Merge remote-tracking branch 'upstream/master' into find_python3

.github/workflows/linux_onnxruntime.yml

@@ -51,7 +51,7 @@ jobs:
       INSTALL_DIR: ${{ github.workspace }}/install/openvino
     steps:
       - name: Clone OpenVINO
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with:
           path: 'openvino'
           submodules: 'true'
@@ -96,7 +96,7 @@ jobs:
       #
 
       - name: Get number of CPU cores
-        uses: SimenB/github-actions-cpu-cores@v1
+        uses: SimenB/github-actions-cpu-cores@v2
         id: cpu-cores
 
       - name: CMake configure

docs/dev/build_windows.md

@@ -25,29 +25,17 @@ Supported configurations:
     ```sh
     git clone https://github.com/openvinotoolkit/openvino.git
     cd openvino
-    git submodule update --init --recursive
-    ```
-   (Extra for WoA) To build on Windows on ARM with ARM plugin:
-    ```sh
-    git clone https://github.com/openvinotoolkit/openvino_contrib.git
-    cd openvino_contrib
-    git submodule update --init --recursive
+    git submodule update --init
     ```
 
 2. Create build directory:
     ```sh
     mkdir build && cd build
     ```
-3. In the `build` directory, run `cmake` to fetch project dependencies and generate a Visual Studio solution.
+3. In the `build` directory, run `cmake` to fetch project dependencies and generate a Visual Studio solution:
 
-   On Windows x86 64-bits:
-    ```sh
-    cmake -G "Visual Studio 16 2019" -DCMAKE_BUILD_TYPE=Release <openvino>
-    ```
-
-   On Windows on ARM for ARM64 architecture:
     ```sh
-    cmake -G "Visual Studio 16 2019" -DOPENVINO_EXTRA_MODULES=<openvino_contrib>/modules/arm_plugin -DCMAKE_BUILD_TYPE=Release <openvino>
+    cmake -G "Visual Studio 17 2022" <openvino>
     ```
 
    > **HINT**: **Generating PDB Files and Debugging Your Build** <br>
@@ -62,16 +50,8 @@ Supported configurations:
 
 ### Additional Build Options
 
-- Internal JIT GEMM implementation is used by default.
-
-- Threading Building Blocks (TBB) is used by default. To build Inference Engine with OpenMP threading, set the `-DTHREADING=OMP` option.
-
-- Required versions of TBB and OpenCV packages are downloaded automatically by the CMake-based script. If you want to use the automatically-downloaded packages but you have already installed TBB or OpenCV packages configured in your environment, you may need to clean the `TBBROOT` and `OpenCV_DIR` environment variables before running the `cmake` command; otherwise they won'tnbe downloaded and the build may fail if incompatible versions were installed.
-
-- If the CMake-based build script can not find and download the OpenCV package that is supported on your platform, or if you want to use a custom build of the OpenCV library, refer to the [Use Custom OpenCV Builds](./cmake_options_for_custom_compilation.md#Building-with-custom-OpenCV) section for details.
-
 - To build the OpenVINO Runtime Python API:
-  1. First, install all additional packages (e.g., cython and opencv) listed in the file:
+  1. First, install all additional packages (e.g., cython) listed in the file:
       ```sh
       pip install -r <openvino>\src\bindings\python\src\compatibility\openvino\requirements-dev.txt
       ```
@@ -95,15 +75,12 @@ Supported configurations:
      pip install build/wheel/openvino-2023.0.0-9612-cp11-cp11-win_arm64.whl
      ```
 
-- OpenVINO runtime compilation options:
-  `-DENABLE_OV_ONNX_FRONTEND=ON` enables the building of the ONNX importer.
-
 ### Building OpenVINO with Ninja* Build System
 
 ```sh
 call "C:\Program Files (x86)\Microsoft Visual Studio\2019\Professional\VC\Auxiliary\Build\vcvars64.bat"
 cmake -G Ninja -Wno-dev -DCMAKE_BUILD_TYPE=Release ..
-cmake --build . --config Release
+ninja .
 ```
 
