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Alexey Suhov committed Feb 11, 2020
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19 changes: 19 additions & 0 deletions .clang-format
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BasedOnStyle: Google
IndentWidth: 4
UseTab: Never
---
Language: Cpp
Standard: Cpp11

AccessModifierOffset: -4
AllowAllArgumentsOnNextLine: false
AllowShortFunctionsOnASingleLine: Empty
AllowShortLambdasOnASingleLine: Empty
AlwaysBreakBeforeMultilineStrings: false
ColumnLimit: 120
DerivePointerAlignment: false
FixNamespaceComments: true
IndentCaseLabels: false
SpaceBeforeCpp11BracedList: true
SpaceBeforeCtorInitializerColon: false
---
4 changes: 2 additions & 2 deletions .gitmodules
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path = inference-engine/thirdparty/ade
url = https://github.com/opencv/ade.git
ignore = dirty
[submodule "inference-engine/thirdparty/ngraph"]
path = inference-engine/thirdparty/ngraph
[submodule "ngraph"]
path = ngraph
url = https://github.com/NervanaSystems/ngraph.git
ignore = dirty
135 changes: 135 additions & 0 deletions CMakeLists.txt
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# Copyright (C) 2018-2020 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
#

cmake_policy(SET CMP0054 NEW)
if (APPLE)
# due to https://cmake.org/cmake/help/v3.12/policy/CMP0068.html
cmake_minimum_required(VERSION 3.9 FATAL_ERROR)
else()
cmake_minimum_required(VERSION 3.5 FATAL_ERROR)
endif()

project(OpenVINO)

set(OpenVINO_MAIN_SOURCE_DIR ${CMAKE_CURRENT_SOURCE_DIR})
set(CMAKE_MODULE_PATH "${OpenVINO_MAIN_SOURCE_DIR}/cmake" ${CMAKE_MODULE_PATH})

include(CTest)
include(features)

# include developer package
include(developer_package)

# These options are shared with 3rdparty plugins
# by means of developer package
include(check_features)

# resolving dependencies for the project
message (STATUS "PROJECT ............................... " ${PROJECT_NAME})
message (STATUS "CMAKE_BINARY_DIR ...................... " ${CMAKE_BINARY_DIR})
message (STATUS "OpenVINO_MAIN_SOURCE_DIR .............. " ${OpenVINO_MAIN_SOURCE_DIR})
if (ENABLE_INFERENCE_ENGINE)
set(IE_MAIN_SOURCE_DIR ${OpenVINO_MAIN_SOURCE_DIR}/inference-engine)
message (STATUS "IE_MAIN_SOURCE_DIR .............. " ${IE_MAIN_SOURCE_DIR})
endif()
message (STATUS "CMAKE_GENERATOR ....................... " ${CMAKE_GENERATOR})
message (STATUS "CMAKE_C_COMPILER_ID ................... " ${CMAKE_C_COMPILER_ID})
message (STATUS "CMAKE_BUILD_TYPE ...................... " ${CMAKE_BUILD_TYPE})

# remove file with exported developer targets to force its regeneration
file(REMOVE "${CMAKE_BINARY_DIR}/targets_developer.cmake")
file(REMOVE "${CMAKE_BINARY_DIR}/targets.cmake")

function(build_ngraph)
if(NOT ENABLE_NGRAPH)
return()
endif()

function(ngraph_set option value)
if(NOT DEFINED ${option})
set(${option} ${value} CACHE BOOL "" FORCE)
endif()
endfunction()

add_definitions(-DENABLE_NGRAPH)
set(NGRAPH_BUILD_DIR ${CMAKE_LIBRARY_OUTPUT_DIRECTORY} CACHE STRING "" FORCE)
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${OpenVINO_MAIN_SOURCE_DIR}/ngraph/cmake/Modules/")

