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7 Commits

Author SHA1 Message Date
a3795cfaea lint 2025-09-16 11:00:20 -07:00
a9d5c00727 more memory? 2025-09-15 21:42:41 +00:00
c1102ca308 more memory? 2025-09-15 21:37:26 +00:00
7856f8d7f4 fixed i think 2025-09-13 13:52:39 +00:00
973c3b531a oops 2025-09-13 13:52:39 +00:00
d5a496e7f1 check 2025-09-13 13:52:39 +00:00
051e544ef6 [BE] Make PyObjectSlot use a global PyInterpreter
ghstack-source-id: 826f3f0c155cd0677776949b0c1c82395a95a1e8
Pull Request resolved: https://github.com/pytorch/pytorch/pull/158409

[BE] Remove pyinterpreter struct from pyobjslot

ghstack-source-id: 826f3f0c155cd0677776949b0c1c82395a95a1e8
Pull Request resolved: https://github.com/pytorch/pytorch/pull/159511
2025-09-13 13:52:39 +00:00
2185 changed files with 37447 additions and 74481 deletions

View File

@ -15,8 +15,6 @@ fi
# Compress the fatbin with -compress-mode=size for CUDA 13
if [[ "$DESIRED_CUDA" == *"13"* ]]; then
export TORCH_NVCC_FLAGS="-compress-mode=size"
# Bundle ptxas into the cu13 wheel, see https://github.com/pytorch/pytorch/issues/163801
export BUILD_BUNDLE_PTXAS=1
fi
SCRIPTPATH="$( cd -- "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P )"
@ -33,7 +31,8 @@ pip install -r /pytorch/requirements.txt
pip install auditwheel==6.2.0 wheel
if [ "$DESIRED_CUDA" = "cpu" ]; then
echo "BASE_CUDA_VERSION is not set. Building cpu wheel."
python /pytorch/.ci/aarch64_linux/aarch64_wheel_ci_build.py --enable-mkldnn
#USE_PRIORITIZED_TEXT_FOR_LD for enable linker script optimization https://github.com/pytorch/pytorch/pull/121975/files
USE_PRIORITIZED_TEXT_FOR_LD=1 python /pytorch/.ci/aarch64_linux/aarch64_wheel_ci_build.py --enable-mkldnn
else
echo "BASE_CUDA_VERSION is set to: $DESIRED_CUDA"
export USE_SYSTEM_NCCL=1
@ -47,5 +46,6 @@ else
export USE_NVIDIA_PYPI_LIBS=1
fi
python /pytorch/.ci/aarch64_linux/aarch64_wheel_ci_build.py --enable-mkldnn --enable-cuda
#USE_PRIORITIZED_TEXT_FOR_LD for enable linker script optimization https://github.com/pytorch/pytorch/pull/121975/files
USE_PRIORITIZED_TEXT_FOR_LD=1 python /pytorch/.ci/aarch64_linux/aarch64_wheel_ci_build.py --enable-mkldnn --enable-cuda
fi

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@ -13,6 +13,49 @@ def list_dir(path: str) -> list[str]:
return check_output(["ls", "-1", path]).decode().split("\n")
def build_ArmComputeLibrary() -> None:
"""
Using ArmComputeLibrary for aarch64 PyTorch
"""
print("Building Arm Compute Library")
acl_build_flags = [
"debug=0",
"neon=1",
"opencl=0",
"os=linux",
"openmp=1",
"cppthreads=0",
"arch=armv8a",
"multi_isa=1",
"fixed_format_kernels=1",
"build=native",
]
acl_install_dir = "/acl"
acl_checkout_dir = os.getenv("ACL_SOURCE_DIR", "ComputeLibrary")
if os.path.isdir(acl_install_dir):
shutil.rmtree(acl_install_dir)
if not os.path.isdir(acl_checkout_dir) or not len(os.listdir(acl_checkout_dir)):
check_call(
[
"git",
"clone",
"https://github.com/ARM-software/ComputeLibrary.git",
"-b",
"v25.02",
"--depth",
"1",
"--shallow-submodules",
]
)
check_call(
["scons", "Werror=1", f"-j{os.cpu_count()}"] + acl_build_flags,
cwd=acl_checkout_dir,
)
for d in ["arm_compute", "include", "utils", "support", "src", "build"]:
shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
def replace_tag(filename) -> None:
with open(filename) as f:
lines = f.readlines()
@ -274,7 +317,7 @@ if __name__ == "__main__":
).decode()
print("Building PyTorch wheel")
build_vars = ""
build_vars = "CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000 "
# MAX_JOB=5 is not required for CPU backend (see commit 465d98b)
if enable_cuda:
build_vars += "MAX_JOBS=5 "
@ -313,17 +356,23 @@ if __name__ == "__main__":
build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1 : branch.find('-')]} PYTORCH_BUILD_NUMBER=1 "
if enable_mkldnn:
build_ArmComputeLibrary()
print("build pytorch with mkldnn+acl backend")
build_vars += "USE_MKLDNN=ON USE_MKLDNN_ACL=ON "
build_vars += "ACL_ROOT_DIR=/acl "
build_vars += (
"USE_MKLDNN=ON USE_MKLDNN_ACL=ON "
"ACL_ROOT_DIR=/acl "
"LD_LIBRARY_PATH=/pytorch/build/lib:/acl/build:$LD_LIBRARY_PATH "
"ACL_INCLUDE_DIR=/acl/build "
"ACL_LIBRARY=/acl/build "
)
if enable_cuda:
build_vars += "BLAS=NVPL "
else:
build_vars += "BLAS=OpenBLAS OpenBLAS_HOME=/opt/OpenBLAS "
build_vars += "BLAS=OpenBLAS OpenBLAS_HOME=/OpenBLAS "
else:
print("build pytorch without mkldnn backend")
os.system(f"cd /pytorch; {build_vars} python3 -m build --wheel --no-isolation")
os.system(f"cd /pytorch; {build_vars} python3 setup.py bdist_wheel")
if enable_cuda:
print("Updating Cuda Dependency")
filename = os.listdir("/pytorch/dist/")

