp {
   Status CheckImageType(const std::string &file_name, bool *valid);
 
   // Count label index,num rows and num samples
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status CountDatasetInfo();
 
   // Private function for computing the assignment of the column name map.

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

@@ -164,13 +164,13 @@ class MindRecordOp : public ParallelOp {
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param int32_t workerId - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // Class functor operator () override.
   // All DatasetOps operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Called first when function is called
@@ -180,7 +180,7 @@ class MindRecordOp : public ParallelOp {
   // Overrides base class reset method.  When an operator does a reset, it cleans up any state
   // info from it's previous execution and then initializes itself so that it can be executed
   // again.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Getter method

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

@@ -99,12 +99,12 @@ class MnistOp : public ParallelOp, public RandomAccessOp {
       return *this;
     }
     // Check validity of input args
-    // @return - The error code return
+    // @return Status The status code returned
     Status SanityCheck();
 
     // The builder "Build" method creates the final object.
     // @param std::shared_ptr<MnistOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<MnistOp> *op);
 
    private:
@@ -133,18 +133,18 @@ class MnistOp : public ParallelOp, public RandomAccessOp {
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param int32_t worker_id - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // Main Loop of MnistOp
   // Master thread: Fill IOBlockQueue, then goes to sleep
   // Worker thread: pulls IOBlock from IOBlockQueue, work on it then put buffer to mOutConnector
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Method derived from RandomAccess Op, enable Sampler to get all ids for each class
   // @param (std::map<uint64_t, std::vector<uint64_t >> * map - key label, val all ids for this class
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetClassIds(std::map<int32_t, std::vector<int64_t>> *cls_ids) const override;
 
   // A print method typically used for debugging
@@ -170,39 +170,39 @@ class MnistOp : public ParallelOp, public RandomAccessOp {
 
  private:
   // Initialize Sampler, calls sampler->Init() within
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InitSampler();
 
   // Load a tensor row according to a pair
   // @param row_id_type row_id - id for this tensor row
   // @param ImageLabelPair pair - <imagefile,label>
   // @param TensorRow row - image & label read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadTensorRow(row_id_type row_id, const MnistLabelPair &mnist_pair, TensorRow *row);
 
   // @param const std::vector<int64_t> &keys - keys in ioblock
   // @param std::unique_ptr<DataBuffer> db
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadBuffer(const std::vector<int64_t> &keys, std::unique_ptr<DataBuffer> *db);
 
   // Iterate through all members in sampleIds and fill them into IOBlock.
   // @param std::shared_ptr<Tensor> sample_ids -
   // @param std::vector<int64_t> *keys - keys in ioblock
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status TraversalSampleIds(const std::shared_ptr<Tensor> &sample_ids, std::vector<int64_t> *keys);
 
   // Check image file stream.
   // @param const std::string *file_name - image file name
   // @param std::ifstream *image_reader - image file stream
   // @param uint32_t num_images - returns the number of images
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status CheckImage(const std::string &file_name, std::ifstream *image_reader, uint32_t *num_images);
 
   // Check label stream.
   // @param const std::string &file_name - label file name
   // @param std::ifstream *label_reader - label file stream
   // @param uint32_t num_labels - returns the number of labels
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status CheckLabel(const std::string &file_name, std::ifstream *label_reader, uint32_t *num_labels);
 
   // Read 4 bytes of data from a file stream.
@@ -219,23 +219,23 @@ class MnistOp : public ParallelOp, public RandomAccessOp {
   // @param std::ifstream *image_reader - image file stream
   // @param std::ifstream *label_reader - label file stream
   // @param int64_t read_num - number of image to read
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ReadImageAndLabel(std::ifstream *image_reader, std::ifstream *label_reader, size_t index);
 
   // Parse all mnist dataset files
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ParseMnistData();
 
   // Read all files in the directory
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WalkAllFiles();
 
   // Called first when function is called
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LaunchThreadsAndInitOp();
 
   // reset Op
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Private function for computing the assignment of the column name map.

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

@@ -63,7 +63,7 @@ class RandomDataOp : public ParallelOp {
     /**
      * The build method that produces the instantiated RandomDataOp as a shared pointer
      * @param out_op - The output RandomDataOperator that was constructed
-     * @return Status - The error code return
+     * @return Status The status code returned
      */
     Status Build(std::shared_ptr<RandomDataOp> *out_op);
 
@@ -128,7 +128,7 @@ class RandomDataOp : public ParallelOp {
    private:
     /**
      * Check if the required parameters are set by the builder.
-     * @return Status - The error code return
+     * @return Status The status code returned
      */
     Status SanityCheck() const;
 
@@ -182,7 +182,7 @@ class RandomDataOp : public ParallelOp {
    * Class functor operator () override.
    * All DatasetOps operate by launching a thread (see ExecutionTree). This class functor will
    * provide the master loop that drives the logic for performing the work.
-   * @return Status - The error code return
+   * @return Status The status code returned
    */
   Status operator()() override;
 
@@ -190,7 +190,7 @@ class RandomDataOp : public ParallelOp {
    * Overrides base class reset method.  When an operator does a reset, it cleans up any state
    * info from it's previous execution and then initializes itself so that it can be executed
    * again.
-   * @return Status - The error code return
+   * @return Status The status code returned
    */
   Status Reset() override;
 
@@ -207,7 +207,7 @@ class RandomDataOp : public ParallelOp {
   /**
    * The entry point code for when workers are launched
    * @param worker_id - The worker id
-   * @return Status - The error code return
+   * @return Status The status code returned
    */
   Status WorkerEntry(int32_t worker_id) override;
 
@@ -219,7 +219,7 @@ class RandomDataOp : public ParallelOp {
   /**
    * Performs a synchronization between workers at the end of an epoch
    * @param worker_id - The worker id
-   * @return Status - The error code return
+   * @return Status The status code returned
    */
   Status EpochSync(int32_t worker_id, bool *quitting);
 
@@ -227,7 +227,7 @@ class RandomDataOp : public ParallelOp {
    * A helper function to stuff the tensor table into a buffer and send it to output connector
    * @param worker_id - The worker id
    * @param in_table - The tensor table to pack and send
-   * @return Status - The error code return
+   * @return Status The status code returned
    */
   Status PackAndSend(int32_t worker_id, std::unique_ptr<TensorQTable> in_table);
 
@@ -235,7 +235,7 @@ class RandomDataOp : public ParallelOp {
    * A helper function to create random data for the row
    * @param worker_id - The worker id
    * @param new_row - The output row to produce
-   * @return Status - The error code return
+   * @return Status The status code returned
    */
   Status CreateRandomRow(int32_t worker_id, TensorRow *new_row);
 

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

@@ -40,7 +40,7 @@ class PKSamplerRT : public SamplerRT {  // NOT YET FINISHED
 
   // @param std::unique_ptr<DataBuffer pBuffer
   // @param int32_t workerId
-  // @return - The error code return
+  // @return Status The status code returned
   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
@@ -53,7 +53,7 @@ class PKSamplerRT : public SamplerRT {  // NOT YET FINISHED
   Status InitSampler() override;
 
   // for next epoch of sampleIds
-  // @return - The error code return
+  // @return Status The status code returned
   Status ResetSampler() override;
 
   // Printer for debugging purposes.

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

@@ -41,13 +41,13 @@ class PythonSamplerRT : public SamplerRT {
   Status InitSampler() override;
 
   // for next epoch of sampleIds
-  // @return - The error code return
+  // @return Status The status code returned
   Status ResetSampler() override;
 
   // Op calls this to get next Buffer that contains all the sampleIds
   // @param std::unique_ptr<DataBuffer> pBuffer - Buffer to be returned to corresponding Dataset Op
   // @param int32_t workerId - not meant to be used
-  // @return - The error code return
+  // @return Status The status code returned
   Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
   // Printer for debugging purposes.

