Port api reference (#11152)

docs/IE_PLUGIN_DG/Intro.md

@@ -9,11 +9,12 @@
 
    Implement Plugin Functionality <openvino_docs_ie_plugin_dg_plugin>
    Implement Executable Network Functionality <openvino_docs_ie_plugin_dg_executable_network>
-   openvino_docs_ie_plugin_dg_quantized_networks
    Implement Synchronous Inference Request <openvino_docs_ie_plugin_dg_infer_request>
    Implement Asynchronous Inference Request <openvino_docs_ie_plugin_dg_async_infer_request>
    openvino_docs_ie_plugin_dg_plugin_build
    openvino_docs_ie_plugin_dg_plugin_testing
+   openvino_docs_ie_plugin_detailed_guides
+   openvino_docs_ie_plugin_api_references
 
 @endsphinxdirective
 
@@ -61,5 +62,5 @@ Detailed guides
 API References
 -----------------------
 
-* [Inference Engine Plugin API](groupie_dev_api.html)
-* [Inference Engine Transformation API](groupie_transformation_api.html)
+* [Inference Engine Plugin API](@ref ie_dev_api)
+* [Inference Engine Transformation API](@ref ie_transformation_api)

docs/IE_PLUGIN_DG/detailed_guides.md

@@ -0,0 +1,18 @@
+# Advanced Topics {#openvino_docs_ie_plugin_detailed_guides}
+
+@sphinxdirective
+
+.. toctree::
+   :maxdepth: 1
+   :hidden:
+
+   openvino_docs_ie_plugin_dg_quantized_networks
+   openvino_docs_IE_DG_lpt
+
+@endsphinxdirective
+
+The guides below provides extra information about specific features of OpenVINO needed for understanding during OpenVINO plugin development:
+
+* [Quantized networks](@ref openvino_docs_ie_plugin_dg_quantized_networks)
+* [Low precision transformations](@ref openvino_docs_IE_DG_lpt) guide
+* [Writing OpenVINO™ transformations](@ref openvino_docs_transformations) guide

docs/IE_PLUGIN_DG/dev_api_references.md

@@ -0,0 +1,17 @@
+# Plugin API Reference {#openvino_docs_ie_plugin_api_references}
+
+@sphinxdirective
+
+.. toctree::
+   :maxdepth: 1
+   :hidden:
+
+   ../groupie_dev_api
+   ../groupie_transformation_api
+
+@endsphinxdirective
+
+The guides below provides extra API references needed for OpenVINO plugin development:
+
+* [OpenVINO Plugin API](@ref ie_dev_api)
+* [OpenVINO Transformation API](@ref ie_transformation_api)

docs/IE_PLUGIN_DG/plugin_transformation_pipeline/PluginTransformationPipeline.md

@@ -1,17 +0,0 @@
-# Plugin Transformation Pipeline {#openvino_docs_IE_DG_plugin_transformation_pipeline}
-
-@sphinxdirective
-
-.. toctree::
-   :maxdepth: 1
-   :caption: Executable Network
-   :hidden:
-
-   Low Precision Transformations <openvino_docs_IE_DG_lpt>
-
-@endsphinxdirective
-
-Typical plugin transformation pipeline includes steps:
-  1. Common transformations
-  2. [Low precision transformations](@ref openvino_docs_IE_DG_lpt)
-  3. Plugin specific transformations

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

docs/documentation.md

@@ -72,9 +72,7 @@
 
    openvino_docs_Extensibility_UG_Intro
    openvino_docs_transformations
-   Inference Engine Plugin Developer Guide <openvino_docs_ie_plugin_dg_overview>
-   groupie_dev_api
-   Plugin Transformation Pipeline <openvino_docs_IE_DG_plugin_transformation_pipeline>
+   OpenVINO Plugin Developer Guide <openvino_docs_ie_plugin_dg_overview>
    
 .. toctree::
    :maxdepth: 1

docs/doxyrest-config.lua

@@ -79,7 +79,7 @@ EXTRA_PAGE_LIST = {}
 --! is not set (otherwise, the title of intro file will be used).
 --!
 
-INDEX_TITLE = "Inference Engine C++ API Reference"
+INDEX_TITLE = "OpenVINO Runtime C++ API Reference"
 
 --!
 --! File with project introduction (reStructuredText). When non-nil, this file

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 +11,35 @@
 // 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 Basics
+ * @ingroup ov_cpp_api
+ * OpenVINO Core C++ API to work with ov::Model, dynamic and static shapes, types
+ *
+ * @defgroup ov_ops_cpp_api 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 Operation sets
+ * @ingroup ov_cpp_api
+ * OpenVINO C++ API to work with operation sets
+ *
+ * @defgroup ov_runtime_cpp_api Inference
+ * @ingroup ov_cpp_api
+ * OpenVINO Inference C++ API provides ov::Core, ov::CompiledModel, ov::InferRequest
+ * and ov::Tensor classes
+ */
+
+/**
+ * @brief OpenVINO C++ API
+ * @ingroup ov_cpp_api
+ */
+namespace ov {}  // namespace ov
+
 #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/core/include/openvino/runtime/allocator.hpp

