Align style doc with samples

cmake/developer_package/add_ie_target.cmake

@@ -31,6 +31,7 @@ addIeTarget(
 function(addIeTarget)
     set(options
         ADD_CPPLINT                   # Enables code style checks for the target
+        ADD_CLANG_FORMAT              # Enables code style checks for the target
         )
     set(oneValueRequiredArgs
         TYPE # type of target, SHARED|STATIC|EXECUTABLE. SHARED and STATIC correspond to add_library, EXECUTABLE to add_executable
@@ -119,6 +120,10 @@ function(addIeTarget)
         # code style
         add_cpplint_target(${ARG_NAME}_cpplint FOR_TARGETS ${ARG_NAME})
     endif()
+    if (ARG_ADD_CLANG_FORMAT)
+        # code style
+        add_clang_format_target(${ARG_NAME}_clang FOR_TARGETS ${ARG_NAME})
+    endif()
     if (ARG_DEVELOPER_PACKAGE)
         # developer package
         openvino_developer_export_targets(COMPONENT ${ARG_DEVELOPER_PACKAGE}
@@ -128,7 +133,6 @@ function(addIeTarget)
         # Provide default compile pdb name equal to target name
         set_target_properties(${ARG_NAME} PROPERTIES COMPILE_PDB_NAME ${ARG_NAME})
     endif()
-
 endfunction()
 
 #[[

cmake/developer_package/plugins/plugins.cmake

@@ -27,7 +27,10 @@ endif()
 #               )
 #
 function(ie_add_plugin)
-    set(options SKIP_INSTALL)
+    set(options 
+        SKIP_INSTALL 
+        ADD_CLANG_FORMAT
+        )
     set(oneValueArgs NAME DEVICE_NAME VERSION_DEFINES_FOR)
     set(multiValueArgs SOURCES OBJECT_LIBRARIES CPPLINT_FILTERS)
     cmake_parse_arguments(IE_PLUGIN "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
@@ -73,7 +76,11 @@ function(ie_add_plugin)
         string(CONCAT custom_filter "${custom_filter}" "," "${filter}")
     endforeach()
 
-    add_cpplint_target(${IE_PLUGIN_NAME}_cpplint FOR_TARGETS ${IE_PLUGIN_NAME} CUSTOM_FILTERS ${custom_filter})
+    if (IE_PLUGIN_ADD_CLANG_FORMAT)
+        add_clang_format_target(${IE_PLUGIN_NAME}_clang FOR_TARGETS ${IE_PLUGIN_NAME})
+    else()
+        add_cpplint_target(${IE_PLUGIN_NAME}_cpplint FOR_TARGETS ${IE_PLUGIN_NAME} CUSTOM_FILTERS ${custom_filter})
+    endif()
 
     # check that plugin with such name is not registered
 

docs/.clang-format

@@ -0,0 +1,25 @@
+BasedOnStyle: Google
+IndentWidth: 4
+UseTab: Never
+
+Language: Cpp
+Standard: Cpp11
+
+AccessModifierOffset: -4
+AlignConsecutiveMacros: true
+AllowAllArgumentsOnNextLine: false
+AllowAllParametersOfDeclarationOnNextLine: false
+AllowShortFunctionsOnASingleLine: Empty
+AllowShortIfStatementsOnASingleLine: Never
+AllowShortLambdasOnASingleLine: Empty
+AllowShortLoopsOnASingleLine: false
+AlwaysBreakBeforeMultilineStrings: false
+ColumnLimit: 160
+# Specialize this comment pragma in order to avoid changes in SEA copyrights
+CommentPragmas: '^#'
+DerivePointerAlignment: false
+FixNamespaceComments: true
+IndentCaseLabels: false
+IndentPPDirectives: BeforeHash
+SpaceBeforeCpp11BracedList: true
+SpaceBeforeCtorInitializerColon: false