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

@@ -40,14 +40,14 @@ class RandomSamplerRT : public SamplerRT {
   // Op calls this to get next Buffer that contains all the sampleIds
   // @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
+  // @return Status The status code returned
   Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
   // meant to be called by base class or python
   Status InitSampler() override;
 
   // for next epoch of sampleIds
-  // @return - The error code return
+  // @return Status The status code returned
   Status ResetSampler() override;
 
   void SamplerPrint(std::ostream &out, bool show_all) const override;

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

@@ -35,12 +35,12 @@ class RandomAccessOp {
  public:
   // Sampler get number of rows in the dataset
   // @param int64_t num - return number of rows for this dataset
-  // @return - The error code return
+  // @return Status The status code returned
   Status GetNumRowsInDataset(int64_t *num_rows) const;
 
   // sampler gets label , imageIds from corresponding Dataset Op, this function is unique to PK
   // @param std::map<int64_t, std::vector<int64_t>> * map
-  // @return - The error code return
+  // @return Status The status code returned
   virtual Status GetClassIds(std::map<int32_t, std::vector<int64_t>> *map) const {
     RETURN_STATUS_UNEXPECTED("GetClassIds needs to be override to support PK");
   }
@@ -71,7 +71,7 @@ class SamplerRT {
   // @note It is Sampler responsibility to make sure that the id is not out of bound.
   // @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
+  // @return Status The status code returned
   virtual Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) = 0;
 
 // This function only called by python layer. Not needed by Android.
@@ -81,7 +81,7 @@ class SamplerRT {
 #endif
 
   // for next epoch of sampleIds
-  // @return - The error code return
+  // @return Status The status code returned
   virtual Status ResetSampler() = 0;
 
   // first handshake between leaf source op and Sampler. This func will determine the amount of data
@@ -114,13 +114,13 @@ class SamplerRT {
 
   // Adds a sampler to become our child.
   // @param std::shared_ptr<DatasetOp> - The sampler to add as a child.
-  // @return - The error code returned.
+  // @return Status The status code returned
   Status AddChild(std::shared_ptr<SamplerRT> 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
   // @param int64_t numElements - must be a non 0 number
-  // @return - The error code returned.
+  // @return Status The status code returned
   Status CreateSamplerTensor(std::shared_ptr<Tensor> *sample_ids, int64_t num_elements);
 
   // A print method typically used for debugging
@@ -146,7 +146,7 @@ class SamplerRT {
   // associated id.
   // @param int64_t* out_associated_id - Out parameter, contains the associated id.
   // @param int64_t id - The id used as an index to get the associated child id.
-  // @return - The error code returned.
+  // @return Status The status code returned
   Status GetAssociatedChildId(int64_t *out_associated_id, int64_t id);
 
  protected:

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

@@ -40,13 +40,13 @@ class SequentialSamplerRT : public SamplerRT {
   Status InitSampler() override;
 
   // for next epoch of sampleIds
-  // @return - The error code return
+  // @return Status The status code returned
   Status ResetSampler() override;
 
   // Op calls this to get next Buffer that contains all the sampleIds
   // @param std::unique_ptr<DataBuffer> pBuffer - Buffer to be returned to corresponding Dataset Op
   // @param int32_t workerId - not meant to be used
-  // @return - The error code return
+  // @return Status The status code returned
   Status GetNextSample(std::unique_ptr<DataBuffer> *out_buffer) override;
 
   // Printer for debugging purposes.

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

@@ -132,12 +132,12 @@ class VOCOp : public ParallelOp, public RandomAccessOp {
     }
 
     // Check validity of input args
-    // @return = The error code return
+    // @return Status The status code returned
     Status SanityCheck();
 
     // The builder "Build" method creates the final object.
     // @param std::shared_ptr<VOCOp> *op - DatasetOp
-    // @return - The error code return
+    // @return Status The status code returned
     Status Build(std::shared_ptr<VOCOp> *op);
 
    private:
@@ -173,13 +173,13 @@ class VOCOp : public ParallelOp, public RandomAccessOp {
 
   // Worker thread pulls a number of IOBlock from IOBlock Queue, make a buffer and push it to Connector
   // @param int32_t workerId - id of each worker
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status WorkerEntry(int32_t worker_id) override;
 
   // Main Loop of VOCOp
   // Master thread: Fill IOBlockQueue, then goes to sleep
   // Worker thread: pulls IOBlock from IOBlockQueue, work on it the put buffer to mOutConnector
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // A print method typically used for debugging
@@ -222,55 +222,55 @@ class VOCOp : public ParallelOp, public RandomAccessOp {
 
  private:
   // Initialize Sampler, calls sampler->Init() within
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status InitSampler();
 
   // Load a tensor row according to image id
   // @param row_id_type row_id - id for this tensor row
   // @param std::string image_id - image id
   // @param TensorRow row - image & target read into this tensor row
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadTensorRow(row_id_type row_id, const std::string &image_id, TensorRow *row);
 
   // @param const std::string &path - path to the image file
   // @param const ColDescriptor &col - contains tensor implementation and datatype
   // @param std::shared_ptr<Tensor> tensor - return
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ReadImageToTensor(const std::string &path, const ColDescriptor &col, std::shared_ptr<Tensor> *tensor);
 
   // @param const std::string &path - path to the image file
   // @param TensorRow *row - return
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ReadAnnotationToTensor(const std::string &path, TensorRow *row);
 
   // @param const std::vector<uint64_t> &keys - keys in ioblock
   // @param std::unique_ptr<DataBuffer> db
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadBuffer(const std::vector<int64_t> &keys, std::unique_ptr<DataBuffer> *db);
 
   // Read image list from ImageSets
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ParseImageIds();
 
   // Read annotation from Annotation folder
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ParseAnnotationIds();
 
   // @param const std::string &path - path to annotation xml
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status ParseAnnotationBbox(const std::string &path);
 
   // @param const std::shared_ptr<Tensor> &sample_ids - sample ids of tensor
   // @param std::vector<int64_t> *keys - image id
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status TraverseSampleIds(const std::shared_ptr<Tensor> &sample_ids, std::vector<int64_t> *keys);
 
   // Called first when function is called
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LaunchThreadsAndInitOp();
 
   // Reset dataset state
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Reset() override;
 
   // Private function for computing the assignment of the column name map.

mindspore/ccsrc/minddata/dataset/engine/datasetops/take_op.h

@@ -75,7 +75,7 @@ class TakeOp : public PipelineOp {
 
   // All dataset ops operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   // Base-class override for NodePass visitor acceptor.

mindspore/ccsrc/minddata/dataset/engine/datasetops/zip_op.h

@@ -101,7 +101,7 @@ class ZipOp : public PipelineOp {
   // Class functor operator () override.
   // All dataset ops operate by launching a thread (see ExecutionTree). This class functor will
   // provide the master loop that drives the logic for performing the work
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status operator()() override;
 
   /// \brief Base-class override for NodePass pre-visit acceptor

mindspore/ccsrc/minddata/dataset/engine/execution_tree.cc

@@ -226,7 +226,7 @@ Status ExecutionTree::LaunchWorkers(int32_t num_workers, std::function<Status(ui
 //    Compulsory transformation/action post optimization.
 //    For example, repeatOp inlining
 //
-// @return Status - The error code return
+// @return Status The status code returned
 Status ExecutionTree::Prepare(int32_t num_epochs, bool partial) {
   num_epochs_ = num_epochs;
   partially_prepare_ = partial;

mindspore/ccsrc/minddata/dataset/engine/execution_tree.h

@@ -115,16 +115,16 @@ class ExecutionTree {
   // provides it with a link to the tree. A node cannot form any relationships (parent/child) with
   // other nodes unless they are associated with the same tree.
   // @param op - The operator to associate
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status AssociateNode(const std::shared_ptr<DatasetOp> &op);
 
   // Sets the root node of the tree
   // @param op - The operator to assign as root
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status AssignRoot(const std::shared_ptr<DatasetOp> &op);
 
   // Start the execution of the tree
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Launch();
 
   /// A print method typically used for debugging
@@ -155,7 +155,7 @@ class ExecutionTree {
   // wrapper for the TaskGroup handling that is stored inside the execution tree.
   // @param num_workers - The number of workers to launch
   // @param func - The function entry point that workers will execute
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LaunchWorkers(int32_t num_workers, std::function<Status(uint32_t)> func, std::string name = "");
 
   // Getter method
@@ -181,32 +181,32 @@ class ExecutionTree {
   //    Compulsory transformation/action post optimization.
   //    For example, repeatOp inlining
   //
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Prepare(int num_epochs = -1, bool partial = false);
 
   // Compulsory transformation/action pre optimization.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status PreAction();
 
   // Compulsory transformation/action post optimization.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status PostAction();
 
   // Optimization transformation/action, optional.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Optimize();
 
   // The DEPRECATED driver of the prepare phase of the execution tree. The prepare phase will recursively
   // walk the tree to perform modifications to the tree or specific nodes within the tree to get
   // it ready for execution.
   // @param Total number of epochs that will be run on this tree
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status PrepareDeprecated();
 
   // Recursive function used during prepare phase to visit a node and drive any pre- and post-
   // node actions during a tree walk.
   // @param op - The dataset op to work on
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status PrepareNode(const std::shared_ptr<DatasetOp> &dataset_op);
 
   // Return the pointer to the TaskGroup

mindspore/ccsrc/minddata/dataset/engine/gnn/edge.h

@@ -51,7 +51,7 @@ class Edge {
   // Get the feature of a edge
   // @param FeatureType feature_type - type of feature
   // @param std::shared_ptr<Feature> *out_feature - Returned feature
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetFeatures(FeatureType feature_type, std::shared_ptr<Feature> *out_feature) = 0;
 