View File

@ -241,7 +241,7 @@ def wait_for_connection(addr, port, timeout=15, attempt_cnt=5):
try:
with socket.create_connection((addr, port), timeout=timeout):
return
except (ConnectionRefusedError, TimeoutError): # noqa: PERF203
except (ConnectionRefusedError, socket.timeout): # noqa: PERF203
if i == attempt_cnt - 1:
raise
time.sleep(timeout)
@ -299,6 +299,40 @@ def install_condaforge_python(host: RemoteHost, python_version="3.8") -> None:
)
def build_OpenBLAS(host: RemoteHost, git_clone_flags: str = "") -> None:
print("Building OpenBLAS")
host.run_cmd(
f"git clone https://github.com/xianyi/OpenBLAS -b v0.3.28 {git_clone_flags}"
)
make_flags = "NUM_THREADS=64 USE_OPENMP=1 NO_SHARED=1 DYNAMIC_ARCH=1 TARGET=ARMV8"
host.run_cmd(
f"pushd OpenBLAS && make {make_flags} -j8 && sudo make {make_flags} install && popd && rm -rf OpenBLAS"
)
def build_ArmComputeLibrary(host: RemoteHost, git_clone_flags: str = "") -> None:
print("Building Arm Compute Library")
acl_build_flags = " ".join(
[
"debug=0",
"neon=1",
"opencl=0",
"os=linux",
"openmp=1",
"cppthreads=0",
"arch=armv8a",
"multi_isa=1",
"fixed_format_kernels=1",
"build=native",
]
)
host.run_cmd(
f"git clone https://github.com/ARM-software/ComputeLibrary.git -b v25.02 {git_clone_flags}"
)
host.run_cmd(f"cd ComputeLibrary && scons Werror=1 -j8 {acl_build_flags}")
def embed_libgomp(host: RemoteHost, use_conda, wheel_name) -> None:
host.run_cmd("pip3 install auditwheel")
host.run_cmd(
@ -408,7 +442,7 @@ def build_torchvision(
if host.using_docker():
build_vars += " CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000"
host.run_cmd(f"cd vision && {build_vars} python3 -m build --wheel --no-isolation")
host.run_cmd(f"cd vision && {build_vars} python3 setup.py bdist_wheel")
vision_wheel_name = host.list_dir("vision/dist")[0]
embed_libgomp(host, use_conda, os.path.join("vision", "dist", vision_wheel_name))
@ -463,7 +497,7 @@ def build_torchdata(
if host.using_docker():
build_vars += " CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000"
host.run_cmd(f"cd data && {build_vars} python3 -m build --wheel --no-isolation")
host.run_cmd(f"cd data && {build_vars} python3 setup.py bdist_wheel")
wheel_name = host.list_dir("data/dist")[0]
embed_libgomp(host, use_conda, os.path.join("data", "dist", wheel_name))
@ -519,7 +553,7 @@ def build_torchtext(
if host.using_docker():
build_vars += " CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000"
host.run_cmd(f"cd text && {build_vars} python3 -m build --wheel --no-isolation")
host.run_cmd(f"cd text && {build_vars} python3 setup.py bdist_wheel")
wheel_name = host.list_dir("text/dist")[0]
embed_libgomp(host, use_conda, os.path.join("text", "dist", wheel_name))
@ -580,7 +614,7 @@ def build_torchaudio(
host.run_cmd(
f"cd audio && export FFMPEG_ROOT=$(pwd)/third_party/ffmpeg && export USE_FFMPEG=1 \
&& ./packaging/ffmpeg/build.sh \
&& {build_vars} python3 -m build --wheel --no-isolation"
&& {build_vars} python3 setup.py bdist_wheel"
)
wheel_name = host.list_dir("audio/dist")[0]
@ -666,6 +700,7 @@ def start_build(
configure_system(
host, compiler=compiler, use_conda=use_conda, python_version=python_version
)
build_OpenBLAS(host, git_clone_flags)
if host.using_docker():
print("Move libgfortant.a into a standard location")
@ -688,12 +723,10 @@ def start_build(
f"git clone --recurse-submodules -b {branch} https://github.com/pytorch/pytorch {git_clone_flags}"
)
host.run_cmd("pytorch/.ci/docker/common/install_openblas.sh")
print("Building PyTorch wheel")
build_opts = ""
if pytorch_build_number is not None:
build_opts += f" -C--build-option=--build-number={pytorch_build_number}"
build_opts += f" --build-number {pytorch_build_number}"
# Breakpad build fails on aarch64
build_vars = "USE_BREAKPAD=0 "
if branch == "nightly":
@ -710,18 +743,15 @@ def start_build(
if host.using_docker():
build_vars += " CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000"
if enable_mkldnn:
host.run_cmd("pytorch/.ci/docker/common/install_acl.sh")
build_ArmComputeLibrary(host, git_clone_flags)
print("build pytorch with mkldnn+acl backend")
build_vars += " USE_MKLDNN=ON USE_MKLDNN_ACL=ON"
build_vars += " BLAS=OpenBLAS"
build_vars += " OpenBLAS_HOME=/opt/OpenBLAS"
build_vars += " ACL_ROOT_DIR=/acl"
host.run_cmd(
f"cd $HOME/pytorch && {build_vars} python3 -m build --wheel --no-isolation{build_opts}"
f"cd $HOME/pytorch && export ACL_ROOT_DIR=$HOME/ComputeLibrary && {build_vars} python3 setup.py bdist_wheel{build_opts}"
)
print("Repair the wheel")
pytorch_wheel_name = host.list_dir("pytorch/dist")[0]
ld_library_path = "/acl/build:$HOME/pytorch/build/lib"
ld_library_path = "$HOME/acl/build:$HOME/pytorch/build/lib"
host.run_cmd(
f"export LD_LIBRARY_PATH={ld_library_path} && auditwheel repair $HOME/pytorch/dist/{pytorch_wheel_name}"
)
@ -733,7 +763,7 @@ def start_build(
else:
print("build pytorch without mkldnn backend")
host.run_cmd(
f"cd pytorch && {build_vars} python3 -m build --wheel --no-isolation{build_opts}"
f"cd pytorch && {build_vars} python3 setup.py bdist_wheel{build_opts}"
)
print("Deleting build folder")
@ -877,7 +907,7 @@ def terminate_instances(instance_type: str) -> None:
def parse_arguments():
from argparse import ArgumentParser
parser = ArgumentParser("Build and test AARCH64 wheels using EC2")
parser = ArgumentParser("Builid and test AARCH64 wheels using EC2")
parser.add_argument("--key-name", type=str)
parser.add_argument("--debug", action="store_true")
parser.add_argument("--build-only", action="store_true")
@ -974,7 +1004,7 @@ if __name__ == "__main__":
install_condaforge_python(host, args.python_version)
sys.exit(0)
python_version = args.python_version if args.python_version is not None else "3.10"
python_version = args.python_version if args.python_version is not None else "3.9"
if args.use_torch_from_pypi:
configure_system(host, compiler=args.compiler, python_version=python_version)

View File

@ -69,8 +69,7 @@ RUN bash ./install_cuda.sh 13.0
ENV DESIRED_CUDA=13.0
FROM ${ROCM_IMAGE} as rocm
ARG PYTORCH_ROCM_ARCH
ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
ENV PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
ENV MKLROOT /opt/intel

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@ -36,12 +36,6 @@ case ${DOCKER_TAG_PREFIX} in
;;
rocm*)
BASE_TARGET=rocm
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
# add gfx950, gfx115x conditionally starting in ROCm 7.0
if [[ "$ROCM_VERSION" == *"7.0"* ]]; then
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
fi
EXTRA_BUILD_ARGS="${EXTRA_BUILD_ARGS} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}"
;;
*)
echo "ERROR: Unknown docker tag ${DOCKER_TAG_PREFIX}"

