1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
|
{ lib
, gcc12Stdenv
, fetchFromGitHub
, fetchurl
, cudaSupport ? opencv.cudaSupport or false
# build
, scons
, addOpenGLRunpath
, autoPatchelfHook
, cmake
, git
, libarchive
, patchelf
, pkg-config
, python3Packages
, shellcheck
# runtime
, flatbuffers
, level-zero
, libusb1
, libxml2
, ocl-icd
, opencv
, protobuf
, pugixml
, snappy
, tbb_2021_5
, cudaPackages
}:
let
inherit (lib)
cmakeBool
;
stdenv = gcc12Stdenv;
# prevent scons from leaking in the default python version
scons' = scons.override { python3 = python3Packages.python; };
tbbbind_version = "2_5";
tbbbind = fetchurl {
url = "https://storage.openvinotoolkit.org/dependencies/thirdparty/linux/tbbbind_${tbbbind_version}_static_lin_v4.tgz";
hash = "sha256-Tr8wJGUweV8Gb7lhbmcHxrF756ZdKdNRi1eKdp3VTuo=";
};
python = python3Packages.python.withPackages (ps: with ps; [
cython
pybind11
setuptools
sphinx
wheel
]);
in
stdenv.mkDerivation rec {
pname = "openvino";
version = "2024.2.0";
src = fetchFromGitHub {
owner = "openvinotoolkit";
repo = "openvino";
rev = "refs/tags/${version}";
fetchSubmodules = true;
hash = "sha256-HiKKvmqgbwW625An+Su0EOHqVrP18yvG2aOzrS0jWr4=";
};
outputs = [
"out"
"python"
];
nativeBuildInputs = [
addOpenGLRunpath
autoPatchelfHook
cmake
git
libarchive
patchelf
pkg-config
python
scons'
shellcheck
] ++ lib.optionals cudaSupport [
cudaPackages.cuda_nvcc
];
postPatch = ''
mkdir -p temp/tbbbind_${tbbbind_version}
pushd temp/tbbbind_${tbbbind_version}
bsdtar -xf ${tbbbind}
echo "${tbbbind.url}" > ie_dependency.info
popd
'';
dontUseSconsCheck = true;
dontUseSconsBuild = true;
dontUseSconsInstall = true;
cmakeFlags = [
"-Wno-dev"
"-DCMAKE_MODULE_PATH:PATH=${placeholder "out"}/lib/cmake"
"-DCMAKE_PREFIX_PATH:PATH=${placeholder "out"}"
"-DOpenCV_DIR=${opencv}/lib/cmake/opencv4/"
"-DProtobuf_LIBRARIES=${protobuf}/lib/libprotobuf${stdenv.hostPlatform.extensions.sharedLibrary}"
"-DPython_EXECUTABLE=${python.interpreter}"
(cmakeBool "CMAKE_VERBOSE_MAKEFILE" true)
(cmakeBool "NCC_SYLE" false)
(cmakeBool "BUILD_TESTING" false)
(cmakeBool "ENABLE_CPPLINT" false)
(cmakeBool "ENABLE_TESTING" false)
(cmakeBool "ENABLE_SAMPLES" false)
# features
(cmakeBool "ENABLE_INTEL_CPU" stdenv.isx86_64)
(cmakeBool "ENABLE_JS" false)
(cmakeBool "ENABLE_LTO" true)
(cmakeBool "ENABLE_ONEDNN_FOR_GPU" false)
(cmakeBool "ENABLE_OPENCV" true)
(cmakeBool "ENABLE_PYTHON" true)
# system libs
(cmakeBool "ENABLE_SYSTEM_FLATBUFFERS" true)
(cmakeBool "ENABLE_SYSTEM_OPENCL" true)
(cmakeBool "ENABLE_SYSTEM_PROTOBUF" false)
(cmakeBool "ENABLE_SYSTEM_PUGIXML" true)
(cmakeBool "ENABLE_SYSTEM_SNAPPY" true)
(cmakeBool "ENABLE_SYSTEM_TBB" true)
];
autoPatchelfIgnoreMissingDeps = [
"libngraph_backend.so"
];
buildInputs = [
flatbuffers
level-zero
libusb1
libxml2
ocl-icd
opencv.cxxdev
pugixml
snappy
tbb_2021_5
] ++ lib.optionals cudaSupport [
cudaPackages.cuda_cudart
];
enableParallelBuilding = true;
postInstall = ''
mkdir -p $python
mv $out/python/* $python/
rmdir $out/python
'';
postFixup = ''
# Link to OpenCL
find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
addOpenGLRunpath "$lib"
done
'';
meta = with lib; {
description = "OpenVINO™ Toolkit repository";
longDescription = ''
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 several components: namely Model Optimizer, nGraph and Inference Engine, as well as CPU, GPU, MYRIAD,
multi device 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*.
'';
homepage = "https://docs.openvinotoolkit.org/";
license = with licenses; [ asl20 ];
platforms = platforms.all;
broken = stdenv.isDarwin; # Cannot find macos sdk
maintainers = with maintainers; [ tfmoraes ];
};
}
|