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python3Packages.torch: fetch upstream patch to allow gcc 14 with cuda 12.9 (#504339)

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This commit is contained in:
Gaétan Lepage
2026-03-29 16:37:02 +00:00
committed by GitHub
parent 40e43b4959 17be5665a5
commit da59361772
4 changed files with 78 additions and 48 deletions
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pkgs/development/python-modules/torch/source/default.nix
+16 -1
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@@ -3,6 +3,7 @@
lib,
fetchFromGitHub,
fetchFromGitLab,
fetchpatch,
git-unroll,
buildPythonPackage,
python,
@@ -304,6 +305,18 @@ buildPythonPackage.override { inherit stdenv; } (finalAttrs: {
patches = [
./clang19-template-warning.patch
# The GCC version upperbounds were wrong for cuda 12.8 and 12.9, which led downstream builds to
# illegitimately fail with:
# RuntimeError: The current installed version of g++ (14.3.0) is greater than the maximum
# required version by CUDA 12.9. Please make sure to use an adequate version of g++
# (>=6.0.0, <14.0).
# TODO: remove at the next release
(fetchpatch {
name = "allow-gcc-14-with-cuda-12.8-9";
url = "https://github.com/pytorch/pytorch/commit/39565a7dcf8f93ea22cedeaa20088b24ff6d2634.patch";
hash = "sha256-Au5fVbs7i33d9c4Xj8koiBP7lGnsTGTaX4VlE2gAfy8=";
})
]
++ lib.optionals cudaSupport [
./fix-cmake-cuda-toolkit.patch
@@ -741,7 +754,9 @@ buildPythonPackage.override { inherit stdenv; } (finalAttrs: {
blasProvider = blas.provider;
# To help debug when a package is broken due to CUDA support
inherit brokenConditions;
tests = callPackage ../tests { };
tests = callPackage ../tests {
inherit rocmSupport cudaSupport;
};
};
meta = {
pkgs/development/python-modules/torch/tests/default.nix
+48 -23
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@@ -1,33 +1,58 @@
{ callPackage }:
{
lib,
stdenv,
callPackage,
torchvision,
torchcodec,
torchaudio,
rec {
# To perform the runtime check use either
# `nix run .#python3Packages.torch.tests.tester-cudaAvailable` (outside the sandbox), or
# `nix build .#python3Packages.torch.tests.tester-cudaAvailable.gpuCheck` (in a relaxed sandbox)
tester-cudaAvailable = callPackage ./mk-runtime-check.nix {
feature = "cuda";
versionAttr = "cuda";
libraries = ps: [ ps.torchWithCuda ];
};
tester-rocmAvailable = callPackage ./mk-runtime-check.nix {
feature = "rocm";
versionAttr = "hip";
libraries = ps: [ ps.torchWithRocm ];
rocmSupport,
cudaSupport,
}:
let
cudaOnly = {
# To perform the runtime check use either
# `nix run .#python3Packages.torch.tests.tester-cudaAvailable` (outside the sandbox), or
# `nix build .#python3Packages.torch.tests.tester-cudaAvailable.gpuCheck` (in a relaxed sandbox)
tester-cudaAvailable = callPackage ./mk-runtime-check.nix {
feature = "cuda";
versionAttr = "cuda";
libraries = ps: [ ps.torchWithCuda ];
};
tester-compileCuda = callPackage ./mk-torch-compile-check.nix {
feature = "cuda";
libraries = ps: [ ps.torchWithCuda ];
};
};
compileCpu = tester-compileCpu.gpuCheck;
rocmOnly = {
tester-rocmAvailable = callPackage ./mk-runtime-check.nix {
feature = "rocm";
versionAttr = "hip";
libraries = ps: [ ps.torchWithRocm ];
};
tester-compileRocm = callPackage ./mk-torch-compile-check.nix {
feature = "rocm";
libraries = ps: [ ps.torchWithRocm ];
};
};
in
let
tester-compileCpu = callPackage ./mk-torch-compile-check.nix {
feature = null;
libraries = ps: [ ps.torch ];
};
tester-compileCuda = callPackage ./mk-torch-compile-check.nix {
feature = "cuda";
libraries = ps: [ ps.torchWithCuda ];
};
tester-compileRocm = callPackage ./mk-torch-compile-check.nix {