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@ -84,8 +84,8 @@ fi
_UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152
_UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96
if [[ "$image" == *rocm* ]]; then
_UCX_COMMIT=29831d319e6be55cb8c768ca61de335c934ca39e
_UCC_COMMIT=9f4b242cbbd8b1462cbc732eb29316cdfa124b77
_UCX_COMMIT=cc312eaa4655c0cc5c2bcd796db938f90563bcf6
_UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d
fi
tag=$(echo $image | awk -F':' '{print $2}')
@ -175,6 +175,20 @@ case "$tag" in
fi
GCC_VERSION=11
VISION=yes
ROCM_VERSION=6.4
NINJA_VERSION=1.9.0
TRITON=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
if [[ $tag =~ "benchmarks" ]]; then
INDUCTOR_BENCHMARKS=yes
fi
;;
pytorch-linux-noble-rocm-alpha-py3)
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
VISION=yes
ROCM_VERSION=7.0
NINJA_VERSION=1.9.0
TRITON=yes
@ -182,9 +196,6 @@ case "$tag" in
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
PYTORCH_ROCM_ARCH="gfx90a;gfx942;gfx950"
if [[ $tag =~ "benchmarks" ]]; then
INDUCTOR_BENCHMARKS=yes
fi
;;
pytorch-linux-jammy-xpu-n-1-py3)
ANACONDA_PYTHON_VERSION=3.10
@ -251,10 +262,13 @@ case "$tag" in
TRITON_CPU=yes
;;
pytorch-linux-jammy-linter)
PYTHON_VERSION=3.10
# TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
# We will need to update mypy version eventually, but that's for another day. The task
# would be to upgrade mypy to 1.0.0 with Python 3.11
PYTHON_VERSION=3.9
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.10-linter)
PYTHON_VERSION=3.10
pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-linter)
PYTHON_VERSION=3.9
CUDA_VERSION=12.8.1
;;
pytorch-linux-jammy-aarch64-py3.10-gcc11)
@ -344,7 +358,7 @@ 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:-gfx90a;gfx942;gfx1100}" \
--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}" \
@ -441,3 +455,12 @@ elif [ "$HAS_TRITON" = "yes" ]; then
echo "expecting triton to not be installed, but it is"
exit 1
fi
# Sanity check cmake version. Executorch reinstalls cmake and I'm not sure if
# they support 4.0.0 yet, so exclude them from this check.
CMAKE_VERSION=$(drun cmake --version)
if [[ "$EXECUTORCH" != *yes* && "$CMAKE_VERSION" != *4.* ]]; then
echo "CMake version is not 4.0.0:"
drun cmake --version
exit 1
fi

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@ -1 +1 @@
deb42f2a8e48f5032b4a98ee781a15fa87a157cf
56392aa978594cc155fa8af48cd949f5b5f1823a

View File

@ -1,2 +1,2 @@
transformers==4.56.0
transformers==4.54.0
soxr==0.5.0

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

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@ -1 +1 @@
7416ffcb92cdbe98d9f97e4e6f95247e46dfc9fd
5ae38bdb0dc066c5823e34dc9797afb9de42c866

27
.ci/docker/common/install_acl.sh Executable file → Normal file
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@ -1,27 +1,16 @@
#!/bin/bash
# Script used only in CD pipeline
set -euo pipefail
set -eux
ACL_VERSION=${ACL_VERSION:-"v25.02"}
ACL_INSTALL_DIR="/acl"
readonly version=v25.02
readonly src_host=https://github.com/ARM-software
readonly src_repo=ComputeLibrary
# Clone ACL
git clone https://github.com/ARM-software/ComputeLibrary.git -b "${ACL_VERSION}" --depth 1 --shallow-submodules
[[ ! -d ${src_repo} ]] && git clone ${src_host}/${src_repo}.git
cd ${src_repo}
git checkout $version
ACL_CHECKOUT_DIR="ComputeLibrary"
# Build with scons
pushd $ACL_CHECKOUT_DIR
scons -j8 Werror=0 debug=0 neon=1 opencl=0 embed_kernels=0 \
os=linux arch=armv8a build=native multi_isa=1 \
fixed_format_kernels=1 openmp=1 cppthreads=0
popd
# Install ACL
sudo mkdir -p ${ACL_INSTALL_DIR}
for d in arm_compute include utils support src build
do
sudo cp -r ${ACL_CHECKOUT_DIR}/${d} ${ACL_INSTALL_DIR}/${d}
done
rm -rf $ACL_CHECKOUT_DIR

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@ -42,27 +42,22 @@ install_pip_dependencies() {
# A workaround, ExecuTorch has moved to numpy 2.0 which is not compatible with the current
# numba and scipy version used in PyTorch CI
conda_run pip uninstall -y numba scipy
# Yaspin is needed for running CI test (get_benchmark_analysis_data.py)
pip_install yaspin==3.1.0
popd
}
setup_executorch() {
pushd executorch
export PYTHON_EXECUTABLE=python
export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON -DEXECUTORCH_BUILD_TESTS=ON"
export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
as_jenkins .ci/scripts/setup-linux.sh --build-tool cmake || true
popd
}
if [ $# -eq 0 ]; then
clone_executorch
install_buck2
install_conda_dependencies
install_pip_dependencies
pushd executorch
setup_executorch
popd
else
"$@"
fi
clone_executorch
install_buck2
install_conda_dependencies
install_pip_dependencies
setup_executorch

View File

@ -19,8 +19,8 @@ pip_install \
transformers==4.36.2
pip_install coloredlogs packaging
pip_install onnxruntime==1.23.0
pip_install onnxscript==0.5.3
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/

12
.ci/docker/common/install_openblas.sh Executable file → Normal file
View File

@ -3,10 +3,8 @@
set -ex
OPENBLAS_VERSION=${OPENBLAS_VERSION:-"v0.3.30"}
# Clone OpenBLAS
git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION}" --depth 1 --shallow-submodules
cd /
git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION:-v0.3.30}" --depth 1 --shallow-submodules
OPENBLAS_CHECKOUT_DIR="OpenBLAS"
OPENBLAS_BUILD_FLAGS="
@ -19,7 +17,5 @@ CFLAGS=-O3
BUILD_BFLOAT16=1
"
make -j8 ${OPENBLAS_BUILD_FLAGS} -C $OPENBLAS_CHECKOUT_DIR
sudo make install -C $OPENBLAS_CHECKOUT_DIR
rm -rf $OPENBLAS_CHECKOUT_DIR
make -j8 ${OPENBLAS_BUILD_FLAGS} -C ${OPENBLAS_CHECKOUT_DIR}
make -j8 ${OPENBLAS_BUILD_FLAGS} install -C ${OPENBLAS_CHECKOUT_DIR}

View File

@ -42,6 +42,12 @@ EOF
rocm_baseurl="http://repo.radeon.com/rocm/apt/${ROCM_VERSION}"
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu"
# Special case for ROCM_VERSION == 7.0
if [[ $(ver "$ROCM_VERSION") -eq $(ver 7.0) ]]; then
rocm_baseurl="https://repo.radeon.com/rocm/apt/7.0_alpha2"
amdgpu_baseurl="https://repo.radeon.com/amdgpu/30.10_alpha2/ubuntu"
fi
# Add amdgpu repository
UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
echo "deb [arch=amd64] ${amdgpu_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list

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@ -12,8 +12,8 @@ function do_install() {
rocm_version_nodot=${rocm_version//./}
# https://github.com/icl-utk-edu/magma/pull/65
MAGMA_VERSION=d6e4117bc88e73f06d26c6c2e14f064e8fc3d1ec
# Version 2.7.2 + ROCm related updates
MAGMA_VERSION=a1625ff4d9bc362906bd01f805dbbe12612953f6
magma_archive="magma-rocm${rocm_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
rocm_dir="/opt/rocm"