@@ -61,6 +61,7 @@ class Tensor;
 /**
  * @brief Wraps allocator implementation to provide safe way to store allocater loaded from shared library
  *        And constructs default based on `new` `delete` c++ calls allocator if created without parameters
+ * @ingroup ov_runtime_cpp_api
  */
 class OPENVINO_API Allocator {
     AllocatorImpl::Ptr _impl;

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

@@ -30,8 +30,8 @@ class VariableState;
 
 /**
  * @brief Tensor API holding host memory
- *
  * It can throw exceptions safely for the application, where it is properly handled.
+ * @ingroup ov_runtime_cpp_api
  */
 class OPENVINO_API Tensor {
 protected:
@@ -208,6 +208,9 @@ public:
     }
 };
 
+/**
+ * @brief A vector of Tensor's
+ */
 using TensorVector = std::vector<Tensor>;
 
 namespace runtime {

src/inference/include/ie/ie_api.h

@@ -2,16 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-/**
- *  @defgroup ie_cpp_api Inference Engine C++ API
- *  Inference Engine C++ API
- */
-
 /**
  * @brief The macro defines a symbol import/export mechanism essential for Microsoft Windows(R) OS.
- *
  * @file ie_api.h
  */
+
 #pragma once
 
 #if defined(OPENVINO_STATIC_LIBRARY) || defined(USE_STATIC_IE) || (defined(__GNUC__) && (__GNUC__ < 4))

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

@@ -14,6 +14,12 @@
 
 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
  */
@@ -22,12 +28,14 @@ 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 +53,13 @@ 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 +113,7 @@ 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 +154,7 @@ 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 +165,26 @@ 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
@@ -213,6 +229,7 @@ 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"};
 
@@ -220,6 +237,7 @@ static constexpr Property<PWLDesignAlgorithm> pwl_design_algorithm{"GNA_PWL_DESI
  * @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 @@ public:
  * 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 @@ public:
  * 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

@@ -22,6 +22,12 @@
 namespace ov {
 namespace intel_gpu {
 
+/**
+ * @defgroup ov_runtime_ocl_gpu_cpp_api Intel GPU OpenCL interoperability
+ * @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
  */
@@ -29,6 +35,7 @@ namespace ocl {
 
 /**
  * @brief Shortcut for defining a handle parameter
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 using gpu_handle_param = void*;
 
@@ -37,6 +44,7 @@ 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 +89,7 @@ public:
  * 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 +134,7 @@ public:
  * 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 +165,7 @@ public:
  * 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 @@ public:
  * 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:

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

@@ -14,6 +14,12 @@
 
 namespace ov {
 
+/**
+ * @defgroup ov_runtime_ocl_gpu_prop_cpp_api Intel GPU OpenCL specific properties
+ * @ingroup ov_runtime_cpp_api
+ * Set of Intel GPU OpenCL specific properties.
+ */
+
 /**
  * @brief Namespace with Intel GPU specific properties
  */
@@ -22,22 +28,26 @@ namespace intel_gpu {
 /**
  * @brief Read-only property which defines size of memory in bytes available for the device. For iGPU it returns host
  * memory size, for dGPU - dedicated gpu memory size
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 static constexpr Property<uint64_t, PropertyMutability::RO> device_total_mem_size{"GPU_DEVICE_TOTAL_MEM_SIZE"};
 
 /**
  * @brief Read-only property to get microarchitecture identifier in major.minor.revision format
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 static constexpr Property<std::string, PropertyMutability::RO> uarch_version{"GPU_UARCH_VERSION"};
 
 /**
  * @brief Read-only property to get count of execution units for current GPU
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 static constexpr Property<int32_t, PropertyMutability::RO> execution_units_count{"GPU_EXECUTION_UNITS_COUNT"};
 
 /**
  * @brief Read-only property to get statistics of GPU memory allocated by engine for each allocation type
  * It contains information about current memory usage
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 static constexpr Property<std::map<std::string, uint64_t>, PropertyMutability::RO> memory_statistics{
     "GPU_MEMORY_STATISTICS"};
@@ -48,7 +58,9 @@ static constexpr Property<std::map<std::string, uint64_t>, PropertyMutability::R
  * not too many iteration counts (less than 16, as a rule of thumb). Turning this key off will achieve better
  * performance for both graph loading time and inference time with many iteration counts (greater than 16). Note that
  * turning this key on will increase the graph loading time in proportion to the iteration counts.
- * Thus, this key should be turned off if graph loading time is considered to be most important target to optimize.*/
+ * Thus, this key should be turned off if graph loading time is considered to be most important target to optimize.
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
+ */
 static constexpr Property<bool> enable_loop_unrolling{"GPU_ENABLE_LOOP_UNROLLING"};
 
 namespace hint {
@@ -57,6 +69,7 @@ namespace hint {
  * - LOW is used for CL_QUEUE_THROTTLE_LOW_KHR OpenCL throttle hint
  * - MEDIUM (DEFAULT) is used for CL_QUEUE_THROTTLE_MED_KHR OpenCL throttle hint
  * - HIGH is used for CL_QUEUE_THROTTLE_HIGH_KHR OpenCL throttle hint
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 using ThrottleLevel = ov::hint::Priority;
 