   // Get nodes on the edge
@@ -71,7 +71,7 @@ class Edge {
 
   // Update feature of edge
   // @param std::shared_ptr<Feature> feature -
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status UpdateFeature(const std::shared_ptr<Feature> &feature) = 0;
 
  protected:

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_data.h

@@ -47,19 +47,19 @@ class GraphData {
   // Get all nodes from the graph.
   // @param NodeType node_type - type of node
   // @param std::shared_ptr<Tensor> *out - Returned nodes id
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetAllNodes(NodeType node_type, std::shared_ptr<Tensor> *out) = 0;
 
   // Get all edges from the graph.
   // @param NodeType edge_type - type of edge
   // @param std::shared_ptr<Tensor> *out - Returned edge ids
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetAllEdges(EdgeType edge_type, std::shared_ptr<Tensor> *out) = 0;
 
   // Get the node id from the edge.
   // @param std::vector<EdgeIdType> edge_list - List of edges
   // @param std::shared_ptr<Tensor> *out - Returned node ids
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetNodesFromEdges(const std::vector<EdgeIdType> &edge_list, std::shared_ptr<Tensor> *out) = 0;
 
   // All neighbors of the acquisition node.
@@ -68,7 +68,7 @@ class GraphData {
   // @param std::shared_ptr<Tensor> *out - Returned neighbor's id. Because the number of neighbors at different nodes is
   // different, the returned tensor is output according to the maximum number of neighbors. If the number of neighbors
   // is not enough, fill in tensor as -1.
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetAllNeighbors(const std::vector<NodeIdType> &node_list, NodeType neighbor_type,
                                  std::shared_ptr<Tensor> *out) = 0;
 
@@ -77,7 +77,7 @@ class GraphData {
   // @param std::vector<NodeIdType> neighbor_nums - Number of neighbors sampled per hop
   // @param std::vector<NodeType> neighbor_types - Neighbor type sampled per hop
   // @param std::shared_ptr<Tensor> *out - Returned neighbor's id.
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetSampledNeighbors(const std::vector<NodeIdType> &node_list,
                                      const std::vector<NodeIdType> &neighbor_nums,
                                      const std::vector<NodeType> &neighbor_types, std::shared_ptr<Tensor> *out) = 0;
@@ -87,7 +87,7 @@ class GraphData {
   // @param NodeIdType samples_num - Number of neighbors sampled
   // @param NodeType neg_neighbor_type - The type of negative neighbor.
   // @param std::shared_ptr<Tensor> *out - Returned negative neighbor's id.
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetNegSampledNeighbors(const std::vector<NodeIdType> &node_list, NodeIdType samples_num,
                                         NodeType neg_neighbor_type, std::shared_ptr<Tensor> *out) = 0;
 
@@ -98,7 +98,7 @@ class GraphData {
   // @param float step_away_param - inout hyper parameter in node2vec algorithm
   // @param NodeIdType default_node - default node id
   // @param std::shared_ptr<Tensor> *out - Returned nodes id in walk path
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status RandomWalk(const std::vector<NodeIdType> &node_list, const std::vector<NodeType> &meta_path,
                             float step_home_param, float step_away_param, NodeIdType default_node,
                             std::shared_ptr<Tensor> *out) = 0;
@@ -108,7 +108,7 @@ class GraphData {
   // @param std::vector<FeatureType> feature_types - Types of features, An error will be reported if the feature type
   // does not exist.
   // @param TensorRow *out - Returned features
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetNodeFeature(const std::shared_ptr<Tensor> &nodes, const std::vector<FeatureType> &feature_types,
                                 TensorRow *out) = 0;
 
@@ -117,7 +117,7 @@ class GraphData {
   // @param std::vector<FeatureType> feature_types - Types of features, An error will be reported if the feature type
   // does not exist.
   // @param Tensor *out - Returned features
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetEdgeFeature(const std::shared_ptr<Tensor> &edges, const std::vector<FeatureType> &feature_types,
                                 TensorRow *out) = 0;
 

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_data_client.h

@@ -57,19 +57,19 @@ class GraphDataClient : public GraphData {
   // Get all nodes from the graph.
   // @param NodeType node_type - type of node
   // @param std::shared_ptr<Tensor> *out - Returned nodes id
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetAllNodes(NodeType node_type, std::shared_ptr<Tensor> *out) override;
 
   // Get all edges from the graph.
   // @param NodeType edge_type - type of edge
   // @param std::shared_ptr<Tensor> *out - Returned edge ids
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetAllEdges(EdgeType edge_type, std::shared_ptr<Tensor> *out) override;
 
   // Get the node id from the edge.
   // @param std::vector<EdgeIdType> edge_list - List of edges
   // @param std::shared_ptr<Tensor> *out - Returned node ids
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNodesFromEdges(const std::vector<EdgeIdType> &edge_list, std::shared_ptr<Tensor> *out) override;
 
   // All neighbors of the acquisition node.
@@ -78,7 +78,7 @@ class GraphDataClient : public GraphData {
   // @param std::shared_ptr<Tensor> *out - Returned neighbor's id. Because the number of neighbors at different nodes is
   // different, the returned tensor is output according to the maximum number of neighbors. If the number of neighbors
   // is not enough, fill in tensor as -1.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetAllNeighbors(const std::vector<NodeIdType> &node_list, NodeType neighbor_type,
                          std::shared_ptr<Tensor> *out) override;
 
@@ -87,7 +87,7 @@ class GraphDataClient : public GraphData {
   // @param std::vector<NodeIdType> neighbor_nums - Number of neighbors sampled per hop
   // @param std::vector<NodeType> neighbor_types - Neighbor type sampled per hop
   // @param std::shared_ptr<Tensor> *out - Returned neighbor's id.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetSampledNeighbors(const std::vector<NodeIdType> &node_list, const std::vector<NodeIdType> &neighbor_nums,
                              const std::vector<NodeType> &neighbor_types, std::shared_ptr<Tensor> *out) override;
 
@@ -96,7 +96,7 @@ class GraphDataClient : public GraphData {
   // @param NodeIdType samples_num - Number of neighbors sampled
   // @param NodeType neg_neighbor_type - The type of negative neighbor.
   // @param std::shared_ptr<Tensor> *out - Returned negative neighbor's id.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNegSampledNeighbors(const std::vector<NodeIdType> &node_list, NodeIdType samples_num,
                                 NodeType neg_neighbor_type, std::shared_ptr<Tensor> *out) override;
 
@@ -107,7 +107,7 @@ class GraphDataClient : public GraphData {
   // @param float step_away_param - inout hyper parameter in node2vec algorithm
   // @param NodeIdType default_node - default node id
   // @param std::shared_ptr<Tensor> *out - Returned nodes id in walk path
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status RandomWalk(const std::vector<NodeIdType> &node_list, const std::vector<NodeType> &meta_path,
                     float step_home_param, float step_away_param, NodeIdType default_node,
                     std::shared_ptr<Tensor> *out) override;
@@ -117,7 +117,7 @@ class GraphDataClient : public GraphData {
   // @param std::vector<FeatureType> feature_types - Types of features, An error will be reported if the feature type
   // does not exist.
   // @param TensorRow *out - Returned features
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNodeFeature(const std::shared_ptr<Tensor> &nodes, const std::vector<FeatureType> &feature_types,
                         TensorRow *out) override;
 
@@ -126,7 +126,7 @@ class GraphDataClient : public GraphData {
   // @param std::vector<FeatureType> feature_types - Types of features, An error will be reported if the feature type
   // does not exist.
   // @param Tensor *out - Returned features
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetEdgeFeature(const std::shared_ptr<Tensor> &edges, const std::vector<FeatureType> &feature_types,
                         TensorRow *out) override;
 

mindspore/ccsrc/minddata/dataset/engine/gnn/graph_data_impl.h

@@ -51,19 +51,19 @@ class GraphDataImpl : public GraphData {
   // Get all nodes from the graph.
   // @param NodeType node_type - type of node
   // @param std::shared_ptr<Tensor> *out - Returned nodes id
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetAllNodes(NodeType node_type, std::shared_ptr<Tensor> *out) override;
 
   // Get all edges from the graph.
   // @param NodeType edge_type - type of edge
   // @param std::shared_ptr<Tensor> *out - Returned edge ids
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetAllEdges(EdgeType edge_type, std::shared_ptr<Tensor> *out) override;
 
   // Get the node id from the edge.
   // @param std::vector<EdgeIdType> edge_list - List of edges
   // @param std::shared_ptr<Tensor> *out - Returned node ids
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNodesFromEdges(const std::vector<EdgeIdType> &edge_list, std::shared_ptr<Tensor> *out) override;
 