ngraph_set(NGRAPH_ADDRESS_SANITIZER FALSE)
ngraph_set(NGRAPH_TOOLS_ENABLE FALSE)
ngraph_set(NGRAPH_CPU_ENABLE FALSE)
ngraph_set(NGRAPH_MLIR_ENABLE FALSE)
ngraph_set(NGRAPH_INTELGPU_ENABLE FALSE)
ngraph_set(NGRAPH_GPU_ENABLE FALSE)
ngraph_set(NGRAPH_INTERPRETER_ENABLE FALSE)
ngraph_set(NGRAPH_NOP_ENABLE FALSE)
ngraph_set(NGRAPH_GPUH_ENABLE FALSE)
ngraph_set(NGRAPH_GENERIC_CPU_ENABLE FALSE)
ngraph_set(NGRAPH_DEBUG_ENABLE FALSE)
ngraph_set(NGRAPH_DEPRECATED_ENABLE FALSE)
ngraph_set(NGRAPH_DEX_ONLY FALSE)
ngraph_set(NGRAPH_ENABLE_CPU_CONV_AUTO FALSE)
ngraph_set(NGRAPH_CODE_COVERAGE_ENABLE FALSE)
ngraph_set(NGRAPH_LIB_VERSIONING_ENABLE FALSE)
if (ENABLE_PYTHON AND NOT WIN32)
ngraph_set(NGRAPH_PYTHON_BUILD_ENABLE TRUE)
else()
ngraph_set(NGRAPH_PYTHON_BUILD_ENABLE FALSE)
endif()
ngraph_set(NGRAPH_PLAIDML_ENABLE FALSE)
ngraph_set(NGRAPH_DISTRIBUTED_ENABLE FALSE)
ngraph_set(NGRAPH_FAST_MATH_ENABLE FALSE)
ngraph_set(NGRAPH_JSON_ENABLE FALSE)
ngraph_set(NGRAPH_STATIC_LIB_ENABLE FALSE)
ngraph_set(NGRAPH_INTERPRETER_STATIC_LIB_ENABLE FALSE)
ngraph_set(NGRAPH_CPU_STATIC_LIB_ENABLE FALSE)
ngraph_set(NGRAPH_DYNAMIC_COMPONENTS_ENABLE FALSE)
ngraph_set(NGRAPH_NATIVE_ARCH_ENABLE FALSE)

if (NOT ANDROID)
ngraph_set(NGRAPH_UNIT_TEST_ENABLE TRUE)
ngraph_set(NGRAPH_UNIT_TEST_OPENVINO_ENABLE TRUE)
else()
ngraph_set(NGRAPH_UNIT_TEST_ENABLE FALSE)
ngraph_set(NGRAPH_UNIT_TEST_OPENVINO_ENABLE FALSE)
endif()

if(CMAKE_CXX_COMPILER_ID MATCHES "Clang")
ie_add_compiler_flags(-Wno-error=uninitialized -Wno-error=literal-conversion)
elseif(UNIX)
ie_add_compiler_flags(-Wno-error=maybe-uninitialized -Wno-error=return-type -fPIC)
endif()
if(ANDROID)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-error=defaulted-function-deleted -Wno-error=unused-command-line-argument")
endif()

# WA for GCC 7.0
if (UNIX)
ie_add_compiler_flags(-Wno-error=return-type -Wno-undef)
elseif(WIN32)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /wd4308 /wd4146")
endif()

if(UNIX)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fvisibility=default")
endif()

if(ENABLE_LTO)
ie_enable_lto()
endif()

ie_cpack_add_component(ngraph)

add_subdirectory(ngraph)
endfunction()

build_ngraph()

if (ENABLE_INFERENCE_ENGINE)
add_subdirectory(inference-engine)
endif()

# cpack

ie_cpack(${IE_CPACK_COMPONENTS_ALL})
46 changes: 31 additions & 15 deletions README.md
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# [OpenVINO™ Toolkit](https://01.org/openvinotoolkit) - Deep Learning Deployment Toolkit repository
[![Stable release](https://img.shields.io/badge/version-2019.R3-green.svg)](https://github.com/opencv/dldt/releases/tag/2019_R3)
[![Stable release](https://img.shields.io/badge/version-2020.1-green.svg)](https://github.com/opencv/dldt/releases/tag/2020.1)
[![Apache License Version 2.0](https://img.shields.io/badge/license-Apache_2.0-green.svg)](LICENSE)

This toolkit allows developers to deploy pre-trained deep learning models through a high-level C++ Inference Engine API integrated with application logic.
This toolkit allows developers to deploy pre-trained deep learning models
through a high-level C++ Inference Engine API integrated with application logic.