docs/onnx_custom_op/CMakeLists.txt

@@ -12,4 +12,5 @@ find_package(ngraph REQUIRED COMPONENTS onnx_importer)
 add_library(${TARGET_NAME} STATIC onnx_custom_op.cpp)
 
 target_link_libraries(${TARGET_NAME} PUBLIC ${NGRAPH_LIBRARIES} ${ONNX_IMPORTER_LIBRARIES})
+add_clang_format_target(${TARGET_NAME}_clang FOR_TARGETS ${TARGET_NAME})
 # [cmake:onnx_custom_op]

docs/snippets/Bfloat16Inference0.cpp

@@ -1,10 +1,10 @@
 #include <inference_engine.hpp>
 
 int main() {
-using namespace InferenceEngine;
-//! [part0]
-InferenceEngine::Core core;
-auto cpuOptimizationCapabilities = core.GetMetric("CPU", METRIC_KEY(OPTIMIZATION_CAPABILITIES)).as<std::vector<std::string>>();
-//! [part0]
-return 0;
+    using namespace InferenceEngine;
+    //! [part0]
+    InferenceEngine::Core core;
+    auto cpuOptimizationCapabilities = core.GetMetric("CPU", METRIC_KEY(OPTIMIZATION_CAPABILITIES)).as<std::vector<std::string>>();
+    //! [part0]
+    return 0;
 }

docs/snippets/Bfloat16Inference1.cpp

@@ -1,13 +1,13 @@
 #include <inference_engine.hpp>
 
 int main() {
-using namespace InferenceEngine;
-//! [part1]
-InferenceEngine::Core core;
-auto network = core.ReadNetwork("sample.xml");
-auto exeNetwork = core.LoadNetwork(network, "CPU");
-auto enforceBF16 = exeNetwork.GetConfig(PluginConfigParams::KEY_ENFORCE_BF16).as<std::string>();
-//! [part1]
+    using namespace InferenceEngine;
+    //! [part1]
+    InferenceEngine::Core core;
+    auto network = core.ReadNetwork("sample.xml");
+    auto exeNetwork = core.LoadNetwork(network, "CPU");
+    auto enforceBF16 = exeNetwork.GetConfig(PluginConfigParams::KEY_ENFORCE_BF16).as<std::string>();
+    //! [part1]
 
-return 0;
+    return 0;
 }

docs/snippets/Bfloat16Inference2.cpp

@@ -1,11 +1,11 @@
 #include <inference_engine.hpp>
 
 int main() {
-using namespace InferenceEngine;
-//! [part2]
-InferenceEngine::Core core;
-core.SetConfig({ { CONFIG_KEY(ENFORCE_BF16), CONFIG_VALUE(NO) } }, "CPU");
-//! [part2]
+    using namespace InferenceEngine;
+    //! [part2]
+    InferenceEngine::Core core;
+    core.SetConfig({{CONFIG_KEY(ENFORCE_BF16), CONFIG_VALUE(NO)}}, "CPU");
+    //! [part2]
 
-return 0;
+    return 0;
 }

docs/snippets/CMakeLists.txt

@@ -68,3 +68,4 @@ endif()
 
 target_link_libraries(${TARGET_NAME} PRIVATE inference_engine_plugin_api
     ngraph inference_engine_transformations)
+add_clang_format_target(${TARGET_NAME}_clang FOR_TARGETS ${TARGET_NAME})

docs/snippets/CPU_Kernel.cpp

@@ -1,14 +1,14 @@
 #include <inference_engine.hpp>
 
 int main() {
-using namespace InferenceEngine;
-//! [part0]
-InferenceEngine::Core core;
-// Load CPU extension as a shared library
-auto extension_ptr = std::make_shared<InferenceEngine::Extension>(std::string{"<shared lib path>"});
-// Add extension to the CPU device
-core.AddExtension(extension_ptr, "CPU");
-//! [part0]
+    using namespace InferenceEngine;
+    //! [part0]
+    InferenceEngine::Core core;
+    // Load CPU extension as a shared library
+    auto extension_ptr = std::make_shared<InferenceEngine::Extension>(std::string {"<shared lib path>"});
+    // Add extension to the CPU device
+    core.AddExtension(extension_ptr, "CPU");
+    //! [part0]
 