   // All neighbors of the acquisition node.
@@ -72,7 +72,7 @@ class GraphDataImpl : public GraphData {
   // @param std::shared_ptr<Tensor> *out - Returned neighbor's id. Because the number of neighbors at different nodes is
   // different, the returned tensor is output according to the maximum number of neighbors. If the number of neighbors
   // is not enough, fill in tensor as -1.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetAllNeighbors(const std::vector<NodeIdType> &node_list, NodeType neighbor_type,
                          std::shared_ptr<Tensor> *out) override;
 
@@ -81,7 +81,7 @@ class GraphDataImpl : public GraphData {
   // @param std::vector<NodeIdType> neighbor_nums - Number of neighbors sampled per hop
   // @param std::vector<NodeType> neighbor_types - Neighbor type sampled per hop
   // @param std::shared_ptr<Tensor> *out - Returned neighbor's id.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetSampledNeighbors(const std::vector<NodeIdType> &node_list, const std::vector<NodeIdType> &neighbor_nums,
                              const std::vector<NodeType> &neighbor_types, std::shared_ptr<Tensor> *out) override;
 
@@ -90,7 +90,7 @@ class GraphDataImpl : public GraphData {
   // @param NodeIdType samples_num - Number of neighbors sampled
   // @param NodeType neg_neighbor_type - The type of negative neighbor.
   // @param std::shared_ptr<Tensor> *out - Returned negative neighbor's id.
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNegSampledNeighbors(const std::vector<NodeIdType> &node_list, NodeIdType samples_num,
                                 NodeType neg_neighbor_type, std::shared_ptr<Tensor> *out) override;
 
@@ -101,7 +101,7 @@ class GraphDataImpl : public GraphData {
   // @param float step_away_param - inout hyper parameter in node2vec algorithm
   // @param NodeIdType default_node - default node id
   // @param std::shared_ptr<Tensor> *out - Returned nodes id in walk path
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status RandomWalk(const std::vector<NodeIdType> &node_list, const std::vector<NodeType> &meta_path,
                     float step_home_param, float step_away_param, NodeIdType default_node,
                     std::shared_ptr<Tensor> *out) override;
@@ -111,7 +111,7 @@ class GraphDataImpl : public GraphData {
   // @param std::vector<FeatureType> feature_types - Types of features, An error will be reported if the feature type
   // does not exist.
   // @param TensorRow *out - Returned features
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNodeFeature(const std::shared_ptr<Tensor> &nodes, const std::vector<FeatureType> &feature_types,
                         TensorRow *out) override;
 
@@ -123,7 +123,7 @@ class GraphDataImpl : public GraphData {
   // @param std::vector<FeatureType> feature_types - Types of features, An error will be reported if the feature type
   // does not exist.
   // @param Tensor *out - Returned features
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetEdgeFeature(const std::shared_ptr<Tensor> &edges, const std::vector<FeatureType> &feature_types,
                         TensorRow *out) override;
 
@@ -132,7 +132,7 @@ class GraphDataImpl : public GraphData {
 
   // Get meta information of graph
   // @param MetaInfo *meta_info - Returned meta information
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetMetaInfo(MetaInfo *meta_info);
 
 #ifdef ENABLE_PYTHON
@@ -202,14 +202,14 @@ class GraphDataImpl : public GraphData {
   };
 
   // Load graph data from mindrecord file
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status LoadNodeAndEdge();
 
   // Create Tensor By Vector
   // @param std::vector<std::vector<T>> &data -
   // @param DataType type -
   // @param std::shared_ptr<Tensor> *out -
-  // @return Status - The error code return
+  // @return Status The status code returned
   template <typename T>
   Status CreateTensorByVector(const std::vector<std::vector<T>> &data, DataType type, std::shared_ptr<Tensor> *out);
 
@@ -217,32 +217,32 @@ class GraphDataImpl : public GraphData {
   // @param std::vector<std::vector<T>> *data - To be completed vector
   // @param size_t max_size - The size of the completed vector
   // @param T default_value - Filled default
-  // @return Status - The error code return
+  // @return Status The status code returned
   template <typename T>
   Status ComplementVector(std::vector<std::vector<T>> *data, size_t max_size, T default_value);
 
   // Get the default feature of a node
   // @param FeatureType feature_type -
   // @param std::shared_ptr<Feature> *out_feature - Returned feature
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNodeDefaultFeature(FeatureType feature_type, std::shared_ptr<Feature> *out_feature);
 
   // Get the default feature of a edge
   // @param FeatureType feature_type -
   // @param std::shared_ptr<Feature> *out_feature - Returned feature
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetEdgeDefaultFeature(FeatureType feature_type, std::shared_ptr<Feature> *out_feature);
 
   // Find node object using node id
   // @param NodeIdType id -
   // @param std::shared_ptr<Node> *node - Returned node object
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetNodeByNodeId(NodeIdType id, std::shared_ptr<Node> *node);
 
   // Find edge object using edge id
   // @param EdgeIdType id -
   // @param std::shared_ptr<Node> *edge - Returned edge object
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetEdgeByEdgeId(EdgeIdType id, std::shared_ptr<Edge> *edge);
 
   // Negative sampling
@@ -250,7 +250,7 @@ class GraphDataImpl : public GraphData {
   // @param std::unordered_set<NodeIdType> &exclude_data - Data to be excluded
   // @param int32_t samples_num -
   // @param std::vector<NodeIdType> *out_samples - Sampling results returned
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status NegativeSample(const std::vector<NodeIdType> &data, const std::vector<NodeIdType> shuffled_ids,
                         size_t *start_index, const std::unordered_set<NodeIdType> &exclude_data, int32_t samples_num,
                         std::vector<NodeIdType> *out_samples);

mindspore/ccsrc/minddata/dataset/engine/gnn/local_edge.h

@@ -43,12 +43,12 @@ class LocalEdge : public Edge {
   // Get the feature of a edge
   // @param FeatureType feature_type - type of feature
   // @param std::shared_ptr<Feature> *out_feature - Returned feature
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetFeatures(FeatureType feature_type, std::shared_ptr<Feature> *out_feature) override;
 
   // Update feature of edge
   // @param std::shared_ptr<Feature> feature -
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status UpdateFeature(const std::shared_ptr<Feature> &feature) override;
 
  private:

mindspore/ccsrc/minddata/dataset/engine/gnn/local_node.h

@@ -40,13 +40,13 @@ class LocalNode : public Node {
   // Get the feature of a node
   // @param FeatureType feature_type - type of feature
   // @param std::shared_ptr<Feature> *out_feature - Returned feature
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetFeatures(FeatureType feature_type, std::shared_ptr<Feature> *out_feature) override;
 
   // Get the all neighbors of a node
   // @param NodeType neighbor_type - type of neighbor
   // @param std::vector<NodeIdType> *out_neighbors - Returned neighbors id
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetAllNeighbors(NodeType neighbor_type, std::vector<NodeIdType> *out_neighbors,
                          bool exclude_itself = false) override;
 
@@ -54,18 +54,18 @@ class LocalNode : public Node {
   // @param NodeType neighbor_type - type of neighbor
   // @param int32_t samples_num - Number of neighbors to be acquired
   // @param std::vector<NodeIdType> *out_neighbors - Returned neighbors id
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetSampledNeighbors(NodeType neighbor_type, int32_t samples_num,
                              std::vector<NodeIdType> *out_neighbors) override;
 
   // Add neighbor of node
   // @param std::shared_ptr<Node> node -
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status AddNeighbor(const std::shared_ptr<Node> &node) override;
 
   // Update feature of node
   // @param std::shared_ptr<Feature> feature -
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status UpdateFeature(const std::shared_ptr<Feature> &feature) override;
 
  private:

mindspore/ccsrc/minddata/dataset/engine/gnn/node.h

@@ -49,13 +49,13 @@ class Node {
   // Get the feature of a node
   // @param FeatureType feature_type - type of feature
   // @param std::shared_ptr<Feature> *out_feature - Returned feature
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetFeatures(FeatureType feature_type, std::shared_ptr<Feature> *out_feature) = 0;
 
   // Get the all neighbors of a node
   // @param NodeType neighbor_type - type of neighbor
   // @param std::vector<NodeIdType> *out_neighbors - Returned neighbors id
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetAllNeighbors(NodeType neighbor_type, std::vector<NodeIdType> *out_neighbors,
                                  bool exclude_itself = false) = 0;
 
@@ -63,18 +63,18 @@ class Node {
   // @param NodeType neighbor_type - type of neighbor
   // @param int32_t samples_num - Number of neighbors to be acquired
   // @param std::vector<NodeIdType> *out_neighbors - Returned neighbors id
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status GetSampledNeighbors(NodeType neighbor_type, int32_t samples_num,
                                      std::vector<NodeIdType> *out_neighbors) = 0;
 