This open source version includes two components, namely Model Optimizer and Inference Engine, as well as CPU, GPU and heterogeneous plugins to accelerate deep learning inferencing on Intel(R) CPUs and Intel(R) Processor Graphics. It supports pre-trained models from the [Open Model Zoo](https://github.com/opencv/open_model_zoo/) along with 100+ open source and public models in popular formats such as Caffe*, Tensorflow*, MXNet* and ONNX*.
This open source version includes two components: namely [Model Optimizer] and
[Inference Engine], as well as CPU, GPU and heterogeneous plugins to accelerate
deep learning inferencing on Intel® CPUs and Intel® Processor Graphics.
It supports pre-trained models from the [Open Model Zoo], along with 100+ open
source and public models in popular formats such as Caffe\*, TensorFlow\*,
MXNet\* and ONNX\*.

## Repository components:
* [Inference Engine](https://software.intel.com/en-us/articles/OpenVINO-InferEngine)
* [Model Optimizer](https://software.intel.com/en-us/articles/OpenVINO-ModelOptimizer)
* [Inference Engine]
* [Model Optimizer]

## License
Deep Learning Deployment Toolkit is licensed under [Apache License Version 2.0](LICENSE).
By contributing to the project, you agree to the license and copyright terms therein
and release your contribution under these terms.

## Documentation
* [OpenVINO™ Release Notes](https://software.intel.com/en-us/articles/OpenVINO-RelNotes)
* [Inference Engine build instructions](inference-engine/README.md)
* [Get Started with Deep Learning Deployment Toolkit on Linux*](get-started-linux.md)
* [OpenVINO™ Inference Engine Build Instructions](build-instruction.md)
* [Get Started with Deep Learning Deployment Toolkit on Linux](get-started-linux.md)\*
* [Introduction to Deep Learning Deployment Toolkit](https://docs.openvinotoolkit.org/latest/_docs_IE_DG_Introduction.html)
* [Inference Engine Developer Guide](https://docs.openvinotoolkit.org/latest/_docs_IE_DG_Deep_Learning_Inference_Engine_DevGuide.html)
* [Model Optimizer Developer Guide](https://docs.openvinotoolkit.org/latest/_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide.html)


## How to Contribute
We welcome community contributions to the Deep Learning Deployment Toolkit repository. If you have an idea how to improve the product, please share it with us doing the following steps:
We welcome community contributions to the Deep Learning Deployment Toolkit
repository. If you have an idea how to improve the product, please share it
with us doing the following steps:

* Make sure you can build the product and run all tests and samples with your patch
* In case of a larger feature, provide a relevant unit tests and sample
* In case of a larger feature, provide relevant unit tests and one or more sample
* Submit a pull request at https://github.com/opencv/dldt/pulls

We will review your contribution and, if any additional fixes or modifications are necessary, may give some feedback to guide you. When accepted, your pull request will be merged into GitHub* repositories.

Deep Learning Deployment Toolkit is licensed under Apache License, Version 2.0. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.
We will review your contribution and, if any additional fixes or modifications
are necessary, may give some feedback to guide you. Your pull request will be
merged into GitHub* repositories if accepted.

## Support
Please report questions, issues and suggestions using:
* [\#openvino](https://stackoverflow.com/search?q=%23openvino) tag on StackOverflow*

* The `openvino` [tag on StackOverflow]\*
* [GitHub* Issues](https://github.com/opencv/dldt/issues)
* [Forum](https://software.intel.com/en-us/forums/computer-vision)

---
\* Other names and brands may be claimed as the property of others.
\* Other names and brands may be claimed as the property of others.

[Open Model Zoo]:https://github.com/opencv/open_model_zoo
[Inference Engine]:https://software.intel.com/en-us/articles/OpenVINO-InferEngine
[Model Optimizer]:https://software.intel.com/en-us/articles/OpenVINO-ModelOptimizer
[tag on StackOverflow]:https://stackoverflow.com/search?q=%23openvino
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