Try to fix API reference for new API

docs/api/api_reference.rst

@@ -10,6 +10,7 @@ API references available:
 
 .. toctree::
    :maxdepth: 2
-
-   ../groupie_cpp_api
+
+   ../groupov_cpp_api
+   ../groupie_c_api
    ie_python_api/api

src/common/transformations/include/transformations_visibility.hpp

@@ -12,7 +12,6 @@
  */
 
 /**
- * @ingroup ie_cpp_api
  * @defgroup ie_transformation_api Inference Engine Transformation API
  * @brief Defines Inference Engine Transformations API which is used to transform ngraph::Function
  *

src/core/include/openvino/core/core_visibility.hpp

@@ -11,6 +11,29 @@
 // OPENVINO_API is used for the public API symbols. It either DLL imports or DLL exports
 //    (or does nothing for static build)
 
+/**
+ * @defgroup ov_cpp_api OpenVINO Runtime C++ API
+ * OpenVINO Runtime C++ API
+ *
+ * @defgroup ov_model_cpp_api OpenVINO Core C++ API to work with ov::Model
+ * @ingroup ov_cpp_api
+ * OpenVINO Core C++ API to work with ov::Model, dynamic and static shapes, types
+ *
+ * @defgroup ov_ops_cpp_api OpenVINO C++ API to create operations
+ * @ingroup ov_cpp_api
+ * OpenVINO C++ API to create operations from different opsets. Such API is used to
+ * creation models from code, write transformations and traverse the model graph
+ *
+ * @defgroup ov_opset_cpp_api OpenVINO C++ API to work with operation sets
+ * @ingroup ov_cpp_api
+ * OpenVINO C++ API to work with operation sets
+ *
+ * @defgroup ov_runtime_cpp_api OpenVINO Inference C++ API
+ * @ingroup ov_cpp_api
+ * OpenVINO Inference C++ API provides ov::Core, ov::CompiledModel, ov::InferRequest
+ * and ov::Tensor classes
+ */
+
 #ifdef _WIN32
 #    pragma warning(disable : 4251)
 #    pragma warning(disable : 4275)

src/core/include/openvino/core/model.hpp

@@ -34,7 +34,11 @@ class FrontEnd;
 }
 
 class ModelAccessor;
-/// A user-defined model.
+
+/**
+ * @brief A user-defined model
+ * @ingroup ov_model_cpp_api
+ */
 class OPENVINO_API Model : public std::enable_shared_from_this<Model> {
     friend class frontend::FrontEnd;
     friend OPENVINO_API std::shared_ptr<Model> clone_model(const Model& func,

src/inference/include/ie/ie_version.hpp

@@ -27,7 +27,6 @@
 #include "ie_api.h"
 
 /**
- * @ingroup ie_cpp_api
  * @brief Inference Engine C++ API
  */
 namespace InferenceEngine {

src/inference/include/openvino/runtime/common.hpp

@@ -46,6 +46,7 @@ namespace ie = InferenceEngine;
 
 /**
  * @brief This type of map is used for result of Core::query_model
+ * @ingroup ov_runtime_cpp_api
  *   - `key` means operation name
  *   - `value` means device name supporting this operation
  */

src/inference/include/openvino/runtime/compiled_model.hpp

@@ -32,6 +32,7 @@ class InferRequest;
 
 /**
  * @brief This class represents a compiled model.
+ * @ingroup ov_runtime_cpp_api
  * A model is compiled by a specific device by applying multiple optimization
  * transformations, then mapping to compute kernels.
  */

src/inference/include/openvino/runtime/core.hpp

@@ -34,6 +34,7 @@ namespace ov {
 
 /**
  * @brief This class represents an OpenVINO runtime Core entity.
+ * @ingroup ov_runtime_cpp_api
  * User applications can create several Core class instances, but in this case the underlying plugins
  * are created multiple times and not shared between several Core instances. The recommended way is to have
  * a single Core instance per application.

src/inference/include/openvino/runtime/exception.hpp

@@ -11,16 +11,19 @@ namespace ov {
 
 /**
  * @brief Thrown in case of cancelled asynchronous operation.
+ * @ingroup ov_runtime_cpp_api
  */
 class OPENVINO_RUNTIME_API Cancelled : public Exception {
     using Exception::Exception;
 };
 
 /**
- * @brief Thrown in case of calling the InferRequest methods while the request is busy with compute operation.
+ * @brief Thrown in case of calling the InferRequest methods while the request is
+ * busy with compute operation.
+ * @ingroup ov_runtime_cpp_api
  */
 class OPENVINO_RUNTIME_API Busy : public Exception {
     using Exception::Exception;
 };
 