-return 0;
+    return 0;
 }

docs/snippets/DynamicBatching.cpp

@@ -2,41 +2,40 @@
 #include <vector>
 
 int main() {
-int FLAGS_bl = 1;
-auto imagesData = std::vector<std::string>(2);
-auto imagesData2 = std::vector<std::string>(4);
-//! [part0]
-int dynBatchLimit = FLAGS_bl; //take dynamic batch limit from command line option
-
-// Read network model
-InferenceEngine::Core core;
-InferenceEngine::CNNNetwork network = core.ReadNetwork("sample.xml");
-
-
-// enable dynamic batching and prepare for setting max batch limit
-const std::map<std::string, std::string> dyn_config = 
-{ { InferenceEngine::PluginConfigParams::KEY_DYN_BATCH_ENABLED, InferenceEngine::PluginConfigParams::YES } };
-network.setBatchSize(dynBatchLimit);
-
-// create executable network and infer request
-auto executable_network = core.LoadNetwork(network, "CPU", dyn_config);
-auto infer_request = executable_network.CreateInferRequest();
-
-// ...
-
-// process a set of images
-// dynamically set batch size for subsequent Infer() calls of this request
-size_t batchSize = imagesData.size();
-infer_request.SetBatch(batchSize);
-infer_request.Infer();
-
-// ...
-
-// process another set of images
-batchSize = imagesData2.size();
-infer_request.SetBatch(batchSize);
-infer_request.Infer();
-//! [part0]
-
-return 0;
+    int FLAGS_bl = 1;
+    auto imagesData = std::vector<std::string>(2);
+    auto imagesData2 = std::vector<std::string>(4);
+    //! [part0]
+    int dynBatchLimit = FLAGS_bl;  // take dynamic batch limit from command line option
+
+    // Read network model
+    InferenceEngine::Core core;
+    InferenceEngine::CNNNetwork network = core.ReadNetwork("sample.xml");
+
+    // enable dynamic batching and prepare for setting max batch limit
+    const std::map<std::string, std::string> dyn_config = {
+        {InferenceEngine::PluginConfigParams::KEY_DYN_BATCH_ENABLED, InferenceEngine::PluginConfigParams::YES}};
+    network.setBatchSize(dynBatchLimit);
+
+    // create executable network and infer request
+    auto executable_network = core.LoadNetwork(network, "CPU", dyn_config);
+    auto infer_request = executable_network.CreateInferRequest();
+
+    // ...
+
+    // process a set of images
+    // dynamically set batch size for subsequent Infer() calls of this request
+    size_t batchSize = imagesData.size();
+    infer_request.SetBatch(batchSize);
+    infer_request.Infer();
+
+    // ...
+
+    // process another set of images
+    batchSize = imagesData2.size();
+    infer_request.SetBatch(batchSize);
+    infer_request.Infer();
+    //! [part0]
+
+    return 0;
 }

docs/snippets/GPU_Kernel.cpp

@@ -1,16 +1,16 @@
 #include <inference_engine.hpp>
 
 int main() {
-using namespace InferenceEngine;
-//! [part0]
-InferenceEngine::Core core;
-// Load GPU Extensions
-core.SetConfig({ { InferenceEngine::PluginConfigParams::KEY_CONFIG_FILE, "<path_to_the_xml_file>" } }, "GPU");
-//! [part0]
+    using namespace InferenceEngine;
+    //! [part0]
+    InferenceEngine::Core core;
+    // Load GPU Extensions
+    core.SetConfig({{InferenceEngine::PluginConfigParams::KEY_CONFIG_FILE, "<path_to_the_xml_file>"}}, "GPU");
+    //! [part0]
 
