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{ lib
, stdenv
, addOpenGLRunpath
, autoPatchelfHook
, buildPythonPackage
, cudaPackages
, fetchurl
, pythonAtLeast
, pythonOlder
, pillow
, python
, torch-bin
}:
let
pyVerNoDot = builtins.replaceStrings [ "." ] [ "" ] python.pythonVersion;
srcs = import ./binary-hashes.nix version;
unsupported = throw "Unsupported system";
version = "0.18.0";
in buildPythonPackage {
inherit version;
pname = "torchvision";
format = "wheel";
src = fetchurl srcs."${stdenv.system}-${pyVerNoDot}" or unsupported;
disabled = (pythonOlder "3.8") || (pythonAtLeast "3.13");
# Note that we don't rely on config.cudaSupport here, because the Linux wheels all come built with CUDA support.
buildInputs = with cudaPackages; lib.optionals stdenv.isLinux [
# $out/${sitePackages}/torchvision/_C.so wants libcudart.so.11.0 but torchvision.libs only ships
# libcudart.$hash.so.11.0
cuda_cudart
];
nativeBuildInputs = lib.optionals stdenv.isLinux [
autoPatchelfHook
addOpenGLRunpath
];
propagatedBuildInputs = [
pillow
torch-bin
];
# The wheel-binary is not stripped to avoid the error of `ImportError: libtorch_cuda_cpp.so: ELF load command address/offset not properly aligned.`.
dontStrip = true;
pythonImportsCheck = [ "torchvision" ];
preInstall = lib.optionalString stdenv.isLinux ''
addAutoPatchelfSearchPath "${torch-bin}/${python.sitePackages}/torch"
'';
meta = with lib; {
description = "PyTorch vision library";
homepage = "https://pytorch.org/";
changelog = "https://github.com/pytorch/vision/releases/tag/v${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;
sourceProvenance = with sourceTypes; [ binaryNativeCode ];
platforms = [ "aarch64-darwin" "x86_64-linux" "aarch64-linux" ];
maintainers = with maintainers; [ junjihashimoto ];
};
}
|
