Merge branch 'master' into DOCS-adjustments-preparing-2025.0-pass-2

.github/dockerfiles/docker_tag

@@ -1 +1 @@
-pr-28380
+pr-28040

.github/dockerfiles/ov_build/ubuntu_22_04_x64_cc/Dockerfile

@@ -36,7 +36,11 @@ RUN apt-get update && \
         # For Java API
         default-jdk \
         # Compiler \
-        clang \
+        clang-15 \
+        # Static analyzer
+        clang-tidy-15 \
+        # clang-tidy uses clang-format as a dependency
+        clang-format-15 \
         && \
     rm -rf /var/lib/apt/lists/*
 
@@ -47,8 +51,8 @@ RUN chmod +x /install_build_dependencies.sh && \
     rm -rf /var/lib/apt/lists/*
 
 # Set clang as a default compiler
-RUN update-alternatives --install /usr/bin/cc cc /usr/bin/clang 100 && \
-    update-alternatives --install /usr/bin/c++ c++ /usr/bin/clang++ 100
+RUN update-alternatives --install /usr/bin/cc cc /usr/bin/clang-15 100 && \
+    update-alternatives --install /usr/bin/c++ c++ /usr/bin/clang++-15 100
 
 # Install sscache
 ARG SCCACHE_VERSION="v0.7.5"

.github/workflows/build_doc.yml

@@ -25,7 +25,7 @@ jobs:
           lfs: 'true'
 
       - name: Install apt-get dependencies
-        uses: awalsh128/cache-apt-pkgs-action@a6c3917cc929dd0345bfb2d3feaf9101823370ad # v1.4.2
+        uses: awalsh128/cache-apt-pkgs-action@5902b33ae29014e6ca012c5d8025d4346556bd40 # v1.4.3
         with:
           packages: graphviz texlive liblua5.2-0 libclang1-9 libclang-cpp9
           version: 3.0

.github/workflows/linux_conditional_compilation.yml

@@ -151,14 +151,17 @@ jobs:
       # Build
       #
 
-      - name: CMake configure - CC COLLECT
+      - name: CMake configure - CC COLLECT with clang-tidy
+         # clang-tidy static analysis check is enabled as part of collection
+         # to avoid an additional separate build execution
         run: |
           cmake \
             -G "${{ env.CMAKE_GENERATOR }}" \
             -DCMAKE_CXX_STANDARD=20 \
             -DBUILD_SHARED_LIBS=OFF \
             -DENABLE_TESTS=ON \
             -DENABLE_CPPLINT=OFF \
+            -DENABLE_CLANG_TIDY=ON \
             -DENABLE_NCC_STYLE=OFF \
             -DCMAKE_COMPILE_WARNING_AS_ERROR=ON \
             -DENABLE_PROFILING_ITT=ON \

cmake/developer_package/OpenVINODeveloperScriptsConfig.cmake

@@ -305,6 +305,7 @@ include(python_requirements)
 
 include(cpplint/cpplint)
 include(clang_format/clang_format)
+include(clang_tidy/clang_tidy)
 include(ncc_naming_style/ncc_naming_style)
 
 # Restore state

cmake/developer_package/clang_tidy/clang_tidy.cmake

@@ -0,0 +1,25 @@
+# Copyright (C) 2018-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+#
+
+if(ENABLE_CLANG_TIDY)
+    set(CLANG_TIDY_REQUIRED_VERSION 15 CACHE STRING "clang-tidy version to use")
+    set(CLANG_TIDY_FILENAME clang-tidy-${CLANG_TIDY_REQUIRED_VERSION} clang-tidy)
+    find_host_program(CLANG_TIDY NAMES ${CLANG_TIDY_FILENAME} PATHS ENV PATH)
+    if(CLANG_TIDY)
+        execute_process(COMMAND ${CLANG_TIDY} ${CMAKE_CURRENT_SOURCE_DIR} ARGS --version OUTPUT_VARIABLE CLANG_VERSION)
+        if(NOT CLANG_VERSION)
+            message(WARNING "Supported clang-tidy version is ${CLANG_TIDY_REQUIRED_VERSION}!")
+            set(ENABLE_CLANG_TIDY OFF)
+        else()
+            string(REGEX REPLACE "[^0-9]+([0-9]+)\\..*" "\\1" CLANG_TIDY_MAJOR_VERSION ${CLANG_VERSION})
+            if(NOT CLANG_TIDY_MAJOR_VERSION EQUAL CLANG_TIDY_REQUIRED_VERSION)
+                message(WARNING "Supported clang-tidy version is ${CLANG_TIDY_REQUIRED_VERSION}! Provided version ${CLANG_TIDY_MAJOR_VERSION}")
+                set(ENABLE_CLANG_TIDY OFF)
+            endif()
+        endif()
+    else()
+        message(WARNING "Supported clang-tidy-${CLANG_TIDY_REQUIRED_VERSION} is not found!")
+        set(ENABLE_CLANG_TIDY OFF)
+    endif()
+endif()