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@ -66,15 +66,15 @@ if [ -n "${UBUNTU_VERSION}" ] && [ -n "${GCC_VERSION}" ] && [[ "${GCC_VERSION}"
# Triton needs at least gcc-9 to build
apt-get install -y g++-9
CXX=g++-9 conda_run python -m build --wheel --no-isolation
CXX=g++-9 conda_run python setup.py bdist_wheel
elif [ -n "${UBUNTU_VERSION}" ] && [ -n "${CLANG_VERSION}" ]; then
# Triton needs <filesystem> which surprisingly is not available with clang-9 toolchain
add-apt-repository -y ppa:ubuntu-toolchain-r/test
apt-get install -y g++-9
CXX=g++-9 conda_run python -m build --wheel --no-isolation
CXX=g++-9 conda_run python setup.py bdist_wheel
else
conda_run python -m build --wheel --no-isolation
conda_run python setup.py bdist_wheel
fi
# Copy the wheel to /opt for multi stage docker builds

View File

@ -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

View File

@ -40,16 +40,12 @@ case ${DOCKER_TAG_PREFIX} in
;;
rocm*)
# we want the patch version of 6.4 instead
if [[ "$GPU_ARCH_VERSION" == *"6.4"* ]]; then
if [[ $(ver $GPU_ARCH_VERSION) -eq $(ver 6.4) ]]; then
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
fi
BASE_TARGET=rocm
GPU_IMAGE=rocm/dev-ubuntu-22.04:${GPU_ARCH_VERSION}-complete
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
# add gfx950, gfx115x conditionally starting in ROCm 7.0
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
fi
DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg ROCM_VERSION=${GPU_ARCH_VERSION}"
;;
*)

View File

@ -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 && \

View File

@ -62,13 +62,6 @@ ARG OPENBLAS_VERSION
ADD ./common/install_openblas.sh install_openblas.sh
RUN bash ./install_openblas.sh && rm install_openblas.sh
# Install Arm Compute Library
FROM base as arm_compute
# use python3.9 to install scons
RUN python3.9 -m pip install scons==4.7.0
RUN ln -sf /opt/python/cp39-cp39/bin/scons /usr/local/bin
COPY ./common/install_acl.sh install_acl.sh
RUN bash ./install_acl.sh && rm install_acl.sh
FROM base as final
# remove unnecessary python versions
@ -77,7 +70,4 @@ RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
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/:$LD_LIBRARY_PATH
ADD ./common/patch_libstdc.sh patch_libstdc.sh
RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH

View File

@ -86,15 +86,6 @@ FROM base as nvpl
ADD ./common/install_nvpl.sh install_nvpl.sh
RUN bash ./install_nvpl.sh && rm install_nvpl.sh
# Install Arm Compute Library
FROM base as arm_compute
# use python3.9 to install scons
RUN python3.9 -m pip install scons==4.7.0
RUN ln -sf /opt/python/cp39-cp39/bin/scons /usr/local/bin
COPY ./common/install_acl.sh install_acl.sh
RUN bash ./install_acl.sh && rm install_acl.sh
FROM base as final
FROM final as cuda_final
ARG BASE_CUDA_VERSION
RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
@ -102,9 +93,5 @@ COPY --from=cuda /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BAS
COPY --from=magma /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=nvpl /opt/nvpl/lib/ /usr/local/lib/
COPY --from=nvpl /opt/nvpl/include/ /usr/local/include/
COPY --from=arm_compute /acl /acl
RUN ln -sf /usr/local/cuda-${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

View File

@ -0,0 +1,71 @@
FROM centos:8 as base
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
ENV PATH /opt/rh/gcc-toolset-11/root/bin/:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# change to a valid repo
RUN sed -i 's|#baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-Linux-*.repo
# enable to install ninja-build
RUN sed -i 's|enabled=0|enabled=1|g' /etc/yum.repos.d/CentOS-Linux-PowerTools.repo
RUN yum -y update
RUN yum install -y wget curl perl util-linux xz bzip2 git patch which zlib-devel sudo
RUN yum install -y autoconf automake make cmake gdb gcc-toolset-11-gcc-c++
FROM base as openssl
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
# Install python
FROM base as python
RUN yum install -y openssl-devel zlib-devel bzip2-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel libpcap-devel xz-devel libffi-devel
ADD common/install_cpython.sh install_cpython.sh
RUN bash ./install_cpython.sh && rm install_cpython.sh
FROM base as conda
ADD ./common/install_conda_docker.sh install_conda.sh
RUN bash ./install_conda.sh && rm install_conda.sh
RUN /opt/conda/bin/conda install -y cmake
FROM base as intel
# Install MKL
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
COPY --from=conda /opt/conda /opt/conda
ENV PATH=/opt/conda/bin:$PATH
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
FROM base as patchelf
ADD ./common/install_patchelf.sh install_patchelf.sh
RUN bash ./install_patchelf.sh && rm install_patchelf.sh
RUN cp $(which patchelf) /patchelf
FROM base as jni
ADD ./common/install_jni.sh install_jni.sh
ADD ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
FROM base as libpng
ADD ./common/install_libpng.sh install_libpng.sh
RUN bash ./install_libpng.sh && rm install_libpng.sh
FROM base as final
COPY --from=openssl /opt/openssl /opt/openssl
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
COPY --from=intel /opt/intel /opt/intel
COPY --from=conda /opt/conda /opt/conda
COPY --from=patchelf /usr/local/bin/patchelf /usr/local/bin/patchelf
COPY --from=jni /usr/local/include/jni.h /usr/local/include/jni.h
COPY --from=libpng /usr/local/bin/png* /usr/local/bin/
COPY --from=libpng /usr/local/bin/libpng* /usr/local/bin/
COPY --from=libpng /usr/local/include/png* /usr/local/include/
COPY --from=libpng /usr/local/include/libpng* /usr/local/include/
COPY --from=libpng /usr/local/lib/libpng* /usr/local/lib/
COPY --from=libpng /usr/local/lib/pkgconfig /usr/local/lib/pkgconfig
RUN yum install -y ninja-build

View File

@ -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.

View File

@ -28,7 +28,6 @@ fi
MANY_LINUX_VERSION=${MANY_LINUX_VERSION:-}
DOCKERFILE_SUFFIX=${DOCKERFILE_SUFFIX:-}
OPENBLAS_VERSION=${OPENBLAS_VERSION:-}
ACL_VERSION=${ACL_VERSION:-}
case ${image} in
manylinux2_28-builder:cpu)
@ -42,6 +41,13 @@ case ${image} in
GPU_IMAGE=arm64v8/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13 --build-arg NINJA_VERSION=1.12.1"
MANY_LINUX_VERSION="2_28_aarch64"
OPENBLAS_VERSION="v0.3.30"
;;
manylinuxcxx11-abi-builder:cpu-cxx11-abi)
TARGET=final
GPU_IMAGE=""
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
MANY_LINUX_VERSION="cxx11-abi"
;;
manylinuxs390x-builder:cpu-s390x)
TARGET=final
@ -76,7 +82,7 @@ case ${image} in
;;
manylinux2_28-builder:rocm*)
# we want the patch version of 6.4 instead
if [[ "$GPU_ARCH_VERSION" == *"6.4"* ]]; then
if [[ $(ver $GPU_ARCH_VERSION) -eq $(ver 6.4) ]]; then
GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
fi
TARGET=rocm_final
@ -84,10 +90,6 @@ case ${image} in
DEVTOOLSET_VERSION="11"
GPU_IMAGE=rocm/dev-almalinux-8:${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
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950;gfx1150;gfx1151"
fi
DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
;;
manylinux2_28-builder:xpu)
@ -119,8 +121,7 @@ tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
DOCKER_BUILDKIT=1 docker build \
${DOCKER_GPU_BUILD_ARG} \
--build-arg "GPU_IMAGE=${GPU_IMAGE}" \
--build-arg "OPENBLAS_VERSION=${OPENBLAS_VERSION:-}" \
--build-arg "ACL_VERSION=${ACL_VERSION:-}" \
--build-arg "OPENBLAS_VERSION=${OPENBLAS_VERSION}" \
--target "${TARGET}" \
-t "${tmp_tag}" \
$@ \