 ## See also

docs/dev/cmake_options_for_custom_compilation.md

@@ -114,6 +114,9 @@ This document provides description and default values for CMake options that can
     * `OFF` is default, because it increases binary size.
 * `SELECTIVE_BUILD` enables [[Conditional compilation|ConditionalCompilation]] feature.
     * `OFF` is default.
+* `ENABLE_MLAS_FOR_CPU` enables MLAS library for CPU plugin
+    * `ON` is default for x86_64 and AARCH64 platforms
+    * Affects only OpenVINO CPU plugin
 
 ## Building with OpenCV
 

docs/dev/static_libaries.md

@@ -135,7 +135,7 @@ cmake -DCMAKE_TOOLCHAIN_FILE=<openvino source dir>/cmake/toolchains/mt.runtime.w
 
 * The enabled and tested capabilities of OpenVINO Runtime in a static build:
     * OpenVINO common runtime - work with `ov::Model`, perform model loading on particular device
-    * CPU and GNA inference plugins (**GPU and MYRIAD are not enabled**)
+    * CPU and GNA inference plugins (**GPU is not enabled**)
     * MULTI, HETERO, AUTO, and BATCH inference modes
     * IR, ONNX, PDPD, and TF frontends to read `ov::Model`
 * Static build support for building static libraries only for OpenVINO Runtime libraries. All other third-party prebuilt dependencies remain in the same format:

src/bindings/c/src/CMakeLists.txt

@@ -8,11 +8,12 @@ set(TARGET_NAME openvino_c)
 ov_deprecated_no_errors()
 add_definitions(-DIN_OV_COMPONENT)
 
-file(GLOB SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp)
-file(GLOB_RECURSE HEADERS ${OpenVINO_C_API_SOURCE_DIR}/include/*.h)
+file(GLOB SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.h ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp)
+file(GLOB_RECURSE LEGACY_HEADERS ${OpenVINO_C_API_SOURCE_DIR}/include/c_api/*.h)
+file(GLOB_RECURSE HEADERS ${OpenVINO_C_API_SOURCE_DIR}/include/openvino/*.h)
 
 # create library
-add_library(${TARGET_NAME} ${HEADERS} ${SOURCES})
+add_library(${TARGET_NAME} ${LEGACY_HEADERS} ${HEADERS} ${SOURCES})
 add_library(openvino::runtime::c ALIAS ${TARGET_NAME})
 
 target_link_libraries(${TARGET_NAME} PRIVATE openvino openvino::util)
@@ -24,7 +25,7 @@ if(NOT BUILD_SHARED_LIBS)
     target_compile_definitions(${TARGET_NAME} PUBLIC OPENVINO_STATIC_LIBRARY)
 endif()
 
-ov_add_clang_format_target(${TARGET_NAME}_clang FOR_TARGETS ${TARGET_NAME})
+ov_add_clang_format_target(${TARGET_NAME}_clang FOR_SOURCES ${HEADERS} ${SOURCES})
 
 set_target_properties(${TARGET_NAME} PROPERTIES INTERPROCEDURAL_OPTIMIZATION_RELEASE ${ENABLE_LTO})
 

src/bindings/c/src/common.h

@@ -17,7 +17,7 @@
 #define CATCH_IE_EXCEPTION(StatusCode, ExceptionType) \
     catch (const InferenceEngine::ExceptionType&) {   \
         return ov_status_e::StatusCode;               \
-    }                                                 \
+    }
 
 #define CATCH_OV_EXCEPTION(StatusCode, ExceptionType) \
     catch (const ov::ExceptionType&) {                \
@@ -42,7 +42,7 @@
     CATCH_IE_EXCEPTION(INFER_CANCELLED, InferCancelled)       \
     catch (...) {                                             \
         return ov_status_e::UNKNOW_EXCEPTION;                 \
-    }                                                         \
+    }
 