-}  // namespace ov
+}  // namespace ov

src/inference/include/openvino/runtime/infer_request.hpp

@@ -29,6 +29,7 @@ class CompiledModel;
 
 /**
  * @brief This is a class of infer request that can be run in asynchronous or synchronous manners.
+ * @ingroup ov_runtime_cpp_api
  */
 class OPENVINO_RUNTIME_API InferRequest {
     std::shared_ptr<InferenceEngine::IInferRequestInternal> _impl;

src/inference/include/openvino/runtime/intel_gna/properties.hpp

@@ -14,20 +14,29 @@
 
 namespace ov {
 
+/**
+ * @defgroup ov_runtime_gna_prop_cpp_api Intel GNA specific properties
+ * @ingroup ov_runtime_cpp_api
+ * Set of Intel GNA specific properties.
+ */
+
 /**
  * @brief Namespace with Intel GNA specific properties
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 namespace intel_gna {
 
 /**
  * @brief Property to get an std::string of GNA Library version, usually in the form
  * <API_REVISION>.<RELEASE_LINE>.<RELEASE>.<BUILD>
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 static constexpr Property<std::string, PropertyMutability::RO> library_full_version{"GNA_LIBRARY_FULL_VERSION"};
 
 /**
  * @brief Scale factor provided by the user to use static quantization.
  * This option should be used with floating point value serialized to string with . (dot) as a decimal separator
+ * @ingroup ov_runtime_gna_prop_cpp_api
  * @details In the case of multiple inputs, individual scale factors can be provided using the
  *  map where key is layer name and value is scale factor
  * Example:
@@ -45,11 +54,13 @@ static constexpr Property<std::map<std::string, float>> scale_factors_per_input{
 
 /**
  * @brief if turned on, dump GNA firmware model into specified file
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 static constexpr Property<std::string> firmware_model_image_path{"GNA_FIRMWARE_MODEL_IMAGE"};
 
 /**
  * @brief Enum to define software acceleration mode
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 enum class ExecutionMode {
     AUTO = 0,  //!< Uses Intel GNA if available, otherwise uses software execution mode on CPU.
@@ -103,6 +114,7 @@ inline std::istream& operator>>(std::istream& is, ExecutionMode& execution_mode)
 
 /**
  * @brief Enum to define HW compile and execution targets
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 enum class HWGeneration {
     UNDEFINED = 0,  //!< GNA HW generation is undefined
@@ -143,6 +155,7 @@ inline std::istream& operator>>(std::istream& is, HWGeneration& hw_generation) {
 /**
  * @brief GNA proc_type setting that should be one of AUTO, HW, GNA_HW_WITH_SW_FBACK,
  *        GNA_SW_EXACT or SW_FP32
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 static constexpr Property<ExecutionMode> execution_mode{"GNA_DEVICE_MODE"};
 
@@ -153,22 +166,26 @@ static constexpr Property<ExecutionMode> execution_mode{"GNA_DEVICE_MODE"};
  * If HW is not present, use the option corresponding to the latest fully supported GNA HW generation.
  * A fully supported GNA HW generation means it must be supported by both the OV GNA Plugin and the core GNA Library.
  * Currently, the latest supported GNA HW generation corresponds to GNA_3_0.
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 static constexpr Property<HWGeneration> execution_target{"GNA_HW_EXECUTION_TARGET"};
 
 /**
  * @brief The option to override the GNA HW compile target. May be one of GNA_2_0, GNA_3_0.
  * By default the same as execution_target.
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 static constexpr Property<HWGeneration> compile_target{"GNA_HW_COMPILE_TARGET"};
 
 /**
  * @brief if enabled produced minimum memory footprint for compiled model in GNA memory, default value is true
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 static constexpr Property<bool> memory_reuse{"GNA_COMPACT_MODE"};
 
 /**
  * @brief Enum to define PWL design algorithm
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 enum class PWLDesignAlgorithm {
     UNDEFINED = 0,             //!< PWL approximation algorithm is undefined
@@ -213,13 +230,15 @@ inline std::istream& operator>>(std::istream& is, PWLDesignAlgorithm& pwl_design
  * If value is UNIFORM_DISTRIBUTION then simple uniform distribution is used to create
  * PWL approximation of activation functions.
  * Uniform distribution usually gives poor approximation with the same number of segments
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 static constexpr Property<PWLDesignAlgorithm> pwl_design_algorithm{"GNA_PWL_DESIGN_ALGORITHM"};
 
