modify headerfile

include/api/cfg.h

@@ -37,7 +37,7 @@ class MixPrecisionCfg {
 
   ~MixPrecisionCfg() = default;
 
-  bool dynamic_loss_scale_ = false;   /**< Enable\disable dynamic loss scale during mix precision training */
+  bool dynamic_loss_scale_ = false;   /**< Enable/disable dynamic loss scale during mix precision training */
   float loss_scale_;                  /**< Initial loss scale factor  */
   bool keep_batchnorm_fp32_ = true;   /**< Keep batch norm in FP32 while training */
   uint32_t num_of_not_nan_iter_th_;   /**< a threshold for modifying loss scale when dynamic loss scale is enabled */

include/api/model.h

@@ -128,7 +128,7 @@ class MS_API Model {
   /// \param[in] backbone The static, non-learnable part of the graph
   /// \param[in] head The trainable part of the graph
   /// \param[in] context A context used to store options during execution
-  /// \param[in] cfg A config used by training
+  /// \param[in] train_cfg A config used by training
   ///
   /// \return Status
   Status BuildTransferLearning(GraphCell backbone, GraphCell head, const std::shared_ptr<Context> &context,
@@ -173,7 +173,6 @@ class MS_API Model {
   ///
   /// \param[in] inputs A vector where model inputs are arranged in sequence.
   /// \param[out] outputs Which is a pointer to a vector. The model outputs are filled in the container in sequence.
-  /// \param[in] whether to use data preprocess in model.
   /// \param[in] before CallBack before predict.
   /// \param[in] after CallBack after predict.
   ///
@@ -225,7 +224,7 @@ class MS_API Model {
 
   /// \brief update gradient tensors of the model.
   ///
-  /// \param[in] inputs A vector new gradients.
+  /// \param[in] gradients A vector new gradients.
   /// \return Status of operation
   Status ApplyGradients(const std::vector<MSTensor> &gradients);
 
@@ -236,7 +235,7 @@ class MS_API Model {
 
   /// \brief update weights tensors of the model.
   ///
-  /// \param[in] inputs A vector new weights.
+  /// \param[in] new_weights A vector new weights.
   /// \return Status of operation
   Status UpdateFeatureMaps(const std::vector<MSTensor> &new_weights);
 
@@ -247,7 +246,7 @@ class MS_API Model {
 
   /// \brief update the optimizer parameters
   ///
-  /// \param[in] inputs A vector new optimizer params.
+  /// \param[in] params A vector new optimizer params.
   /// \return Status of operation
   Status SetOptimizerParams(const std::vector<MSTensor> &params);
 
@@ -299,7 +298,7 @@ class MS_API Model {
 
   /// \brief Bind GLTexture2D object to cl Memory.
   ///
-  /// \param[in] inputGlTexture The input GLTexture id for Model.
+  /// \param[in] inputGLTexture The input GLTexture id for Model.
   /// \param[in] outputGLTexture The output GLTexture id for Model.
   ///
   /// \return Status of operation.

include/api/serialization.h

@@ -59,7 +59,7 @@ class MS_API Serialization {
   ///
   /// \param[in] files The path of model files.
   /// \param[in] model_type The Type of model file, options are ModelType::kMindIR, ModelType::kOM.
-  /// \param[out] graph The output parameter, an object saves graph data.
+  /// \param[out] graphs The output parameter, an object saves graph data.
   /// \param[in] dec_key The decryption key, key length is 16, 24, or 32.
   /// \param[in] dec_mode The decryption mode, optional options are AES-GCM, AES-CBC.
   ///

include/api/types.h

@@ -216,22 +216,22 @@ class MS_API MSTensor {
 
   /// \brief Set the shape of for the MSTensor. Only valid for Lite.
   ///
-  /// \param[in] Shape of the MSTensor, a vector of int64_t.
+  /// \param[in] shape Shape of the MSTensor, a vector of int64_t.
   void SetShape(const std::vector<int64_t> &shape);
 
   /// \brief Set the data type for the MSTensor. Only valid for Lite.
   ///
-  /// \param[in] The data type of the MSTensor.
+  /// \param[in] data_type The data type of the MSTensor.
   void SetDataType(enum DataType data_type);
 
   /// \brief Set the name for the MSTensor. Only valid for Lite.
   ///
-  /// \param[in] The name of the MSTensor.
+  /// \param[in] name The name of the MSTensor.
   inline void SetTensorName(const std::string &name);
 
   /// \brief Set the Allocator for the MSTensor. Only valid for Lite.
   ///
-  /// \param[in] A pointer to Allocator.
+  /// \param[in] allocator A pointer to Allocator.
   void SetAllocator(std::shared_ptr<Allocator> allocator);
 
   /// \brief Obtain the Allocator of the MSTensor. Only valid for Lite.
@@ -241,7 +241,7 @@ class MS_API MSTensor {
 
   /// \brief Set the format for the MSTensor. Only valid for Lite.
   ///
-  /// \param[in] The format of the MSTensor.
+  /// \param[in] format The format of the MSTensor.
   void SetFormat(mindspore::Format format);
 
   /// \brief Obtain the format of the MSTensor. Only valid for Lite.
@@ -257,7 +257,7 @@ class MS_API MSTensor {
   ///
   /// \note The memory pointed to origin data pointer of MSTensor needs to be managed by the user
   ///
-  /// \param[in] A pointer to the data of the MSTensor.
+  /// \param[in] data A pointer to the data of the MSTensor.
   void SetData(void *data);
 
   /// \brief Get the quantization parameters of the MSTensor. Only valid for Lite.
@@ -267,7 +267,7 @@ class MS_API MSTensor {
 
   /// \brief Set the quantization parameters for the MSTensor. Only valid for Lite.
   ///
-  /// \param[in] The quantization parameters of the MSTensor.
+  /// \param[in] quant_params The quantization parameters of the MSTensor.
   void SetQuantParams(std::vector<QuantParam> quant_params);
 
   const std::shared_ptr<Impl> impl() const { return impl_; }

mindspore/core/abstract/abstract_value.h

@@ -93,7 +93,7 @@ class MS_CORE_API AbstractBase : public Base {
 
   /// \brief Set the type for the AbstractBase.
   ///
-  /// \param[in] value The type of an anf node.
+  /// \param[in] type The type of an anf node.
   void set_type(const TypePtr &type) {
     MS_EXCEPTION_IF_NULL(type);
     type_ = type;
@@ -101,7 +101,7 @@ class MS_CORE_API AbstractBase : public Base {
 
   /// \brief Set the shape for the AbstractBase.
   ///
-  /// \param[in] value The shape of an anf node.
+  /// \param[in] shape The shape of an anf node.
   virtual void set_shape(const BaseShapePtr &shape) {
     MS_EXCEPTION_IF_NULL(shape);
     shape_ = shape;
@@ -852,7 +852,7 @@ class MS_CORE_API AbstractTuple final : public AbstractSequence {
   /// \brief Constructor of AbstractTuple.
   ///
   /// \param[in] elements A list of abstracts.
-  /// \param[in] tuple_node The nodes of tuple, usually are MakeTuple CNodes or tuple ValueNodes.
+  /// \param[in] tuple_nodes The nodes of tuple, usually are MakeTuple CNodes or tuple ValueNodes.
   explicit AbstractTuple(AbstractBasePtrList &&elements,
                          const std::shared_ptr<AnfNodeWeakPtrList> &tuple_nodes = nullptr)
       : AbstractSequence(std::move(elements), tuple_nodes) {}
@@ -860,7 +860,7 @@ class MS_CORE_API AbstractTuple final : public AbstractSequence {
   /// \brief Constructor of AbstractTuple.
   ///
   /// \param[in] elements A list of abstracts.
-  /// \param[in] tuple_node The nodes of tuple, usually are MakeTuple CNodes or tuple ValueNodes.
+  /// \param[in] tuple_nodes The nodes of tuple, usually are MakeTuple CNodes or tuple ValueNodes.
   explicit AbstractTuple(const AbstractBasePtrList &elements,
                          const std::shared_ptr<AnfNodeWeakPtrList> &tuple_nodes = nullptr)
       : AbstractSequence(elements, tuple_nodes) {}
@@ -915,14 +915,14 @@ class MS_CORE_API AbstractList final : public AbstractSequence {
   /// \brief Constructor of AbstractList.
   ///
   /// \param[in] elements A list of abstracts.
-  /// \param[in] list_node The nodes of list, usually are MakeList CNodes or list ValueNodes.
+  /// \param[in] list_nodes The nodes of list, usually are MakeList CNodes or list ValueNodes.
   explicit AbstractList(AbstractBasePtrList &&elements, const std::shared_ptr<AnfNodeWeakPtrList> &list_nodes = nullptr)
       : AbstractSequence(std::move(elements), list_nodes) {}
 
   /// \brief Constructor of AbstractList.
   ///
   /// \param[in] elements A list of abstracts.
-  /// \param[in] list_node The nodes of list, usually are MakeList CNodes or list ValueNodes.
+  /// \param[in] list_nodes The nodes of list, usually are MakeList CNodes or list ValueNodes.
   explicit AbstractList(const AbstractBasePtrList &elements,
                         const std::shared_ptr<AnfNodeWeakPtrList> &list_nodes = nullptr)
       : AbstractSequence(elements, list_nodes) {}
@@ -1269,7 +1269,7 @@ class MS_CORE_API AbstractRefKey final : public AbstractBase {
 
   /// \brief Get the ref key.
   ///
-  /// \param[in] The pointer to RefKey.
+  /// \return The pointer to RefKey.
   RefKeyPtr ref_key_value() const { return ref_key_value_; }
 
   AbstractBasePtr Join(const AbstractBasePtr &other) override;

mindspore/core/ir/dtype/number.h

@@ -69,7 +69,7 @@ class MS_CORE_API Number : public Object {
 
   /// \brief Get type name for Number object.
   ///
-  /// \param Define the type name.
+  /// \param type_name Define the type name.
   /// \return The full type name of the Number object.
   std::string GetTypeName(const std::string &type_name) const {
     std::ostringstream oss;

mindspore/core/mindapi/ir/anf.h

@@ -116,7 +116,7 @@ class MIND_API Parameter : public AnfNode {
 
   /// \brief Set the name of this Parameter.
   ///
-  /// \param[in] The name.
+  /// \param[in] name The name.
   void set_name(const std::string &name);
 
   /// \brief Check if there is a default parameter.