 #define GET_PROPERTY_FROM_ARGS_LIST                     \
     std::string property_key = va_arg(args_ptr, char*); \

src/bindings/python/src/openvino/frontend/tensorflow/graph_iterator.py

@@ -40,6 +40,10 @@ def get_input_names(self) -> list:
             return []
         inp_ops = filter(lambda op: op.type == "Placeholder", self.m_graph.get_operations())
         inp_names = []
+        if hasattr(self.m_graph, 'inputs') and self.m_graph.inputs:
+            for inp in self.m_graph.inputs:
+                inp_names.append(inp.op.name)
+            return inp_names
         for inp in inp_ops:
             assert isinstance(inp, tf.Operation), "Unknown node type. Expected tf.Operation, got {}".format(type(inp))
             assert hasattr(inp, "node_def") and isinstance(inp.node_def, tf.compat.v1.NodeDef), \
@@ -58,11 +62,13 @@ def get_output_names(self) -> list:
         # Note: used only for the library functions
         if not self.m_inner_graph:
             return []
-        # tf.Graph has ordered outputs which are stored in 'outputs' field,
-        # but using this field results in mismatch of outputs in inner graph and outputs in outer graph
-        # during the injection of subgraph.
-        # For this reason only nodes without outputs are considered graph outputs here
-        # as this approach does not lead to conflicts.
+
+        if hasattr(self.m_graph, 'outputs') and self.m_graph.outputs:
+            outputs = []
+            for out in self.m_graph.outputs:
+                outputs.append(out.name)
+            return outputs
+        # If graph has no 'outputs' field, find nodes without outputs and consider them graph outputs.
         # The order of outputs is important and wrong order may lead to conversion error.
         non_outputs = set()
         for op in self.m_graph.get_operations():

src/bindings/python/src/openvino/frontend/tensorflow/node_decoder.py

@@ -54,6 +54,7 @@ def __init__(self, operation: tf.Operation, share_weights: bool, inner_graph: bo
         self.m_operation = operation
         self.m_inner_graph = inner_graph
         self.m_data_type = None
+        self.m_parsed_content = None
 
         # Copies value from inner buffer of TF_Operation to NodeDef class.
         self.m_node_def = self.m_operation.node_def
@@ -87,11 +88,11 @@ def __init__(self, operation: tf.Operation, share_weights: bool, inner_graph: bo
         if self.m_operation.type == "Placeholder":
             self.m_data_type = tf.dtypes.DType(self.m_node_def.attr["dtype"].type).name
 
-            if self.m_data_type == "resource" and not self.m_inner_graph:
+            if not self.m_inner_graph:
                 variable_value = TFGraphNodeDecoder.get_variable(self.m_operation)
                 if variable_value is not None:
                     # does not copy data
-                    self.m_parsed_content = variable_value.value().__array__()
+                    self.m_parsed_content = variable_value.__array__()
 
                     if isinstance(self.m_parsed_content, bytes):
                         self.m_data_type = "string"
@@ -103,7 +104,7 @@ def get_op_name(self) -> str:
     def get_op_type(self) -> str:
         if self.m_operation.type == "Placeholder":
             type_attr = tf.dtypes.DType(self.m_node_def.attr["dtype"].type)
-            if type_attr.name == "resource" and not self.m_inner_graph:
+            if not self.m_inner_graph and self.m_parsed_content is not None:
                 if TFGraphNodeDecoder.get_variable(self.m_operation) is not None:
                     return "Const"
                 raise Exception("Could not get variable for resource Placeholder {0}".format(self.m_operation.name))
@@ -116,10 +117,11 @@ def get_variable(operation):
             return None
         for var_tensor, op_tensor in tf_graph.captures:
             if operation.outputs[0].name == op_tensor.name:
-                resource_name = var_tensor._name
+                if var_tensor.dtype.name != 'resource':
+                    return var_tensor
                 for variable_value in operation.graph.variables:
-                    if variable_value.name == resource_name:
-                        return variable_value
+                    if id(variable_value.handle) == id(var_tensor):
+                        return variable_value.value()
                 return None
         return None
 

src/bindings/python/src/openvino/frontend/tensorflow/utils.py

@@ -339,7 +339,7 @@ def create_tf_graph_iterator(input_model, placeholder_shapes, placeholder_data_t
         if hasattr(input_model, 'outputs') and hasattr(input_model, 'structured_outputs') and \
                 isinstance(input_model.structured_outputs, dict):
             external_names = sorted(list(input_model.structured_outputs.keys()))
-            internal_names = sorted([tensor.name for tensor in input_model.outputs])
+            internal_names = [tensor.name for tensor in input_model.outputs]
             if len(external_names) == len(internal_names):
                 for external_name, internal_name in zip(external_names, internal_names):
                     output_names_map = output_names_map or {}