{ buildPythonPackage, cudaSupport ? false, cudatoolkit ? null, cudnn ? null, fetchFromGitHub, fetchpatch, lib, numpy, pyyaml, cffi, cmake, git, stdenv, linkFarm, symlinkJoin, utillinux, which }: assert cudnn == null || cudatoolkit != null; assert !cudaSupport || cudatoolkit != null; let cudatoolkit_joined = symlinkJoin { name = "${cudatoolkit.name}-unsplit"; paths = [ cudatoolkit.out cudatoolkit.lib ]; }; # Normally libcuda.so.1 is provided at runtime by nvidia-x11 via # LD_LIBRARY_PATH=/run/opengl-driver/lib. We only use the stub # libcuda.so from cudatoolkit for running tests, so that we don’t have # to recompile pytorch on every update to nvidia-x11 or the kernel. cudaStub = linkFarm "cuda-stub" [{ name = "libcuda.so.1"; path = "${cudatoolkit}/lib/stubs/libcuda.so"; }]; cudaStubEnv = lib.optionalString cudaSupport "LD_LIBRARY_PATH=${cudaStub}\${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH} "; in buildPythonPackage rec { version = "0.3.1"; pname = "pytorch"; name = "${pname}-${version}"; src = fetchFromGitHub { owner = "pytorch"; repo = "pytorch"; rev = "v${version}"; fetchSubmodules = true; sha256 = "1k8fr97v5pf7rni5cr2pi21ixc3pdj3h3lkz28njbjbgkndh7mr3"; }; patches = [ (fetchpatch { # make sure stdatomic.h is included when checking for ATOMIC_INT_LOCK_FREE # Fixes this test failure: # RuntimeError: refcounted file mapping not supported on your system at /tmp/nix-build-python3.6-pytorch-0.3.0.drv-0/source/torch/lib/TH/THAllocator.c:525 url = "https://github.com/pytorch/pytorch/commit/502aaf39cf4a878f9e4f849e5f409573aa598aa9.patch"; stripLen = 3; extraPrefix = "torch/lib/"; sha256 = "1miz4lhy3razjwcmhxqa4xmlcmhm65lqyin1czqczj8g16d3f62f"; }) ]; postPatch = '' substituteInPlace test/run_test.sh --replace \ "INIT_METHOD='file://'\$TEMP_DIR'/shared_init_file' \$PYCMD ./test_distributed.py" \ "echo Skipped for Nix package" ''; preConfigure = lib.optionalString cudaSupport '' export CC=${cudatoolkit.cc}/bin/gcc '' + lib.optionalString (cudaSupport && cudnn != null) '' export CUDNN_INCLUDE_DIR=${cudnn}/include ''; buildInputs = [ cmake git numpy.blas utillinux which ] ++ lib.optionals cudaSupport [cudatoolkit_joined cudnn]; propagatedBuildInputs = [ cffi numpy pyyaml ]; checkPhase = '' ${cudaStubEnv}${stdenv.shell} test/run_test.sh ''; meta = { description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration."; homepage = http://pytorch.org/; license = lib.licenses.bsd3; platforms = lib.platforms.linux; maintainers = with lib.maintainers; [ teh ]; }; }