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
|
{ config, stdenv, lib
, fetchFromGitHub
, fetchurl
, fetchpatch
, cmake
, boost
, gflags
, glog
, hdf5-cpp
, opencv4
, protobuf
, doxygen
, blas
, Accelerate, CoreGraphics, CoreVideo
, lmdbSupport ? true, lmdb
, leveldbSupport ? true, leveldb, snappy
, cudaSupport ? config.cudaSupport, cudaPackages ? { }
, cudnnSupport ? cudaSupport
, ncclSupport ? false
, pythonSupport ? false, python ? null, numpy ? null
, substituteAll
}:
let
inherit (cudaPackages) cudatoolkit nccl;
# The default for cudatoolkit 10.1 is CUDNN 8.0.5, the last version to support CUDA 10.1.
# However, this caffe does not build with CUDNN 8.x, so we use CUDNN 7.6.5 instead.
# Earlier versions of cudatoolkit use pre-8.x CUDNN, so we use the default.
cudnn = if lib.versionOlder cudatoolkit.version "10.1"
then cudaPackages.cudnn
else cudaPackages.cudnn_7_6;
in
assert leveldbSupport -> (leveldb != null && snappy != null);
assert cudnnSupport -> cudaSupport;
assert ncclSupport -> cudaSupport;
assert pythonSupport -> (python != null && numpy != null);
let
toggle = bool: if bool then "ON" else "OFF";
test_model_weights = fetchurl {
url = "http://dl.caffe.berkeleyvision.org/bvlc_reference_caffenet.caffemodel";
sha256 = "472d4a06035497b180636d8a82667129960371375bd10fcb6df5c6c7631f25e0";
};
in
stdenv.mkDerivation rec {
pname = "caffe";
version = "1.0";
src = fetchFromGitHub {
owner = "BVLC";
repo = "caffe";
rev = version;
sha256 = "104jp3cm823i3cdph7hgsnj6l77ygbwsy35mdmzhmsi4jxprd9j3";
};
nativeBuildInputs = [ cmake doxygen ];
cmakeFlags =
# It's important that caffe is passed the major and minor version only because that's what
# boost_python expects
[ (if pythonSupport then "-Dpython_version=${python.pythonVersion}" else "-DBUILD_python=OFF")
"-DBLAS=open"
] ++ (if cudaSupport then [
"-DCUDA_ARCH_NAME=All"
"-DCUDA_HOST_COMPILER=${cudatoolkit.cc}/bin/cc"
] else [ "-DCPU_ONLY=ON" ])
++ ["-DUSE_NCCL=${toggle ncclSupport}"]
++ ["-DUSE_LEVELDB=${toggle leveldbSupport}"]
++ ["-DUSE_LMDB=${toggle lmdbSupport}"];
buildInputs = [ boost gflags glog protobuf hdf5-cpp opencv4 blas ]
++ lib.optional cudaSupport cudatoolkit
++ lib.optional cudnnSupport cudnn
++ lib.optional lmdbSupport lmdb
++ lib.optional ncclSupport nccl
++ lib.optionals leveldbSupport [ leveldb snappy ]
++ lib.optionals pythonSupport [ python numpy ]
++ lib.optionals stdenv.isDarwin [ Accelerate CoreGraphics CoreVideo ]
;
propagatedBuildInputs = lib.optionals pythonSupport (
# requirements.txt
let pp = python.pkgs; in ([
pp.numpy pp.scipy pp.scikit-image pp.h5py
pp.matplotlib pp.ipython pp.networkx pp.nose
pp.pandas pp.python-dateutil pp.protobuf pp.gflags
pp.pyyaml pp.pillow pp.six
] ++ lib.optional leveldbSupport pp.leveldb)
);
outputs = [ "bin" "out" ];
propagatedBuildOutputs = []; # otherwise propagates out -> bin cycle
patches = [
./darwin.patch
(fetchpatch {
name = "support-opencv4";
url = "https://github.com/BVLC/caffe/pull/6638/commits/0a04cc2ccd37ba36843c18fea2d5cbae6e7dd2b5.patch";
hash = "sha256-ZegTvp0tTHlopQv+UzHDigs6XLkP2VfqLCWXl6aKJSI=";
})
] ++ lib.optional pythonSupport (substituteAll {
src = ./python.patch;
inherit (python.sourceVersion) major minor; # Should be changed in case of PyPy
});
postPatch = ''
substituteInPlace src/caffe/util/io.cpp --replace \
'SetTotalBytesLimit(kProtoReadBytesLimit, 536870912)' \
'SetTotalBytesLimit(kProtoReadBytesLimit)'
'' + lib.optionalString (cudaSupport && lib.versionAtLeast cudatoolkit.version "9.0") ''
# CUDA 9.0 doesn't support sm_20
sed -i 's,20 21(20) ,,' cmake/Cuda.cmake
'';
preConfigure = lib.optionalString pythonSupport ''
# We need this when building with Python bindings
export BOOST_LIBRARYDIR="${boost.out}/lib";
'';
postInstall = ''
# Internal static library.
rm $out/lib/libproto.a
# Install models
cp -a ../models $out/share/Caffe/models
moveToOutput "bin" "$bin"
'' + lib.optionalString pythonSupport ''
mkdir -p $out/${python.sitePackages}
mv $out/python/caffe $out/${python.sitePackages}
rm -rf $out/python
'';
doInstallCheck = false; # build takes more than 30 min otherwise
installCheckPhase = ''
model=bvlc_reference_caffenet
m_path="$out/share/Caffe/models/$model"
$bin/bin/caffe test \
-model "$m_path/deploy.prototxt" \
-solver "$m_path/solver.prototxt" \
-weights "${test_model_weights}"
'';
meta = with lib; {
description = "Deep learning framework";
longDescription = ''
Caffe is a deep learning framework made with expression, speed, and
modularity in mind. It is developed by the Berkeley Vision and Learning
Center (BVLC) and by community contributors.
'';
homepage = "http://caffe.berkeleyvision.org/";
maintainers = with maintainers; [ ];
broken = (pythonSupport && (python.isPy310)) || cudaSupport;
license = licenses.bsd2;
platforms = platforms.linux ++ platforms.darwin;
};
}
|