feature = "rocm";
libraries = ps: [ ps.torchWithRocm ];
};
in
{
inherit tester-compileCpu;
compileCpu = tester-compileCpu.gpuCheck;
mnist-example = callPackage ./mnist-example { };
# Core packages from the torch ecosystem
inherit torchvision torchaudio torchcodec;
}
// lib.optionalAttrs cudaSupport cudaOnly
// lib.optionalAttrs rocmSupport rocmOnly
pkgs/development/python-modules/torchaudio/default.nix
+14 -12
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@@ -1,5 +1,6 @@
{
lib,
stdenv,
buildPythonPackage,
fetchFromGitHub,
@@ -53,18 +54,6 @@ buildPythonPackage.override { inherit (torch) stdenv; } (finalAttrs: {
TORCHAUDIO_TEST_ALLOW_SKIP_IF_NO_CUDA = 1;
TORCHAUDIO_TEST_ALLOW_SKIP_IF_NO_MULTIGPU_CUDA = 1;
# At of 2026-03-27, the default `cudaPackages` version is 12.9.1
# According to Nvidia, it should support GCC versions up to 14.x:
# -> https://docs.nvidia.com/cuda/archive/12.9.1/cuda-installation-guide-linux/index.html#host-compiler-support-policy
# However, PyTorch's *strict* upper bound is 14.0:
# -> https://github.com/pytorch/pytorch/blob/v2.11.0/torch/utils/cpp_extension.py#L75
# Hence, the build fails with:
# RuntimeError: The current installed version of g++ (14.3.0) is greater than the maximum
# required version by CUDA 12.9. Please make sure to use an adequate version of g++
# (>=6.0.0, <14.0).
# Hence, we disable the version check to silence the error:
TORCH_DONT_CHECK_COMPILER_ABI = cudaSupport;
# ROCM
USE_ROCM = rocmSupport;
PYTORCH_ROCM_ARCH = lib.optionalString rocmSupport torch.gpuTargetString;
@@ -80,6 +69,11 @@ buildPythonPackage.override { inherit (torch) stdenv; } (finalAttrs: {
# RuntimeError: Test is known to fail for Python 3.10, disabling for now
# See: https://github.com/pytorch/audio/pull/2224#issuecomment-1048329450
TORCHAUDIO_TEST_ALLOW_SKIP_IF_ON_PYTHON_310 = true;
# Fails on aarch64-linux with:
# RuntimeError: `fbgemm` is not available
TORCHAUDIO_TEST_ALLOW_SKIP_IF_NO_QUANTIZATION =
stdenv.hostPlatform.isLinux && stdenv.hostPlatform.isAarch64;
};
build-system = [
@@ -128,9 +122,17 @@ buildPythonPackage.override { inherit (torch) stdenv; } (finalAttrs: {
# Very long to run
"AutogradCPUTest"
]
++ lib.optionals (stdenv.hostPlatform.isLinux && stdenv.hostPlatform.isAarch64) [
# AssertionError: Tensor-likes are not close!
"test_batch_inverse_spectrogram"
"test_batch_pitch_shift"
"test_batch_spectrogram"
"test_griffinlim_0_99"
];
passthru.gpuCheck = torchaudio.overridePythonAttrs (old: {
pname = "${finalAttrs.pname}-gpuCheck";
requiredSystemFeatures = [ "cuda" ];
env = (old.env or { }) // {
pkgs/development/python-modules/torchvision/default.nix
-12
View File
@@ -63,18 +63,6 @@ buildPythonPackage.override { inherit (torch) stdenv; } (finalAttrs: {
TORCHVISION_LIBRARY = "${libjpeg_turbo}/lib/";
}
// lib.optionalAttrs cudaSupport {
# At of 2026-03-27, the default `cudaPackages` version is 12.9.1
# According to Nvidia, it should support GCC versions up to 14.x:
# -> https://docs.nvidia.com/cuda/archive/12.9.1/cuda-installation-guide-linux/index.html#host-compiler-support-policy
# However, PyTorch's *strict* upper bound is 14.0:
# -> https://github.com/pytorch/pytorch/blob/v2.11.0/torch/utils/cpp_extension.py#L75
# Hence, the build fails with:
# RuntimeError: The current installed version of g++ (14.3.0) is greater than the maximum
# required version by CUDA 12.9. Please make sure to use an adequate version of g++
# (>=6.0.0, <14.0).
# Hence, we disable the version check to silence the error:
TORCH_DONT_CHECK_COMPILER_ABI = 1;
TORCH_CUDA_ARCH_LIST = "${lib.concatStringsSep ";" cudaCapabilities}";
FORCE_CUDA = 1;
};