   // Add neighbor of node
   // @param std::shared_ptr<Node> node -
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status AddNeighbor(const std::shared_ptr<Node> &node) = 0;
 
   // Update feature of node
   // @param std::shared_ptr<Feature> feature -
-  // @return Status - The error code return
+  // @return Status The status code returned
   virtual Status UpdateFeature(const std::shared_ptr<Feature> &feature) = 0;
 
  protected:

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

@@ -57,6 +57,10 @@ class RepeatNode : public DatasetNode {
   /// \return Status Status::OK() if all the parameters are valid
   Status ValidateParams() override;
 
+  /// \brief Getter
+  /// \return Number of cycles to repeat the execution
+  const int32_t Count() const { return repeat_count_; }
+
   /// \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

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

@@ -55,6 +55,10 @@ class SkipNode : public DatasetNode {
   /// \return Status Status::OK() if all the parameters are valid
   Status ValidateParams() override;
 
+  /// \brief Getter
+  /// \return Number of rows to skip
+  const int32_t Count() const { return skip_count_; }
+
   /// \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

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

@@ -55,6 +55,10 @@ class TakeNode : public DatasetNode {
   /// \return Status Status::OK() if all the parameters are valid
   Status ValidateParams() override;
 
+  /// \brief Getter
+  /// \return Number of rows to output
+  const int32_t Count() const { return take_count_; }
+
   /// \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

mindspore/ccsrc/minddata/dataset/engine/opt/optional/tensor_op_fusion_pass.h

@@ -29,7 +29,7 @@ class TensorOpFusionPass : public NodePass {
   /// \brief Identifies and fuses tensor ops within MapOp
   /// \param[in] node The node being visited
   /// \param[inout] *modified indicates whether the node has been visited
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<MapOp> node, bool *modified) override;
 };
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/engine/opt/pass.h

@@ -135,7 +135,7 @@ class IRTreePass : public IRPass {
   ///     "modified" flag needs to be set to true if tree is modified during the pass execution.
   /// \param[inout] tree The tree to operate on.
   /// \param[inout] Indicate if the tree was modified.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   virtual Status RunOnTree(std::shared_ptr<DatasetNode> root_ir, bool *modified) { return Status::OK(); }
 };
 
@@ -170,14 +170,14 @@ class IRNodePass : public IRPass {
   ///     a tree traversal.  "modified" flag needs to be set to true if node is modified during the pass execution
   /// \param[in] node The node being visited
   /// \param[out] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   virtual Status Visit(std::shared_ptr<DatasetNode> node, bool *modified) { return Status::OK(); }
 
   /// \brief Derived classes may implement the VisitAfter function to implement node level tree transformation
   ///     "modified" flag needs to be set to true if node is modified during the pass execution
   /// \param[in] node The node being visited
   /// \param[out] modified Indicator if the node was changed at all.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   virtual Status VisitAfter(std::shared_ptr<DatasetNode> node, bool *modified) { return Status::OK(); }
 
   // Visit()/VisitAfter() method to be overridden.
@@ -266,7 +266,7 @@ class TreePass : public Pass {
   ///     "modified" flag needs to be set to true if tree is modified during the pass execution.
   /// \param[inout] tree The tree to operate on.
   /// \param[inout] Indicate of the tree was modified.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   virtual Status RunOnTree(ExecutionTree *tree, bool *modified) { return Status::OK(); }
 };
 
@@ -301,14 +301,14 @@ class NodePass : public Pass {
   ///     a tree traversal.  "modified" flag needs to be set to true if tree is modified during the pass execution
   /// \param[in] node The node being visited
   /// \param[out] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   virtual Status PreRunOnNode(std::shared_ptr<DatasetOp> node, bool *modified) { return Status::OK(); }
 
   /// \brief Derived classes may implement the RunOnNode function to implement node level tree transformation
   ///     "modified" flag needs to be set to true if tree is modified during the pass execution
   /// \param[in] node The node being visited
   /// \param[out] modified Indicator if the node was changed at all.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   virtual Status RunOnNode(std::shared_ptr<DatasetOp> node, bool *modified) { return Status::OK(); }
 
   // Visit methods to be overridden.

mindspore/ccsrc/minddata/dataset/engine/opt/post/repeat_pass.h

@@ -41,80 +41,80 @@ class RepeatPass : public NodePass {
   /// \brief Identifies the subtree below this node as being in a repeated path of the tree.
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<RepeatOp> node, bool *modified) override;
 
   /// \brief Identifies the subtree below this node as being in a repeated path of the tree.
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<EpochCtrlOp> node, bool *modified) override;
 
   /// \brief Identifies the subtree below this node as being in a cache merge path
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<CacheMergeOp> node, bool *modified) override;
 
   /// \brief Identifies the subtree below this node as being cached
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<CacheOp> node, bool *modified) override;
 
   /// \brief Hooks up any identified eoe nodes under this repeat.
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<RepeatOp> node, bool *modified) override;
 
   /// \brief Hooks up any identified eoe nodes under this repeat.
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<EpochCtrlOp> node, bool *modified) override;
 
   /// \brief CacheOp removes previous leaf ops and replaces them with itself
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<CacheOp> node, bool *modified) override;
 
   /// \brief Turns of the tracking for operations under merge op
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<CacheMergeOp> node, bool *modified) override;
 
   /// \brief Saves the lookup up in case it needs to be referenced by a repeat
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<CacheLookupOp> node, bool *modified) override;
 
   /// \brief Set the epoch count for DeviceQueue
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<DeviceQueueOp> node, bool *modified) override;
 
   /// \brief Special case for GeneratorOp
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<GeneratorOp> node, bool *modified) override;
 
   /// \brief All operators have a flag that might be set related to the repeat and any leaf nodes need to be set up
   ///     for use with a controlling repeat above it.
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<DatasetOp> node, bool *modified) override;
 
  private:
   /// \brief Adds an operator to the eoe operator stack save area
   /// \param op - The dataset op to work add to eoe stack
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   void AddToEOEOpStack(std::shared_ptr<DatasetOp> dataset_op);
 
   /// \brief Pops an operator from the eoe operator stack save area
@@ -127,7 +127,7 @@ class RepeatPass : public NodePass {
 
   /// \brief Adds an operator to the cached operator stack save area
   /// \param op - The dataset op to work add to cached stack
-  /// \return Status - The error code return
+  /// \return Status The status code returned
   void AddToCachedOpStack(std::shared_ptr<DatasetOp> dataset_op);
 
   /// \brief Pops an operator from the cached operator stack save area

mindspore/ccsrc/minddata/dataset/engine/opt/pre/cache_error_pass.h

@@ -38,123 +38,123 @@ class CacheErrorPass : public NodePass {
   /// \brief Identifies the subtree below this node as being cached
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<CacheOp> node, bool *modified) override;
 
   /// \brief Returns an error if ZipOp exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<ZipOp> node, bool *modified) override;
 
   /// \brief Returns an error if MapOp with non-deterministic TensorOps exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<MapOp> node, bool *modified) override;
 
   /// \brief Returns an error if ConcatOp exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<ConcatOp> node, bool *modified) override;
 
   /// \brief Returns an error if TakeOp exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<TakeOp> node, bool *modified) override;
 
   /// \brief Returns an error if SkipOp exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<SkipOp> node, bool *modified) override;
 
   /// \brief Returns an error if SkipOp exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<BatchOp> node, bool *modified) override;
 
 #ifdef ENABLE_PYTHON
   /// \brief Returns an error if FilterOp exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status PreRunOnNode(std::shared_ptr<FilterOp> node, bool *modified) override;
 #endif
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<ImageFolderOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<AlbumOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<MnistOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<CifarOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<CocoOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<CelebAOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<ManifestOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<VOCOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<MindRecordOp> node, bool *modified) override;
 
   /// \brief Identifies the leaf dataset as being mappable
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<GeneratorOp> node, bool *modified) override;
 
   /// \brief Identifies the subtree above this node as not being cached
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<CacheOp> node, bool *modified) override;
 
   /// \brief Identifies and block repeat under cache scenarios
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnNode(std::shared_ptr<RepeatOp> node, bool *modified) override;
 
  private:

mindspore/ccsrc/minddata/dataset/engine/opt/pre/cache_transform_pass.h

@@ -48,14 +48,14 @@ class CacheTransformPass : public TreePass {
     /// \brief Identifies the subtree below this node as a cached descendant tree.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status PreRunOnNode(std::shared_ptr<CacheOp> node, bool *modified) override;
 
     /// \brief Resets the tracking of the cache within the tree and assigns the operators that
     ///     will be involved in a cache transformation
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<CacheOp> node, bool *modified) override;
 
