blob: b00de428c8d463b8d58eb399b55c550530a0467d (
plain) (
blame)
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
|
{ callPackage
, stdenv
, fetchzip
, lib
, libcxx
, addOpenGLRunpath
, patchelf
, fixDarwinDylibNames
, cudaSupport
}:
let
# The binary libtorch distribution statically links the CUDA
# toolkit. This means that we do not need to provide CUDA to
# this derivation. However, we should ensure on version bumps
# that the CUDA toolkit for `passthru.tests` is still
# up-to-date.
version = "1.10.0";
device = if cudaSupport then "cuda" else "cpu";
srcs = import ./binary-hashes.nix version;
unavailable = throw "libtorch is not available for this platform";
libcxx-for-libtorch = if stdenv.hostPlatform.system == "x86_64-darwin" then libcxx else stdenv.cc.cc.lib;
in stdenv.mkDerivation {
inherit version;
pname = "libtorch";
src = fetchzip srcs."${stdenv.targetPlatform.system}-${device}" or unavailable;
nativeBuildInputs =
if stdenv.isDarwin then [ fixDarwinDylibNames ]
else [ patchelf ] ++ lib.optionals cudaSupport [ addOpenGLRunpath ];
dontBuild = true;
dontConfigure = true;
dontStrip = true;
installPhase = ''
# Copy headers and CMake files.
mkdir -p $dev
cp -r include $dev
cp -r share $dev
install -Dm755 -t $out/lib lib/*${stdenv.hostPlatform.extensions.sharedLibrary}*
# We do not care about Java support...
rm -f $out/lib/lib*jni* 2> /dev/null || true
# Fix up library paths for split outputs
substituteInPlace $dev/share/cmake/Torch/TorchConfig.cmake \
--replace \''${TORCH_INSTALL_PREFIX}/lib "$out/lib" \
substituteInPlace \
$dev/share/cmake/Caffe2/Caffe2Targets-release.cmake \
--replace \''${_IMPORT_PREFIX}/lib "$out/lib" \
'';
postFixup = let
rpath = lib.makeLibraryPath [ stdenv.cc.cc.lib ];
in lib.optionalString stdenv.isLinux ''
find $out/lib -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
echo "setting rpath for $lib..."
patchelf --set-rpath "${rpath}:$out/lib" "$lib"
${lib.optionalString cudaSupport ''
addOpenGLRunpath "$lib"
''}
done
'' + lib.optionalString stdenv.isDarwin ''
for f in $out/lib/*.dylib; do
otool -L $f
done
for f in $out/lib/*.dylib; do
install_name_tool -id $out/lib/$(basename $f) $f || true
for rpath in $(otool -L $f | grep rpath | awk '{print $1}');do
install_name_tool -change $rpath $out/lib/$(basename $rpath) $f
done
if otool -L $f | grep /usr/lib/libc++ >& /dev/null; then
install_name_tool -change /usr/lib/libc++.1.dylib ${libcxx-for-libtorch.outPath}/lib/libc++.1.0.dylib $f
fi
done
for f in $out/lib/*.dylib; do
otool -L $f
done
'';
outputs = [ "out" "dev" ];
passthru.tests.cmake = callPackage ./test {
inherit cudaSupport;
};
meta = with lib; {
description = "C++ API of the PyTorch machine learning framework";
homepage = "https://pytorch.org/";
# Includes CUDA and Intel MKL, but redistributions of the binary are not limited.
# https://docs.nvidia.com/cuda/eula/index.html
# https://www.intel.com/content/www/us/en/developer/articles/license/onemkl-license-faq.html
license = licenses.bsd3;
maintainers = with maintainers; [ junjihashimoto ];
platforms = platforms.unix;
};
}
|