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
|
{ lib
, stdenv
, buildPythonPackage
, fetchurl
, isPy37
, isPy38
, isPy39
, patchelf
, pillow
, python
, pytorch-bin
}:
let
pyVerNoDot = builtins.replaceStrings [ "." ] [ "" ] python.pythonVersion;
srcs = import ./binary-hashes.nix version;
unsupported = throw "Unsupported system";
version = "0.11.1";
in buildPythonPackage {
inherit version;
pname = "torchvision";
format = "wheel";
src = fetchurl srcs."${stdenv.system}-${pyVerNoDot}" or unsupported;
disabled = !(isPy37 || isPy38 || isPy39);
nativeBuildInputs = [
patchelf
];
propagatedBuildInputs = [
pillow
pytorch-bin
];
# The wheel-binary is not stripped to avoid the error of `ImportError: libtorch_cuda_cpp.so: ELF load command address/offset not properly aligned.`.
dontStrip = true;
pythonImportsCheck = [ "torchvision" ];
postFixup = let
rpath = lib.makeLibraryPath [ stdenv.cc.cc.lib ];
in ''
# Note: after patchelf'ing, libcudart can still not be found. However, this should
# not be an issue, because PyTorch is loaded before torchvision and brings
# in the necessary symbols.
patchelf --set-rpath "${rpath}:${pytorch-bin}/${python.sitePackages}/torch/lib:" \
"$out/${python.sitePackages}/torchvision/_C.so"
'';
meta = with lib; {
description = "PyTorch vision library";
homepage = "https://pytorch.org/";
changelog = "https://github.com/pytorch/vision/releases/tag/v${version}";
# 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;
platforms = platforms.linux;
maintainers = with maintainers; [ junjihashimoto ];
};
}
|