@@ -64,6 +77,7 @@ using ThrottleLevel = ov::hint::Priority;
  * @brief This key instructs the GPU plugin to use OpenCL queue throttle hints
  * as defined in https://www.khronos.org/registry/OpenCL/specs/opencl-2.1-extensions.pdf,
  * chapter 9.19. This option should be used with ov::intel_gpu::hint::ThrottleLevel values.
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 static constexpr Property<ThrottleLevel> queue_throttle{"GPU_QUEUE_THROTTLE"};
 
@@ -74,6 +88,7 @@ static constexpr Property<ThrottleLevel> queue_throttle{"GPU_QUEUE_THROTTLE"};
  * - LOW is used for CL_QUEUE_PRIORITY_LOW_KHR OpenCL priority hint
  * - MEDIUM (DEFAULT) is used for CL_QUEUE_PRIORITY_MED_KHR OpenCL priority hint
  * - HIGH is used for CL_QUEUE_PRIORITY_HIGH_KHR OpenCL priority hint
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 static constexpr Property<ov::hint::Priority> queue_priority{"GPU_QUEUE_PRIORITY"};
 
@@ -83,11 +98,13 @@ static constexpr Property<ov::hint::Priority> queue_priority{"GPU_QUEUE_PRIORITY
  * - LOW - instructs the GPU Plugin to use LITTLE cores if they are available
  * - MEDIUM (DEFAULT) - instructs the GPU Plugin to use any available cores (BIG or LITTLE cores)
  * - HIGH - instructs the GPU Plugin to use BIG cores if they are available
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 static constexpr Property<ov::hint::Priority> host_task_priority{"GPU_HOST_TASK_PRIORITY"};
 
 /**
  * @brief This key identifies available device memory size in bytes
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
  */
 static constexpr Property<int64_t> available_device_mem{"AVAILABLE_DEVICE_MEM_SIZE"};
 }  // namespace hint
@@ -96,15 +113,32 @@ static constexpr Property<int64_t> available_device_mem{"AVAILABLE_DEVICE_MEM_SI
  * @brief These keys instruct the GPU plugin to use surface/buffer memory type.
  */
 namespace memory_type {
-static constexpr auto surface = "GPU_SURFACE";  //!< Native video decoder surface
-static constexpr auto buffer = "GPU_BUFFER";    //!< OpenCL buffer
+
+/**
+ * @brief Native video decoder surface
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
+ */
+static constexpr auto surface = "GPU_SURFACE";
+
+/*
+ * @brief OpenCL buffer
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
+ */
+static constexpr auto buffer = "GPU_BUFFER";
+
 }  // namespace memory_type
 
 /**
  * @brief Possible return value for ov::device::capabilities property
  */
 namespace capability {
-constexpr static const auto HW_MATMUL = "GPU_HW_MATMUL";  //!< Device has hardware block for matrix multiplication
+
+/**
+ * @brief Device has hardware block for matrix multiplication
+ * @ingroup ov_runtime_ocl_gpu_prop_cpp_api
+ */
+constexpr static const auto HW_MATMUL = "GPU_HW_MATMUL";
+
 }  // namespace capability
 }  // namespace intel_gpu
 }  // namespace ov

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

@@ -19,6 +19,7 @@ using gpu_handle_param = void*;
 
 /**
  * @brief Enum to define the type of the shared context
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 enum class ContextType {
     OCL = 0,        //!< Pure OpenCL context
@@ -54,40 +55,47 @@ inline std::istream& operator>>(std::istream& is, ContextType& context_type) {
 /**
  * @brief Shared device context type: can be either pure OpenCL (OCL)
  * or shared video decoder (VA_SHARED) context
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<ContextType> context_type{"CONTEXT_TYPE"};
 
 /**
  * @brief This key identifies OpenCL context handle
  * in a shared context or shared memory blob parameter map
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<gpu_handle_param> ocl_context{"OCL_CONTEXT"};
 
 /**
  * @brief This key identifies ID of device in OpenCL context
  * if multiple devices are present in the context
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<int> ocl_context_device_id{"OCL_CONTEXT_DEVICE_ID"};
 
 /**
  * @brief In case of multi-tile system,
  * this key identifies tile within given context
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<int> tile_id{"TILE_ID"};
 
 /**
  * @brief This key identifies OpenCL queue handle in a shared context
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<gpu_handle_param> ocl_queue{"OCL_QUEUE"};
 
 /**
  * @brief This key identifies video acceleration device/display handle
  * in a shared context or shared memory blob parameter map
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<gpu_handle_param> va_device{"VA_DEVICE"};
 
 /**
  * @brief Enum to define the type of the shared memory buffer
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 enum class SharedMemType {
     OCL_BUFFER = 0,         //!< Shared OpenCL buffer blob
@@ -148,18 +156,21 @@ inline std::istream& operator>>(std::istream& is, SharedMemType& share_mem_type)
 /**
  * @brief This key identifies type of internal shared memory
  * in a shared memory blob parameter map.
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<SharedMemType> shared_mem_type{"SHARED_MEM_TYPE"};
 