View File

@ -10,11 +10,6 @@ boto3==1.35.42
#Pinned versions: 1.19.12, 1.16.34
#test that import:
build==1.3.0
#Description: A simple, correct Python build frontend.
#Pinned versions: 1.3.0
#test that import:
click
#Description: Command Line Interface Creation Kit
#Pinned versions:
@ -52,10 +47,10 @@ flatbuffers==24.12.23
#Pinned versions: 24.12.23
#test that import:
hypothesis==6.56.4
hypothesis==5.35.1
# Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
#Description: advanced library for generating parametrized tests
#Pinned versions: 6.56.4
#Pinned versions: 5.35.1
#test that import: test_xnnpack_integration.py, test_pruning_op.py, test_nn.py
junitparser==2.1.1
@ -98,9 +93,8 @@ librosa==0.10.2 ; python_version == "3.12" and platform_machine != "s390x"
#Pinned versions:
#test that import:
mypy==1.16.0 ; platform_system == "Linux"
mypy==1.16.0
# Pin MyPy version because new errors are likely to appear with each release
# Skip on Windows as lots of type annotations are POSIX specific
#Description: linter
#Pinned versions: 1.16.0
#test that import: test_typing.py, test_type_hints.py
@ -111,17 +105,20 @@ networkx==2.8.8
#Pinned versions: 2.8.8
#test that import: functorch
ninja==1.11.1.4
ninja==1.11.1.3
#Description: build system. Used in some tests. Used in build to generate build
#time tracing information
#Pinned versions: 1.11.1.4
#Pinned versions: 1.11.1.3
#test that import: run_test.py, test_cpp_extensions_aot.py,test_determination.py
numba==0.49.0 ; python_version < "3.9" and platform_machine != "s390x"
numba==0.55.2 ; python_version == "3.9" and platform_machine != "s390x"
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
@ -136,7 +133,7 @@ numba==0.60.0 ; python_version == "3.12" and platform_machine != "s390x"
#test_nn.py, test_namedtensor.py, test_linalg.py, test_jit_cuda_fuser.py,
#test_jit.py, test_indexing.py, test_datapipe.py, test_dataloader.py,
#test_binary_ufuncs.py
numpy==1.22.4; python_version == "3.10"
numpy==1.22.4; python_version == "3.9" or python_version == "3.10"
numpy==1.26.2; python_version == "3.11" or python_version == "3.12"
numpy==2.1.2; python_version >= "3.13"
@ -168,12 +165,12 @@ optree==0.13.0
pillow==11.0.0
#Description: Python Imaging Library fork
#Pinned versions: 11.0.0
#Pinned versions: 10.3.0
#test that import:
protobuf==5.29.5
protobuf==5.29.4
#Description: Google's data interchange format
#Pinned versions: 5.29.5
#Pinned versions: 5.29.4
#test that import: test_tensorboard.py, test/onnx/*
psutil
@ -216,7 +213,7 @@ pytest-subtests==0.13.1
#Pinned versions:
#test that import:
xdoctest==1.3.0
xdoctest==1.1.0
#Description: runs doctests in pytest
#Pinned versions: 1.1.0
#test that import:
@ -241,9 +238,10 @@ 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
@ -266,7 +264,7 @@ scipy==1.14.1 ; python_version >= "3.12"
#test that import:
# needed by torchgen utils
typing-extensions==4.12.2
typing-extensions>=4.10.0
#Description: type hints for python
#Pinned versions:
#test that import:
@ -327,6 +325,8 @@ pywavelets==1.7.0 ; python_version >= "3.12"
lxml==5.3.0
#Description: This is a requirement of unittest-xml-reporting
# Python-3.9 binaries
PyGithub==2.3.0
sympy==1.13.3
@ -339,7 +339,7 @@ onnx==1.18.0
#Pinned versions:
#test that import:
onnxscript==0.5.3
onnxscript==0.4.0
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
@ -359,10 +359,9 @@ pwlf==2.2.1
#test that import: test_sac_estimator.py
# To build PyTorch itself
pyyaml==6.0.2
pyyaml
pyzstd
setuptools==78.1.1
packaging==23.1
setuptools>=70.1.0
six
scons==4.5.2 ; platform_machine == "aarch64"
@ -377,16 +376,13 @@ dataclasses_json==0.6.7
#Pinned versions: 0.6.7
#test that import:
cmake==3.31.6
cmake==4.0.0
#Description: required for building
tlparse==0.4.0
#Description: required for log parsing
filelock==3.18.0
#Description: required for inductor testing
cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x" and platform_system != "Darwin"
cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x"
#Description: required for testing CUDAGraph::raw_cuda_graph(). See https://nvidia.github.io/cuda-python/cuda-bindings/latest/support.html for how this version was chosen. Note "Any fix in the latest bindings would be backported to the prior major version" means that only the newest version of cuda-bindings will get fixes. Depending on the latest version of 12.x is okay because all 12.y versions will be supported via "CUDA minor version compatibility". Pytorch builds against 13.z versions of cuda toolkit work with 12.x versions of cuda-bindings as well because newer drivers work with old toolkits.
#test that import: test_cuda.py

View File

@ -1,15 +1,8 @@
sphinx==5.3.0
#Description: This is used to generate PyTorch docs
#Pinned versions: 5.3.0
-e git+https://github.com/pytorch/pytorch_sphinx_theme.git@1657ad2fc1acdc98aa719eebecbb0128a7c13ce4#egg=pytorch_sphinx_theme2
standard-imghdr==3.13.0; python_version >= "3.13"
#Description: This is needed by Sphinx, so it needs to be added here.
# The reasons are as follows:
# 1) This module has been removed from the Python standard library since Python 3.13(https://peps.python.org/pep-0594/#imghdr);
# 2) The current version of Sphinx (5.3.0) is not compatible with Python 3.13.
# Once Sphinx is upgraded to a version compatible with Python 3.13 or later, we can remove this dependency.
-e git+https://github.com/pytorch/pytorch_sphinx_theme.git@71e55749be14ceb56e7f8211a9fb649866b87ad4#egg=pytorch_sphinx_theme2
# TODO: sphinxcontrib.katex 0.9.0 adds a local KaTeX server to speed up pre-rendering
# but it doesn't seem to work and hangs around idly. The initial thought that it is probably
# something related to Docker setup. We can investigate this later.

View File

@ -7,4 +7,4 @@ set -ex
SCRIPTPATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
USE_NVSHMEM=0 USE_CUSPARSELT=0 BUILD_PYTHONLESS=1 DESIRED_PYTHON="3.10" ${SCRIPTPATH}/../manywheel/build.sh
USE_NVSHMEM=0 USE_CUSPARSELT=0 BUILD_PYTHONLESS=1 DESIRED_PYTHON="3.9" ${SCRIPTPATH}/../manywheel/build.sh

View File

@ -41,6 +41,7 @@ def sample_vllm_test_library():
"pytest -v -s basic_correctness/test_cumem.py",
"pytest -v -s basic_correctness/test_basic_correctness.py",
"pytest -v -s basic_correctness/test_cpu_offload.py",
"VLLM_TEST_ENABLE_ARTIFICIAL_PREEMPT=1 pytest -v -s basic_correctness/test_preemption.py",
],
},
"vllm_basic_models_test": {
@ -67,12 +68,15 @@ def sample_vllm_test_library():
"-v",
"-s",
"entrypoints/llm",
"--ignore=entrypoints/llm/test_lazy_outlines.py",
"--ignore=entrypoints/llm/test_generate.py",
"--ignore=entrypoints/llm/test_generate_multiple_loras.py",
"--ignore=entrypoints/llm/test_collective_rpc.py",
]
),
"pytest -v -s entrypoints/llm/test_generate.py",
"pytest -v -s entrypoints/offline_mode",
"pytest -v -s entrypoints/llm/test_lazy_outlines.py",
"pytest -v -s entrypoints/llm/test_generate.py ",
"VLLM_USE_V1=0 pytest -v -s entrypoints/offline_mode",
],
},
"vllm_regression_test": {

View File

@ -1,11 +1,11 @@
SHELL=/usr/bin/env bash
DOCKER_CMD ?= docker
DESIRED_ROCM ?= 7.0
DESIRED_ROCM ?= 6.4
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;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 \
@ -16,20 +16,20 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
magma-rocm/build_magma.sh
.PHONY: all
all: magma-rocm70
all: magma-rocm64
all: magma-rocm63
.PHONY:
clean:
$(RM) -r magma-*
$(RM) -r output
.PHONY: magma-rocm70
magma-rocm70: DESIRED_ROCM := 7.0
magma-rocm70:
$(DOCKER_RUN)
.PHONY: magma-rocm64
magma-rocm64: DESIRED_ROCM := 6.4
magma-rocm64:
$(DOCKER_RUN)
.PHONY: magma-rocm63
magma-rocm63: DESIRED_ROCM := 6.3
magma-rocm63:
$(DOCKER_RUN)

View File

@ -6,8 +6,8 @@ set -eou pipefail
# The script expects DESIRED_CUDA and PACKAGE_NAME to be set
ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
# https://github.com/icl-utk-edu/magma/pull/65
MAGMA_VERSION=d6e4117bc88e73f06d26c6c2e14f064e8fc3d1ec
# Version 2.7.2 + ROCm related updates
MAGMA_VERSION=a1625ff4d9bc362906bd01f805dbbe12612953f6
# Folders for the build
PACKAGE_FILES=${ROOT_DIR}/magma-rocm/package_files # metadata
@ -20,7 +20,7 @@ mkdir -p ${PACKAGE_DIR} ${PACKAGE_OUTPUT}/linux-64 ${PACKAGE_BUILD} ${PACKAGE_RE
# Fetch magma sources and verify checksum
pushd ${PACKAGE_DIR}
git clone https://github.com/jeffdaily/magma
git clone https://bitbucket.org/icl/magma.git
pushd magma
git checkout ${MAGMA_VERSION}
popd

View File

@ -142,7 +142,7 @@ time CMAKE_ARGS=${CMAKE_ARGS[@]} \
EXTRA_CAFFE2_CMAKE_FLAGS=${EXTRA_CAFFE2_CMAKE_FLAGS[@]} \
BUILD_LIBTORCH_CPU_WITH_DEBUG=$BUILD_DEBUG_INFO \
USE_NCCL=${USE_NCCL} USE_RCCL=${USE_RCCL} USE_KINETO=${USE_KINETO} \
python -m build --wheel --no-isolation --outdir /tmp/$WHEELHOUSE_DIR
python setup.py bdist_wheel -d /tmp/$WHEELHOUSE_DIR
echo "Finished setup.py bdist at $(date)"
# Build libtorch packages

View File

@ -104,7 +104,7 @@ if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
export ROCclr_DIR=/opt/rocm/rocclr/lib/cmake/rocclr
fi
echo "Calling -m pip install . -v --no-build-isolation at $(date)"
echo "Calling 'python -m pip install .' at $(date)"
if [[ $LIBTORCH_VARIANT = *"static"* ]]; then
STATIC_CMAKE_FLAG="-DTORCH_STATIC=1"

View File

@ -107,10 +107,6 @@ if [[ $ROCM_INT -ge 60200 ]]; then
ROCM_SO_FILES+=("librocm-core.so")
fi
if [[ $ROCM_INT -ge 70000 ]]; then
ROCM_SO_FILES+=("librocroller.so")
fi
OS_NAME=`awk -F= '/^NAME/{print $2}' /etc/os-release`
if [[ "$OS_NAME" == *"CentOS Linux"* || "$OS_NAME" == *"AlmaLinux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"

View File

@ -89,7 +89,7 @@ fi
if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
export USE_MKLDNN=1
export USE_MKLDNN_ACL=1
export ACL_ROOT_DIR=/acl
export ACL_ROOT_DIR=/ComputeLibrary
fi
if [[ "$BUILD_ENVIRONMENT" == *riscv64* ]]; then
@ -290,13 +290,13 @@ else
WERROR=1 python setup.py clean
WERROR=1 python -m build --wheel --no-isolation
WERROR=1 python setup.py bdist_wheel
else
python setup.py clean
if [[ "$BUILD_ENVIRONMENT" == *xla* ]]; then
source .ci/pytorch/install_cache_xla.sh
fi
python -m build --wheel --no-isolation
python setup.py bdist_wheel
fi
pip_install_whl "$(echo dist/*.whl)"

View File

@ -58,7 +58,7 @@ time python tools/setup_helpers/generate_code.py \
# Build the docs
pushd docs/cpp
time make VERBOSE=1 html
time make VERBOSE=1 html -j
popd
popd

View File

@ -0,0 +1,40 @@
#!/bin/bash
# This is where the local pytorch install in the docker image is located
pt_checkout="/var/lib/jenkins/workspace"
source "$pt_checkout/.ci/pytorch/common_utils.sh"
echo "functorch_doc_push_script.sh: Invoked with $*"
set -ex -o pipefail
version=${DOCS_VERSION:-nightly}
echo "version: $version"
# Build functorch docs
pushd $pt_checkout/functorch/docs
make html
popd
git clone https://github.com/pytorch/functorch -b gh-pages --depth 1 functorch_ghpages
pushd functorch_ghpages
if [ "$version" == "main" ]; then
version=nightly
fi
git rm -rf "$version" || true
mv "$pt_checkout/functorch/docs/build/html" "$version"
git add "$version" || true
git status
git config user.email "soumith+bot@pytorch.org"
git config user.name "pytorchbot"
# If there aren't changes, don't make a commit; push is no-op
git commit -m "Generate Python docs from pytorch/pytorch@${GITHUB_SHA}" || true
git status
if [[ "${WITH_PUSH:-}" == true ]]; then
git push -u origin gh-pages
fi
popd

View File

@ -35,12 +35,11 @@ fi
print_cmake_info
if [[ ${BUILD_ENVIRONMENT} == *"distributed"* ]]; then
# Needed for inductor benchmarks, as lots of HF networks make `torch.distribtued` calls
USE_DISTRIBUTED=1 USE_OPENMP=1 WERROR=1 python -m build --wheel --no-isolation
USE_OPENMP=1 WERROR=1 python setup.py bdist_wheel
else
# Explicitly set USE_DISTRIBUTED=0 to align with the default build config on mac. This also serves as the sole CI config that tests
# that building with USE_DISTRIBUTED=0 works at all. See https://github.com/pytorch/pytorch/issues/86448
USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python -m build --wheel --no-isolation -C--build-option=--plat-name=macosx_11_0_arm64
# NB: we always build with distributed; USE_DISTRIBUTED turns off all
# backends (specifically the gloo backend), so test that this case works too
USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel --plat-name macosx_11_0_arm64
fi
if which sccache > /dev/null; then
print_sccache_stats

View File

@ -13,9 +13,13 @@ if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available(
fi
popd
python -mpip install -r requirements.txt
# enable debug asserts in serialization
export TORCH_SERIALIZATION_DEBUG=1
python -mpip install --no-input -r requirements.txt
setup_test_python() {
# The CircleCI worker hostname doesn't resolve to an address.
# This environment variable makes ProcessGroupGloo default to
@ -55,7 +59,7 @@ test_python_shard() {
setup_test_python
time python test/run_test.py --verbose --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests --shard "$1" "$NUM_TEST_SHARDS"
time python test/run_test.py --verbose --exclude-jit-executor --exclude-distributed-tests --shard "$1" "$NUM_TEST_SHARDS"
assert_git_not_dirty
}

View File

@ -26,7 +26,6 @@ if [[ "${SHARD_NUMBER:-2}" == "2" ]]; then
time python test/run_test.py --verbose -i distributed/test_c10d_spawn_gloo
time python test/run_test.py --verbose -i distributed/test_c10d_spawn_nccl
time python test/run_test.py --verbose -i distributed/test_compute_comm_reordering
time python test/run_test.py --verbose -i distributed/test_aten_comm_compute_reordering
time python test/run_test.py --verbose -i distributed/test_store
time python test/run_test.py --verbose -i distributed/test_symmetric_memory
time python test/run_test.py --verbose -i distributed/test_pg_wrapper

View File

@ -1,25 +0,0 @@
From 6e08c9d08e9de59c7af28b720289debbbd384764 Mon Sep 17 00:00:00 2001
From: Michael Wang <13521008+isVoid@users.noreply.github.com>
Date: Tue, 1 Apr 2025 17:28:05 -0700
Subject: [PATCH] Avoid bumping certain driver API to avoid future breakage
(#185)
Co-authored-by: isVoid <isVoid@users.noreply.github.com>
---
numba_cuda/numba/cuda/cudadrv/driver.py | 3 +++
1 file changed, 3 insertions(+)
diff --git a/numba_cuda/numba/cuda/cudadrv/driver.py b/numba_cuda/numba/cuda/cudadrv/driver.py
index 1641bf77..233e9ed7 100644
--- a/numba_cuda/numba/cuda/cudadrv/driver.py
+++ b/numba_cuda/numba/cuda/cudadrv/driver.py
@@ -365,6 +365,9 @@ def _find_api(self, fname):
else:
variants = ('_v2', '')
+ if fname in ("cuCtxGetDevice", "cuCtxSynchronize"):
+ return getattr(self.lib, fname)
+
for variant in variants:
try:
return getattr(self.lib, f'{fname}{variant}')

View File

@ -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__":

View File

@ -32,18 +32,6 @@ if [[ "$BUILD_ENVIRONMENT" != *rocm* && "$BUILD_ENVIRONMENT" != *s390x* && -d /v
git config --global --add safe.directory /var/lib/jenkins/workspace
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
fi
echo "Environment variables:"
env
@ -324,29 +312,23 @@ test_python_shard() {
# modify LD_LIBRARY_PATH to ensure it has the conda env.
# This set of tests has been shown to be buggy without it for the split-build
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
assert_git_not_dirty
}
test_python() {
# shellcheck disable=SC2086
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests $INCLUDE_CLAUSE --verbose $PYTHON_TEST_EXTRA_OPTION
time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --verbose $PYTHON_TEST_EXTRA_OPTION
assert_git_not_dirty
}
test_python_smoke() {
# Smoke tests for H100/B200
# Smoke tests for H100
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 inductor/test_fp8 $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
assert_git_not_dirty
}
test_h100_distributed() {
# Distributed tests at H100
time python test/run_test.py --include distributed/_composable/test_composability/test_pp_composability.py $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
@ -392,7 +374,6 @@ test_dynamo_wrapped_shard() {
--exclude-distributed-tests \
--exclude-torch-export-tests \
--exclude-aot-dispatch-tests \
--exclude-quantization-tests \
--shard "$1" "$NUM_TEST_SHARDS" \
--verbose \
--upload-artifacts-while-running
@ -437,7 +418,7 @@ test_inductor_distributed() {
# this runs on both single-gpu and multi-gpu instance. It should be smart about skipping tests that aren't supported
# with if required # gpus aren't available
python test/run_test.py --include distributed/test_dynamo_distributed distributed/test_inductor_collectives distributed/test_aten_comm_compute_reordering distributed/test_compute_comm_reordering --verbose
python test/run_test.py --include distributed/test_dynamo_distributed distributed/test_inductor_collectives distributed/test_compute_comm_reordering --verbose
assert_git_not_dirty
}
@ -886,7 +867,7 @@ 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_$test.csv"
python benchmarks/dynamo/check_accuracy.py \
@ -1165,12 +1146,6 @@ test_distributed() {
fi
}
test_quantization() {
echo "Testing quantization"
python test/test_quantization.py
}
test_rpc() {
echo "Testing RPC C++ tests"
# NB: the ending test_rpc must match the current function name for the current
@ -1417,7 +1392,7 @@ EOF
pip3 install -r requirements.txt
# shellcheck source=./common-build.sh
source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
python -m build --wheel --no-isolation -C--build-option=--bdist-dir="base_bdist_tmp" --outdir "base_dist"
python setup.py bdist_wheel --bdist-dir="base_bdist_tmp" --dist-dir="base_dist"
python -mpip install base_dist/*.whl
echo "::endgroup::"
@ -1565,10 +1540,14 @@ test_executorch() {
install_torchvision
install_torchaudio
INSTALL_SCRIPT="$(pwd)/.ci/docker/common/install_executorch.sh"
pushd /executorch
"${INSTALL_SCRIPT}" setup_executorch
export PYTHON_EXECUTABLE=python
export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
# NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
# from the PR
bash .ci/scripts/setup-linux.sh --build-tool cmake
echo "Run ExecuTorch unit tests"
pytest -v -n auto
@ -1582,14 +1561,17 @@ test_executorch() {
popd
# Test torchgen generated code for Executorch.
echo "Testing ExecuTorch op registration"
"$BUILD_BIN_DIR"/test_edge_op_registration
assert_git_not_dirty
}
test_linux_aarch64() {
python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
test_transformers test_multiprocessing test_numpy_interop test_autograd test_binary_ufuncs test_complex test_spectral_ops \
test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops profiler/test_memory_profiler \
distributed/elastic/timer/api_test distributed/elastic/timer/local_timer_example distributed/elastic/timer/local_timer_test \
test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
--shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
# Dynamo tests
@ -1619,7 +1601,7 @@ test_operator_benchmark() {
test_inductor_set_cpu_affinity
cd benchmarks/operator_benchmark/pt_extension
python -m pip install . -v --no-build-isolation
python -m pip install .
cd "${TEST_DIR}"/benchmarks/operator_benchmark
$TASKSET python -m benchmark_all_test --device "$1" --tag-filter "$2" \
@ -1632,25 +1614,6 @@ test_operator_benchmark() {
--expected "expected_ci_operator_benchmark_eager_float32_cpu.csv"
}
test_operator_microbenchmark() {
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
TEST_DIR=$(pwd)
cd benchmarks/operator_benchmark/pt_extension
python -m pip install .
cd "${TEST_DIR}"/benchmarks/operator_benchmark
for OP_BENCHMARK_TESTS in matmul mm addmm bmm; do
$TASKSET python -m pt.${OP_BENCHMARK_TESTS}_test --tag-filter long \
--output-json-for-dashboard "${TEST_REPORTS_DIR}/operator_microbenchmark_${OP_BENCHMARK_TESTS}_compile.json" \
--benchmark-name "PyTorch operator microbenchmark" --use-compile
$TASKSET python -m pt.${OP_BENCHMARK_TESTS}_test --tag-filter long \
--output-json-for-dashboard "${TEST_REPORTS_DIR}/operator_microbenchmark_${OP_BENCHMARK_TESTS}.json" \
--benchmark-name "PyTorch operator microbenchmark"
done
}
if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-bazel-* ]]; then
(cd test && python -c "import torch; print(torch.__config__.show())")
@ -1683,8 +1646,6 @@ elif [[ "${TEST_CONFIG}" == *executorch* ]]; then
test_executorch
elif [[ "$TEST_CONFIG" == 'jit_legacy' ]]; then
test_python_legacy_jit
elif [[ "$TEST_CONFIG" == 'quantization' ]]; then
test_quantization
elif [[ "${BUILD_ENVIRONMENT}" == *libtorch* ]]; then
# TODO: run some C++ tests
echo "no-op at the moment"
@ -1707,8 +1668,6 @@ elif [[ "${TEST_CONFIG}" == *operator_benchmark* ]]; then
test_operator_benchmark cpu ${TEST_MODE}
fi
elif [[ "${TEST_CONFIG}" == *operator_microbenchmark* ]]; then
test_operator_microbenchmark
elif [[ "${TEST_CONFIG}" == *inductor_distributed* ]]; then
test_inductor_distributed
elif [[ "${TEST_CONFIG}" == *inductor-halide* ]]; then
@ -1811,14 +1770,10 @@ elif [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
test_xpu_bin
elif [[ "${TEST_CONFIG}" == smoke ]]; then
test_python_smoke
elif [[ "${TEST_CONFIG}" == smoke_b200 ]]; then
test_python_smoke_b200
elif [[ "${TEST_CONFIG}" == h100_distributed ]]; then
test_h100_distributed
elif [[ "${TEST_CONFIG}" == "h100-symm-mem" ]]; then
test_h100_symm_mem
elif [[ "${TEST_CONFIG}" == "b200-symm-mem" ]]; then
test_h100_symm_mem
elif [[ "${TEST_CONFIG}" == h100_cutlass_backend ]]; then
test_h100_cutlass_backend
else