cmake/developer_package/features.cmake

@@ -78,6 +78,8 @@ ov_dependent_option (ENABLE_CPPLINT_REPORT "Build cpplint report instead of fail
 
 ov_option (ENABLE_CLANG_FORMAT "Enable clang-format checks during the build" ${STYLE_CHECKS_DEFAULT})
 
+ov_option (ENABLE_CLANG_TIDY "Enable clang-tidy checks during the build" ${STYLE_CHECKS_DEFAULT})
+
 ov_option (ENABLE_NCC_STYLE "Enable ncc style check" ${STYLE_CHECKS_DEFAULT})
 
 ov_option (ENABLE_UNSAFE_LOCATIONS "skip check for MD5 for dependency" OFF)

cmake/developer_package/plugins/plugins.cmake

@@ -34,10 +34,11 @@ endif()
 #               [SKIP_INSTALL]
 #               [SKIP_REGISTRATION] Skip creation of <device>.xml
 #               [ADD_CLANG_FORMAT]
+#               [ADD_CLANG_TIDY]
 #               )
 #
 function(ov_add_plugin)
-    set(options SKIP_INSTALL PSEUDO_DEVICE ADD_CLANG_FORMAT AS_EXTENSION SKIP_REGISTRATION)
+    set(options SKIP_INSTALL PSEUDO_DEVICE ADD_CLANG_FORMAT ADD_CLANG_TIDY AS_EXTENSION SKIP_REGISTRATION)
     set(oneValueArgs NAME DEVICE_NAME VERSION_DEFINES_FOR PSEUDO_PLUGIN_FOR)
     set(multiValueArgs DEFAULT_CONFIG SOURCES OBJECT_LIBRARIES CPPLINT_FILTERS)
     cmake_parse_arguments(OV_PLUGIN "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
@@ -105,6 +106,12 @@ function(ov_add_plugin)
             string(CONCAT custom_filter "${custom_filter}" "," "${filter}")
         endforeach()
 
+        if (OV_PLUGIN_ADD_CLANG_TIDY)
+            if (ENABLE_CLANG_TIDY)
+                set_target_properties(${OV_PLUGIN_NAME} PROPERTIES CXX_CLANG_TIDY clang-tidy-${CLANG_TIDY_REQUIRED_VERSION})
+            endif()
+        endif()
+
         if (OV_PLUGIN_ADD_CLANG_FORMAT)
             ov_add_clang_format_target(${OV_PLUGIN_NAME}_clang FOR_SOURCES ${OV_PLUGIN_SOURCES})
         else()

cmake/packaging/debian.cmake

@@ -100,6 +100,7 @@ macro(ov_cpack_settings)
         2024.4.0
         2024.5.0
         2024.6.0
+        2025.0.0
         )
 
     ov_check_conflicts_versions(conflicting_versions)

cmake/packaging/rpm.cmake

@@ -88,6 +88,7 @@ macro(ov_cpack_settings)
         2024.4.0
         2024.5.0
         2024.6.0
+        2025.0.0
         )
 
     ov_check_conflicts_versions(conflicting_versions)

docs/articles_en/openvino-workflow/running-inference/inference-devices-and-modes/cpu-device.rst