 /**
  * @brief This key identifies OpenCL memory handle
  * in a shared memory blob parameter map
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<gpu_handle_param> mem_handle{"MEM_HANDLE"};
 
 /**
  * @brief This key identifies video decoder surface handle
  * in a shared memory blob parameter map
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 #ifdef _WIN32
 static constexpr Property<gpu_handle_param> dev_object_handle{"DEV_OBJECT_HANDLE"};
@@ -170,6 +181,7 @@ static constexpr Property<uint32_t> dev_object_handle{"DEV_OBJECT_HANDLE"};
 /**
  * @brief This key identifies video decoder surface plane
  * in a shared memory blob parameter map
+ * @ingroup ov_runtime_ocl_gpu_cpp_api
  */
 static constexpr Property<uint32_t> va_plane{"VA_PLANE"};
 

src/inference/include/openvino/runtime/intel_myriad/hddl_properties.hpp

@@ -18,68 +18,81 @@ namespace hddl {
 
 /**
  * @brief Property to get a int of the device number
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<int, PropertyMutability::RO> device_num{"HDDL_DEVICE_NUM"};
 
 /**
  * @brief Property to get a std::vector<std::string> of device names
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<std::string>, PropertyMutability::RO> device_name{"HDDL_DEVICE_NAME"};
 
 /**
  * @brief  Property to get a std::vector<float> of device thermal
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<float>, PropertyMutability::RO> device_thermal{"HDDL_DEVICE_THERMAL"};
 
 /**
  * @brief  Property to get a std::vector<uint32> of device ids
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<unsigned int>, PropertyMutability::RO> device_id{"HDDL_DEVICE_ID"};
 
 /**
  * @brief  Property to get a std::vector<int> of device subclasses
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<int>, PropertyMutability::RO> device_subclass{"HDDL_DEVICE_SUBCLASS"};
 
 /**
  * @brief  Property to get a std::vector<uint32> of device total memory
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<unsigned int>, PropertyMutability::RO> device_memory_total{
     "HDDL_DEVICE_MEMORY_TOTAL"};
 
 /**
  * @brief  Property to get a std::vector<uint32> of device used memory
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<unsigned int>, PropertyMutability::RO> device_memory_used{
     "HDDL_DEVICE_MEMORY_USED"};
 
 /**
  * @brief  Property to get a std::vector<float> of device utilization
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<float>, PropertyMutability::RO> device_utilization{"HDDL_DEVICE_UTILIZATION"};
 
 /**
  * @brief  Property to get a std::vector<std::string> of stream ids
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<std::string>, PropertyMutability::RO> stream_id{"HDDL_STREAM_ID"};
 
 /**
  * @brief  Property to get a std::vector<std::string> of device tags
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<std::string>, PropertyMutability::RO> device_tag{"HDDL_DEVICE_TAG"};
 
 /**
  * @brief  Property to get a std::vector<int> of group ids
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::vector<int>, PropertyMutability::RO> group_id{"HDDL_GROUP_ID"};
 
 /**
  * @brief  Property to get a int number of device be using for group
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<int, PropertyMutability::RO> device_group_using_num{"HDDL_DEVICE_GROUP_USING_NUM"};
 
 /**
  * @brief  Property to get a int number of total device
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<int, PropertyMutability::RO> device_total_num{"HDDL_DEVICE_TOTAL_NUM"};
 
@@ -100,6 +113,7 @@ static constexpr Property<int, PropertyMutability::RO> device_total_num{"HDDL_DE
  *     }
  * }
  * It means that an executable network marked with tagA will be executed on 3 devices
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::string, PropertyMutability::RW> graph_tag{"HDDL_GRAPH_TAG"};
 
@@ -116,6 +130,7 @@ static constexpr Property<std::string, PropertyMutability::RW> graph_tag{"HDDL_G
  *     "stream_device_number":5
  * }
  * It means that 5 device will be used for stream-affinity
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::string, PropertyMutability::RW> set_stream_id{"HDDL_SET_STREAM_ID"};
 
@@ -132,6 +147,7 @@ static constexpr Property<std::string, PropertyMutability::RW> set_stream_id{"HD
  *     "bypass_device_number": 5
  * }
  * It means that 5 device will be used for Bypass scheduler.
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::string, PropertyMutability::RW> set_device_tag{"HDDL_SET_DEVICE_TAG"};
 
@@ -145,6 +161,7 @@ static constexpr Property<std::string, PropertyMutability::RW> set_device_tag{"H
  * If "NO", the network allocated is not bind to the device (with the specified "DEVICE_TAG"). If the same network
  * is allocated on multiple other devices (also set BIND_DEVICE to "False"), then inference through any handle of these
  * networks may be executed on any of these devices those have the network loaded.
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<bool, PropertyMutability::RW> bind_device{"HDDL_BIND_DEVICE"};
 