-//! [part1]
-core.SetConfig({ { PluginConfigParams::KEY_DUMP_KERNELS, PluginConfigParams::YES } }, "GPU");
-//! [part1]
+    //! [part1]
+    core.SetConfig({{PluginConfigParams::KEY_DUMP_KERNELS, PluginConfigParams::YES}}, "GPU");
+    //! [part1]
 
-return 0;
+    return 0;
 }

docs/snippets/GPU_Kernels_Tuning.cpp

@@ -1,13 +1,13 @@
 #include <inference_engine.hpp>
 
 int main() {
-using namespace InferenceEngine;
-//! [part0]
-Core ie;          
-  ie.SetConfig({{ CONFIG_KEY(TUNING_MODE), CONFIG_VALUE(TUNING_CREATE) }}, "GPU");
-  ie.SetConfig({{ CONFIG_KEY(TUNING_FILE), "/path/to/tuning/file.json" }}, "GPU");
-  // Further LoadNetwork calls will use the specified tuning parameters
-//! [part0]
+    using namespace InferenceEngine;
+    //! [part0]
+    Core ie;
+    ie.SetConfig({{CONFIG_KEY(TUNING_MODE), CONFIG_VALUE(TUNING_CREATE)}}, "GPU");
+    ie.SetConfig({{CONFIG_KEY(TUNING_FILE), "/path/to/tuning/file.json"}}, "GPU");
+    // Further LoadNetwork calls will use the specified tuning parameters
+    //! [part0]
 
-return 0;
+    return 0;
 }

docs/snippets/Graph_debug_capabilities0.cpp

@@ -1,13 +1,12 @@
 #include <inference_engine.hpp>
 #include <ngraph/pass/visualize_tree.hpp>
 
-
 int main() {
-using namespace InferenceEngine;
-//! [part0]
-std::shared_ptr<ngraph::Function> nGraph;
-// ...
-ngraph::pass::VisualizeTree("after.png").run_on_function(nGraph);     // Visualize the nGraph function to an image
-//! [part0]
-return 0;
+    using namespace InferenceEngine;
+    //! [part0]
+    std::shared_ptr<ngraph::Function> nGraph;
+    // ...
+    ngraph::pass::VisualizeTree("after.png").run_on_function(nGraph);  // Visualize the nGraph function to an image
+    //! [part0]
+    return 0;
 }

docs/snippets/Graph_debug_capabilities1.cpp

@@ -1,14 +1,13 @@
 #include <inference_engine.hpp>
 #include <ngraph/pass/visualize_tree.hpp>
 
-
 int main() {
-using namespace InferenceEngine;
-//! [part1]
-std::shared_ptr<ngraph::Function> nGraph;
-// ...
-CNNNetwork network(nGraph);
-network.serialize("test_ir.xml", "test_ir.bin");
-//! [part1]
-return 0;
+    using namespace InferenceEngine;
+    //! [part1]
+    std::shared_ptr<ngraph::Function> nGraph;
+    // ...
+    CNNNetwork network(nGraph);
+    network.serialize("test_ir.xml", "test_ir.bin");
+    //! [part1]
+    return 0;
 }

docs/snippets/HETERO0.cpp

@@ -1,14 +1,15 @@
 #include <inference_engine.hpp>
 #include <ngraph/ngraph.hpp>
+
 #include "hetero/hetero_plugin_config.hpp"
 
 int main() {
-InferenceEngine::Core core;
-auto network = core.ReadNetwork("sample.xml");
-auto function = network.getFunction();
-//! [part0]
-for (auto && op : function->get_ops())
-    op->get_rt_info()["affinity"] = std::make_shared<ngraph::VariantWrapper<std::string>>("CPU");
-//! [part0]
-return 0;
+    InferenceEngine::Core core;
+    auto network = core.ReadNetwork("sample.xml");
+    auto function = network.getFunction();
+    //! [part0]
+    for (auto&& op : function->get_ops())
+        op->get_rt_info()["affinity"] = std::make_shared<ngraph::VariantWrapper<std::string>>("CPU");
+    //! [part0]
+    return 0;
 }