@@ -355,6 +355,7 @@ All parameters must be set before calling ``ov::Core::compile_model()`` in order
 - ``ov::hint::num_request``
 - ``ov::hint::scheduling_core_type``
 - ``ov::hint::enable_hyper_threading``
+- ``ov::hint::enable_cpu_reservation``
 - ``ov::hint::enable_cpu_pinning``
 - ``ov::num_streams``
 - ``ov::inference_num_threads``

src/bindings/python/constraints.txt

@@ -10,7 +10,7 @@ pytest-timeout==2.3.1
 # Python bindings
 build<1.3
 pygments>=2.8.1
-setuptools>=70.1,<75.8
+setuptools>=70.1,<75.9
 sympy>=1.10
 wheel>=0.38.1
 patchelf<=0.17.2.1

src/bindings/python/src/openvino/_ov_api.py

@@ -63,13 +63,13 @@ def clone(self) -> "Model":
         return Model(self.__model.clone())
 
     def __copy__(self) -> "Model":
-        raise TypeError("Cannot copy 'openvino.runtime.Model'. Please, use deepcopy instead.")
+        raise TypeError("Cannot copy 'openvino.Model'. Please, use deepcopy instead.")
 
     def __deepcopy__(self, memo: Dict) -> "Model":
         """Returns a deepcopy of Model.
 
         :return: A copy of Model.
-        :rtype: openvino.runtime.Model
+        :rtype: openvino.Model
         """
         return Model(self.__model.clone())
 
@@ -108,14 +108,14 @@ def infer(
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -190,14 +190,14 @@ def start_async(
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -241,7 +241,7 @@ def get_compiled_model(self) -> "CompiledModel":
         """Gets the compiled model this InferRequest is using.
 
         :return: a CompiledModel object
-        :rtype: openvino.runtime.ie_api.CompiledModel
+        :rtype: openvino.CompiledModel
         """
         return CompiledModel(super().get_compiled_model())
 
@@ -250,7 +250,7 @@ def results(self) -> OVDict:
         """Gets all outputs tensors of this InferRequest.
 
         :return: Dictionary of results from output tensors with ports as keys.
-        :rtype: Dict[openvino.runtime.ConstOutput, numpy.array]
+        :rtype: Dict[openvino.ConstOutput, numpy.array]
         """
         return OVDict(super().results)
 
@@ -277,15 +277,15 @@ def create_infer_request(self) -> InferRequest:
         The created request has allocated input and output tensors.
 
         :return: New InferRequest object.
-        :rtype: openvino.runtime.InferRequest
+        :rtype: openvino.InferRequest
         """
         return InferRequest(super().create_infer_request())
 
     def query_state(self) -> None:
         """Gets state control interface for the underlaying infer request.
 
         :return: List of VariableState objects.
-        :rtype: List[openvino.runtime.VariableState]
+        :rtype: List[openvino.VariableState]
         """
         if self._infer_request is None:
             self._infer_request = self.create_infer_request()
@@ -316,14 +316,14 @@ def infer_new_request(self, inputs: Any = None) -> OVDict:
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -361,14 +361,14 @@ def __call__(
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -448,7 +448,7 @@ def __iter__(self) -> Iterable[InferRequest]:
         will put the parent AsyncInferQueue object in an invalid state.
 
         :return: a generator that yields InferRequests.
-        :rtype: Iterable[openvino.runtime.InferRequest]
+        :rtype: Iterable[openvino.InferRequest]
         """
         return (InferRequest(x) for x in super().__iter__())
 
@@ -462,7 +462,7 @@ def __getitem__(self, i: int) -> InferRequest:
         :param i:  InferRequest id.
         :type i: int
         :return: InferRequests from the pool with given id.
-        :rtype: openvino.runtime.InferRequest
+        :rtype: openvino.InferRequest
         """
         return InferRequest(super().__getitem__(i))
 
@@ -478,14 +478,14 @@ def start_async(
 
         (1) `int`
         (2) `str`
-        (3) `openvino.runtime.ConstOutput`
+        (3) `openvino.ConstOutput`
 
         The allowed types of values in the `inputs` are:
 
         (1) `numpy.ndarray` and all the types that are castable to it, e.g. `torch.Tensor`
-        (2) `openvino.runtime.Tensor`
+        (2) `openvino.Tensor`
 
-        Can be called with only one `openvino.runtime.Tensor` or `numpy.ndarray`,
+        Can be called with only one `openvino.Tensor` or `numpy.ndarray`,
         it will work only with one-input models. When model has more inputs,
         function throws error.
 