@@ -155,6 +172,7 @@ static constexpr Property<bool, PropertyMutability::RW> bind_device{"HDDL_BIND_D
  * When there are multiple devices running a certain network (a same network running on multiple devices in Bypass
  * Scheduler), the device with a larger number has a higher priority, and more inference tasks will be fed to it with
  * priority.
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::string, PropertyMutability::RW> runtime_priority{"HDDL_RUNTIME_PRIORITY"};
 
@@ -164,6 +182,7 @@ static constexpr Property<std::string, PropertyMutability::RW> runtime_priority{
  * SGAD is short for "Single Graph All Device". With this scheduler, once application allocates 1 network, all devices
  * (managed by SGAD scheduler) will be loaded with this graph. The number of network that can be loaded to one device
  * can exceed one. Once application deallocates 1 network from device, all devices will unload the network from them.
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<bool, PropertyMutability::RW> use_sgad{"HDDL_USE_SGAD"};
 
@@ -173,6 +192,7 @@ static constexpr Property<bool, PropertyMutability::RW> use_sgad{"HDDL_USE_SGAD"
  * This config gives a "group id" for a certain device when this device has been reserved for certain client, client
  * can use this device grouped by calling this group id while other client can't use this device
  * Each device has their own group id. Device in one group shares same group id.
+ * @ingroup ov_runtime_hddl_prop_cpp_api
  */
 static constexpr Property<std::string, PropertyMutability::RW> group_device{"HDDL_GROUP_DEVICE"};
 

src/inference/include/openvino/runtime/intel_myriad/myriad_properties.hpp

@@ -9,6 +9,20 @@
 
 namespace ov {
 
+/**
+ * @defgroup ov_runtime_myriad_hddl_prop_cpp_api Intel MYRIAD & HDDL specific properties
+ * @ingroup ov_runtime_cpp_api
+ * Set of Intel MYRIAD & HDDL specific properties.
+ *
+ * @defgroup ov_runtime_myriad_prop_cpp_api Intel MYRIAD specific properties
+ * @ingroup ov_runtime_cpp_api
+ * Set of Intel MYRIAD specific properties.
+ *
+ * @defgroup ov_runtime_hddl_prop_cpp_api Intel HDDL specific properties
+ * @ingroup ov_runtime_cpp_api
+ * Set of Intel HDDL specific properties.
+ */
+
 /**
  * @brief Namespace with Intel MYRIAD specific properties
  */
@@ -16,11 +30,13 @@ namespace intel_myriad {
 
 /**
  * @brief Turn on HW stages usage (applicable for MyriadX devices only).
+ * @ingroup ov_runtime_myriad_hddl_prop_cpp_api
  */
 static constexpr Property<bool, PropertyMutability::RW> enable_hw_acceleration{"MYRIAD_ENABLE_HW_ACCELERATION"};
 
 /**
  * @brief The flag for adding to the profiling information the time of obtaining a tensor.
+ * @ingroup ov_runtime_myriad_hddl_prop_cpp_api
  */
 static constexpr Property<bool, PropertyMutability::RW> enable_receiving_tensor_time{
     "MYRIAD_ENABLE_RECEIVING_TENSOR_TIME"};
@@ -28,11 +44,13 @@ static constexpr Property<bool, PropertyMutability::RW> enable_receiving_tensor_
 /**
  * @brief This option allows to pass custom layers binding xml.
  * If layer is present in such an xml, it would be used during inference even if the layer is natively supported
+ * @ingroup ov_runtime_myriad_hddl_prop_cpp_api
  */
 static constexpr Property<std::string, PropertyMutability::RW> custom_layers{"MYRIAD_CUSTOM_LAYERS"};
 
 /**
  * @brief Enum to define possible device protocols
+ * @ingroup ov_runtime_myriad_hddl_prop_cpp_api
  */
 enum class Protocol {
     PCIE = 0,  //!< Will use a device with PCIE protocol
@@ -68,16 +86,19 @@ inline std::istream& operator>>(std::istream& is, Protocol& protocol) {
 
 /**
  * @brief This option allows to specify protocol.
+ * @ingroup ov_runtime_myriad_prop_cpp_api
  */
 static constexpr Property<Protocol, PropertyMutability::RW> protocol{"MYRIAD_PROTOCOL"};
 
 /**
  * @brief The flag to reset stalled devices.
+ * @ingroup ov_runtime_myriad_prop_cpp_api
  */
 static constexpr Property<bool, PropertyMutability::RW> enable_force_reset{"MYRIAD_ENABLE_FORCE_RESET"};
 
 /**
  * @brief Enum to define possible device mymory types
+ * @ingroup ov_runtime_myriad_prop_cpp_api
  */
 enum class DDRType {
     MYRIAD_DDR_AUTO = 0,         //!<  Automatic setting of DDR memory type
@@ -127,8 +148,8 @@ inline std::istream& operator>>(std::istream& is, DDRType& ddrType) {
 
 /**
  * @brief This option allows to specify device memory type.
+ * @ingroup ov_runtime_myriad_prop_cpp_api
  */
-
 static constexpr Property<DDRType, PropertyMutability::RW> ddr_type{"MYRIAD_DDR_TYPE"};
 }  // namespace intel_myriad
 }  // namespace ov