 /**
  * @brief The option to allow to specify the maximum error percent that the optimized algorithm finding
  * will be used to find PWL functions.
  * By default (in case of NO value set), 1.0 value is used.
+ * @ingroup ov_runtime_gna_prop_cpp_api
  */
 static constexpr Property<float> pwl_max_error_percent{"GNA_PWL_MAX_ERROR_PERCENT"};
 

src/inference/include/openvino/runtime/intel_gpu/ocl/dx.hpp

@@ -3,7 +3,7 @@
 //
 
 /**
- * @brief a header that defines wrappers for internal GPU plugin-specific
+ * @brief A header that defines wrappers for internal GPU plugin-specific
  * shared Video Acceleration device contexts
  * and shared memory tensors which contain Video Acceleration surfaces
  *
@@ -35,6 +35,7 @@ namespace ocl {
  * which is shared with Direct3D 11 buffer.
  * The plugin object derived from this class can be obtained with D3DContext::create_tensor() call.
  * @note User can also obtain OpenCL buffer handle from this class.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class D3DBufferTensor : public ClBufferTensor {
 public:
@@ -62,6 +63,7 @@ class D3DBufferTensor : public ClBufferTensor {
  * which is shared with Direct3D 11 2D texture.
  * The plugin object derived from this class can be obtained with D3DContext::create_tensor() call.
  * @note User can also obtain OpenCL 2D image handle from this class.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class D3DSurface2DTensor : public ClImage2DTensor {
 public:
@@ -99,6 +101,7 @@ class D3DSurface2DTensor : public ClImage2DTensor {
  * The plugin object derived from this class can be obtained either with
  * CompiledModel::get_context() or Core::create_context() calls.
  * @note User can also obtain OpenCL context handle from this class.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class D3DContext : public ClContext {
 public:

src/inference/include/openvino/runtime/intel_gpu/ocl/ocl.hpp

@@ -22,13 +22,21 @@
 namespace ov {
 namespace intel_gpu {
 
+/**
+ * @defgroup ov_runtime_ocl_gpu_cpp_api Intel GPU OpenCL remote objects API
+ * @ingroup ov_runtime_cpp_api
+ * Set of C++ classes and properties to work with Remote API for Intel GPU OpenCL plugin.
+ */
+
 /**
  * @brief Namespace with Intel GPU OpenCL specific remote objects
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 namespace ocl {
 
 /**
  * @brief Shortcut for defining a handle parameter
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 using gpu_handle_param = void*;
 
@@ -37,6 +45,7 @@ using gpu_handle_param = void*;
  * which can be shared with user-supplied OpenCL buffer.
  * The plugin object derived from this class can be obtained with ClContext::create_tensor() call.
  * @note User can obtain OpenCL buffer handle from this class.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class ClBufferTensor : public RemoteTensor {
 public:
@@ -81,6 +90,7 @@ class ClBufferTensor : public RemoteTensor {
  * which can be shared with user-supplied OpenCL 2D Image.
  * The plugin object derived from this class can be obtained with ClContext::create_tensor() call.
  * @note User can obtain OpenCL image handle from this class.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class ClImage2DTensor : public RemoteTensor {
 public:
@@ -125,6 +135,7 @@ class ClImage2DTensor : public RemoteTensor {
  * which can be shared with user-supplied USM device pointer.
  * The plugin object derived from this class can be obtained with ClContext::create_tensor() call.
  * @note User can obtain USM pointer from this class.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class USMTensor : public RemoteTensor {
 public:
@@ -155,6 +166,7 @@ class USMTensor : public RemoteTensor {
  * which is shared with OpenCL context object.
  * The plugin object derived from this class can be obtained either with
  * CompiledModel::get_context() or Core::create_context() calls.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class ClContext : public RemoteContext {
 protected:

src/inference/include/openvino/runtime/intel_gpu/ocl/va.hpp

@@ -33,6 +33,7 @@ namespace ocl {
  * which is shared with VA output surface.
  * The plugin object derived from this class can be obtained with VAContext::create_tensor() call.
  * @note User can also obtain OpenCL 2D image handle from this class.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class VASurfaceTensor : public ClImage2DTensor {
 public:
@@ -69,6 +70,7 @@ class VASurfaceTensor : public ClImage2DTensor {
  * The plugin object derived from this class can be obtained either with
  * CompiledModel::get_context() or Core::create_context() calls.
  * @note User can also obtain OpenCL context handle from this class.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 class VAContext : public ClContext {
 public: