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Author SHA1 Message Date
5ffea8b44e add ABI stable method for updating constant buffer 2025-10-01 15:00:36 -07:00
2785 changed files with 36319 additions and 86897 deletions

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@ -8,8 +8,6 @@ if [[ "$GPU_ARCH_VERSION" == *"12.6"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0"
elif [[ "$GPU_ARCH_VERSION" == *"12.8"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;12.0"
elif [[ "$GPU_ARCH_VERSION" == *"12.9"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;12.0"
elif [[ "$GPU_ARCH_VERSION" == *"13.0"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;11.0;12.0+PTX"
fi

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@ -37,9 +37,9 @@ case ${DOCKER_TAG_PREFIX} in
rocm*)
BASE_TARGET=rocm
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
# add gfx950, gfx115x conditionally starting in ROCm 7.0
# add gfx950 conditionally starting in ROCm 7.0
if [[ "$ROCM_VERSION" == *"7.0"* ]]; then
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950"
fi
EXTRA_BUILD_ARGS="${EXTRA_BUILD_ARGS} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}"
;;

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@ -113,7 +113,6 @@ case "$tag" in
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
TRITON=yes
INSTALL_MINGW=yes
;;
pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11)
CUDA_VERSION=13.0.0
@ -182,7 +181,7 @@ case "$tag" in
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
PYTORCH_ROCM_ARCH="gfx90a;gfx942;gfx950;gfx1100"
PYTORCH_ROCM_ARCH="gfx90a;gfx942;gfx950"
if [[ $tag =~ "benchmarks" ]]; then
INDUCTOR_BENCHMARKS=yes
fi
@ -345,7 +344,7 @@ docker build \
--build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
--build-arg "KATEX=${KATEX:-}" \
--build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
--build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}" \
--build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx90a;gfx942}" \
--build-arg "IMAGE_NAME=${IMAGE_NAME}" \
--build-arg "UCX_COMMIT=${UCX_COMMIT}" \
--build-arg "UCC_COMMIT=${UCC_COMMIT}" \
@ -362,7 +361,6 @@ docker build \
--build-arg "OPENBLAS=${OPENBLAS:-}" \
--build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
--build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
--build-arg "INSTALL_MINGW=${INSTALL_MINGW:-}" \
-f $(dirname ${DOCKERFILE})/Dockerfile \
-t "$tmp_tag" \
"$@" \

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@ -1 +1 @@
deb42f2a8e48f5032b4a98ee781a15fa87a157cf
e0dda9059d082537cee36be6c5e4fe3b18c880c0

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@ -1 +1 @@
v2.27.7-1
v2.27.5-1

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@ -1 +1 @@
7416ffcb92cdbe98d9f97e4e6f95247e46dfc9fd
27664085f804afc83df26f740bb46c365854f2c4

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@ -83,6 +83,10 @@ function build_cpython {
py_suffix=${py_ver::-1}
py_folder=$py_suffix
fi
# Update to rc2 due to https://github.com/python/cpython/commit/c72699086fe4
if [ "$py_suffix" == "3.14.0" ]; then
py_suffix="3.14.0rc2"
fi
wget -q $PYTHON_DOWNLOAD_URL/$py_folder/Python-$py_suffix.tgz -O Python-$py_ver.tgz
do_cpython_build $py_ver Python-$py_suffix

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@ -10,7 +10,7 @@ else
arch_path='sbsa'
fi
NVSHMEM_VERSION=3.4.5
NVSHMEM_VERSION=3.3.24
function install_cuda {
version=$1
@ -150,7 +150,7 @@ function install_130 {
CUDNN_VERSION=9.13.0.50
echo "Installing CUDA 13.0 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
# install CUDA 13.0 in the same container
install_cuda 13.0.2 cuda_13.0.2_580.95.05_linux
install_cuda 13.0.0 cuda_13.0.0_580.65.06_linux
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
install_cudnn 13 $CUDNN_VERSION

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@ -1,10 +0,0 @@
#!/bin/bash
set -ex
# Install MinGW-w64 for Windows cross-compilation
apt-get update
apt-get install -y g++-mingw-w64-x86-64-posix
echo "MinGW-w64 installed successfully"
x86_64-w64-mingw32-g++ --version

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@ -19,8 +19,8 @@ pip_install \
transformers==4.36.2
pip_install coloredlogs packaging
pip_install onnxruntime==1.23.1
pip_install onnxscript==0.5.4
pip_install onnxruntime==1.22.1
pip_install onnxscript==0.4.0
# Cache the transformers model to be used later by ONNX tests. We need to run the transformers
# package to download the model. By default, the model is cached at ~/.cache/huggingface/hub/

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@ -1,9 +0,0 @@
#!/bin/bash
set -xe
# Script used in Linux x86 and aarch64 CD pipeline
# Workaround for exposing statically linked libstdc++ CXX11 ABI symbols.
# see: https://github.com/pytorch/pytorch/issues/133437
LIBNONSHARED=$(gcc -print-file-name=libstdc++_nonshared.a)
nm -g $LIBNONSHARED | grep " T " | grep recursive_directory_iterator | cut -c 20- > weaken-symbols.txt
objcopy --weaken-symbols weaken-symbols.txt $LIBNONSHARED $LIBNONSHARED

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@ -39,20 +39,16 @@ case ${DOCKER_TAG_PREFIX} in
DOCKER_GPU_BUILD_ARG=""
;;
rocm*)
# we want the patch version of 7.0 instead
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
fi
# we want the patch version of 6.4 instead
if [[ "$GPU_ARCH_VERSION" == *"6.4"* ]]; then
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.4"
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
fi
BASE_TARGET=rocm
GPU_IMAGE=rocm/dev-ubuntu-22.04:${GPU_ARCH_VERSION}-complete
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
# add gfx950, gfx115x conditionally starting in ROCm 7.0
# add gfx950 conditionally starting in ROCm 7.0
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950"
fi
DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg ROCM_VERSION=${GPU_ARCH_VERSION}"
;;

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@ -130,8 +130,7 @@ ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/op
RUN for cpython_version in "cp312-cp312" "cp313-cp313" "cp313-cp313t"; do \
/opt/python/${cpython_version}/bin/python -m pip install setuptools wheel; \
done;
ADD ./common/patch_libstdc.sh patch_libstdc.sh
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
# cmake-3.18.4 from pip; force in case cmake3 already exists
RUN yum install -y python3-pip && \

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@ -78,6 +78,4 @@ RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
COPY --from=openblas /opt/OpenBLAS/ /opt/OpenBLAS/
COPY --from=arm_compute /acl /acl
ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:/acl/build/:$LD_LIBRARY_PATH
ADD ./common/patch_libstdc.sh patch_libstdc.sh
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:/acl/build/:$LD_LIBRARY_PATH

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@ -106,5 +106,3 @@ COPY --from=arm_compute /acl /acl
RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
ENV PATH=/usr/local/cuda/bin:$PATH
ENV LD_LIBRARY_PATH=/acl/build/:$LD_LIBRARY_PATH
ADD ./common/patch_libstdc.sh patch_libstdc.sh
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh

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@ -115,9 +115,6 @@ RUN env GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=True pip3 install grpcio
# cmake-3.28.0 from pip for onnxruntime
RUN python3 -mpip install cmake==3.28.0
ADD ./common/patch_libstdc.sh patch_libstdc.sh
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
# build onnxruntime 1.21.0 from sources.
# it is not possible to build it from sources using pip,
# so just build it from upstream repository.

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@ -75,22 +75,18 @@ case ${image} in
DOCKERFILE_SUFFIX="_cuda_aarch64"
;;
manylinux2_28-builder:rocm*)
# we want the patch version of 7.0 instead
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
fi
# we want the patch version of 6.4 instead
if [[ "$GPU_ARCH_VERSION" == *"6.4"* ]]; then
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.4"
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
fi
TARGET=rocm_final
MANY_LINUX_VERSION="2_28"
DEVTOOLSET_VERSION="11"
GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
# add gfx950, gfx115x conditionally starting in ROCm 7.0
# add gfx950 conditionally starting in ROCm 7.0
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950"
fi
DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
;;

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@ -10,6 +10,11 @@ BAD_SSL = "https://self-signed.badssl.com"
print("Testing SSL certificate checking for Python:", sys.version)
if sys.version_info[:2] < (2, 7) or sys.version_info[:2] < (3, 4):
print("This version never checks SSL certs; skipping tests")
sys.exit(0)
EXC = OSError
print(f"Connecting to {GOOD_SSL} should work")

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@ -120,8 +120,9 @@ ninja==1.11.1.4
numba==0.55.2 ; python_version == "3.10" and platform_machine != "s390x"
numba==0.60.0 ; python_version == "3.12" and platform_machine != "s390x"
#Description: Just-In-Time Compiler for Numerical Functions
#Pinned versions: 0.55.2, 0.60.0
#Pinned versions: 0.54.1, 0.49.0, <=0.49.1
#test that import: test_numba_integration.py
#For numba issue see https://github.com/pytorch/pytorch/issues/51511
#Need release > 0.61.2 for s390x due to https://github.com/numba/numba/pull/10073
#numpy
@ -241,9 +242,10 @@ pygments==2.15.0
#Pinned versions: 14.1.0
#test that import:
scikit-image==0.22.0
scikit-image==0.19.3 ; python_version < "3.10"
scikit-image==0.22.0 ; python_version >= "3.10"
#Description: image processing routines
#Pinned versions: 0.22.0
#Pinned versions:
#test that import: test_nn.py
#scikit-learn
@ -334,12 +336,12 @@ sympy==1.13.3
#Pinned versions:
#test that import:
onnx==1.19.1
onnx==1.18.0
#Description: Required by onnx tests, and mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
onnxscript==0.5.4
onnxscript==0.4.0
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:

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@ -100,16 +100,9 @@ COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/huggingface-requirements.txt huggingface-requirements.txt
COPY ci_commit_pins/timm.txt timm.txt
COPY ci_commit_pins/torchbench.txt torchbench.txt
# Only build aoti cpp tests when INDUCTOR_BENCHMARKS is set to True
ENV BUILD_AOT_INDUCTOR_TEST ${INDUCTOR_BENCHMARKS}
RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface-requirements.txt torchbench.txt
ARG INSTALL_MINGW
COPY ./common/install_mingw.sh install_mingw.sh
RUN if [ -n "${INSTALL_MINGW}" ]; then bash ./install_mingw.sh; fi
RUN rm install_mingw.sh
ARG TRITON
ARG TRITON_CPU

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@ -57,8 +57,8 @@ def clone_external_repo(target: str, repo: str, dst: str = "", update_submodules
logger.info("Successfully cloned %s", target)
return r, commit
except GitCommandError:
logger.exception("Git operation failed")
except GitCommandError as e:
logger.error("Git operation failed: %s", e)
raise

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@ -143,7 +143,7 @@ def sample_vllm_test_library():
"pytest -v -s compile/test_decorator.py",
],
},
"vllm_language_model_test_extended_generation_28_failure_test": {
"vllm_languagde_model_test_extended_generation_28_failure_test": {
"title": "Language Models Test (Extended Generation) 2.8 release failure",
"id": "vllm_languagde_model_test_extended_generation_28_failure_test",
"package_install": [

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@ -63,7 +63,7 @@ class VllmBuildParameters:
# DOCKERFILE_PATH: path to Dockerfile used when use_local_dockerfile is True"
use_local_dockerfile: bool = env_bool_field("USE_LOCAL_DOCKERFILE", True)
dockerfile_path: Path = env_path_field(
"DOCKERFILE_PATH", ".github/ci_configs/vllm/Dockerfile"
"DOCKERFILE_PATH", ".github/ci_configs/vllm/Dockerfile.tmp_vllm"
)
# the cleaning script to remove torch dependencies from pip

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@ -6,7 +6,7 @@ dependencies = [
"GitPython==3.1.45",
"docker==7.1.0",
"pytest==7.3.2",
"uv==0.9.5"
"uv==0.8.6"
]
[tool.setuptools]

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@ -5,7 +5,7 @@ DESIRED_ROCM ?= 7.0
DESIRED_ROCM_SHORT = $(subst .,,$(DESIRED_ROCM))
PACKAGE_NAME = magma-rocm
# inherit this from underlying docker image, do not pass this env var to docker
#PYTORCH_ROCM_ARCH ?= gfx900;gfx906;gfx908;gfx90a;gfx942;gfx950;gfx1030;gfx1100;gfx1101;gfx1102;gfx1150;gfx1151;gfx1200;gfx1201
#PYTORCH_ROCM_ARCH ?= gfx900;gfx906;gfx908;gfx90a;gfx942;gfx950;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201
DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
-v $(shell git rev-parse --show-toplevel)/.ci:/builder \
@ -18,6 +18,7 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
.PHONY: all
all: magma-rocm70
all: magma-rocm64
all: magma-rocm63
.PHONY:
clean:
@ -33,3 +34,8 @@ magma-rocm70:
magma-rocm64: DESIRED_ROCM := 6.4
magma-rocm64:
$(DOCKER_RUN)
.PHONY: magma-rocm63
magma-rocm63: DESIRED_ROCM := 6.3
magma-rocm63:
$(DOCKER_RUN)

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@ -187,22 +187,19 @@ if [[ $CUDA_VERSION == 12* || $CUDA_VERSION == 13* ]]; then
export USE_CUFILE=0
else
DEPS_LIST+=(
"/usr/local/cuda/lib64/libnvToolsExt.so.1"
"/usr/local/cuda/lib64/libcublas.so.12"
"/usr/local/cuda/lib64/libcublasLt.so.12"
"/usr/local/cuda/lib64/libcudart.so.12"
"/usr/local/cuda/lib64/libnvrtc.so.12"
"/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12")
DEPS_SONAME+=(
"libnvToolsExt.so.1"
"libcublas.so.12"
"libcublasLt.so.12"
"libcudart.so.12"
"libnvrtc.so.12"
"libcupti.so.12")
if [[ $CUDA_VERSION != 12.9* ]]; then
DEPS_LIST+=("/usr/local/cuda/lib64/libnvToolsExt.so.1")
DEPS_SONAME+=("libnvToolsExt.so.1")
fi
fi
else
echo "Using nvidia libs from pypi."

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@ -233,9 +233,7 @@ if [[ "${BUILD_ENVIRONMENT}" != *cuda* ]]; then
export BUILD_STATIC_RUNTIME_BENCHMARK=ON
fi
if [[ "$BUILD_ENVIRONMENT" == *-full-debug* ]]; then
export CMAKE_BUILD_TYPE=Debug
elif [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
export CMAKE_BUILD_TYPE=RelWithAssert
fi
@ -301,11 +299,6 @@ else
python -m build --wheel --no-isolation
fi
pip_install_whl "$(echo dist/*.whl)"
if [[ "$BUILD_ENVIRONMENT" == *full-debug* ]]; then
# Regression test for https://github.com/pytorch/pytorch/issues/164297
# Torch should be importable and that's about it
pushd /; python -c "import torch;print(torch.__config__.show(), torch.randn(5) + 1.7)"; popd
fi
if [[ "${BUILD_ADDITIONAL_PACKAGES:-}" == *vision* ]]; then
install_torchvision

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@ -256,7 +256,7 @@ test_torchbench_smoketest() {
local device=mps
local dtypes=(undefined float16 bfloat16 notset)
local dtype=${dtypes[$1]}
local models=(llama BERT_pytorch dcgan yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor vgg16)
local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor timm_resnet timm_vovnet vgg16)
for backend in eager inductor; do
@ -319,7 +319,7 @@ test_aoti_torchbench_smoketest() {
local device=mps
local dtypes=(undefined float16 bfloat16 notset)
local dtype=${dtypes[$1]}
local models=(llama BERT_pytorch dcgan yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor vgg16)
local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor timm_resnet timm_vovnet vgg16)
echo "Launching torchbench inference performance run for AOT Inductor and dtype ${dtype}"
local dtype_arg="--${dtype}"

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@ -32,9 +32,6 @@ LIBTORCH_NAMESPACE_LIST = (
"torch::",
)
# Patterns for detecting statically linked libstdc++ symbols
STATICALLY_LINKED_CXX11_ABI = [re.compile(r".*recursive_directory_iterator.*")]
def _apply_libtorch_symbols(symbols):
return [
@ -56,17 +53,12 @@ def get_symbols(lib: str) -> list[tuple[str, str, str]]:
return [x.split(" ", 2) for x in lines.decode("latin1").split("\n")[:-1]]
def grep_symbols(
lib: str, patterns: list[Any], symbol_type: str | None = None
) -> list[str]:
def grep_symbols(lib: str, patterns: list[Any]) -> list[str]:
def _grep_symbols(
symbols: list[tuple[str, str, str]], patterns: list[Any]
) -> list[str]:
rc = []
for _s_addr, _s_type, s_name in symbols:
# Filter by symbol type if specified
if symbol_type and _s_type != symbol_type:
continue
for pattern in patterns:
if pattern.match(s_name):
rc.append(s_name)
@ -88,18 +80,6 @@ def grep_symbols(
return functools.reduce(list.__add__, (x.result() for x in tasks), [])
def check_lib_statically_linked_libstdc_cxx_abi_symbols(lib: str) -> None:
cxx11_statically_linked_symbols = grep_symbols(
lib, STATICALLY_LINKED_CXX11_ABI, symbol_type="T"
)
num_statically_linked_symbols = len(cxx11_statically_linked_symbols)
print(f"num_statically_linked_symbols (T): {num_statically_linked_symbols}")
if num_statically_linked_symbols > 0:
raise RuntimeError(
f"Found statically linked libstdc++ symbols (recursive_directory_iterator): {cxx11_statically_linked_symbols[:100]}"
)
def check_lib_symbols_for_abi_correctness(lib: str) -> None:
print(f"lib: {lib}")
cxx11_symbols = grep_symbols(lib, LIBTORCH_CXX11_PATTERNS)
@ -127,7 +107,6 @@ def main() -> None:
libtorch_cpu_path = str(install_root / "lib" / "libtorch_cpu.so")
check_lib_symbols_for_abi_correctness(libtorch_cpu_path)
check_lib_statically_linked_libstdc_cxx_abi_symbols(libtorch_cpu_path)
if __name__ == "__main__":

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@ -34,14 +34,12 @@ fi
# Patch numba to avoid CUDA-13 crash, see https://github.com/pytorch/pytorch/issues/162878
if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
NUMBA_CUDA_DIR=$(python -c "import os;import numba.cuda; print(os.path.dirname(numba.cuda.__file__))" 2>/dev/null || true)
if [ -n "$NUMBA_CUDA_DIR" ]; then
NUMBA_PATCH="$(dirname "$(realpath "${BASH_SOURCE[0]}")")/numba-cuda-13.patch"
pushd "$NUMBA_CUDA_DIR"
patch -p4 <"$NUMBA_PATCH"
popd
fi
NUMBA_CUDA_DIR=$(python -c "import os;import numba.cuda; print(os.path.dirname(numba.cuda.__file__))" 2>/dev/null || true)
if [ -n "$NUMBA_CUDA_DIR" ]; then
NUMBA_PATCH="$(dirname "$(realpath "${BASH_SOURCE[0]}")")/numba-cuda-13.patch"
pushd "$NUMBA_CUDA_DIR"
patch -p4 <"$NUMBA_PATCH"
popd
fi
echo "Environment variables:"
@ -337,13 +335,13 @@ test_python() {
test_python_smoke() {
# Smoke tests for H100/B200
time python test/run_test.py --include test_matmul_cuda test_scaled_matmul_cuda inductor/test_fp8 inductor/test_max_autotune $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
time python test/run_test.py --include test_matmul_cuda inductor/test_fp8 inductor/test_max_autotune $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
assert_git_not_dirty
}
test_python_smoke_b200() {
# Targeted smoke tests for B200 - staged approach to avoid too many failures
time python test/run_test.py --include test_matmul_cuda test_scaled_matmul_cuda inductor/test_fp8 $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
time python test/run_test.py --include test_matmul_cuda inductor/test_fp8 $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
assert_git_not_dirty
}
@ -460,37 +458,31 @@ test_inductor_shard() {
--verbose
}
test_inductor_aoti_cpp() {
test_inductor_aoti() {
# docker build uses bdist_wheel which does not work with test_aot_inductor
# TODO: need a faster way to build
if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
# We need to hipify before building again
python3 tools/amd_build/build_amd.py
fi
if [[ "$BUILD_ENVIRONMENT" == *sm86* ]]; then
BUILD_COMMAND=(TORCH_CUDA_ARCH_LIST=8.6 USE_FLASH_ATTENTION=OFF python -m pip install --no-build-isolation -v -e .)
# TODO: Replace me completely, as one should not use conda libstdc++, nor need special path to TORCH_LIB
TEST_ENVS=(CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="/opt/conda/envs/py_3.10/lib:${TORCH_LIB_DIR}:${LD_LIBRARY_PATH}")
else
BUILD_COMMAND=(python -m pip install --no-build-isolation -v -e .)
TEST_ENVS=(CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}")
fi
# aoti cmake custom command requires `torch` to be installed
# initialize the cmake build cache and install torch
/usr/bin/env "${BUILD_COMMAND[@]}"
# rebuild with the build cache with `BUILD_AOT_INDUCTOR_TEST` enabled
/usr/bin/env CMAKE_FRESH=1 BUILD_AOT_INDUCTOR_TEST=1 "${BUILD_COMMAND[@]}"
/usr/bin/env "${TEST_ENVS[@]}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference cpp/test_vec_half_AVX2 -dist=loadfile
}
test_inductor_aoti_cross_compile_for_windows() {
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
# Set WINDOWS_CUDA_HOME environment variable
WINDOWS_CUDA_HOME="$(pwd)/win-torch-wheel-extracted"
export WINDOWS_CUDA_HOME
echo "WINDOWS_CUDA_HOME is set to: $WINDOWS_CUDA_HOME"
echo "Contents:"
ls -lah "$(pwd)/win-torch-wheel-extracted/lib/x64/" || true
python test/inductor/test_aoti_cross_compile_windows.py -k compile --package-dir "$TEST_REPORTS_DIR" --win-torch-lib-dir "$(pwd)/win-torch-wheel-extracted/torch/lib"
}
test_inductor_cpp_wrapper_shard() {
if [[ -z "$NUM_TEST_SHARDS" ]]; then
echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
@ -844,7 +836,7 @@ test_dynamo_benchmark() {
elif [[ "${suite}" == "timm_models" ]]; then
export TORCHBENCH_ONLY_MODELS="inception_v3"
elif [[ "${suite}" == "torchbench" ]]; then
export TORCHBENCH_ONLY_MODELS="BERT_pytorch"
export TORCHBENCH_ONLY_MODELS="hf_Bert"
fi
fi
test_single_dynamo_benchmark "dashboard" "$suite" "$shard_id" "$@"
@ -875,13 +867,13 @@ test_inductor_torchbench_smoketest_perf() {
mkdir -p "$TEST_REPORTS_DIR"
python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --float16 --training \
--batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only BERT_pytorch \
--batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only hf_Bert \
--output "$TEST_REPORTS_DIR/inductor_training_smoketest.csv"
# The threshold value needs to be actively maintained to make this check useful
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_training_smoketest.csv" -t 1.4
# Check memory compression ratio for a few models
for test in BERT_pytorch yolov3; do
for test in hf_Albert timm_vision_transformer; do
python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --amp --training \
--disable-cudagraphs --batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" \
--only $test --output "$TEST_REPORTS_DIR/inductor_training_smoketest_$test.csv"
@ -892,7 +884,7 @@ test_inductor_torchbench_smoketest_perf() {
done
# Perform some "warm-start" runs for a few huggingface models.
for test in AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
for test in AlbertForQuestionAnswering AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
python benchmarks/dynamo/huggingface.py --accuracy --training --amp --inductor --device cuda --warm-start-latency \
--only $test --output "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv"
python benchmarks/dynamo/check_accuracy.py \
@ -906,7 +898,7 @@ test_inductor_set_cpu_affinity(){
export LD_PRELOAD="$JEMALLOC_LIB":"$LD_PRELOAD"
export MALLOC_CONF="oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:-1,muzzy_decay_ms:-1"
if [[ "$(uname -m)" != "aarch64" ]]; then
if [[ "${TEST_CONFIG}" != *aarch64* ]]; then
# Use Intel OpenMP for x86
IOMP_LIB="$(dirname "$(which python)")/../lib/libiomp5.so"
export LD_PRELOAD="$IOMP_LIB":"$LD_PRELOAD"
@ -920,7 +912,7 @@ test_inductor_set_cpu_affinity(){
cores=$((cpus / thread_per_core))
# Set number of cores to 16 on aarch64 for performance runs
if [[ "$(uname -m)" == "aarch64" && $cores -gt 16 ]]; then
if [[ "${TEST_CONFIG}" == *aarch64* && $cores -gt 16 ]]; then
cores=16
fi
export OMP_NUM_THREADS=$cores
@ -1621,7 +1613,6 @@ test_operator_benchmark() {
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
TEST_DIR=$(pwd)
ARCH=$(uname -m)
test_inductor_set_cpu_affinity
@ -1636,7 +1627,7 @@ test_operator_benchmark() {
pip_install pandas
python check_perf_csv.py \
--actual "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.csv" \
--expected "${ARCH}_expected_ci_operator_benchmark_eager_float32_cpu.csv"
--expected "expected_ci_operator_benchmark_eager_float32_cpu.csv"
}
test_operator_microbenchmark() {
@ -1673,7 +1664,7 @@ if [[ "${TEST_CONFIG}" == *numpy_2* ]]; then
python -m pip install --pre numpy==2.0.2 scipy==1.13.1 numba==0.60.0
fi
python test/run_test.py --include dynamo/test_functions.py dynamo/test_unspec.py test_binary_ufuncs.py test_fake_tensor.py test_linalg.py test_numpy_interop.py test_tensor_creation_ops.py test_torch.py torch_np/test_basic.py
elif [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" == 'default' ]]; then
elif [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" != *perf_cpu_aarch64* ]]; then
test_linux_aarch64
elif [[ "${TEST_CONFIG}" == *backward* ]]; then
test_forward_backward_compatibility
@ -1724,8 +1715,6 @@ elif [[ "${TEST_CONFIG}" == *inductor-triton-cpu* ]]; then
test_inductor_triton_cpu
elif [[ "${TEST_CONFIG}" == *inductor-micro-benchmark* ]]; then
test_inductor_micro_benchmark
elif [[ "${TEST_CONFIG}" == *aoti_cross_compile_for_windows* ]]; then
test_inductor_aoti_cross_compile_for_windows
elif [[ "${TEST_CONFIG}" == *huggingface* ]]; then
install_torchvision
id=$((SHARD_NUMBER-1))
@ -1766,7 +1755,7 @@ elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper* ]]; then
install_torchvision
PYTHONPATH=/torchbench test_inductor_cpp_wrapper_shard "$SHARD_NUMBER"
if [[ "$SHARD_NUMBER" -eq "1" ]]; then
test_inductor_aoti_cpp
test_inductor_aoti
fi
elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
install_torchvision

View File

@ -15,35 +15,37 @@ if errorlevel 1 exit /b 1
if not errorlevel 0 exit /b 1
cd %TMP_DIR_WIN%\build\torch\test
:: Enable delayed variable expansion to make the list
setlocal enabledelayedexpansion
set EXE_LIST=
for /r "." %%a in (*.exe) do (
if "%%~na" == "c10_intrusive_ptr_benchmark" (
@REM NB: This is not a gtest executable file, thus couldn't be handled by
@REM pytest-cpp and is excluded from test discovery by run_test
call "%%~fa"
call :libtorch_check "%%~na" "%%~fa"
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
) else (
if "%%~na" == "verify_api_visibility" (
@REM Skip verify_api_visibility as it is a compile-level test
) else (
set EXE_LIST=!EXE_LIST! cpp/%%~na
)
)
)
goto :eof
:libtorch_check
cd %CWD%
set CPP_TESTS_DIR=%TMP_DIR_WIN%\build\torch\test
:: Run python test\run_test.py on the list
set NO_TD=True && python test\run_test.py --cpp --verbose -i !EXE_LIST!
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
:: Skip verify_api_visibility as it a compile level test
if "%~1" == "verify_api_visibility" goto :eof
goto :eof
echo Running "%~2"
if "%~1" == "c10_intrusive_ptr_benchmark" (
:: NB: This is not a gtest executable file, thus couldn't be handled by pytest-cpp
call "%~2"
goto :eof
)
python test\run_test.py --cpp --verbose -i "cpp/%~1"
if errorlevel 1 (
echo %1 failed with exit code %errorlevel%
goto fail
)
if not errorlevel 0 (
echo %1 failed with exit code %errorlevel%
goto fail
)
:eof
exit /b 0

View File

@ -38,7 +38,7 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
fi
# TODO: Move this to .ci/docker/requirements-ci.txt
python -m pip install "psutil==5.9.1" nvidia-ml-py "pytest-shard==0.1.2"
python -m pip install "psutil==5.9.1" "pynvml==11.4.1" "pytest-shard==0.1.2"
run_tests() {
# Run nvidia-smi if available

View File

@ -37,10 +37,10 @@ IF "%CUDA_PATH_V128%"=="" (
)
IF "%BUILD_VISION%" == "" (
set TORCH_CUDA_ARCH_LIST=7.0;7.5;8.0;8.6;9.0;10.0;12.0
set TORCH_CUDA_ARCH_LIST=6.1;7.0;7.5;8.0;8.6;9.0;10.0;12.0
set TORCH_NVCC_FLAGS=-Xfatbin -compress-all
) ELSE (
set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_100,code=compute_100 -gencode=arch=compute_120,code=compute_120
set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_100,code=compute_100 -gencode=arch=compute_120,code=compute_120
)
set "CUDA_PATH=%CUDA_PATH_V128%"

View File

@ -7,9 +7,12 @@ if "%DESIRED_PYTHON%" == "3.13t" (
set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.13.0/python-3.13.0-amd64.exe"
set ADDITIONAL_OPTIONS="Include_freethreaded=1"
set PYTHON_EXEC="python3.13t"
) else if "%DESIRED_PYTHON%"=="3.14" (
echo Python version is set to 3.14 or 3.14t
set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.14.0/python-3.14.0rc1-amd64.exe"
) else if "%DESIRED_PYTHON%"=="3.14t" (
echo Python version is set to 3.14 or 3.14t
set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.14.0/python-3.14.0-amd64.exe"
set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.14.0/python-3.14.0rc1-amd64.exe"
set ADDITIONAL_OPTIONS="Include_freethreaded=1"
set PYTHON_EXEC="python3.14t"
) else (

View File

@ -71,7 +71,14 @@ export PYTORCH_BUILD_NUMBER=1
# Set triton version as part of PYTORCH_EXTRA_INSTALL_REQUIREMENTS
TRITON_VERSION=$(cat $PYTORCH_ROOT/.ci/docker/triton_version.txt)
TRITON_CONSTRAINT="platform_system == 'Linux'"
# Here PYTORCH_EXTRA_INSTALL_REQUIREMENTS is already set for the all the wheel builds hence append TRITON_CONSTRAINT
TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64'"
# CUDA 12.9/13.0 builds have triton for Linux and Linux aarch64 binaries.
if [[ "$DESIRED_CUDA" == "cu129" ]] || [[ "$DESIRED_CUDA" == "cu130" ]]; then
TRITON_CONSTRAINT="platform_system == 'Linux'"
fi
if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" && ! "$PYTORCH_BUILD_VERSION" =~ .*xpu.* ]]; then
TRITON_REQUIREMENT="triton==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
@ -163,13 +170,8 @@ if [[ "$(uname)" != Darwin ]]; then
MEMORY_LIMIT_MAX_JOBS=12
NUM_CPUS=$(( $(nproc) - 2 ))
if [[ "$(uname)" == Linux ]]; then
# Defaults here for **binary** linux builds so they can be changed in one place
export MAX_JOBS=${MAX_JOBS:-$(( ${NUM_CPUS} > ${MEMORY_LIMIT_MAX_JOBS} ? ${MEMORY_LIMIT_MAX_JOBS} : ${NUM_CPUS} ))}
else
# For other builds
export MAX_JOBS=${NUM_CPUS}
fi
# Defaults here for **binary** linux builds so they can be changed in one place
export MAX_JOBS=${MAX_JOBS:-$(( ${NUM_CPUS} > ${MEMORY_LIMIT_MAX_JOBS} ? ${MEMORY_LIMIT_MAX_JOBS} : ${NUM_CPUS} ))}
cat >>"$envfile" <<EOL
export MAX_JOBS="${MAX_JOBS}"

View File

@ -59,14 +59,13 @@ performance-*,
-performance-enum-size,
readability-container-size-empty,
readability-delete-null-pointer,
readability-duplicate-include,
readability-duplicate-include
readability-misplaced-array-index,
readability-redundant*,
readability-redundant*
readability-simplify-subscript-expr,
readability-string-compare,
-readability-redundant-access-specifiers,
-readability-redundant-control-flow,
-readability-redundant-inline-specifier,
'
HeaderFilterRegex: '^(aten/|c10/|torch/).*$'
WarningsAsErrors: '*'

View File

@ -1,359 +0,0 @@
---
name: docstring
description: Write docstrings for PyTorch functions and methods following PyTorch conventions. Use when writing or updating docstrings in PyTorch code.
---
# PyTorch Docstring Writing Guide
This skill describes how to write docstrings for functions and methods in the PyTorch project, following the conventions in `torch/_tensor_docs.py` and `torch/nn/functional.py`.
## General Principles
- Use **raw strings** (`r"""..."""`) for all docstrings to avoid issues with LaTeX/math backslashes
- Follow **Sphinx/reStructuredText** (reST) format for documentation
- Be **concise but complete** - include all essential information
- Always include **examples** when possible
- Use **cross-references** to related functions/classes
## Docstring Structure
### 1. Function Signature (First Line)
Start with the function signature showing all parameters:
```python
r"""function_name(param1, param2, *, kwarg1=default1, kwarg2=default2) -> ReturnType
```
**Notes:**
- Include the function name
- Show positional and keyword-only arguments (use `*` separator)
- Include default values
- Show return type annotation
- This line should NOT end with a period
### 2. Brief Description
Provide a one-line description of what the function does:
```python
r"""conv2d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1) -> Tensor
Applies a 2D convolution over an input image composed of several input
planes.
```
### 3. Mathematical Formulas (if applicable)
Use Sphinx math directives for mathematical expressions:
```python
.. math::
\text{Softmax}(x_{i}) = \frac{\exp(x_i)}{\sum_j \exp(x_j)}
```
Or inline math: `:math:\`x^2\``
### 4. Cross-References
Link to related classes and functions using Sphinx roles:
- `:class:\`~torch.nn.ModuleName\`` - Link to a class
- `:func:\`torch.function_name\`` - Link to a function
- `:meth:\`~Tensor.method_name\`` - Link to a method
- `:attr:\`attribute_name\`` - Reference an attribute
- The `~` prefix shows only the last component (e.g., `Conv2d` instead of `torch.nn.Conv2d`)
**Example:**
```python
See :class:`~torch.nn.Conv2d` for details and output shape.
```
### 5. Notes and Warnings
Use admonitions for important information:
```python
.. note::
This function doesn't work directly with NLLLoss,
which expects the Log to be computed between the Softmax and itself.
Use log_softmax instead (it's faster and has better numerical properties).
.. warning::
:func:`new_tensor` always copies :attr:`data`. If you have a Tensor
``data`` and want to avoid a copy, use :func:`torch.Tensor.requires_grad_`
or :func:`torch.Tensor.detach`.
```
### 6. Args Section
Document all parameters with type annotations and descriptions:
```python
Args:
input (Tensor): input tensor of shape :math:`(\text{minibatch} , \text{in\_channels} , iH , iW)`
weight (Tensor): filters of shape :math:`(\text{out\_channels} , kH , kW)`
bias (Tensor, optional): optional bias tensor of shape :math:`(\text{out\_channels})`. Default: ``None``
stride (int or tuple): the stride of the convolving kernel. Can be a single number or a
tuple `(sH, sW)`. Default: 1
```
**Formatting rules:**
- Parameter name in **lowercase**
- Type in parentheses: `(Type)`, `(Type, optional)` for optional parameters
- Description follows the type
- For optional parameters, include "Default: ``value``" at the end
- Use double backticks for inline code: ``` ``None`` ```
- Indent continuation lines by 2 spaces
### 7. Keyword Args Section (if applicable)
Sometimes keyword arguments are documented separately:
```python
Keyword args:
dtype (:class:`torch.dtype`, optional): the desired type of returned tensor.
Default: if None, same :class:`torch.dtype` as this tensor.
device (:class:`torch.device`, optional): the desired device of returned tensor.
Default: if None, same :class:`torch.device` as this tensor.
requires_grad (bool, optional): If autograd should record operations on the
returned tensor. Default: ``False``.
```
### 8. Returns Section (if needed)
Document the return value:
```python
Returns:
Tensor: Sampled tensor of same shape as `logits` from the Gumbel-Softmax distribution.
If ``hard=True``, the returned samples will be one-hot, otherwise they will
be probability distributions that sum to 1 across `dim`.
```
Or simply include it in the function signature line if obvious from context.
### 9. Examples Section
Always include examples when possible:
```python
Examples::
>>> inputs = torch.randn(33, 16, 30)
>>> filters = torch.randn(20, 16, 5)
>>> F.conv1d(inputs, filters)
>>> # With square kernels and equal stride
>>> filters = torch.randn(8, 4, 3, 3)
>>> inputs = torch.randn(1, 4, 5, 5)
>>> F.conv2d(inputs, filters, padding=1)
```
**Formatting rules:**
- Use `Examples::` with double colon
- Use `>>>` prompt for Python code
- Include comments with `#` when helpful
- Show actual output when it helps understanding (indent without `>>>`)
### 10. External References
Link to papers or external documentation:
```python
.. _Link Name:
https://arxiv.org/abs/1611.00712
```
Reference them in text: ```See `Link Name`_```
## Method Types
### Native Python Functions
For regular Python functions, use a standard docstring:
```python
def relu(input: Tensor, inplace: bool = False) -> Tensor:
r"""relu(input, inplace=False) -> Tensor
Applies the rectified linear unit function element-wise. See
:class:`~torch.nn.ReLU` for more details.
"""
# implementation
```
### C-Bound Functions (using add_docstr)
For C-bound functions, use `_add_docstr`:
```python
conv1d = _add_docstr(
torch.conv1d,
r"""
conv1d(input, weight, bias=None, stride=1, padding=0, dilation=1, groups=1) -> Tensor
Applies a 1D convolution over an input signal composed of several input
planes.
See :class:`~torch.nn.Conv1d` for details and output shape.
Args:
input: input tensor of shape :math:`(\text{minibatch} , \text{in\_channels} , iW)`
weight: filters of shape :math:`(\text{out\_channels} , kW)`
...
""",
)
```
### In-Place Variants
For in-place operations (ending with `_`), reference the original:
```python
add_docstr_all(
"abs_",
r"""
abs_() -> Tensor
In-place version of :meth:`~Tensor.abs`
""",
)
```
### Alias Functions
For aliases, simply reference the original:
```python
add_docstr_all(
"absolute",
r"""
absolute() -> Tensor
Alias for :func:`abs`
""",
)
```
## Common Patterns
### Shape Documentation
Use LaTeX math notation for tensor shapes:
```python
:math:`(\text{minibatch} , \text{in\_channels} , iH , iW)`
```
### Reusable Argument Definitions
For commonly used arguments, define them once and reuse:
```python
common_args = parse_kwargs(
"""
dtype (:class:`torch.dtype`, optional): the desired type of returned tensor.
Default: if None, same as this tensor.
"""
)
# Then use with .format():
r"""
...
Keyword args:
{dtype}
{device}
""".format(**common_args)
```
### Template Insertion
Insert reproducibility notes or other common text:
```python
r"""
{tf32_note}
{cudnn_reproducibility_note}
""".format(**reproducibility_notes, **tf32_notes)
```
## Complete Example
Here's a complete example showing all elements:
```python
def gumbel_softmax(
logits: Tensor,
tau: float = 1,
hard: bool = False,
eps: float = 1e-10,
dim: int = -1,
) -> Tensor:
r"""
Sample from the Gumbel-Softmax distribution and optionally discretize.
Args:
logits (Tensor): `[..., num_features]` unnormalized log probabilities
tau (float): non-negative scalar temperature
hard (bool): if ``True``, the returned samples will be discretized as one-hot vectors,
but will be differentiated as if it is the soft sample in autograd. Default: ``False``
dim (int): A dimension along which softmax will be computed. Default: -1
Returns:
Tensor: Sampled tensor of same shape as `logits` from the Gumbel-Softmax distribution.
If ``hard=True``, the returned samples will be one-hot, otherwise they will
be probability distributions that sum to 1 across `dim`.
.. note::
This function is here for legacy reasons, may be removed from nn.Functional in the future.
Examples::
>>> logits = torch.randn(20, 32)
>>> # Sample soft categorical using reparametrization trick:
>>> F.gumbel_softmax(logits, tau=1, hard=False)
>>> # Sample hard categorical using "Straight-through" trick:
>>> F.gumbel_softmax(logits, tau=1, hard=True)
.. _Link 1:
https://arxiv.org/abs/1611.00712
"""
# implementation
```
## Quick Checklist
When writing a PyTorch docstring, ensure:
- [ ] Use raw string (`r"""`)
- [ ] Include function signature on first line
- [ ] Provide brief description
- [ ] Document all parameters in Args section with types
- [ ] Include default values for optional parameters
- [ ] Use Sphinx cross-references (`:func:`, `:class:`, `:meth:`)
- [ ] Add mathematical formulas if applicable
- [ ] Include at least one example in Examples section
- [ ] Add warnings/notes for important caveats
- [ ] Link to related module class with `:class:`
- [ ] Use proper math notation for tensor shapes
- [ ] Follow consistent formatting and indentation
## Common Sphinx Roles Reference
- `:class:\`~torch.nn.Module\`` - Class reference
- `:func:\`torch.function\`` - Function reference
- `:meth:\`~Tensor.method\`` - Method reference
- `:attr:\`attribute\`` - Attribute reference
- `:math:\`equation\`` - Inline math
- `:ref:\`label\`` - Internal reference
- ``` ``code`` ``` - Inline code (use double backticks)
## Additional Notes
- **Indentation**: Use 4 spaces for code, 2 spaces for continuation of parameter descriptions
- **Line length**: Try to keep lines under 100 characters when possible
- **Periods**: End sentences with periods, but not the signature line
- **Backticks**: Use double backticks for code: ``` ``True`` ``None`` ``False`` ```
- **Types**: Common types are `Tensor`, `int`, `float`, `bool`, `str`, `tuple`, `list`, etc.

View File

@ -1,385 +0,0 @@
---
name: skill-writer
description: Guide users through creating Agent Skills for Claude Code. Use when the user wants to create, write, author, or design a new Skill, or needs help with SKILL.md files, frontmatter, or skill structure.
---
# Skill Writer
This Skill helps you create well-structured Agent Skills for Claude Code that follow best practices and validation requirements.
## When to use this Skill
Use this Skill when:
- Creating a new Agent Skill
- Writing or updating SKILL.md files
- Designing skill structure and frontmatter
- Troubleshooting skill discovery issues
- Converting existing prompts or workflows into Skills
## Instructions
### Step 1: Determine Skill scope
First, understand what the Skill should do:
1. **Ask clarifying questions**:
- What specific capability should this Skill provide?
- When should Claude use this Skill?
- What tools or resources does it need?
- Is this for personal use or team sharing?
2. **Keep it focused**: One Skill = one capability
- Good: "PDF form filling", "Excel data analysis"
- Too broad: "Document processing", "Data tools"
### Step 2: Choose Skill location
Determine where to create the Skill:
**Personal Skills** (`~/.claude/skills/`):
- Individual workflows and preferences
- Experimental Skills
- Personal productivity tools
**Project Skills** (`.claude/skills/`):
- Team workflows and conventions
- Project-specific expertise
- Shared utilities (committed to git)
### Step 3: Create Skill structure
Create the directory and files:
```bash
# Personal
mkdir -p ~/.claude/skills/skill-name
# Project
mkdir -p .claude/skills/skill-name
```
For multi-file Skills:
```
skill-name/
├── SKILL.md (required)
├── reference.md (optional)
├── examples.md (optional)
├── scripts/
│ └── helper.py (optional)
└── templates/
└── template.txt (optional)
```
### Step 4: Write SKILL.md frontmatter
Create YAML frontmatter with required fields:
```yaml
---
name: skill-name
description: Brief description of what this does and when to use it
---
```
**Field requirements**:
- **name**:
- Lowercase letters, numbers, hyphens only
- Max 64 characters
- Must match directory name
- Good: `pdf-processor`, `git-commit-helper`
- Bad: `PDF_Processor`, `Git Commits!`
- **description**:
- Max 1024 characters
- Include BOTH what it does AND when to use it
- Use specific trigger words users would say
- Mention file types, operations, and context
**Optional frontmatter fields**:
- **allowed-tools**: Restrict tool access (comma-separated list)
```yaml
allowed-tools: Read, Grep, Glob
```
Use for:
- Read-only Skills
- Security-sensitive workflows
- Limited-scope operations
### Step 5: Write effective descriptions
The description is critical for Claude to discover your Skill.
**Formula**: `[What it does] + [When to use it] + [Key triggers]`
**Examples**:
✅ **Good**:
```yaml
description: Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.
```
✅ **Good**:
```yaml
description: Analyze Excel spreadsheets, create pivot tables, and generate charts. Use when working with Excel files, spreadsheets, or analyzing tabular data in .xlsx format.
```
❌ **Too vague**:
```yaml
description: Helps with documents
description: For data analysis
```
**Tips**:
- Include specific file extensions (.pdf, .xlsx, .json)
- Mention common user phrases ("analyze", "extract", "generate")
- List concrete operations (not generic verbs)
- Add context clues ("Use when...", "For...")
### Step 6: Structure the Skill content
Use clear Markdown sections:
```markdown
# Skill Name
Brief overview of what this Skill does.
## Quick start
Provide a simple example to get started immediately.
## Instructions
Step-by-step guidance for Claude:
1. First step with clear action
2. Second step with expected outcome
3. Handle edge cases
## Examples
Show concrete usage examples with code or commands.
## Best practices
- Key conventions to follow
- Common pitfalls to avoid
- When to use vs. not use
## Requirements
List any dependencies or prerequisites:
```bash
pip install package-name
```
## Advanced usage
For complex scenarios, see [reference.md](reference.md).
```
### Step 7: Add supporting files (optional)
Create additional files for progressive disclosure:
**reference.md**: Detailed API docs, advanced options
**examples.md**: Extended examples and use cases
**scripts/**: Helper scripts and utilities
**templates/**: File templates or boilerplate
Reference them from SKILL.md:
```markdown
For advanced usage, see [reference.md](reference.md).
Run the helper script:
\`\`\`bash
python scripts/helper.py input.txt
\`\`\`
```
### Step 8: Validate the Skill
Check these requirements:
✅ **File structure**:
- [ ] SKILL.md exists in correct location
- [ ] Directory name matches frontmatter `name`
✅ **YAML frontmatter**:
- [ ] Opening `---` on line 1
- [ ] Closing `---` before content
- [ ] Valid YAML (no tabs, correct indentation)
- [ ] `name` follows naming rules
- [ ] `description` is specific and < 1024 chars
✅ **Content quality**:
- [ ] Clear instructions for Claude
- [ ] Concrete examples provided
- [ ] Edge cases handled
- [ ] Dependencies listed (if any)
✅ **Testing**:
- [ ] Description matches user questions
- [ ] Skill activates on relevant queries
- [ ] Instructions are clear and actionable
### Step 9: Test the Skill
1. **Restart Claude Code** (if running) to load the Skill
2. **Ask relevant questions** that match the description:
```
Can you help me extract text from this PDF?
```
3. **Verify activation**: Claude should use the Skill automatically
4. **Check behavior**: Confirm Claude follows the instructions correctly
### Step 10: Debug if needed
If Claude doesn't use the Skill:
1. **Make description more specific**:
- Add trigger words
- Include file types
- Mention common user phrases
2. **Check file location**:
```bash
ls ~/.claude/skills/skill-name/SKILL.md
ls .claude/skills/skill-name/SKILL.md
```
3. **Validate YAML**:
```bash
cat SKILL.md | head -n 10
```
4. **Run debug mode**:
```bash
claude --debug
```
## Common patterns
### Read-only Skill
```yaml
---
name: code-reader
description: Read and analyze code without making changes. Use for code review, understanding codebases, or documentation.
allowed-tools: Read, Grep, Glob
---
```
### Script-based Skill
```yaml
---
name: data-processor
description: Process CSV and JSON data files with Python scripts. Use when analyzing data files or transforming datasets.
---
# Data Processor
## Instructions
1. Use the processing script:
\`\`\`bash
python scripts/process.py input.csv --output results.json
\`\`\`
2. Validate output with:
\`\`\`bash
python scripts/validate.py results.json
\`\`\`
```
### Multi-file Skill with progressive disclosure
```yaml
---
name: api-designer
description: Design REST APIs following best practices. Use when creating API endpoints, designing routes, or planning API architecture.
---
# API Designer
Quick start: See [examples.md](examples.md)
Detailed reference: See [reference.md](reference.md)
## Instructions
1. Gather requirements
2. Design endpoints (see examples.md)
3. Document with OpenAPI spec
4. Review against best practices (see reference.md)
```
## Best practices for Skill authors
1. **One Skill, one purpose**: Don't create mega-Skills
2. **Specific descriptions**: Include trigger words users will say
3. **Clear instructions**: Write for Claude, not humans
4. **Concrete examples**: Show real code, not pseudocode
5. **List dependencies**: Mention required packages in description
6. **Test with teammates**: Verify activation and clarity
7. **Version your Skills**: Document changes in content
8. **Use progressive disclosure**: Put advanced details in separate files
## Validation checklist
Before finalizing a Skill, verify:
- [ ] Name is lowercase, hyphens only, max 64 chars
- [ ] Description is specific and < 1024 chars
- [ ] Description includes "what" and "when"
- [ ] YAML frontmatter is valid
- [ ] Instructions are step-by-step
- [ ] Examples are concrete and realistic
- [ ] Dependencies are documented
- [ ] File paths use forward slashes
- [ ] Skill activates on relevant queries
- [ ] Claude follows instructions correctly
## Troubleshooting
**Skill doesn't activate**:
- Make description more specific with trigger words
- Include file types and operations in description
- Add "Use when..." clause with user phrases
**Multiple Skills conflict**:
- Make descriptions more distinct
- Use different trigger words
- Narrow the scope of each Skill
**Skill has errors**:
- Check YAML syntax (no tabs, proper indentation)
- Verify file paths (use forward slashes)
- Ensure scripts have execute permissions
- List all dependencies
## Examples
See the documentation for complete examples:
- Simple single-file Skill (commit-helper)
- Skill with tool permissions (code-reviewer)
- Multi-file Skill (pdf-processing)
## Output format
When creating a Skill, I will:
1. Ask clarifying questions about scope and requirements
2. Suggest a Skill name and location
3. Create the SKILL.md file with proper frontmatter
4. Include clear instructions and examples
5. Add supporting files if needed
6. Provide testing instructions
7. Validate against all requirements
The result will be a complete, working Skill that follows all best practices and validation rules.

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@ -7,12 +7,16 @@ max-line-length = 120
# C408 ignored because we like the dict keyword argument syntax
# E501 is not flexible enough, we're using B950 instead
ignore =
E203,E305,E402,E501,E704,E741,F405,F841,F999,W503,W504,C408,E302,W291,E303,F824,
E203,E305,E402,E501,E704,E721,E741,F405,F841,F999,W503,W504,C408,E302,W291,E303,F824,
# shebang has extra meaning in fbcode lints, so I think it's not worth trying
# to line this up with executable bit
EXE001,
# these ignores are from flake8-bugbear; please fix!
B007,B008,B017,B019,B023,B028,B903,B905,B906,B907,B908,B910
B007,B008,B017,B019,B023,B028,B903,B904,B905,B906,B907,B908,B910
# these ignores are from flake8-comprehensions; please fix!
C407,
# these ignores are from flake8-logging-format; please fix!
G100,G101,G200
# these ignores are from flake8-simplify. please fix or ignore with commented reason
SIM105,SIM108,SIM110,SIM111,SIM113,SIM114,SIM115,SIM116,SIM117,SIM118,SIM119,SIM12,
# SIM104 is already covered by pyupgrade ruff

View File

@ -8,7 +8,6 @@ assignees: ''
---
> NOTE: Remember to label this issue with "`ci: sev`"
> If you want autorevert to be disabled, keep the ci: disable-autorevert label
<!-- Add the `merge blocking` label to this PR to prevent PRs from being merged while this issue is open -->

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@ -1,7 +1,7 @@
---
name: "D❌\U0001F519 ISABLE AUTOREVERT"
name: DISABLE AUTOREVERT
about: Disables autorevert when open
title: "[DISABLE AUTOREVERT]"
title: "❌​\U0001F519 [DISABLE AUTOREVERT]"
labels: 'ci: disable-autorevert'
assignees: ''

View File

@ -65,7 +65,7 @@ runs:
cd .ci/lumen_cli
python3 -m pip install -e .
)
MAX_JOBS="$(nproc --ignore=10)"
MAX_JOBS="$(nproc --ignore=6)"
export MAX_JOBS
# Split the comma-separated list and build each target

View File

@ -274,6 +274,8 @@ runs:
-w /var/lib/jenkins/workspace \
"${DOCKER_IMAGE}"
)
# Propagate download.pytorch.org IP to container
grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts"
echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}"
docker exec -t "${container_name}" sh -c "pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}"

View File

@ -28,10 +28,6 @@ runs:
echo "instance-type: $(get_ec2_metadata instance-type)"
echo "system info $(uname -a)"
- name: Print GPU info (if present)
shell: bash
run: if [ -f /usr/bin/nvidia-smi ]; then nvidia-smi; fi
- name: Check if in a container runner
shell: bash
id: check_container_runner
@ -86,6 +82,37 @@ runs:
# Prune all of the docker images
docker system prune -af
- name: Manually resolve download.pytorch.org
shell: bash
continue-on-error: true
run: |
set +e
set -x
PT_DOMAIN=download.pytorch.org
# TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400,
# cleaning this up once the issue is fixed. There are more than one resolved IP here, the last
# one is returned at random
RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1)
if [ -z "${RESOLVED_IP}" ]; then
echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..."
RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1)
if [ -z "${RESOLVED_IP}" ]; then
echo "Couldn't resolve ${PT_DOMAIN}, exiting..."
exit 1
fi
fi
if grep -r "${PT_DOMAIN}" /etc/hosts; then
# Clean up any old records first
sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts
fi
echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts
cat /etc/hosts
- name: Check that the docker daemon is running
shell: bash
continue-on-error: true

View File

@ -111,23 +111,3 @@ runs:
# This video group ID maps to subgid 1 inside the docker image due to the /etc/subgid entries.
# The group name corresponding to group ID 1 can change depending on the OS, so both are necessary.
echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd $DEVICE_FLAG --group-add video --group-add $render_gid --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host" >> "${GITHUB_ENV}"
- name: configure aws credentials
id: aws_creds
uses: aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722 # v4.1.0
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
aws-region: us-east-1
role-duration-seconds: 18000
- name: Login to Amazon ECR
id: login-ecr
continue-on-error: true
uses: aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076 # v2.0.1
- name: Preserve github env variables for use in docker
shell: bash
run: |
env | grep '^GITHUB' >> "${RUNNER_TEMP}/github_env_${GITHUB_RUN_ID}"
env | grep '^CI' >> "${RUNNER_TEMP}/github_env_${GITHUB_RUN_ID}"
env | grep '^RUNNER' >> "${RUNNER_TEMP}/github_env_${GITHUB_RUN_ID}"

View File

@ -33,6 +33,10 @@ runs:
)
echo "CONTAINER_NAME=${container_name}" >> "$GITHUB_ENV"
if [[ "${GPU_ARCH_TYPE}" != "rocm" && "${BUILD_ENVIRONMENT}" != "linux-aarch64-binary-manywheel" && "${BUILD_ENVIRONMENT}" != "linux-s390x-binary-manywheel" && "${GPU_ARCH_TYPE}" != "xpu" ]]; then
# Propagate download.pytorch.org IP to container. This is only needed on Linux non aarch64 runner
grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" bash -c "/bin/cat >> /etc/hosts"
fi
docker exec -t -w "${PYTORCH_ROOT}" "${container_name}" bash -c "bash .circleci/scripts/binary_populate_env.sh"
# Generate test script

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@ -1 +1 @@
69bbe7363897764f9e758d851cd0340147d27f94
87ff22e49ed0e92576c4935ccb8c143daac4a3cd

View File

@ -1 +1 @@
218d2ab791d437309f91e0486eb9fa7f00badc17
966da7e46f65d6d49df3e31214470a4fe5cc8e66

View File

@ -1 +1 @@
e5192819208c4d68194844b7dfafbc00020d0dea
78a47f87ce259a48f0391fa9ae15add05ea7432b

View File

@ -1 +1 @@
df6798dfb931ce7c7fe5bed2447cd1092a5981af
0fc62aa26a30ed7ca419d285f285cb5ba02c4394

View File

@ -1,41 +1,59 @@
# TODO(elainwy): remove this file after the torch nightly dockerfile is in sync in vllm repo
# The vLLM Dockerfile is used to construct vLLM image against torch nightly and torch main that can be directly used for testing
ARG CUDA_VERSION=12.8.1
ARG PYTHON_VERSION=3.12
# BUILD_BASE_IMAGE: used to setup python build xformers, and vllm wheels, It can be replaced with a different base image from local machine,
# by default, it uses the torch-nightly-base stage from this docker image
ARG BUILD_BASE_IMAGE=torch-nightly-base
# FINAL_BASE_IMAGE: used to set up vllm-instaled environment and build flashinfer,
# by default, it uses devel-ubuntu22.04 official image.
ARG FINAL_BASE_IMAGE=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04
# The logic is copied from https://github.com/vllm-project/vllm/blob/main/docker/Dockerfile
ARG GET_PIP_URL="https://bootstrap.pypa.io/get-pip.py"
#################### TORCH NIGHTLY BASE IMAGE ####################
# A base image for building vLLM with devel ubuntu 22.04, this is mainly used to build vllm in vllm builtkite ci
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 as torch-nightly-base
ARG CUDA_VERSION
ARG PYTHON_VERSION
ARG GET_PIP_URL
# Install system dependencies and uv, then create Python virtual environment
# Install Python and other dependencies
RUN apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl sudo vim python3-pip \
&& curl -LsSf https://astral.sh/uv/install.sh | sh \
&& $HOME/.local/bin/uv venv /opt/venv --python ${PYTHON_VERSION} \
&& rm -f /usr/bin/python3 /usr/bin/python3-config /usr/bin/pip \
&& ln -s /opt/venv/bin/python3 /usr/bin/python3 \
&& ln -s /opt/venv/bin/python3-config /usr/bin/python3-config \
&& ln -s /opt/venv/bin/pip /usr/bin/pip \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim \
&& add-apt-repository -y ppa:deadsnakes/ppa \
&& apt-get update -y \
&& apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
&& update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS ${GET_PIP_URL} | python${PYTHON_VERSION} \
&& python3 --version && python3 -m pip --version
# Upgrade to GCC 10 to avoid https://gcc.gnu.org/bugzilla/show_bug.cgi?id=92519
# as it was causing spam when compiling the CUTLASS kernels
RUN apt-get install -y gcc-10 g++-10
RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 110 --slave /usr/bin/g++ g++ /usr/bin/g++-10
RUN <<EOF
gcc --version
EOF
# Ensure gcc >= 10 to avoid CUTLASS issues (bug 92519)
RUN current_gcc_version=$(gcc -dumpversion | cut -f1 -d.) && \
if command -v apt-get >/dev/null; then \
if [ "$current_gcc_version" -lt 10 ]; then \
echo "GCC version is $current_gcc_version, installing gcc-10..."; \
apt-get update \
&& apt-get install -y gcc-10 g++-10 \
&& update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 100 \
&& update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-10 100; \
else \
echo "GCC version is $current_gcc_version, no need to install gcc-10."; \
fi \
fi \
&& gcc --version && g++ --version
# Install uv for faster pip installs
# install uv for faster pip installs
RUN --mount=type=cache,target=/root/.cache/uv \
python3 -m pip install uv==0.8.4
@ -43,32 +61,36 @@ ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"
# Use copy mode to avoid hardlink failures with Docker cache mounts
ENV UV_LINK_MODE=copy
#################### TORCH NIGHTLY BASE IMAGE ####################
#################### BASE BUILD IMAGE ####################
# A base image for building vLLM with torch nightly or torch wheels
# prepare basic build environment
FROM ${BUILD_BASE_IMAGE} AS base
USER root
ARG CUDA_VERSION
ARG PYTHON_VERSION
# Only work with PyTorch manylinux builder
# TODO (huydhn): Only work with PyTorch manylinux builder
ENV PATH="/opt/python/cp312-cp312/bin:${PATH}"
# Install some system dependencies and double check python version
RUN if command -v apt-get >/dev/null; then \
apt-get update -y \
&& apt-get install -y ccache software-properties-common git wget sudo vim; \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim; \
else \
dnf install -y git wget sudo; \
dnf install -y git curl wget sudo; \
fi \
&& python3 --version && python3 -m pip --version
# Install uv for faster pip installs if not existed
RUN --mount=type=cache,target=/root/.cache/uv \
python3 -m pip install uv==0.8.4
if ! python3 -m uv --version >/dev/null 2>&1; then \
python3 -m pip install uv==0.8.4; \
fi
ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"
# Use copy mode to avoid hardlink failures with Docker cache mounts
@ -76,15 +98,15 @@ ENV UV_LINK_MODE=copy
WORKDIR /workspace
# Install build and runtime dependencies
# install build and runtime dependencies
COPY requirements/common.txt requirements/common.txt
COPY use_existing_torch.py use_existing_torch.py
COPY pyproject.toml pyproject.toml
# Install build and runtime dependencies without stable torch version
# install build and runtime dependencies without stable torch version
RUN python3 use_existing_torch.py
# Default mount file as placeholder, this just avoid the mount error
# default mount file as placeholder, this just avoid the mount error
# change to a different vllm folder if this does not exist anymore
ARG TORCH_WHEELS_PATH="./requirements"
ARG PINNED_TORCH_VERSION
@ -116,36 +138,56 @@ RUN --mount=type=cache,target=/root/.cache/uv \
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/common.txt
# Must put before installing xformers, so it can install the correct version of xfomrers.
ARG xformers_cuda_arch_list='7.5;8.0+PTX;9.0a'
ENV TORCH_CUDA_ARCH_LIST=${xformers_cuda_arch_list}
ARG max_jobs=16
ENV MAX_JOBS=${max_jobs}
RUN --mount=type=cache,target=/root/.cache/uv bash - <<'BASH'
export TORCH_CUDA_ARCH_LIST='7.5 8.0+PTX 9.0a'
git clone https://github.com/facebookresearch/xformers.git
RUN echo ${TORCH_CUDA_ARCH_LIST}
RUN echo ${MAX_JOBS}
RUN pip freeze | grep -E 'ninja'
pushd xformers
git checkout v0.0.32.post2
git submodule update --init --recursive
python3 setup.py bdist_wheel --dist-dir=../xformers-dist --verbose
popd
# Build xformers with cuda and torch nightly/wheel
# following official xformers guidance: https://github.com/facebookresearch/xformers#build
# sha for https://github.com/facebookresearch/xformers/tree/v0.0.32.post2
ARG XFORMERS_COMMIT=5d4b92a5e5a9c6c6d4878283f47d82e17995b468
ENV CCACHE_DIR=/root/.cache/ccache
rm -rf xformers
BASH
RUN --mount=type=cache,target=/root/.cache/ccache \
--mount=type=cache,target=/root/.cache/uv \
echo 'git clone xformers...' \
&& git clone https://github.com/facebookresearch/xformers.git --recursive \
&& cd xformers \
&& git checkout ${XFORMERS_COMMIT} \
&& git submodule update --init --recursive \
&& echo 'finish git clone xformers...' \
&& rm -rf build \
&& python3 setup.py bdist_wheel --dist-dir=../xformers-dist --verbose \
&& cd .. \
&& rm -rf xformers
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system xformers-dist/*.whl
uv pip install --system xformers-dist/*.whl --verbose
# Build can take a long time, and the torch nightly version fetched from url can be different in next docker stage.
# track the nightly torch version used in the build, when we set up runtime environment we can make sure the version is the same
RUN uv pip freeze | grep -i '^torch\|^torchvision\|^torchaudio' > torch_build_versions.txt
RUN cat torch_build_versions.txt
RUN pip freeze | grep -E 'torch|xformers|torchvision|torchaudio'
#################### BASE BUILD IMAGE ####################
#################### WHEEL BUILD IMAGE ####################
# Image used to build vllm wheel
FROM base AS build
ARG TARGETPLATFORM
COPY . .
RUN python3 use_existing_torch.py
RUN --mount=type=cache,target=/root/.cache/uv \
@ -155,17 +197,20 @@ ARG GIT_REPO_CHECK=0
RUN --mount=type=bind,source=.git,target=.git \
if [ "$GIT_REPO_CHECK" != "0" ]; then bash tools/check_repo.sh ; fi
# Max jobs used by Ninja to build extensions
ARG max_jobs=16
ENV MAX_JOBS=${max_jobs}
ARG nvcc_threads=8
ARG nvcc_threads=4
ENV NVCC_THREADS=$nvcc_threads
ARG torch_cuda_arch_list='8.0;8.6;8.9;9.0'
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
ARG USE_SCCACHE
ARG SCCACHE_BUCKET_NAME=vllm-build-sccache
ARG SCCACHE_REGION_NAME=us-west-2
ARG SCCACHE_S3_NO_CREDENTIALS=0
# Use sccache to speed up compilation
# if USE_SCCACHE is set, use sccache to speed up compilation
RUN --mount=type=cache,target=/root/.cache/uv \
--mount=type=bind,source=.git,target=.git \
if [ "$USE_SCCACHE" = "1" ]; then \
@ -190,9 +235,6 @@ RUN --mount=type=cache,target=/root/.cache/uv \
&& sccache --show-stats; \
fi
ARG torch_cuda_arch_list='8.0 8.6 8.9 9.0'
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
ARG vllm_target_device="cuda"
ENV VLLM_TARGET_DEVICE=${vllm_target_device}
ENV CCACHE_DIR=/root/.cache/ccache
@ -206,10 +248,17 @@ RUN --mount=type=cache,target=/root/.cache/ccache \
export VLLM_DOCKER_BUILD_CONTEXT=1 && \
python3 setup.py bdist_wheel --dist-dir=vllm-dist --py-limited-api=cp38; \
fi
RUN echo "[INFO] Listing current directory:" && \
ls -al && \
echo "[INFO] Showing torch_build_versions.txt content:" && \
cat torch_build_versions.txt
#################### WHEEL BUILD IMAGE ####################
################### VLLM INSTALLED IMAGE ####################
# Setup clean environment for vLLM for test and api server using ubuntu22.04 with AOT flashinfer
FROM ${FINAL_BASE_IMAGE} AS vllm-base
USER root
@ -217,7 +266,7 @@ ARG CUDA_VERSION
ARG PYTHON_VERSION
ARG GET_PIP_URL
# Only work with PyTorch manylinux builder
# TODO (huydhn): Only work with PyTorch manylinux builder
ENV PATH="/opt/python/cp312-cp312/bin:${PATH}"
# prepare for environment starts
@ -226,19 +275,20 @@ WORKDIR /workspace
# Install Python and other dependencies
RUN if command -v apt-get >/dev/null; then \
apt-get update -y \
&& apt-get install -y ccache software-properties-common git sudo vim python3-pip; \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim \
&& add-apt-repository -y ppa:deadsnakes/ppa \
&& apt-get update -y \
&& apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
&& update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS ${GET_PIP_URL} | python${PYTHON_VERSION}; \
else \
dnf install -y git wget sudo; \
dnf install -y git curl wget sudo; \
fi \
&& curl -LsSf https://astral.sh/uv/install.sh | sh \
&& $HOME/.local/bin/uv venv /opt/venv --python ${PYTHON_VERSION} \
&& rm -f /usr/bin/python3 /usr/bin/python3-config /usr/bin/pip \
&& ln -s /opt/venv/bin/python3 /usr/bin/python3 \
&& ln -s /opt/venv/bin/python3-config /usr/bin/python3-config \
&& ln -s /opt/venv/bin/pip /usr/bin/pip \
&& python3 --version && python3 -m pip --version
# Get the torch versions, and whls used in previous stage
# Get the torch versions, and whls used in previous stagtes for consistency
COPY --from=base /workspace/torch_build_versions.txt ./torch_build_versions.txt
COPY --from=base /workspace/xformers-dist /wheels/xformers
COPY --from=build /workspace/vllm-dist /wheels/vllm
@ -249,27 +299,19 @@ RUN echo "[INFO] Listing current directory before torch install step:" && \
# Install uv for faster pip installs if not existed
RUN --mount=type=cache,target=/root/.cache/uv \
python3 -m pip install uv==0.8.4
if ! python3 -m uv --version > /dev/null 2>&1; then \
python3 -m pip install uv==0.8.4; \
fi
ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"
# Use copy mode to avoid hardlink failures with Docker cache mounts
ENV UV_LINK_MODE=copy
# Install build and runtime dependencies, this is needed for flashinfer install
COPY requirements/build.txt requirements/build.txt
COPY use_existing_torch.py use_existing_torch.py
RUN python3 use_existing_torch.py
RUN cat requirements/build.txt
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/build.txt
# Default mount file as placeholder, this just avoid the mount error
ARG TORCH_WHEELS_PATH="./requirements"
# Install torch, torchaudio and torchvision. If TORCH_WHEELS_PATH is default
# to ./requirements, it will pull the nightly versions using pip. Otherwise,
# it will use the local wheels from TORCH_WHEELS_PATH
# Install torch, torchaudio and torchvision
# if TORCH_WHEELS_PATH is default "./requirements", it will pull the nightly versions using pip using torch_build_versions.txt
# otherwise, it will use the whls from TORCH_WHEELS_PATH from the host machine
RUN --mount=type=bind,source=${TORCH_WHEELS_PATH},target=/dist \
--mount=type=cache,target=/root/.cache/uv \
if [ -n "$TORCH_WHEELS_PATH" ] && [ "$TORCH_WHEELS_PATH" != "./requirements" ] && [ -d "/dist" ] && ls /dist/torch*.whl >/dev/null 2>&1; then \
@ -283,9 +325,6 @@ RUN --mount=type=bind,source=${TORCH_WHEELS_PATH},target=/dist \
uv pip install --system $(cat torch_build_versions.txt | xargs) --index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.'); \
fi
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system --pre apache-tvm-ffi==0.1.0b15
# Install the vllm wheel from previous stage
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system /wheels/vllm/*.whl --verbose
@ -294,15 +333,19 @@ RUN --mount=type=cache,target=/root/.cache/uv \
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system /wheels/xformers/*.whl --verbose
# Build FlashInfer from source
# Build flashinfer from source.
ARG torch_cuda_arch_list='8.0;8.9;9.0a;10.0a;12.0'
# install package for build flashinfer
# see issue: https://github.com/flashinfer-ai/flashinfer/issues/738
RUN pip install build==1.3.0
RUN pip freeze | grep -E 'setuptools|packaging|build'
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
# TODO(elainewy): remove this once vllm commit is updated, and install flashinfer from pip
# see https://github.com/pytorch/pytorch/pull/165274#issuecomment-3408531784
# Build flashinfer for torch nightly from source around 10 mins
ARG FLASHINFER_GIT_REPO="https://github.com/flashinfer-ai/flashinfer.git"
# Keep this in sync with https://github.com/vllm-project/vllm/blob/main/requirements/cuda.txt
ARG FLASHINFER_GIT_REF="v0.2.14.post1"
RUN --mount=type=cache,target=/root/.cache/uv \
git clone --depth 1 --recursive --shallow-submodules \
--branch ${FLASHINFER_GIT_REF} \
@ -314,7 +357,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
&& cd .. \
&& rm -rf flashinfer
# Install FlashInfer
# install flashinfer python
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system wheels/flashinfer/*.whl --verbose
@ -324,6 +367,49 @@ RUN uv pip freeze | grep -i '^torch\|^torchvision\|^torchaudio\|^xformers\|^vllm
################### VLLM INSTALLED IMAGE ####################
#################### UNITTEST IMAGE #############################
FROM vllm-base as test
ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"
# Use copy mode to avoid hardlink failures with Docker cache mounts
ENV UV_LINK_MODE=copy
COPY tests/ tests/
COPY examples examples
COPY benchmarks benchmarks
COPY ./vllm/collect_env.py .
COPY requirements/common.txt requirements/common.txt
COPY use_existing_torch.py use_existing_torch.py
COPY pyproject.toml pyproject.toml
# Install build and runtime dependencies without stable torch version
COPY requirements/nightly_torch_test.txt requirements/nightly_torch_test.txt
RUN python3 use_existing_torch.py
# install packages
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/common.txt
# enable fast downloads from hf (for testing)
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system hf_transfer
ENV HF_HUB_ENABLE_HF_TRANSFER 1
# install development dependencies (for testing)
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -e tests/vllm_test_utils
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/nightly_torch_test.txt
# Logging to confirm the torch versions
RUN pip freeze | grep -E 'torch|xformers|vllm|flashinfer'
# Logging to confirm all the packages are installed
RUN pip freeze
#################### UNITTEST IMAGE #############################
#################### EXPORT STAGE ####################
FROM scratch as export-wheels

View File

@ -1,14 +1,9 @@
import glob
import os
requires_files = glob.glob("requirements/*.txt")
requires_files += ["pyproject.toml"]
for file in requires_files:
if not os.path.exists(file):
print(f"!!! skipping missing {file}")
continue
print(f">>> cleaning {file}")
with open(file) as f:
lines = f.readlines()

View File

@ -15,11 +15,6 @@
- "module: reinplacing"
then:
- "module: pt2-dispatcher"
- any:
- "vllm-compile"
then:
- "module: vllm"
- "oncall: pt2"
- any:
- "module: vmap"
then:
@ -32,6 +27,10 @@
- "module: pt2 optimizer"
then:
- "module: dynamo"
- any:
- "module: flex attention"
then:
- "module: higher order operators"
- any:
- "module: aotinductor"
then:

29
.github/labeler.yml vendored
View File

@ -133,32 +133,3 @@
"ciflow/vllm":
- .github/ci_commit_pins/vllm.txt
"ciflow/b200":
- test/test_matmul_cuda.py
- test/test_scaled_matmul_cuda.py
- test/inductor/test_fp8.py
- aten/src/ATen/native/cuda/Blas.cpp
- torch/**/*cublas*
- torch/_inductor/kernel/mm.py
- test/inductor/test_max_autotune.py
- third_party/fbgemm
"ciflow/h100":
- test/test_matmul_cuda.py
- test/test_scaled_matmul_cuda.py
- test/inductor/test_fp8.py
- aten/src/ATen/native/cuda/Blas.cpp
- torch/**/*cublas*
- torch/_inductor/kernel/mm.py
- test/inductor/test_max_autotune.py
- third_party/fbgemm
"ciflow/rocm":
- test/test_matmul_cuda.py
- test/test_scaled_matmul_cuda.py
- test/inductor/test_fp8.py
- aten/src/ATen/native/cuda/Blas.cpp
- torch/_inductor/kernel/mm.py
- test/inductor/test_max_autotune.py
- third_party/fbgemm

View File

@ -540,26 +540,6 @@
- Lint
- pull
- name: PrivateUse1
patterns:
- torch/accelerator/**
- torch/utils/backend_registration.py
- torch/csrc/acc/**
- torch/csrc/DeviceAccelerator.*
- torch/csrc/profiler/standalone/privateuse1_observer.*
- aten/src/ATen/DeviceAccelerator.*
- aten/src/ATen/core/GeneratorForPrivateuseone.*
- aten/src/ATen/detail/PrivateUse1HooksInterface.*
- docs/source/accelerator/**
- test/cpp_extensions/open_registration_extension/torch_openreg/**
approved_by:
- albanD
- fffrog
mandatory_checks_name:
- EasyCLA
- Lint
- pull
- name: superuser
patterns:
- '*'

View File

@ -3,7 +3,6 @@ ciflow_tracking_issue: 64124
ciflow_push_tags:
- ciflow/b200
- ciflow/b200-symm-mem
- ciflow/b200-distributed
- ciflow/binaries
- ciflow/binaries_libtorch
- ciflow/binaries_wheel
@ -16,8 +15,7 @@ ciflow_push_tags:
- ciflow/inductor-micro-benchmark
- ciflow/inductor-micro-benchmark-cpu-x86
- ciflow/inductor-perf-compare
- ciflow/inductor-perf-test-nightly-rocm-mi300
- ciflow/inductor-perf-test-nightly-rocm-mi355
- ciflow/inductor-perf-test-nightly-rocm
- ciflow/inductor-perf-test-nightly-x86-zen
- ciflow/inductor-periodic
- ciflow/inductor-rocm
@ -32,8 +30,6 @@ ciflow_push_tags:
- ciflow/riscv64
- ciflow/rocm
- ciflow/rocm-mi300
- ciflow/rocm-mi355
- ciflow/rocm-navi31
- ciflow/s390
- ciflow/slow
- ciflow/torchbench

Binary file not shown.

View File

@ -512,8 +512,6 @@ def perform_misc_tasks(
"keep-going",
branch == MAIN_BRANCH
or bool(tag and re.match(r"^trunk/[a-f0-9]{40}$", tag))
# Pattern for tags created via manual run on HUD
or bool(tag and re.match(r"^ciflow/[^/]+/[a-f0-9]{40}$", tag))
or check_for_setting(labels, pr_body, "keep-going"),
)
set_output(

View File

@ -16,18 +16,16 @@ from typing import Optional
# NOTE: Please also update the CUDA sources in `PIP_SOURCES` in tools/nightly.py when changing this
CUDA_ARCHES = ["12.6", "12.8", "12.9", "13.0"]
CUDA_ARCHES = ["12.6", "12.8", "13.0"]
CUDA_STABLE = "12.8"
CUDA_ARCHES_FULL_VERSION = {
"12.6": "12.6.3",
"12.8": "12.8.1",
"12.9": "12.9.1",
"13.0": "13.0.2",
"13.0": "13.0.0",
}
CUDA_ARCHES_CUDNN_VERSION = {
"12.6": "9",
"12.8": "9",
"12.9": "9",
"13.0": "9",
}
@ -40,7 +38,7 @@ CPU_AARCH64_ARCH = ["cpu-aarch64"]
CPU_S390X_ARCH = ["cpu-s390x"]
CUDA_AARCH64_ARCHES = ["12.6-aarch64", "12.8-aarch64", "12.9-aarch64", "13.0-aarch64"]
CUDA_AARCH64_ARCHES = ["12.6-aarch64", "12.8-aarch64", "13.0-aarch64"]
PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
@ -56,7 +54,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | "
"nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | "
"nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | "
"nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'"
@ -73,44 +71,27 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | "
"nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | "
"nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | "
"nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'"
),
"12.9": (
"nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | "
"nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | "
"nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | "
"nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | "
"nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | "
"nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | "
"nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | "
"nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | "
"nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | "
"nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | "
"nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | "
"nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'"
),
"13.0": (
"nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | "
"nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | "
"nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | "
"nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | "
"nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | "
"nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | "
"nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | "
"nvidia-cublas==13.1.0.3; platform_system == 'Linux' | "
"nvidia-cufft==12.0.0.61; platform_system == 'Linux' | "
"nvidia-cublas==13.0.0.19; platform_system == 'Linux' | "
"nvidia-cufft==12.0.0.15; platform_system == 'Linux' | "
"nvidia-curand==10.4.0.35; platform_system == 'Linux' | "
"nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | "
"nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | "
"nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | "
"nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | "
"nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | "
"nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | "
"nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | "
"nvidia-nvtx==13.0.85; platform_system == 'Linux' | "
"nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | "
"nvidia-cufile==1.15.1.6; platform_system == 'Linux'"
"nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | "
"nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | "
"nvidia-nvtx==13.0.39; platform_system == 'Linux' | "
"nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | "
"nvidia-cufile==1.15.0.42; platform_system == 'Linux'"
),
"xpu": (
"intel-cmplr-lib-rt==2025.2.1 | "
@ -241,11 +222,7 @@ def generate_libtorch_matrix(
arches += CUDA_ARCHES
arches += ROCM_ARCHES
elif os == "windows":
# TODO (huydhn): Only build CUDA 12.9 for Linux. This logic is to be cleaned up
# in 2.10
windows_cuda_arches = CUDA_ARCHES.copy()
windows_cuda_arches.remove("12.9")
arches += windows_cuda_arches
arches += CUDA_ARCHES
if libtorch_variants is None:
libtorch_variants = [
"shared-with-deps",
@ -309,11 +286,7 @@ def generate_wheels_matrix(
if os == "linux":
arches += CUDA_ARCHES + ROCM_ARCHES + XPU_ARCHES
elif os == "windows":
# TODO (huydhn): Only build CUDA 12.9 for Linux. This logic is to be cleaned up
# in 2.10
windows_cuda_arches = CUDA_ARCHES.copy()
windows_cuda_arches.remove("12.9")
arches += windows_cuda_arches + XPU_ARCHES
arches += CUDA_ARCHES + XPU_ARCHES
elif os == "linux-aarch64":
# Separate new if as the CPU type is different and
# uses different build/test scripts
@ -349,7 +322,7 @@ def generate_wheels_matrix(
# cuda linux wheels require PYTORCH_EXTRA_INSTALL_REQUIREMENTS to install
if (
arch_version in ["13.0", "12.9", "12.8", "12.6"]
arch_version in ["13.0", "12.8", "12.6"]
and os == "linux"
or arch_version in CUDA_AARCH64_ARCHES
):
@ -413,6 +386,5 @@ def generate_wheels_matrix(
validate_nccl_dep_consistency("13.0")
validate_nccl_dep_consistency("12.9")
validate_nccl_dep_consistency("12.8")
validate_nccl_dep_consistency("12.6")

View File

@ -18,7 +18,6 @@ class GitHubComment:
body_text: str
created_at: str
author_login: str
author_url: Optional[str]
author_association: str
editor_login: Optional[str]
database_id: int

Binary file not shown.

View File

@ -38,7 +38,6 @@ def mock_get_comments() -> list[GitHubComment]:
body_text="mock_body_text",
created_at="",
author_login="",
author_url=None,
author_association="",
editor_login=None,
database_id=1,
@ -49,7 +48,6 @@ def mock_get_comments() -> list[GitHubComment]:
body_text=" #" + LABEL_ERR_MSG_TITLE.replace("`", ""),
created_at="",
author_login=BOT_AUTHORS[1],
author_url=None,
author_association="",
editor_login=None,
database_id=2,

View File

@ -32,7 +32,6 @@ from trymerge import (
main as trymerge_main,
MandatoryChecksMissingError,
MergeRule,
PostCommentError,
RE_GHSTACK_DESC,
read_merge_rules,
remove_job_name_suffix,
@ -589,23 +588,6 @@ class TestTryMerge(TestCase):
self.assertEqual(mock_merge_base, pr.get_merge_base())
mocked_gh_fetch_merge_base.assert_called_once()
def test_app_can_revert(self, *args: Any) -> None:
pr = GitHubPR("pytorch", "pytorch", 164660)
repo = DummyGitRepo()
app_comment_id, impostor_comment_id = 3375785595, 3377647892
# Check that app can revert
self.assertIsNotNone(validate_revert(repo, pr, comment_id=app_comment_id))
# But impostor can not
self.assertRaises(
PostCommentError,
lambda: validate_revert(repo, pr, comment_id=impostor_comment_id),
)
# Despite it's name being the name of the bot
self.assertEqual(
pr.get_comment_by_id(impostor_comment_id).author_login,
"pytorch-auto-revert",
)
@mock.patch("trymerge.gh_graphql", side_effect=mocked_gh_graphql)
@mock.patch("trymerge.gh_fetch_merge_base", return_value="")

View File

@ -234,7 +234,6 @@ query ($owner: String!, $name: String!, $number: Int!) {
createdAt
author {
login
url
}
authorAssociation
editor {
@ -1092,9 +1091,8 @@ class GitHubPR:
editor = node["editor"]
return GitHubComment(
body_text=node["bodyText"],
created_at=node.get("createdAt", ""),
created_at=node["createdAt"] if "createdAt" in node else "",
author_login=node["author"]["login"],
author_url=node["author"].get("url", None),
author_association=node["authorAssociation"],
editor_login=editor["login"] if editor else None,
database_id=node["databaseId"],
@ -2031,17 +2029,16 @@ def validate_revert(
# For some reason, one can not be a member of private repo, only CONTRIBUTOR
if pr.is_base_repo_private():
allowed_reverters.append("CONTRIBUTOR")
# Special case the pytorch-auto-revert app, whose does not have association
# But should be able to issue revert command
if comment.author_url == "https://github.com/apps/pytorch-auto-revert":
allowed_reverters.append("NONE")
if author_association not in allowed_reverters:
raise PostCommentError(
f"Will not revert as @{author_login} is not one of "
f"[{', '.join(allowed_reverters)}], but instead is {author_association}."
)
# Raises exception if matching rule is not found, but ignores all status checks
find_matching_merge_rule(
pr, repo, skip_mandatory_checks=True, skip_internal_checks=True
)
commit_sha = get_pr_commit_sha(repo, pr)
return (author_login, commit_sha)

View File

@ -177,9 +177,6 @@ jobs:
runs-on: linux.rocm.gpu.mi250
timeout-minutes: !{{ common.timeout_minutes }}
!{{ upload.binary_env(config) }}
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm

View File

@ -26,8 +26,9 @@ name: !{{ build_environment }}
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "!{{ py_ver.strip('t') + ('.4' if '3.14' not in py_ver else '.0') }}"
python-version: "!{{ (py_ver.strip('t') + '.4') if '3.14' not in py_ver else '3.14.0-rc.2' }}"
freethreaded: !{{ "true" if py_ver.endswith('t') else "false" }}
{%- endmacro %}

View File

@ -79,9 +79,9 @@ jobs:
runs-on: "windows-11-arm64-preview"
{%- else %}
{%- if branches == "nightly" %}
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
{%- else %}
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge.nonephemeral"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral"
{%- endif %}
{%- endif %}
timeout-minutes: !{{ common.timeout_minutes_windows_binary }}

View File

@ -72,7 +72,7 @@ jobs:
# Let's try to figure out how this can be improved
timeout-minutes: 360
- docs_type: python
runner: ${{ inputs.runner_prefix }}linux.c7i.2xlarge
runner: ${{ inputs.runner_prefix }}linux.2xlarge
# It takes less than 30m to finish python docs unless there are issues
timeout-minutes: 30
# Set a fixed name for this job instead of using the current matrix-generated name, i.e. build-docs (cpp, linux.12xlarge, 180)

View File

@ -40,15 +40,6 @@ jobs:
# Use gh CLI to get changed files in the PR with explicit repo
CHANGED_FILES=$(gh api repos/${{ github.repository }}/pulls/$PR_NUMBER/files --paginate --jq '.[] | select(.status != "removed") | .filename' | tr '\n' ' ' | sed 's/ $//')
# See https://github.com/pytorch/pytorch/pull/134215#issuecomment-2332128790
PYI_FILES_TO_ADD=""
for file in ${CHANGED_FILES}; do
if [[ "${file}" == *".pyi.in" ]]; then
PYI_FILES_TO_ADD="${PYI_FILES_TO_ADD} ${file//.in/}"
fi
done
CHANGED_FILES="${CHANGED_FILES}${PYI_FILES_TO_ADD}"
if [ -z "$CHANGED_FILES" ]; then
echo "No changed files found, setting to '*'"
CHANGED_FILES="*"

View File

@ -37,7 +37,7 @@ on:
runner:
required: false
type: string
default: "linux.c7i.2xlarge"
default: "linux.2xlarge"
description: |
Label of the runner this job should run on.
test-matrix:

View File

@ -224,46 +224,6 @@ jobs:
continue-on-error: true
uses: ./.github/actions/download-td-artifacts
- name: Download Windows torch wheel for cross-compilation
if: matrix.win_torch_wheel_artifact != ''
uses: seemethere/download-artifact-s3@1da556a7aa0a088e3153970611f6c432d58e80e6 # v4.2.0
with:
name: ${{ matrix.win_torch_wheel_artifact }}
path: win-torch-wheel
- name: Extract Windows wheel and setup CUDA libraries
if: matrix.win_torch_wheel_artifact != ''
shell: bash
run: |
set -x
# Find the wheel file
WHEEL_FILE=$(find win-torch-wheel -name "*.whl" -type f | head -n 1)
if [ -z "$WHEEL_FILE" ]; then
echo "Error: No wheel file found in win-torch-wheel directory"
exit 1
fi
echo "Found wheel file: $WHEEL_FILE"
# Unzip the wheel file
unzip -q "$WHEEL_FILE" -d win-torch-wheel-extracted
echo "Extracted wheel contents"
# Setup CUDA libraries (cuda.lib and cudart.lib) directory
mkdir -p win-torch-wheel-extracted/lib/x64
if [ -f "win-torch-wheel/cuda.lib" ]; then
mv win-torch-wheel/cuda.lib win-torch-wheel-extracted/lib/x64/
echo "Moved cuda.lib to win-torch-wheel-extracted/lib/x64/"
fi
if [ -f "win-torch-wheel/cudart.lib" ]; then
mv win-torch-wheel/cudart.lib win-torch-wheel-extracted/lib/x64/
echo "Moved cudart.lib to win-torch-wheel-extracted/lib/x64/"
fi
# Verify CUDA libraries are present
echo "CUDA libraries:"
ls -la win-torch-wheel-extracted/lib/x64/ || echo "No CUDA libraries found"
- name: Parse ref
id: parse-ref
run: .github/scripts/parse_ref.py
@ -429,6 +389,8 @@ jobs:
"${DOCKER_IMAGE}" \
${DOCKER_SHELL_CMD}
)
# Propagate download.pytorch.org IP to container
grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts"
echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}"
if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then

View File

@ -102,6 +102,19 @@ jobs:
exit 1
fi
- name: configure aws credentials
id: aws_creds
uses: aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722 # v4.1.0
with:
role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
aws-region: us-east-1
role-duration-seconds: 18000
- name: Login to Amazon ECR
id: login-ecr
continue-on-error: true
uses: aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076 # v2.0.1
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main

View File

@ -168,31 +168,6 @@ jobs:
run: |
.ci/pytorch/win-build.sh
# Collect Windows torch libs and CUDA libs for cross-compilation
- name: Collect Windows CUDA libs for cross-compilation
if: steps.build.outcome != 'skipped' && inputs.cuda-version != 'cpu'
shell: bash
run: |
set -ex
# Create directory structure if does not exist
mkdir -p /c/${{ github.run_id }}/build-results
# Copy CUDA libs
CUDA_PATH="/c/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v${{ inputs.cuda-version }}"
if [ -f "${CUDA_PATH}/lib/x64/cuda.lib" ]; then
cp "${CUDA_PATH}/lib/x64/cuda.lib" /c/${{ github.run_id }}/build-results/
fi
if [ -f "${CUDA_PATH}/lib/x64/cudart.lib" ]; then
cp "${CUDA_PATH}/lib/x64/cudart.lib" /c/${{ github.run_id }}/build-results/
fi
# List collected files
echo "Collected CUDA libs:"
ls -lah /c/${{ github.run_id }}/build-results/*.lib
# Upload to github so that people can click and download artifacts
- name: Upload artifacts to s3
if: steps.build.outcome != 'skipped'

View File

@ -1,62 +0,0 @@
name: CI for distributed tests on B200
on:
pull_request:
paths:
- .github/workflows/b200-distributed.yml
workflow_dispatch:
push:
tags:
- ciflow/b200-distributed/*
schedule:
- cron: 46 8 * * * # about 1:46am PDT
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
permissions:
id-token: write
contents: read
jobs:
get-label-type:
if: github.repository_owner == 'pytorch'
name: get-label-type
uses: pytorch/pytorch/.github/workflows/_runner-determinator.yml@main
with:
triggering_actor: ${{ github.triggering_actor }}
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
linux-jammy-cuda12_8-py3_10-gcc11-build-distributed-b200:
name: linux-jammy-cuda12.8-py3.10-gcc11-build-distributed-b200
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runner: linux.12xlarge.memory
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-distributed-b200
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11
cuda-arch-list: '10.0'
test-matrix: |
{ include: [
{ config: "distributed", shard: 1, num_shards: 2, runner: "linux.dgx.b200.8" },
{ config: "distributed", shard: 2, num_shards: 2, runner: "linux.dgx.b200.8" },
]}
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc11-test-distributed-b200:
name: linux-jammy-cuda12.8-py3.10-gcc11-test-b200
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-jammy-cuda12_8-py3_10-gcc11-build-distributed-b200
with:
timeout-minutes: 1200
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-distributed-b200
docker-image: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-build-distributed-b200.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-build-distributed-b200.outputs.test-matrix }}
aws-role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
secrets: inherit

View File

@ -46,12 +46,10 @@ jobs:
fail-fast: false
matrix:
include: [
{ name: "manylinux2_28-builder", tag: "cuda13.0", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "cuda13.0", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "cuda12.8", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "cuda12.9", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "cuda12.6", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinuxaarch64-builder", tag: "cuda13.0", runner: "linux.arm64.2xlarge.ephemeral" },
{ name: "manylinuxaarch64-builder", tag: "cuda12.9", runner: "linux.arm64.2xlarge.ephemeral" },
{ name: "manylinuxaarch64-builder", tag: "cuda12.8", runner: "linux.arm64.2xlarge.ephemeral" },
{ name: "manylinuxaarch64-builder", tag: "cuda12.6", runner: "linux.arm64.2xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "rocm6.4", runner: "linux.9xlarge.ephemeral" },

View File

@ -27,8 +27,9 @@ jobs:
fail-fast: false
matrix:
python-version: [ '3.12' ]
# TODO (huydhn): Add cu130 after https://github.com/vllm-project/vllm/issues/24464 is resolved
platform: [ 'manylinux_2_28_x86_64', 'manylinux_2_28_aarch64' ]
device: [ 'cu128', 'cu129', 'cu130' ]
device: [ 'cu128', 'cu129' ]
include:
- platform: manylinux_2_28_x86_64
device: cu128
@ -38,10 +39,6 @@ jobs:
device: cu129
manylinux-image: 'pytorch/manylinux2_28-builder:cuda12.9'
runner: linux.12xlarge.memory
- platform: manylinux_2_28_x86_64
device: cu130
manylinux-image: 'pytorch/manylinux2_28-builder:cuda13.0'
runner: linux.12xlarge.memory
- platform: manylinux_2_28_aarch64
device: cu128
manylinux-image: 'pytorch/manylinuxaarch64-builder:cuda12.8'
@ -50,11 +47,6 @@ jobs:
device: cu129
manylinux-image: 'pytorch/manylinuxaarch64-builder:cuda12.9'
runner: linux.arm64.r7g.12xlarge.memory
exclude:
# TODO (huydhn): Add cu130 aarch64 once PyTorch is on 2.9+ and
# xformers is update to support 13.0
- platform: manylinux_2_28_aarch64
device: cu130
name: "Build ${{ matrix.device }} vLLM wheel on ${{ matrix.platform }}"
runs-on: ${{ matrix.runner }}
timeout-minutes: 480
@ -177,12 +169,7 @@ jobs:
fail-fast: false
matrix:
platform: [ 'manylinux_2_28_x86_64', 'manylinux_2_28_aarch64' ]
device: [ 'cu128', 'cu129', 'cu130' ]
exclude:
# TODO (huydhn): Add cu130 aarch64 once PyTorch is on 2.9+ and
# xformers is update to support 13.0
- platform: manylinux_2_28_aarch64
device: cu130
device: [ 'cu128', 'cu129' ]
env:
PLATFORM: ${{ matrix.platform }}
BUILD_DEVICE: ${{ matrix.device }}

View File

@ -132,7 +132,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -178,7 +178,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -204,52 +204,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.r7g.12xlarge.memory
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_10-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -270,7 +224,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -381,7 +335,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -427,7 +381,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -453,52 +407,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.r7g.12xlarge.memory
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_11-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -519,7 +427,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -630,7 +538,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -676,7 +584,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -702,52 +610,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.r7g.12xlarge.memory
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -768,7 +630,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -879,7 +741,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -925,7 +787,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -951,52 +813,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.r7g.12xlarge.memory
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
build_name: manywheel-py3_13-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1017,7 +833,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1128,7 +944,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13t-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1174,7 +990,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13t-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1200,52 +1016,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.r7g.12xlarge.memory
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13t-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13t-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
build_name: manywheel-py3_13t-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1266,7 +1036,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13t-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1377,7 +1147,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1423,7 +1193,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1449,52 +1219,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.r7g.12xlarge.memory
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
build_name: manywheel-py3_14-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1515,7 +1239,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1626,7 +1350,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14t-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1672,7 +1396,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14t-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1698,52 +1422,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.r7g.12xlarge.memory
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14t-cuda-aarch64-12_9
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14t-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
build_name: manywheel-py3_14t-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1764,7 +1442,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14t-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

View File

@ -248,74 +248,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
libtorch-cuda12_9-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: libtorch-cxx11-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: libtorch-cuda12_9-shared-with-deps-release
build_environment: linux-binary-libtorch
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
libtorch-cuda12_9-shared-with-deps-release-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- libtorch-cuda12_9-shared-with-deps-release-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: libtorch-cxx11-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
build_name: libtorch-cuda12_9-shared-with-deps-release
build_environment: linux-binary-libtorch
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
libtorch-cuda12_9-shared-with-deps-release-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: libtorch-cuda12_9-shared-with-deps-release-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: libtorch-cxx11-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
build_name: libtorch-cuda12_9-shared-with-deps-release
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
libtorch-cuda13_0-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -426,9 +358,6 @@ jobs:
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -544,9 +473,6 @@ jobs:
DOCKER_IMAGE_TAG_PREFIX: rocm7.0
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm

View File

@ -127,7 +127,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_6-test: # Testing
@ -193,7 +193,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_8-test: # Testing
@ -241,72 +241,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_10-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_10-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -325,7 +259,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda13_0-test: # Testing
@ -413,9 +347,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.10"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -528,9 +459,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm7.0
DESIRED_PYTHON: "3.10"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -793,7 +721,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_6-test: # Testing
@ -859,7 +787,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_8-test: # Testing
@ -907,72 +835,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_11-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_11-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -991,7 +853,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda13_0-test: # Testing
@ -1079,9 +941,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.11"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -1194,9 +1053,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm7.0
DESIRED_PYTHON: "3.11"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -1459,7 +1315,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_6-test: # Testing
@ -1525,7 +1381,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_8-test: # Testing
@ -1573,72 +1429,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_12-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1657,7 +1447,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda13_0-test: # Testing
@ -1745,9 +1535,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.12"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -1860,9 +1647,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm7.0
DESIRED_PYTHON: "3.12"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -2125,7 +1909,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_6-test: # Testing
@ -2191,7 +1975,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_8-test: # Testing
@ -2239,72 +2023,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_13-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
build_name: manywheel-py3_13-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
build_name: manywheel-py3_13-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -2323,7 +2041,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda13_0-test: # Testing
@ -2411,9 +2129,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.13"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -2526,9 +2241,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm7.0
DESIRED_PYTHON: "3.13"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -2791,7 +2503,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_6-test: # Testing
@ -2857,7 +2569,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_8-test: # Testing
@ -2905,72 +2617,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_13t-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
build_name: manywheel-py3_13t-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13t-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
build_name: manywheel-py3_13t-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -2989,7 +2635,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda13_0-test: # Testing
@ -3077,9 +2723,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.13t"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -3192,9 +2835,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm7.0
DESIRED_PYTHON: "3.13t"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -3457,7 +3097,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_6-test: # Testing
@ -3523,7 +3163,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_8-test: # Testing
@ -3571,72 +3211,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_14-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
build_name: manywheel-py3_14-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
build_name: manywheel-py3_14-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -3655,7 +3229,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda13_0-test: # Testing
@ -3743,9 +3317,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.14"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -3858,9 +3429,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm7.0
DESIRED_PYTHON: "3.14"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -4123,7 +3691,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14t-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_6-test: # Testing
@ -4189,7 +3757,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14t-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_8-test: # Testing
@ -4237,72 +3805,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14t-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.4.5; platform_system == 'Linux' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_14t-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
build_name: manywheel-py3_14t-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14t-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
build_name: manywheel-py3_14t-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -4321,7 +3823,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14t-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.88; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.96; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.85; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.1.0.3; platform_system == 'Linux' | nvidia-cufft==12.0.0.61; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.4.66; platform_system == 'Linux' | nvidia-cusparse==12.6.3.3; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.4.5; platform_system == 'Linux' | nvidia-nvtx==13.0.85; platform_system == 'Linux' | nvidia-nvjitlink==13.0.88; platform_system == 'Linux' | nvidia-cufile==1.15.1.6; platform_system == 'Linux'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | nvidia-nvtx==13.0.39; platform_system == 'Linux' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | nvidia-cufile==1.15.0.42; platform_system == 'Linux'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda13_0-test: # Testing
@ -4409,9 +3911,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.14t"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
@ -4524,9 +4023,6 @@ jobs:
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm7.0
DESIRED_PYTHON: "3.14t"
permissions:
id-token: write
contents: read
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm

View File

@ -63,6 +63,7 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.10.4"
freethreaded: false

View File

@ -59,6 +59,7 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.10.4"
freethreaded: false
@ -168,6 +169,7 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.11.4"
freethreaded: false
@ -277,6 +279,7 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.12.4"
freethreaded: false
@ -386,6 +389,7 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.13.4"
freethreaded: false
@ -495,6 +499,7 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.13.4"
freethreaded: true
@ -604,8 +609,9 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.14.0"
python-version: "3.14.0-rc.2"
freethreaded: false
- name: Checkout PyTorch
uses: actions/checkout@v4
@ -713,8 +719,9 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.14.0"
python-version: "3.14.0-rc.2"
freethreaded: true
- name: Checkout PyTorch
uses: actions/checkout@v4

View File

@ -44,7 +44,7 @@ jobs:
libtorch-cpu-shared-with-deps-debug-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -291,7 +291,7 @@ jobs:
libtorch-cuda12_6-shared-with-deps-debug-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -541,7 +541,7 @@ jobs:
libtorch-cuda12_8-shared-with-deps-debug-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -791,7 +791,7 @@ jobs:
libtorch-cuda13_0-shared-with-deps-debug-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch

View File

@ -44,7 +44,7 @@ jobs:
libtorch-cpu-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -291,7 +291,7 @@ jobs:
libtorch-cuda12_6-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -541,7 +541,7 @@ jobs:
libtorch-cuda12_8-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -791,7 +791,7 @@ jobs:
libtorch-cuda13_0-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch

View File

@ -44,7 +44,7 @@ jobs:
wheel-py3_10-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -279,7 +279,7 @@ jobs:
wheel-py3_10-cuda12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -517,7 +517,7 @@ jobs:
wheel-py3_10-cuda12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -755,7 +755,7 @@ jobs:
wheel-py3_10-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -993,7 +993,7 @@ jobs:
wheel-py3_10-xpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -1229,7 +1229,7 @@ jobs:
wheel-py3_11-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -1464,7 +1464,7 @@ jobs:
wheel-py3_11-cuda12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -1702,7 +1702,7 @@ jobs:
wheel-py3_11-cuda12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -1940,7 +1940,7 @@ jobs:
wheel-py3_11-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -2178,7 +2178,7 @@ jobs:
wheel-py3_11-xpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -2414,7 +2414,7 @@ jobs:
wheel-py3_12-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -2649,7 +2649,7 @@ jobs:
wheel-py3_12-cuda12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -2887,7 +2887,7 @@ jobs:
wheel-py3_12-cuda12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -3125,7 +3125,7 @@ jobs:
wheel-py3_12-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -3363,7 +3363,7 @@ jobs:
wheel-py3_12-xpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -3599,7 +3599,7 @@ jobs:
wheel-py3_13-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -3834,7 +3834,7 @@ jobs:
wheel-py3_13-cuda12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -4072,7 +4072,7 @@ jobs:
wheel-py3_13-cuda12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -4310,7 +4310,7 @@ jobs:
wheel-py3_13-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -4548,7 +4548,7 @@ jobs:
wheel-py3_13-xpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -4784,7 +4784,7 @@ jobs:
wheel-py3_13t-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -5019,7 +5019,7 @@ jobs:
wheel-py3_13t-cuda12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -5257,7 +5257,7 @@ jobs:
wheel-py3_13t-cuda12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -5495,7 +5495,7 @@ jobs:
wheel-py3_13t-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -5733,7 +5733,7 @@ jobs:
wheel-py3_13t-xpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -5969,7 +5969,7 @@ jobs:
wheel-py3_14-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -6204,7 +6204,7 @@ jobs:
wheel-py3_14-cuda12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -6442,7 +6442,7 @@ jobs:
wheel-py3_14-cuda12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -6680,7 +6680,7 @@ jobs:
wheel-py3_14-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -6918,7 +6918,7 @@ jobs:
wheel-py3_14-xpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -7154,7 +7154,7 @@ jobs:
wheel-py3_14t-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -7389,7 +7389,7 @@ jobs:
wheel-py3_14t-cuda12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -7627,7 +7627,7 @@ jobs:
wheel-py3_14t-cuda12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -7865,7 +7865,7 @@ jobs:
wheel-py3_14t-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -8103,7 +8103,7 @@ jobs:
wheel-py3_14t-xpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.12xlarge"
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch

View File

@ -37,7 +37,7 @@ jobs:
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runner: "linux.c7i.12xlarge"
runner: "linux.12xlarge"
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-sm90-dist
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11
cuda-arch-list: '9.0'

View File

@ -2,7 +2,7 @@ name: inductor-perf-nightly-h100
on:
schedule:
- cron: 15 0 * * 1-6
- cron: 15 0,12 * * 1-6
- cron: 0 7 * * 0
# NB: GitHub has an upper limit of 10 inputs here, so before we can sort it
# out, let try to run torchao cudagraphs_low_precision as part of cudagraphs
@ -130,7 +130,7 @@ jobs:
name: test-periodically
uses: ./.github/workflows/_linux-test.yml
needs: build
if: github.event.schedule == '15 0 * * 1-6'
if: github.event.schedule == '15 0,12 * * 1-6'
with:
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm90
dashboard-tag: training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-cudagraphs_low_precision-true

View File

@ -63,7 +63,6 @@ jobs:
# Same as the build job
python-version: 3.12.7
test-matrix: ${{ needs.macos-perf-py3-arm64-build.outputs.test-matrix }}
timeout-minutes: 300
disable-monitor: false
monitor-log-interval: 15
monitor-data-collect-interval: 4

View File

@ -1,132 +0,0 @@
name: inductor-perf-nightly-rocm-mi300
on:
push:
tags:
- ciflow/inductor-perf-test-nightly-rocm-mi300/*
schedule:
- cron: 15 0 * * *
# NB: GitHub has an upper limit of 10 inputs here, so before we can sort it
# out, let try to run torchao cudagraphs_low_precision as part of cudagraphs
workflow_dispatch:
inputs:
training:
description: Run training (on by default)?
required: false
type: boolean
default: true
inference:
description: Run inference (on by default)?
required: false
type: boolean
default: true
default:
description: Run inductor_default?
required: false
type: boolean
default: false
dynamic:
description: Run inductor_dynamic_shapes?
required: false
type: boolean
default: false
cppwrapper:
description: Run inductor_cpp_wrapper?
required: false
type: boolean
default: false
cudagraphs:
description: Run inductor_cudagraphs?
required: false
type: boolean
default: true
freezing_cudagraphs:
description: Run inductor_cudagraphs with freezing for inference?
required: false
type: boolean
default: false
aotinductor:
description: Run aot_inductor for inference?
required: false
type: boolean
default: false
maxautotune:
description: Run inductor_max_autotune?
required: false
type: boolean
default: false
benchmark_configs:
description: The list of configs used the benchmark
required: false
type: string
default: inductor_huggingface_perf_rocm_mi300,inductor_timm_perf_rocm_mi300,inductor_torchbench_perf_rocm_mi300
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
permissions: read-all
jobs:
get-label-type:
name: get-label-type
uses: pytorch/pytorch/.github/workflows/_runner-determinator.yml@main
if: ${{ (github.event_name != 'schedule' || github.repository == 'pytorch/pytorch') && github.repository_owner == 'pytorch' }}
with:
triggering_actor: ${{ github.triggering_actor }}
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
opt_out_experiments: lf
linux-jammy-rocm-py3_10-inductor-benchmark-build:
if: github.repository_owner == 'pytorch'
name: rocm-py3_10-inductor-benchmark-build
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-jammy-rocm-py3_10
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3-benchmarks
test-matrix: |
{ include: [
{ config: "inductor_huggingface_perf_rocm_mi300", shard: 1, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_huggingface_perf_rocm_mi300", shard: 2, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_huggingface_perf_rocm_mi300", shard: 3, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_huggingface_perf_rocm_mi300", shard: 4, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_huggingface_perf_rocm_mi300", shard: 5, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm_mi300", shard: 1, num_shards: 7, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm_mi300", shard: 2, num_shards: 7, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm_mi300", shard: 3, num_shards: 7, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm_mi300", shard: 4, num_shards: 7, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm_mi300", shard: 5, num_shards: 7, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm_mi300", shard: 6, num_shards: 7, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm_mi300", shard: 7, num_shards: 7, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 1, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 2, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 3, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 4, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 5, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 6, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 7, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 8, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm_mi300", shard: 9, num_shards: 9, runner: "linux.rocm.gpu.gfx942.1" },
]}
secrets: inherit
linux-jammy-rocm-py3_10-inductor-benchmark-test:
permissions:
id-token: write
contents: read
name: rocm-py3_10-inductor-benchmark-test
uses: ./.github/workflows/_rocm-test.yml
needs: linux-jammy-rocm-py3_10-inductor-benchmark-build
with:
build-environment: linux-jammy-rocm-py3_10
dashboard-tag: training-true-inference-true-default-true-dynamic-true-cudagraphs-true-cppwrapper-true-aotinductor-true-freezing_cudagraphs-true-cudagraphs_low_precision-true
docker-image: ${{ needs.linux-jammy-rocm-py3_10-inductor-benchmark-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-rocm-py3_10-inductor-benchmark-build.outputs.test-matrix }}
timeout-minutes: 720
# Disable monitor in perf tests for more investigation
disable-monitor: true
monitor-log-interval: 10
monitor-data-collect-interval: 2
secrets: inherit

View File

@ -1,11 +1,11 @@
name: inductor-perf-nightly-rocm-mi355
name: inductor-perf-nightly-rocm
on:
push:
tags:
- ciflow/inductor-perf-test-nightly-rocm-mi355/*
- ciflow/inductor-perf-test-nightly-rocm/*
schedule:
- cron: 15 0 * * *
- cron: 0 7 * * 0,3
# NB: GitHub has an upper limit of 10 inputs here, so before we can sort it
# out, let try to run torchao cudagraphs_low_precision as part of cudagraphs
workflow_dispatch:
@ -59,7 +59,7 @@ on:
description: The list of configs used the benchmark
required: false
type: string
default: inductor_huggingface_perf_rocm_mi355,inductor_timm_perf_rocm_mi355,inductor_torchbench_perf_rocm_mi355
default: inductor_huggingface_perf_rocm,inductor_timm_perf_rocm,inductor_torchbench_perf_rocm
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
@ -88,27 +88,23 @@ jobs:
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3-benchmarks
test-matrix: |
{ include: [
{ config: "inductor_huggingface_perf_rocm_mi355", shard: 1, num_shards: 5, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_huggingface_perf_rocm_mi355", shard: 2, num_shards: 5, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_huggingface_perf_rocm_mi355", shard: 3, num_shards: 5, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_huggingface_perf_rocm_mi355", shard: 4, num_shards: 5, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_huggingface_perf_rocm_mi355", shard: 5, num_shards: 5, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_timm_perf_rocm_mi355", shard: 1, num_shards: 7, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_timm_perf_rocm_mi355", shard: 2, num_shards: 7, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_timm_perf_rocm_mi355", shard: 3, num_shards: 7, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_timm_perf_rocm_mi355", shard: 4, num_shards: 7, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_timm_perf_rocm_mi355", shard: 5, num_shards: 7, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_timm_perf_rocm_mi355", shard: 6, num_shards: 7, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_timm_perf_rocm_mi355", shard: 7, num_shards: 7, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 1, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 2, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 3, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 4, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 5, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 6, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 7, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 8, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_torchbench_perf_rocm_mi355", shard: 9, num_shards: 9, runner: "linux.rocm.gpu.mi355.1" },
{ config: "inductor_huggingface_perf_rocm", shard: 1, num_shards: 4, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_huggingface_perf_rocm", shard: 2, num_shards: 4, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_huggingface_perf_rocm", shard: 3, num_shards: 4, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_huggingface_perf_rocm", shard: 4, num_shards: 4, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm", shard: 1, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm", shard: 2, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm", shard: 3, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm", shard: 4, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_timm_perf_rocm", shard: 5, num_shards: 5, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm", shard: 1, num_shards: 8, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm", shard: 2, num_shards: 8, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm", shard: 3, num_shards: 8, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm", shard: 4, num_shards: 8, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm", shard: 5, num_shards: 8, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm", shard: 6, num_shards: 8, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm", shard: 7, num_shards: 8, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "inductor_torchbench_perf_rocm", shard: 8, num_shards: 8, runner: "linux.rocm.gpu.gfx942.1" },
]}
secrets: inherit

View File

@ -88,6 +88,7 @@ jobs:
with:
build-environment: linux-jammy-rocm-py3_10
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3-benchmarks
sync-tag: rocm-build
test-matrix: |
{ include: [
{ config: "dynamo_eager_torchbench", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
@ -105,16 +106,6 @@ jobs:
{ config: "dynamic_aot_eager_huggingface", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "dynamic_aot_eager_timm", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "dynamic_aot_eager_timm", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "dynamic_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "dynamic_inductor_timm", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "dynamic_inductor_timm", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "dynamic_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "dynamic_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "aot_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "aot_inductor_timm", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "aot_inductor_timm", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "aot_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
{ config: "aot_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx942.1" },
]}
secrets: inherit

View File

@ -12,7 +12,6 @@ on:
- landchecks/*
tags:
- ciflow/pull/*
- ciflow/trunk/*
workflow_dispatch:
permissions: read-all
@ -33,12 +32,10 @@ jobs:
name: Get changed files
uses: ./.github/workflows/_get-changed-files.yml
with:
all_files: ${{ contains(github.event.pull_request.labels.*.name, 'lint-all-files') || contains(github.event.pull_request.labels.*.name, 'Reverted') || github.event_name == 'push' }}
all_files: ${{ contains(github.event.pull_request.labels.*.name, 'lint-all-files') || contains(github.event.pull_request.labels.*.name, 'Reverted') }}
lintrunner-clang:
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
# Needed to prevent deduping on HUD
name: lintrunner-clang-${{ needs.get-changed-files.outputs.changed-files == '*' && 'all' || 'partial' }}
needs: [get-label-type, get-changed-files]
# Only run if there are changed files relevant to clangtidy / clangformat
if: |
@ -78,7 +75,6 @@ jobs:
# fails to find types when it should
lintrunner-mypy:
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
name: lintrunner-mypy-${{ needs.get-changed-files.outputs.changed-files == '*' && 'all' || 'partial' }}
needs: [get-label-type, get-changed-files]
# Only run if there are changed files relevant to mypy
if: |
@ -103,7 +99,6 @@ jobs:
lintrunner-noclang:
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
name: lintrunner-noclang-${{ needs.get-changed-files.outputs.changed-files == '*' && 'all' || 'partial' }}
needs: [get-label-type, get-changed-files]
with:
timeout: 120
@ -118,9 +113,9 @@ jobs:
CHANGED_FILES="${{ needs.get-changed-files.outputs.changed-files }}"
echo "Running all other linters"
if [ "$CHANGED_FILES" = '*' ]; then
ADDITIONAL_LINTRUNNER_ARGS="--skip CLANGTIDY,CLANGFORMAT,MYPY,MYPYSTRICT,PYREFLY --all-files" .github/scripts/lintrunner.sh
ADDITIONAL_LINTRUNNER_ARGS="--skip CLANGTIDY,CLANGFORMAT,MYPY,MYPYSTRICT --all-files" .github/scripts/lintrunner.sh
else
ADDITIONAL_LINTRUNNER_ARGS="--skip CLANGTIDY,CLANGFORMAT,MYPY,MYPYSTRICT,PYREFLY ${CHANGED_FILES}" .github/scripts/lintrunner.sh
ADDITIONAL_LINTRUNNER_ARGS="--skip CLANGTIDY,CLANGFORMAT,MYPY,MYPYSTRICT ${CHANGED_FILES}" .github/scripts/lintrunner.sh
fi
quick-checks:

View File

@ -7,11 +7,9 @@ on:
workflow_dispatch:
inputs:
test_mode:
type: choice
options:
- 'short'
- 'long'
- 'all'
required: false
type: string
default: 'short'
description: tag filter for operator benchmarks, options from long, short, all
schedule:
# Run at 07:00 UTC every Sunday
@ -30,49 +28,38 @@ permissions:
contents: read
jobs:
x86-opbenchmark-build:
opbenchmark-build:
if: github.repository_owner == 'pytorch'
name: x86-opbenchmark-build
name: opbenchmark-build
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-jammy-py3.10-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
test-matrix: |
{ include: [
{ config: "cpu_operator_benchmark_${{ inputs.test_mode || 'short' }}", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
{ config: "cpu_operator_benchmark_short", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
]}
secrets: inherit
x86-opbenchmark-test:
name: x86-opbenchmark-test
uses: ./.github/workflows/_linux-test.yml
needs: x86-opbenchmark-build
with:
build-environment: linux-jammy-py3.10-gcc11-build
docker-image: ${{ needs.x86-opbenchmark-build.outputs.docker-image }}
test-matrix: ${{ needs.x86-opbenchmark-build.outputs.test-matrix }}
secrets: inherit
aarch64-opbenchmark-build:
if: github.repository_owner == 'pytorch'
name: aarch64-opbenchmark-build
opbenchmark-on-demand-build:
if: ${{ github.event_name == 'workflow_dispatch' && github.repository_owner == 'pytorch' }}
name: opbenchmark-on-demand-build
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-jammy-aarch64-py3.10
runner: linux.arm64.m7g.4xlarge
docker-image-name: ci-image:pytorch-linux-jammy-aarch64-py3.10-gcc11
build-environment: linux-jammy-py3.10-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
test-matrix: |
{ include: [
{ config: "cpu_operator_benchmark_short", shard: 1, num_shards: 1, runner: "linux.arm64.m8g.4xlarge" },
{ config: "cpu_operator_benchmark_${{ inputs.test_mode }}", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
]}
secrets: inherit
aarch64-opbenchmark-test:
name: aarch64-opbenchmark-test
opbenchmark-test:
name: opbenchmark-test
uses: ./.github/workflows/_linux-test.yml
needs: aarch64-opbenchmark-build
needs: opbenchmark-build
with:
build-environment: linux-jammy-aarch64-py3.10
docker-image: ${{ needs.aarch64-opbenchmark-build.outputs.docker-image }}
test-matrix: ${{ needs.aarch64-opbenchmark-build.outputs.test-matrix }}
build-environment: linux-jammy-py3.10-gcc11-build
docker-image: ${{ needs.opbenchmark-build.outputs.docker-image }}
test-matrix: ${{ needs.opbenchmark-build.outputs.test-matrix }}
secrets: inherit

View File

@ -18,7 +18,6 @@ permissions:
contents: read
jobs:
# H100 A100 runners
opmicrobenchmark-build:
if: github.repository_owner == 'pytorch'
name: opmicrobenchmark-build
@ -45,56 +44,3 @@ jobs:
docker-image: ${{ needs.opmicrobenchmark-build.outputs.docker-image }}
test-matrix: ${{ needs.opmicrobenchmark-build.outputs.test-matrix }}
secrets: inherit
# B200 runner
opmicrobenchmark-build-b200:
if: github.repository_owner == 'pytorch'
name: opmicrobenchmark-build-b200
uses: ./.github/workflows/_linux-build.yml
with:
runner: linux.12xlarge.memory
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm100
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11
cuda-arch-list: '10.0'
test-matrix: |
{ include: [
{ config: "operator_microbenchmark_test", shard: 1, num_shards: 1, runner: "linux.dgx.b200" },
]}
secrets: inherit
opmicrobenchmark-test-b200:
name: opmicrobenchmark-test-b200
uses: ./.github/workflows/_linux-test.yml
needs: opmicrobenchmark-build-b200
with:
timeout-minutes: 500
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm100
docker-image: ${{ needs.opmicrobenchmark-build-b200.outputs.docker-image }}
test-matrix: ${{ needs.opmicrobenchmark-build-b200.outputs.test-matrix }}
aws-role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
secrets: inherit
# ROCM MI300 runner
opmicrobenchmark-build-rocm:
if: github.repository_owner == 'pytorch'
name: opmicrobenchmark-build-rocm
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-jammy-rocm-py3_10
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3-benchmarks
test-matrix: |
{ include: [
{ config: "operator_microbenchmark_test", shard: 1, num_shards: 1, runner: "linux.rocm.gpu.gfx942.1" },
]}
secrets: inherit
opmicrobenchmark-test-rocm:
name: opmicrobenchmark-test-rocm
uses: ./.github/workflows/_rocm-test.yml
needs: opmicrobenchmark-build-rocm
with:
timeout-minutes: 500
build-environment: linux-jammy-rocm-py3_10
docker-image: ${{ needs.opmicrobenchmark-build-rocm.outputs.docker-image }}
test-matrix: ${{ needs.opmicrobenchmark-build-rocm.outputs.test-matrix }}
secrets: inherit

View File

@ -147,16 +147,15 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-debug
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9
cuda-arch-list: 8.9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 2, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 3, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 4, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 5, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 6, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 7, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g6.4xlarge.experimental.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 1, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 2, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 3, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 4, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 5, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 6, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu", owners: ["oncall:debug-build"] },
{ config: "default", shard: 7, num_shards: 7, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge.nvidia.gpu", owners: ["oncall:debug-build"] },
]}
secrets: inherit
@ -183,11 +182,11 @@ jobs:
docker-image-name: ci-image:pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11
test-matrix: |
{ include: [
{ config: "nogpu_AVX512", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "nogpu_AVX512", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "nogpu_AVX512", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "nogpu_NO_AVX2", shard: 1, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "nogpu_NO_AVX2", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge" },
{ config: "nogpu_AVX512", shard: 1, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g4dn.4xlarge.nvidia.gpu" },
{ config: "nogpu_AVX512", shard: 2, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g4dn.4xlarge.nvidia.gpu" },
{ config: "nogpu_AVX512", shard: 3, num_shards: 3, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g4dn.4xlarge.nvidia.gpu" },
{ config: "nogpu_NO_AVX2", shard: 1, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g4dn.4xlarge.nvidia.gpu" },
{ config: "nogpu_NO_AVX2", shard: 2, num_shards: 2, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g4dn.4xlarge.nvidia.gpu" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.g4dn.4xlarge.nvidia.gpu" },
]}
secrets: inherit
@ -214,9 +213,9 @@ jobs:
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3
test-matrix: |
{ include: [
{ config: "distributed", shard: 1, num_shards: 3, runner: "linux.rocm.gpu.mi250.4", owners: ["module:rocm", "oncall:distributed"] },
{ config: "distributed", shard: 2, num_shards: 3, runner: "linux.rocm.gpu.mi250.4", owners: ["module:rocm", "oncall:distributed"] },
{ config: "distributed", shard: 3, num_shards: 3, runner: "linux.rocm.gpu.mi250.4", owners: ["module:rocm", "oncall:distributed"] },
{ config: "distributed", shard: 1, num_shards: 3, runner: "linux.rocm.gpu.4", owners: ["module:rocm", "oncall:distributed"] },
{ config: "distributed", shard: 2, num_shards: 3, runner: "linux.rocm.gpu.4", owners: ["module:rocm", "oncall:distributed"] },
{ config: "distributed", shard: 3, num_shards: 3, runner: "linux.rocm.gpu.4", owners: ["module:rocm", "oncall:distributed"] },
]}
secrets: inherit

View File

@ -127,6 +127,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
# More memory is needed to build with asan
runner: linux.2xlarge.memory
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3.10-clang18-asan
@ -347,8 +348,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
# This should sync with the build in xpu.yml but xpu uses a larger runner
# sync-tag: linux-xpu-n-build
sync-tag: linux-xpu-n-build
runner_prefix: ${{ needs.get-label-type.outputs.label-type }}
build-environment: linux-jammy-xpu-n-py3.10
docker-image-name: ci-image:pytorch-linux-jammy-xpu-n-py3

View File

@ -45,6 +45,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-noble-rocm-py3.12-mi300
docker-image-name: ci-image:pytorch-linux-noble-rocm-n-py3
sync-tag: rocm-build
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 6, runner: "linux.rocm.gpu.gfx942.1" },

View File

@ -1,9 +1,6 @@
name: rocm-mi355
on:
push:
tags:
- ciflow/rocm-mi355/*
workflow_dispatch:
schedule:
- cron: 30 11,1 * * * # about 4:30am PDT and 6:30pm PDT
@ -42,14 +39,15 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-noble-rocm-py3.12-mi355
docker-image-name: ci-image:pytorch-linux-noble-rocm-n-py3
sync-tag: rocm-build
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 6, runner: "linux.rocm.gpu.mi355.1" },
{ config: "default", shard: 2, num_shards: 6, runner: "linux.rocm.gpu.mi355.1" },
{ config: "default", shard: 3, num_shards: 6, runner: "linux.rocm.gpu.mi355.1" },
{ config: "default", shard: 4, num_shards: 6, runner: "linux.rocm.gpu.mi355.1" },
{ config: "default", shard: 5, num_shards: 6, runner: "linux.rocm.gpu.mi355.1" },
{ config: "default", shard: 6, num_shards: 6, runner: "linux.rocm.gpu.mi355.1" },
{ config: "default", shard: 1, num_shards: 6, runner: "linux.rocm.gpu.mi355.2" },
{ config: "default", shard: 2, num_shards: 6, runner: "linux.rocm.gpu.mi355.2" },
{ config: "default", shard: 3, num_shards: 6, runner: "linux.rocm.gpu.mi355.2" },
{ config: "default", shard: 4, num_shards: 6, runner: "linux.rocm.gpu.mi355.2" },
{ config: "default", shard: 5, num_shards: 6, runner: "linux.rocm.gpu.mi355.2" },
{ config: "default", shard: 6, num_shards: 6, runner: "linux.rocm.gpu.mi355.2" },
]}
secrets: inherit
@ -66,7 +64,5 @@ jobs:
build-environment: linux-noble-rocm-py3.12-mi355
docker-image: ${{ needs.linux-noble-rocm-py3_12-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-noble-rocm-py3_12-build.outputs.test-matrix }}
tests-to-include: >-
${{ github.event_name == 'schedule' && 'test_nn test_torch test_cuda test_ops test_unary_ufuncs test_binary_ufuncs test_autograd inductor/test_torchinductor test_matmul_cuda test_scaled_matmul_cuda'
|| '' }}
tests-to-include: "test_nn test_torch test_cuda test_ops test_unary_ufuncs test_binary_ufuncs test_autograd inductor/test_torchinductor"
secrets: inherit

View File

@ -1,75 +0,0 @@
name: rocm-navi31
on:
push:
tags:
- ciflow/rocm-navi31/*
workflow_dispatch:
schedule:
# We have several schedules so jobs can check github.event.schedule to activate only for a fraction of the runs.
# Also run less frequently on weekends.
- cron: 45 */2 * * 1-5
- cron: 45 4,12 * * 0,6
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
permissions: read-all
jobs:
target-determination:
if: github.repository_owner == 'pytorch'
name: before-test
uses: ./.github/workflows/target_determination.yml
permissions:
id-token: write
contents: read
get-label-type:
name: get-label-type
uses: pytorch/pytorch/.github/workflows/_runner-determinator.yml@main
if: ${{ (github.event_name != 'schedule' || github.repository == 'pytorch/pytorch') && github.repository_owner == 'pytorch' }}
with:
triggering_actor: ${{ github.triggering_actor }}
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
linux-jammy-rocm-py3_10-build:
if: ${{ (github.event_name != 'schedule' || github.repository == 'pytorch/pytorch') && github.repository_owner == 'pytorch' }}
name: linux-jammy-rocm-py3.10
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-rocm-py3.10
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3
sync-tag: rocm-build
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 2, runner: "linux.rocm.gpu.gfx1100" },
{ config: "default", shard: 2, num_shards: 2, runner: "linux.rocm.gpu.gfx1100" },
]}
secrets: inherit
linux-jammy-rocm-py3_10-test:
permissions:
id-token: write
contents: read
name: linux-jammy-rocm-py3_10
uses: ./.github/workflows/_rocm-test.yml
needs:
- linux-jammy-rocm-py3_10-build
- target-determination
with:
build-environment: linux-jammy-rocm-py3.10
docker-image: ${{ needs.linux-jammy-rocm-py3_10-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-rocm-py3_10-build.outputs.test-matrix }}
tests-to-include: >-
${{ github.event_name == 'schedule' && 'test_nn test_torch test_cuda test_ops test_unary_ufuncs test_binary_ufuncs
test_autograd inductor/test_torchinductor inductor/test_kernel_benchmark
inductor/test_pad_mm inductor/test_benchmark_fusion inductor/test_aot_inductor
inductor/test_torchinductor inductor/test_decompose_mem_bound_mm
inductor/test_flex_attention inductor/test_max_autotune' || '' }}
secrets: inherit

View File

@ -26,23 +26,11 @@ jobs:
id-token: write
contents: read
get-label-type:
name: get-label-type
uses: pytorch/pytorch/.github/workflows/_runner-determinator.yml@main
if: ${{ (github.event_name != 'schedule' || github.repository == 'pytorch/pytorch') && github.repository_owner == 'pytorch' }}
with:
triggering_actor: ${{ github.triggering_actor }}
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
linux-jammy-rocm-py3_10-build:
if: ${{ (github.event_name != 'schedule' || github.repository == 'pytorch/pytorch') && github.repository_owner == 'pytorch' }}
name: linux-jammy-rocm-py3.10
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-rocm-py3.10
docker-image-name: ci-image:pytorch-linux-jammy-rocm-n-py3
sync-tag: rocm-build

View File

@ -140,6 +140,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
# More memory is needed to build with asan
runner: linux.2xlarge.memory
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3.10-clang18-asan

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