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

@@ -18,6 +18,7 @@ namespace ov {
 /**
  * @struct ProfilingInfo
  * @brief Represents basic inference profiling information per operation.
+ * @ingroup ov_runtime_cpp_api
  *
  * If the operation is executed using tiling, the sum time per each tile is indicated as the total execution time.
  * Due to parallel execution, the total execution time for all nodes might be greater than the total inference time.
@@ -41,6 +42,7 @@ struct ProfilingInfo {
      * @brief The absolute time, in microseconds, that the node ran (in total).
      */
     std::chrono::microseconds real_time;
+
     /**
      * @brief The net host CPU time that the node ran.
      */

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

@@ -23,6 +23,11 @@
 
 namespace ov {
 
+/**
+ * @defgroup ov_runtime_cpp_prop_api Device properties
+ * @ingroup ov_runtime_cpp_api
+ */
+
 /**
  * @brief Enum to define property value mutability
  */
@@ -197,25 +202,27 @@ struct Property<T, PropertyMutability::RO> : public util::BaseProperty<T, Proper
 
 /**
  * @brief Read-only property to get a std::vector<PropertyName> of supported read-only properties.
- *
  * This can be used as a compiled model property as well.
- *
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::vector<PropertyName>, PropertyMutability::RO> supported_properties{
     "SUPPORTED_PROPERTIES"};
 
 /**
  * @brief Read-only property to get a std::vector<std::string> of available device IDs
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::vector<std::string>, PropertyMutability::RO> available_devices{"AVAILABLE_DEVICES"};
 
 /**
  * @brief Read-only property to get a name of name of a model
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::string, PropertyMutability::RO> model_name{"NETWORK_NAME"};
 
 /**
  * @brief Read-only property to get an unsigned integer value of optimal number of compiled model infer requests.
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<uint32_t, PropertyMutability::RO> optimal_number_of_infer_requests{
     "OPTIMAL_NUMBER_OF_INFER_REQUESTS"};
@@ -227,17 +234,19 @@ namespace hint {
 
 /**
  * @brief Hint for device to use specified precision for inference
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<element::Type, PropertyMutability::RW> inference_precision{"INFERENCE_PRECISION_HINT"};
 
 /**
  * @brief Enum to define possible priorities hints
+ * @ingroup ov_runtime_cpp_prop_api
  */
 enum class Priority {
-    LOW = 0,
-    MEDIUM = 1,
-    HIGH = 2,
-    DEFAULT = MEDIUM,
+    LOW = 0,           //!<  Low priority
+    MEDIUM = 1,        //!<  Medium priority
+    HIGH = 2,          //!<  High priority
+    DEFAULT = MEDIUM,  //!<  Default priority is MEDIUM
 };
 
 /** @cond INTERNAL */
@@ -273,17 +282,19 @@ inline std::istream& operator>>(std::istream& is, Priority& priority) {
 /**
  * @brief High-level OpenVINO model priority hint
  * Defines what model should be provided with more performant bounded resource first
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<Priority> model_priority{"MODEL_PRIORITY"};
 
 /**
  * @brief Enum to define possible performance mode hints
+ * @ingroup ov_runtime_cpp_prop_api
  */
 enum class PerformanceMode {
-    UNDEFINED = -1,
-    LATENCY = 1,
-    THROUGHPUT = 2,
-    CUMULATIVE_THROUGHPUT = 3,
+    UNDEFINED = -1,             //!<  Undefined value, performance setting may vary from device to device
+    LATENCY = 1,                //!<  Optimize for latency
+    THROUGHPUT = 2,             //!<  Optimize for throughput
+    CUMULATIVE_THROUGHPUT = 3,  //!< Optimize for cumulative throughput
 };
 
 /** @cond INTERNAL */
@@ -324,6 +335,7 @@ inline std::istream& operator>>(std::istream& is, PerformanceMode& performance_m
  * @brief High-level OpenVINO Performance Hints
  * unlike low-level properties that are individual (per-device), the hints are something that every device accepts
  * and turns into device-specific settings
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<PerformanceMode> performance_mode{"PERFORMANCE_HINT"};
 
@@ -331,25 +343,27 @@ static constexpr Property<PerformanceMode> performance_mode{"PERFORMANCE_HINT"};
  * @brief (Optional) property that backs the (above) Performance Hints
  * by giving additional information on how many inference requests the application will be keeping in flight
  * usually this value comes from the actual use-case (e.g. number of video-cameras, or other sources of inputs)
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<uint32_t> num_requests{"PERFORMANCE_HINT_NUM_REQUESTS"};
 
 /**
  * @brief This key identifies shared pointer to the ov::Model, required for some properties (ov::max_batch_size and
  * ov::optimal_batch_size)
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::shared_ptr<ov::Model>> model{"MODEL_PTR"};
 
 /**
  * @brief Special key for auto batching feature configuration. Enabled by default
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<bool, PropertyMutability::RW> allow_auto_batching{"ALLOW_AUTO_BATCHING"};
 }  // namespace hint
 
 /**
  * @brief The name for setting performance counters option.
- *
- * It is passed to Core::set_property()
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<bool> enable_profiling{"PERF_COUNT"};
 
@@ -360,6 +374,7 @@ namespace log {
 
 /**
  * @brief Enum to define possible log levels
+ * @ingroup ov_runtime_cpp_prop_api
  */
 enum class Level {
     NO = -1,      //!< disable any logging
@@ -414,12 +429,14 @@ inline std::istream& operator>>(std::istream& is, Level& level) {
 
 /**
  * @brief the property for setting desirable log level.
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<Level> level{"LOG_LEVEL"};
 }  // namespace log
 
 /**
  * @brief This property defines the directory which will be used to store any data cached by plugins.
+ * @ingroup ov_runtime_cpp_prop_api
  *
  * The underlying cache structure is not defined and might differ between OpenVINO releases
  * Cached data might be platform / device specific and might be invalid after OpenVINO version change
@@ -440,6 +457,7 @@ static constexpr Property<std::string> cache_dir{"CACHE_DIR"};
 
 /**
  * @brief Read-only property to provide information about a range for streams on platforms where streams are supported.
+ * @ingroup ov_runtime_cpp_prop_api
  *
  * Property returns a value of std::tuple<unsigned int, unsigned int> type, where:
  *  - First value is bottom bound.
@@ -450,6 +468,7 @@ static constexpr Property<std::tuple<unsigned int, unsigned int>, PropertyMutabi
 
 /**
  * @brief Read-only property to query information optimal batch size for the given device and the network
+ * @ingroup ov_runtime_cpp_prop_api
  *
  * Property returns a value of unsigned int type,
  * Returns optimal batch size for a given network on the given device. The returned value is aligned to power of 2.
@@ -464,18 +483,21 @@ static constexpr Property<unsigned int, PropertyMutability::RO> optimal_batch_si
 /**
  * @brief Read-only property to get maximum batch size which does not cause performance degradation due to memory swap
  * impact.
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<uint32_t, PropertyMutability::RO> max_batch_size{"MAX_BATCH_SIZE"};
 
 /**
  * @brief Read-write property to set the timeout used to collect the inputs for the auto-batching
  * impact.
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<uint32_t, PropertyMutability::RW> auto_batch_timeout{"AUTO_BATCH_TIMEOUT"};
 
 /**
  * @brief Read-only property to provide a hint for a range for number of async infer requests. If device supports
  * streams, the metric provides range for number of IRs per stream.
+ * @ingroup ov_runtime_cpp_prop_api
  *
  * Property returns a value of std::tuple<unsigned int, unsigned int, unsigned int> type, where:
  *  - First value is bottom bound.
@@ -493,11 +515,13 @@ namespace device {
 /**
  * @brief the property for setting of required device to execute on
  * values: device id starts from "0" - first device, "1" - second device, etc
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::string> id{"DEVICE_ID"};
 
 /**
  * @brief Type for device Priorities config option, with comma-separated devices listed in the desired priority
+ * @ingroup ov_runtime_cpp_prop_api
  */
 struct Priorities : public Property<std::string> {
 private:
@@ -528,11 +552,13 @@ public:
 
 /**
  * @brief Device Priorities config option, with comma-separated devices listed in the desired priority
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Priorities priorities{"MULTI_DEVICE_PRIORITIES"};
 
 /**
  * @brief Type for property to pass set of properties to specified device
+ * @ingroup ov_runtime_cpp_prop_api
  */
 struct Properties {
     /**
@@ -562,6 +588,7 @@ struct Properties {
 
 /**
  * @brief Property to pass set of property values to specified device
+ * @ingroup ov_runtime_cpp_prop_api
  * Usage Example:
  * @code
  * core.compile_model("HETERO"
@@ -574,16 +601,19 @@ static constexpr Properties properties;
 
 /**
  * @brief Read-only property to get a std::string value representing a full device name.
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::string, PropertyMutability::RO> full_name{"FULL_DEVICE_NAME"};
 
 /**
  * @brief Read-only property which defines the device architecture.
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::string, PropertyMutability::RO> architecture{"DEVICE_ARCHITECTURE"};
 
 /**
  * @brief Enum to define possible device types
+ * @ingroup ov_runtime_cpp_prop_api
  */
 enum class Type {
     INTEGRATED = 0,  //!<  Device is integrated into host system
@@ -618,22 +648,26 @@ inline std::istream& operator>>(std::istream& is, Type& device_type) {
 
 /**
  * @brief Read-only property to get a type of device. See Type enum definition for possible return values
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<Type, PropertyMutability::RO> type{"DEVICE_TYPE"};
 
 /**
  * @brief Read-only property which defines Giga OPS per second count (GFLOPS or GIOPS) for a set of precisions supported
  * by specified device
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::map<element::Type, float>, PropertyMutability::RO> gops{"DEVICE_GOPS"};
 
 /**
- * @brief  Read-only property to get a float of device thermal
+ * @brief Read-only property to get a float of device thermal
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<float, PropertyMutability::RO> thermal{"DEVICE_THERMAL"};
 
 /**
  * @brief Read-only property to get a std::vector<std::string> of capabilities options per device.
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<std::vector<std::string>, PropertyMutability::RO> capabilities{"OPTIMIZATION_CAPABILITIES"};
 
@@ -641,6 +675,10 @@ static constexpr Property<std::vector<std::string>, PropertyMutability::RO> capa
  * @brief Namespace with possible values for ov::device::capabilities property
  */
 namespace capability {
+/**
+ * @addtogroup ov_runtime_cpp_prop_api
+ * @{
+ */
 constexpr static const auto FP32 = "FP32";                    //!< Device supports fp32 inference
 constexpr static const auto BF16 = "BF16";                    //!< Device supports bf16 inference
 constexpr static const auto FP16 = "FP16";                    //!< Device supports fp16 inference
@@ -649,6 +687,7 @@ constexpr static const auto INT16 = "INT16";                  //!< Device suppor
 constexpr static const auto BIN = "BIN";                      //!< Device supports binary inference
 constexpr static const auto WINOGRAD = "WINOGRAD";            //!< Device supports winograd optimization
 constexpr static const auto EXPORT_IMPORT = "EXPORT_IMPORT";  //!< Device supports compiled model export and import
+/** @}*/
 }  // namespace capability
 
 }  // namespace device
@@ -659,6 +698,7 @@ constexpr static const auto EXPORT_IMPORT = "EXPORT_IMPORT";  //!< Device suppor
 namespace streams {
 /**
  * @brief Class to represent number of streams in streams executor
+ * @ingroup ov_runtime_cpp_prop_api
  */
 struct Num {
     using Base = std::tuple<int32_t>;  //!< NumStreams is representable as int32_t
@@ -676,12 +716,21 @@ struct Num {
 
 /**
  * @brief The number of executor logical partitions
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<Num, PropertyMutability::RW> num{"NUM_STREAMS"};
 
-static constexpr Num AUTO{-1};  //!< Creates bare minimum of streams to improve the performance
-static constexpr Num NUMA{
-    -2};  //!< Creates as many streams as needed to accommodate NUMA and avoid associated penalties
+/**
+ * @brief Creates bare minimum of streams to improve the performance
+ * @ingroup ov_runtime_cpp_prop_api
+ */
+static constexpr Num AUTO{-1};
+
+/**
+ * @brief Creates as many streams as needed to accommodate NUMA and avoid associated penalties
+ * @ingroup ov_runtime_cpp_prop_api
+ */
+static constexpr Num NUMA{-2};
 
 /** @cond INTERNAL */
 inline std::ostream& operator<<(std::ostream& os, const Num& num_val) {
@@ -716,21 +765,25 @@ inline std::istream& operator>>(std::istream& is, Num& num_val) {
 
 /**
  * @brief The number of executor logical partitions
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<streams::Num, PropertyMutability::RW> num_streams{"NUM_STREAMS"};
 
 /**
  * @brief Maximum number of threads that can be used for inference tasks
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<int32_t, PropertyMutability::RW> inference_num_threads{"INFERENCE_NUM_THREADS"};
 
 /**
  * @brief Maximum number of threads that can be used for compilation tasks
+ * @ingroup ov_runtime_cpp_prop_api
  */
 static constexpr Property<int32_t, PropertyMutability::RW> compilation_num_threads{"COMPILATION_NUM_THREADS"};
 
 /**
  * @brief Enum to define possible affinity patterns
+ * @ingroup ov_runtime_cpp_prop_api
  */
 enum class Affinity {
     NONE = -1,  //!<  Disable threads affinity pinning
@@ -777,6 +830,7 @@ inline std::istream& operator>>(std::istream& is, Affinity& affinity) {
 
 /**
  * @brief The name for setting CPU affinity per thread option.
+ * @ingroup ov_runtime_cpp_prop_api
  * @note The setting is ignored, if the OpenVINO compiled with OpenMP and any affinity-related OpenMP's
  * environment variable is set (as affinity is configured explicitly)
  */

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

@@ -29,6 +29,7 @@ class CompiledModel;
 
 /**
  * @brief This class represents an abstraction
+ * @ingroup ov_runtime_cpp_api
  * for remote (non-CPU) accelerator device-specific inference context.
  * Such context represents a scope on the device within which compiled
  * models and remote memory tensors can exist, function, and exchange data.

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

@@ -17,7 +17,8 @@ namespace ov {
 class RemoteContext;
 
 /**
- * @brief Remote memory access and interpretation API.
+ * @brief Remote memory access and interoperability API.
+ * @ingroup ov_runtime_cpp_api
  */
 class OPENVINO_RUNTIME_API RemoteTensor : public Tensor {
     using Tensor::Tensor;

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

@@ -25,6 +25,7 @@ class InferRequest;
 
 /**
  * @brief VariableState class
+ * @ingroup ov_runtime_cpp_api
  */
 class OPENVINO_RUNTIME_API VariableState {
     std::shared_ptr<InferenceEngine::IVariableStateInternal> _impl;