 #ifndef ENABLE_ANDROID
@@ -63,95 +63,95 @@ class CacheTransformPass : public TreePass {
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<TFReaderOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<ClueOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<CsvOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<TextFileOp> node, bool *modified) override;
 #endif
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<RandomDataOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<ImageFolderOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<AlbumOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<MnistOp> node, bool *modified) override;
 
 #ifdef ENABLE_PYTHON
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<GeneratorOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<ManifestOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<VOCOp> node, bool *modified) override;
 #endif
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<CifarOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<CocoOp> node, bool *modified) override;
 
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<CelebAOp> node, bool *modified) override;
 
 #ifndef ENABLE_ANDROID
     /// \brief Perform leaf node cache transform identifications
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<MindRecordOp> node, bool *modified) override;
 #endif
 
@@ -161,12 +161,12 @@ class CacheTransformPass : public TreePass {
    private:
     /// \brief Common code for mappable leaf setup.
     /// \param[in] node The leaf node performing setup work.
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status MappableCacheLeafSetup(std::shared_ptr<DatasetOp> leaf_op);
 
     /// \brief Common code for non-mappable leaf setup.
     /// \param[in] node The leaf node performing setup work.
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status NonMappableCacheLeafSetup(std::shared_ptr<DatasetOp> leaf_op);
 
     /// \brief Assigns the leaf and cache operators that are involved in a cache transformation
@@ -191,7 +191,7 @@ class CacheTransformPass : public TreePass {
   /// \brief Runs a cache_pass first to set up the transformation nodes, and then drives any of these transformations
   /// \param[inout] tree The tree to operate on.
   /// \param[inout] Indicate of the tree was modified.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnTree(ExecutionTree *tree, bool *modified) override;
 
  private:
@@ -212,7 +212,7 @@ class CacheTransformPass : public TreePass {
   /// \param[in] leaf_op The leaf node in the transform
   /// \param[in] cache_op The cache op in the transform (will get removed)
   /// \param[in] cache_client The cache client
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status ExecuteCacheTransform(ExecutionTree *tree, std::shared_ptr<DatasetOp> leaf_op,
                                std::shared_ptr<DatasetOp> cache_op, std::shared_ptr<CacheClient> cache_client);
 };

mindspore/ccsrc/minddata/dataset/engine/opt/pre/cache_validation_pass.h

@@ -38,61 +38,61 @@ class CacheValidationPass : public IRNodePass {
   /// \brief Returns an error if BatchNode exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Visit(std::shared_ptr<BatchNode> node, bool *modified) override;
 
   /// \brief Returns an error if ConcatNode exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Visit(std::shared_ptr<ConcatNode> node, bool *modified) override;
 
   /// \brief Returns an error if FilterNode exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Visit(std::shared_ptr<FilterNode> node, bool *modified) override;
 
   /// \brief Returns an error if SkipNode exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Visit(std::shared_ptr<SkipNode> node, bool *modified) override;
 
   /// \brief Returns an error if TakeNode exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Visit(std::shared_ptr<TakeNode> node, bool *modified) override;
 
   /// \brief Returns an error if ZipNode exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Visit(std::shared_ptr<ZipNode> node, bool *modified) override;
 
   /// \brief Returns an error if MapNode with non-deterministic tensor operations exists under a cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Visit(std::shared_ptr<MapNode> node, bool *modified) override;
 
   /// \brief Returns an error if there is a cache over another cache
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status Visit(std::shared_ptr<DatasetNode> node, bool *modified) override;
 
   /// \brief Identifies and block repeat under cache scenarios
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status VisitAfter(std::shared_ptr<RepeatNode> node, bool *modified) override;
 
   /// \brief Identifies the subtree above this node as not being cached
   /// \param[in] node The node being visited
   /// \param[inout] modified Indicator if the node was changed at all
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status VisitAfter(std::shared_ptr<DatasetNode> node, bool *modified) override;
 
  private:

mindspore/ccsrc/minddata/dataset/engine/opt/pre/epoch_ctrl_pass.h

@@ -45,27 +45,27 @@ class EpochCtrlPass : public IRTreePass {
     /// \brief Performs finder work for BuildVocabNode that has special rules about epoch control injection.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status Visit(std::shared_ptr<RootNode> node, bool *modified) override;
 
     /// \brief Performs finder work for BuildVocabNode that has special rules about epoch control injection.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status Visit(std::shared_ptr<BuildVocabNode> node, bool *modified) override;
 
 #ifndef ENABLE_ANDROID
     /// \brief Performs finder work for BuildSentenceVocabNode that has special rules about epoch control injection.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status Visit(std::shared_ptr<BuildSentenceVocabNode> node, bool *modified) override;
 #endif
 
     /// \brief Register the TransferNode for further action.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status VisitAfter(std::shared_ptr<TransferNode> node, bool *modified) override;
 
     /// \brief Getter
@@ -89,7 +89,7 @@ class EpochCtrlPass : public IRTreePass {
   /// \brief Runs an injection pass to inject in operators needed at the pre pass stage
   /// \param[inout] tree The tree to operate on.
   /// \param[inout] Indicate of the tree was modified.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnTree(std::shared_ptr<DatasetNode> root_ir, bool *modified) override;
 };
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/engine/opt/pre/epoch_injection_pass.h

@@ -46,20 +46,20 @@ class EpochInjectionPass : public TreePass {
     /// \brief Performs finder work for BuildVocabOp that has special rules about epoch control injection.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status PreRunOnNode(std::shared_ptr<BuildVocabOp> node, bool *modified) override;
 
     /// \brief Performs finder work for BuildSentencePieceVocabOp that has special rules about epoch control injection.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status PreRunOnNode(std::shared_ptr<BuildSentencePieceVocabOp> node, bool *modified) override;
 #endif
 
     /// \brief Register the DeviceQueueOp for further action.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<DeviceQueueOp> node, bool *modified) override;
 
     /// \brief Getter
@@ -79,7 +79,7 @@ class EpochInjectionPass : public TreePass {
   /// \brief Runs an injection pass to inject in operators needed at the pre pass stage
   /// \param[inout] tree The tree to operate on.
   /// \param[inout] Indicate of the tree was modified.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnTree(ExecutionTree *tree, bool *modified) override;
 };
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/engine/opt/pre/node_removal_pass.cc

@@ -17,7 +17,10 @@
 #include <vector>
 #include <algorithm>
 #include "minddata/dataset/engine/opt/pre/node_removal_pass.h"
+#include "minddata/dataset/engine/ir/datasetops/repeat_node.h"
 #include "minddata/dataset/engine/ir/datasetops/shuffle_node.h"
+#include "minddata/dataset/engine/ir/datasetops/skip_node.h"
+#include "minddata/dataset/engine/ir/datasetops/take_node.h"
 
 namespace mindspore {
 namespace dataset {
@@ -47,7 +50,16 @@ Status NodeRemovalPass::RemovalNodes::VisitAfter(std::shared_ptr<DatasetNode> no
   return Status::OK();
 }
 
-// Perform ShuffleOp removal check.
+// Perform RepeatNode removal check.
+Status NodeRemovalPass::RemovalNodes::Visit(std::shared_ptr<RepeatNode> node, bool *modified) {
+  *modified = false;
+  if (node->Count() == 1) {
+    nodes_to_remove_.push_back(std::static_pointer_cast<DatasetNode>(node));
+  }
+  return Status::OK();
+}
+
+// Perform ShuffleNode removal check.
 Status NodeRemovalPass::RemovalNodes::Visit(std::shared_ptr<ShuffleNode> node, bool *modified) {
   *modified = false;
 #if 0
@@ -60,6 +72,24 @@ Status NodeRemovalPass::RemovalNodes::Visit(std::shared_ptr<ShuffleNode> node, b
   return Status::OK();
 }
 
+// Perform SkipNode removal check.
+Status NodeRemovalPass::RemovalNodes::Visit(std::shared_ptr<SkipNode> node, bool *modified) {
+  *modified = false;
+  if (node->Count() == 0) {
+    nodes_to_remove_.push_back(std::static_pointer_cast<DatasetNode>(node));
+  }
+  return Status::OK();
+}
+
+// Perform TakeNode removal check.
+Status NodeRemovalPass::RemovalNodes::Visit(std::shared_ptr<TakeNode> node, bool *modified) {
+  *modified = false;
+  if (node->Count() == -1) {
+    nodes_to_remove_.push_back(std::static_pointer_cast<DatasetNode>(node));
+  }
+  return Status::OK();
+}
+
 // constructor
 NodeRemovalPass::NodeRemovalPass() {}
 

mindspore/ccsrc/minddata/dataset/engine/opt/pre/node_removal_pass.h

@@ -45,21 +45,39 @@ class NodeRemovalPass : public IRTreePass {
     /// \brief Identifies the subtree below this node as a cached descendant tree.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status Visit(std::shared_ptr<DatasetNode> node, bool *modified) override;
 
     /// \brief Resets the tracking of the cache within the tree
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status VisitAfter(std::shared_ptr<DatasetNode> node, bool *modified) override;
 
+    /// \brief Perform RepeatNode removal check
+    /// \param[in] node The node being visited
+    /// \param[inout] modified Indicator if the node was changed at all
+    /// \return Status The status code returned
+    Status Visit(std::shared_ptr<RepeatNode> node, bool *modified) override;
+
     /// \brief Perform ShuffleNode removal check
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status Visit(std::shared_ptr<ShuffleNode> node, bool *modified) override;
 
+    /// \brief Perform SkipNode removal check
+    /// \param[in] node The node being visited
+    /// \param[inout] modified Indicator if the node was changed at all
+    /// \return Status The status code returned
+    Status Visit(std::shared_ptr<SkipNode> node, bool *modified) override;
+
+    /// \brief Perform TakeNode removal check
+    /// \param[in] node The node being visited
+    /// \param[inout] modified Indicator if the node was changed at all
+    /// \return Status The status code returned
+    Status Visit(std::shared_ptr<TakeNode> node, bool *modified) override;
+
     /// \brief Getter
     /// \return All the nodes to be removed
     std::vector<std::shared_ptr<DatasetNode>> nodes_to_remove() { return nodes_to_remove_; }
@@ -79,7 +97,7 @@ class NodeRemovalPass : public IRTreePass {
   /// \brief Runs a removal_nodes pass first to find out which nodes to remove, then removes them.
   /// \param[inout] tree The tree to operate on.
   /// \param[inout] Indicate of the tree was modified.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnTree(std::shared_ptr<DatasetNode> root_ir, bool *modified) override;
 };
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/engine/opt/pre/removal_pass.h

@@ -46,20 +46,20 @@ class RemovalPass : public TreePass {
     /// \brief Identifies the subtree below this node as a cached descendant tree.
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status PreRunOnNode(std::shared_ptr<CacheOp> node, bool *modified) override;
 
     /// \brief Resets the tracking of the cache within the tree
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<CacheOp> node, bool *modified) override;
 #endif
 
     /// \brief Perform ShuffleOp removal check
     /// \param[in] node The node being visited
     /// \param[inout] modified Indicator if the node was changed at all
-    /// \return Status The error code return
+    /// \return Status The status code returned
     Status RunOnNode(std::shared_ptr<ShuffleOp> node, bool *modified) override;
 
     /// \brief Getter
@@ -81,7 +81,7 @@ class RemovalPass : public TreePass {
   /// \brief Runs a removal_nodes pass first to find out which nodes to remove, then removes them.
   /// \param[inout] tree The tree to operate on.
   /// \param[inout] Indicate of the tree was modified.
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RunOnTree(ExecutionTree *tree, bool *modified) override;
 };
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/engine/perf/connector_size.h

@@ -53,7 +53,7 @@ class ConnectorSize : public Sampling {
   std::string Name() const override { return kConnectorSizeSamplingName; }
 
   // Save sampling data to file
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status SaveToFile() override;
 
   Status Init(const std::string &dir_path, const std::string &device_id) override;

mindspore/ccsrc/minddata/dataset/engine/perf/connector_throughput.h

@@ -65,7 +65,7 @@ class ConnectorThroughput : public Sampling {
   std::string Name() const override { return name_; };
 
   // Save sampling data to file
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status SaveToFile() override;
 
   Status Init(const std::string &dir_path, const std::string &device_id);

mindspore/ccsrc/minddata/dataset/engine/perf/dataset_iterator_tracing.h

@@ -32,13 +32,13 @@ class DatasetIteratorTracing : public Tracing {
   ~DatasetIteratorTracing() override = default;
 
   // Record tracing data
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Record(const int32_t type, const int32_t extra_info, const int32_t batch_num, const int32_t value);
 
   std::string Name() const override { return kDatasetIteratorTracingName; };
 
   // Save tracing data to file
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status SaveToFile() override;
 
   Status Init(const std::string &dir_path, const std::string &device_id) override;

mindspore/ccsrc/minddata/dataset/engine/perf/device_queue_tracing.h

@@ -32,13 +32,13 @@ class DeviceQueueTracing : public Tracing {
   ~DeviceQueueTracing() override = default;
 
   // Record tracing data
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Record(const int32_t type, const int32_t extra_info, const int32_t batch_num, const int32_t value);
 
   std::string Name() const override { return kDeviceQueueTracingName; };
 
   // Save tracing data to file
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status SaveToFile() override;
 
   Status Init(const std::string &dir_path, const std::string &device_id) override;

mindspore/ccsrc/minddata/dataset/engine/perf/profiling.h

@@ -87,19 +87,19 @@ class ProfilingManager {
   Status Initialize();
 
   // Save profile data to file
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status SaveProfilingData();
 
   // Sampling node getter
   // @param name - The name of the requested node
   // @param node - Pointer to the shared pointer for the Sampling node
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetSamplingNode(const std::string &name, std::shared_ptr<Sampling> *node);
 
   // Tracing node getter
   // @param name - The name of the requested node
   // @param node - Pointer to the shared pointer for the Tracing node
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status GetTracingNode(const std::string &name, std::shared_ptr<Tracing> *node);
 
   // If profiling is enabled.
@@ -120,12 +120,12 @@ class ProfilingManager {
 
   // Register profile node to tree
   // @param node - Profiling node
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status RegisterTracingNode(std::shared_ptr<Tracing> node);
 
   // Register profile node to tree
   // @param node - Profiling node
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status RegisterSamplingNode(std::shared_ptr<Sampling> node);
 
   ExecutionTree *tree_ = nullptr;  // ExecutionTree pointer

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

@@ -442,7 +442,7 @@ class SchemaObj {
   Status parse_column(nlohmann::json columns);
 
   /// \brief Get schema file from JSON file
-  /// \param[in] json_obj Object of JSON parsed.
+  /// \param[in] json_obj parsed JSON object
   /// \return Status code
   Status from_json(nlohmann::json json_obj);
 

mindspore/ccsrc/minddata/dataset/kernels/data/data_utils.h

@@ -77,7 +77,7 @@ Status TypeCast(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *o
 // @param std::shared_ptr<Tensor> *dst - return tensor padded
 // @param std::vector<dsize_t> pad_shape - shape to pad to
 // @param std::shared_ptr<Tensor> pad_val - value to pad with in Tensor format,
-// @return - The error code return
+// @return Status The status code returned
 Status PadEnd(const std::shared_ptr<Tensor> &src, std::shared_ptr<Tensor> *dst, const std::vector<dsize_t> &pad_shape,
               const std::shared_ptr<Tensor> &pad_val);
 
@@ -86,7 +86,7 @@ Status PadEnd(const std::shared_ptr<Tensor> &src, std::shared_ptr<Tensor> *dst,
 // @param std::shared_ptr<Tensor> *dst - return tensor padded
 // @param std::vector<dsize_t> pad_shape - shape to pad to
 // @param float pad_val - value to pad with
-// @return - The error code return
+// @return Status The status code returned
 Status PadEndNumeric(const std::shared_ptr<Tensor> &src, std::shared_ptr<Tensor> *dst,
                      const std::vector<dsize_t> &pad_shape, float pad_val);
 
@@ -98,7 +98,7 @@ Status PadEndNumeric(const std::shared_ptr<Tensor> &src, std::shared_ptr<Tensor>
 // @param std::vector<dsize_t> cur_ind - recursion helper
 // @param T pad_val - value to pad tensor with
 // @param size_t cur_dim - recursion helper
-// @return Status - The error code return
+// @return Status The status code returned
 Status PadEndNumericHelper(const std::shared_ptr<Tensor> &src, std::shared_ptr<Tensor> dst,
                            std::vector<dsize_t> cur_ind, size_t cur_dim = 0);
 
@@ -107,7 +107,7 @@ Status PadEndNumericHelper(const std::shared_ptr<Tensor> &src, std::shared_ptr<T
 // @param std::shared_ptr<Tensor> *dst - return tensor padded
 // @param std::vector<dsize_t> pad_shape - shape to pad to
 // @param std::string pad_val - value to pad with
-// @return - The error code return
+// @return Status The status code returned
 Status PadEndString(const std::shared_ptr<Tensor> &src, std::shared_ptr<Tensor> *dst,
                     const std::vector<dsize_t> &pad_shape, const std::string &pad_val);
 
@@ -119,7 +119,7 @@ Status PadEndString(const std::shared_ptr<Tensor> &src, std::shared_ptr<Tensor>
 // @param std::vector<dsize_t> cur_ind - recursion helperas text
 // @param std::string pad_val - value to pad tensor with
 // @param size_t cur_dim - recursion helper
-// @return Status - The error code return
+// @return Status The status code returned
 Status PadEndStringHelper(const std::shared_ptr<Tensor> &src, std::vector<std::string> *dst,
                           const TensorShape &dst_shape, std::vector<dsize_t> cur_ind, size_t cur_dim,
                           const std::string &pad_value);

mindspore/ccsrc/minddata/dataset/kernels/data/to_float16_op.h

@@ -36,7 +36,7 @@ class ToFloat16Op : public TensorOp {
   // Overrides the base class compute function
   // Calls the ToFloat16 function in ImageUtils, this function takes an input tensor
   // and transforms its data to float16, the output memory is manipulated to contain the result
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) override;
 
   Status OutputType(const std::vector<DataType> &inputs, std::vector<DataType> &outputs) override;

mindspore/ccsrc/minddata/dataset/kernels/image/cut_out_op.h

@@ -58,7 +58,7 @@ class CutOutOp : public TensorOp {
   // Overrides the base class compute function
   // Calls the erase function in ImageUtils, this function takes an input tensor
   // and overwrites some of its data using openCV, the output memory is manipulated to contain the result
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) override;
 
   std::string Name() const override { return kCutOutOp; }

mindspore/ccsrc/minddata/dataset/kernels/image/random_color_adjust_op.h

@@ -50,7 +50,7 @@ class RandomColorAdjustOp : public TensorOp {
   // Overrides the base class compute function.
   // Calls multiple transform functions in ImageUtils, this function takes an input tensor.
   // and transforms its data using openCV, the output memory is manipulated to contain the result.
-  // @return Status - The error code return.
+  // @return Status The status code returned.
   Status Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) override;
 
   std::string Name() const override { return kRandomColorAdjustOp; }

mindspore/ccsrc/minddata/dataset/kernels/image/random_rotation_op.h

@@ -61,7 +61,7 @@ class RandomRotationOp : public TensorOp {
   // Overrides the base class compute function
   // Calls the rotate function in ImageUtils, this function takes an input tensor
   // and transforms its data using openCV, the output memory is manipulated to contain the result
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) override;
   Status OutputShape(const std::vector<TensorShape> &inputs, std::vector<TensorShape> &outputs) override;
 

mindspore/ccsrc/minddata/dataset/kernels/image/uniform_aug_op.h

@@ -43,7 +43,7 @@ class UniformAugOp : public TensorOp {
   void Print(std::ostream &out) const override { out << Name() << ":: number of ops " << num_ops_; }
 
   // Overrides the base class compute function
-  // @return Status - The error code return
+  // @return Status The status code returned
   Status Compute(const TensorRow &input, TensorRow *output) override;
 
   std::string Name() const override { return kUniformAugOp; }

mindspore/ccsrc/minddata/dataset/util/data_helper.h

@@ -53,7 +53,7 @@ class DataHelper {
   /// \param key Key of field to write to
   /// \param value Value array to write to file
   /// \param out_file Optional input for output file path, will write to input file if not specified
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status UpdateArray(const std::string &in_file, const std::string &key, const std::vector<std::string> &value,
                      const std::string &out_file = "");
 
@@ -62,7 +62,7 @@ class DataHelper {
   /// \param key Key of field to write to
   /// \param value Value array to write to file
   /// \param out_file Optional parameter for output file path, will write to input file if not specified
-  /// \return Status The error code return
+  /// \return Status The status code returned
   template <typename T>
   Status UpdateArray(const std::string &in_file, const std::string &key, const std::vector<T> &value,
                      const std::string &out_file = "") {
@@ -99,7 +99,7 @@ class DataHelper {
   /// \param key Key of field to write to
   /// \param value Value to write to file
   /// \param out_file Optional parameter for output file path, will write to input file if not specified
-  /// \return Status The error code return
+  /// \return Status The status code returned
   template <typename T>
   Status UpdateValue(const std::string &in_file, const std::string &key, const T &value,
                      const std::string &out_file = "") {
@@ -134,7 +134,7 @@ class DataHelper {
   /// \brief Template function to write tensor to file
   /// \param[in] in_file File to write to
   /// \param[in] data Array of type T values
-  /// \return Status The error code return
+  /// \return Status The status code returned
   template <typename T>
   Status WriteBinFile(const std::string &in_file, const std::vector<T> &data) {
     try {
@@ -157,7 +157,7 @@ class DataHelper {
   /// \param[in] in_file File name to write to
   /// \param[in] data Pointer to data
   /// \param[in] length Length of values to write from pointer
-  /// \return Status The error code return
+  /// \return Status The status code returned
   template <typename T>
   Status WriteBinFile(const std::string &in_file, T *data, size_t length) {
     try {
@@ -188,7 +188,7 @@ class DataHelper {
   /// note This function will return okay even if key not found
   /// \param[in] in_file Json file to remove key from
   /// \param[in] key The key to remove
-  /// \return Status The error code return
+  /// \return Status The status code returned
   Status RemoveKey(const std::string &in_file, const std::string &key, const std::string &out_file = "");
 
   /// \brief A print method typically used for debugging

mindspore/dataset/engine/datasets.py

@@ -669,8 +669,6 @@ class Dataset:
             >>> repeat_and_shuffle = data.repeat(50)
             >>> repeat_and_shuffle = repeat_and_shuffle.shuffle(10)
         """
-        if count == 1:
-            return self
         return RepeatDataset(self, count)
 
     @check_skip
@@ -717,8 +715,6 @@ class Dataset:
             >>> # Create a dataset where the dataset includes 50 elements.
             >>> data = data.take(50)
         """
-        if count == -1:
-            return self
         return TakeDataset(self, count)
 
     def _get_absolute_split_sizes(self, sizes):

tests/ut/cpp/dataset/c_api_dataset_ops_test.cc

@@ -1311,6 +1311,51 @@ TEST_F(MindDataTestPipeline, TestSkipDataset) {
   iter->Stop();
 }
 
+TEST_F(MindDataTestPipeline, TestSkipTakeRepeat) {
+  MS_LOG(INFO) << "Doing MindDataTestPipeline-TestSkipTakeRepeat.";
+
+  // Create an ImageFolder Dataset
+  std::string folder_path = datasets_root_path_ + "/testPK/data/";
+  std::shared_ptr<Dataset> ds = ImageFolder(folder_path, true, RandomSampler(false, 6));
+
+  // Create a Skip operation on ds
+  int32_t count = 0;
+  ds = ds->Skip(count);
+
+  // Create a Project operation on ds
+  std::vector<std::string> column_project = {"image"};
+  ds = ds->Project(column_project);
+
+  // Add a Take(-1)
+  ds = ds->Take(-1);
+
+  // Add a Repeat(1)
+  ds = ds->Repeat(1);
+
+  // 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();
+
+  // iterate over 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);
+  }
+  MS_LOG(INFO) << "Number of rows: " << i;
+
+  // Expect 6 rows
+  EXPECT_EQ(i, 6);
+
+  // Manually terminate the pipeline
+  iter->Stop();
+}
+
 TEST_F(MindDataTestPipeline, TestSkipGetDatasetSize) {
   MS_LOG(INFO) << "Doing MindDataTestPipeline-TestSkipGetDatasetSize.";
 

tests/ut/python/dataset/test_take.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 # ==============================================================================
 import numpy as np
-
+import pytest
 import mindspore.dataset as ds
 from mindspore import log as logger
 
@@ -163,7 +163,7 @@ def test_take_08():
 
 def test_take_09():
     """
-    Test take: repeat count is -1, and read the whole dataset, take after repeat
+    Test take: take count is -1, and read the whole dataset, take after repeat
     """
     logger.info("test_take_09")
     data1 = ds.GeneratorDataset(generator, ["data"])
@@ -180,7 +180,7 @@ def test_take_09():
 
 def test_take_10():
     """
-    Test take: repeat count is -1, and read the whole dataset, take before repeat
+    Test take: take count is -1, and read the whole dataset, take before repeat
     """
     logger.info("test_take_10")
     data1 = ds.GeneratorDataset(generator, ["data"])
@@ -341,6 +341,18 @@ def test_take_18():
     assert sum([1 for _ in data1]) == 2
 
 
+def test_take_19():
+    """
+    Test take: take is after batch, that mean take(N), N refer to batches num
+    """
+    logger.info("test_take_19")
+    with pytest.raises(ValueError) as info:
+        data1 = ds.GeneratorDataset(generator, ["data"])
+
+        data1 = data1.batch(2)
+        data1 = data1.take(0)
+    assert "positive integer" in str(info.value)
+
 if __name__ == '__main__':
     test_take_01()
     test_take_02()
@@ -360,4 +372,5 @@ if __name__ == '__main__':
     test_take_16()
     test_take_17()
     test_take_18()
+    test_take_19()
     logger.info('== test take operation finished ==')