@@ -574,7 +574,7 @@ def compile_model(
 
         :param model: Model acquired from read_model function or a path to a model in IR / ONNX / PDPD /
                       TF and TFLite format.
-        :type model: Union[openvino.runtime.Model, str, pathlib.Path]
+        :type model: Union[openvino.Model, str, pathlib.Path]
         :param device_name: Optional. Name of the device to load the model to. If not specified,
                             the default OpenVINO device will be selected by AUTO plugin.
         :type device_name: str
@@ -584,7 +584,7 @@ def compile_model(
         :param weights: Optional. Weights of model in memory to be loaded to the model.
         :type weights: bytes, optional, keyword-only
         :return: A compiled model.
-        :rtype: openvino.runtime.CompiledModel
+        :rtype: openvino.CompiledModel
         """
         if isinstance(model, Model):
             model = model._Model__model
@@ -635,7 +635,7 @@ def import_model(
                        (property name, property value) relevant only for this load operation.
         :type config: dict, optional
         :return: A compiled model.
-        :rtype: openvino.runtime.CompiledModel
+        :rtype: openvino.CompiledModel
 
         :Example:
 
@@ -680,15 +680,15 @@ def compile_model(
 
     :param model: Model acquired from read_model function or a path to a model in IR / ONNX / PDPD /
                     TF and TFLite format.
-    :type model: Union[openvino.runtime.Model, str, pathlib.Path]
+    :type model: Union[openvino.Model, str, pathlib.Path]
     :param device_name: Optional. Name of the device to load the model to. If not specified,
                         the default OpenVINO device will be selected by AUTO plugin.
     :type device_name: str
     :param config: Optional dict of pairs:
                     (property name, property value) relevant only for this load operation.
     :type config: dict, optional
     :return: A compiled model.
-    :rtype: openvino.runtime.CompiledModel
+    :rtype: openvino.CompiledModel
 
     """
     core = Core()

src/bindings/python/src/openvino/helpers/packing.py

@@ -21,7 +21,7 @@ def pack_data(array: np.ndarray, type: Type) -> np.ndarray:
     :param array: numpy array with values to pack.
     :type array: numpy array
     :param type: Type to interpret the array values. Type must be u1, u4, i4, nf4 or f4e2m1.
-    :type type: openvino.runtime.Type
+    :type type: openvino.Type
     """
     assert type in [Type.u1, Type.u4, Type.i4, Type.nf4, Type.f4e2m1], "Packing algorithm for the" "data types stored in 1, 2 or 4 bits"
 
@@ -58,9 +58,9 @@ def unpack_data(array: np.ndarray, type: Type, shape: Union[list, Shape]) -> np.
     :param array: numpy array to unpack.
     :type array: numpy array
     :param type: Type to extract from array values. Type must be u1, u4, i4, nf4 or f4e2m1.
-    :type type: openvino.runtime.Type
+    :type type: openvino.Type
     :param shape: the new shape for the unpacked array.
-    :type shape: Union[list, openvino.runtime.Shape]
+    :type shape: Union[list, openvino.Shape]
     """
     assert type in [Type.u1, Type.u4, Type.i4, Type.nf4, Type.f4e2m1], "Unpacking algorithm for the" "data types stored in 1, 2 or 4 bits"
     unpacked = np.unpackbits(array.view(np.uint8))

src/bindings/python/src/openvino/utils/data_helpers/wrappers.py

@@ -36,7 +36,7 @@ class OVDict(Mapping):
     This class is a dict-like object. It provides possibility to
     address data tensors with three key types:
 
-    * `openvino.runtime.ConstOutput` - port of the output
+    * `openvino.ConstOutput` - port of the output
     * `int` - index of the output
     * `str` - names of the output