View File

@ -1,32 +0,0 @@
#!/bin/bash
set -ex -o pipefail
# Suppress ANSI color escape sequences
export TERM=vt100
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
# shellcheck source=./common-build.sh
source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
echo "Environment variables"
env
echo "Testing FA3 stable wheel still works with currently built torch"
echo "Installing ABI Stable FA3 wheel"
# The wheel was built on https://github.com/Dao-AILab/flash-attention/commit/b3846b059bf6b143d1cd56879933be30a9f78c81
# on torch nightly torch==2.9.0.dev20250830+cu129
$MAYBE_SUDO pip -q install https://s3.amazonaws.com/ossci-linux/wheels/flash_attn_3-3.0.0b1-cp39-abi3-linux_x86_64.whl
pushd flash-attention/hopper
export PYTHONPATH=$PWD
pytest -v -s \
"test_flash_attn.py::test_flash_attn_output[1-1-192-False-False-False-0.0-False-False-mha-dtype0]" \
"test_flash_attn.py::test_flash_attn_varlen_output[511-1-64-True-False-False-0.0-False-False-gqa-dtype2]" \
"test_flash_attn.py::test_flash_attn_kvcache[1-128-128-False-False-True-None-0.0-False-False-True-False-True-False-gqa-dtype0]" \
"test_flash_attn.py::test_flash_attn_race_condition[97-97-192-True-dtype0]" \
"test_flash_attn.py::test_flash_attn_combine[2-3-64-dtype1]" \
"test_flash_attn.py::test_flash3_bw_compatibility"
popd

View File

@ -70,7 +70,7 @@ sccache --zero-stats
sccache --show-stats
# Build the wheel
python -m build --wheel --no-build-isolation
python setup.py bdist_wheel
if ($LASTEXITCODE -ne 0) { exit 1 }
# Install the wheel locally

View File

@ -38,12 +38,10 @@ if errorlevel 1 goto fail
if not errorlevel 0 goto fail
:: Update CMake
:: TODO: Investigate why this helps MKL detection, even when CMake from choco is not used
call choco upgrade -y cmake --no-progress --installargs 'ADD_CMAKE_TO_PATH=System' --apply-install-arguments-to-dependencies --version=3.27.9
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
:: TODO: Move to .ci/docker/requirements-ci.txt
call pip install mkl==2024.2.0 mkl-static==2024.2.0 mkl-include==2024.2.0
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
@ -132,14 +130,14 @@ if "%USE_CUDA%"=="1" (
:: Print all existing environment variable for debugging
set
python -m build --wheel --no-isolation
python setup.py bdist_wheel
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
sccache --show-stats
python -c "import os, glob; os.system('python -mpip install --no-index --no-deps ' + glob.glob('dist/*.whl')[0])"
(
if "%BUILD_ENVIRONMENT%"=="" (
echo NOTE: To run `import torch`, please make sure to activate the conda environment by running `call %CONDA_ROOT_DIR%\Scripts\activate.bat %CONDA_ROOT_DIR%\envs\py_tmp` in Command Prompt before running Git Bash.
echo NOTE: To run `import torch`, please make sure to activate the conda environment by running `call %CONDA_PARENT_DIR%\Miniconda3\Scripts\activate.bat %CONDA_PARENT_DIR%\Miniconda3` in Command Prompt before running Git Bash.
) else (
copy /Y "dist\*.whl" "%PYTORCH_FINAL_PACKAGE_DIR%"

View File

@ -3,12 +3,12 @@ if "%BUILD_ENVIRONMENT%"=="" (
) else (
set CONDA_PARENT_DIR=C:\Jenkins
)
set CONDA_ROOT_DIR=%CONDA_PARENT_DIR%\Miniconda3
:: Be conservative here when rolling out the new AMI with conda. This will try
:: to install conda as before if it couldn't find the conda installation. This
:: can be removed eventually after we gain enough confidence in the AMI
if not exist %CONDA_ROOT_DIR% (
if not exist %CONDA_PARENT_DIR%\Miniconda3 (
set INSTALL_FRESH_CONDA=1
)
@ -17,14 +17,10 @@ if "%INSTALL_FRESH_CONDA%"=="1" (
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
%TMP_DIR_WIN%\Miniconda3-latest-Windows-x86_64.exe /InstallationType=JustMe /RegisterPython=0 /S /AddToPath=0 /D=%CONDA_ROOT_DIR%
%TMP_DIR_WIN%\Miniconda3-latest-Windows-x86_64.exe /InstallationType=JustMe /RegisterPython=0 /S /AddToPath=0 /D=%CONDA_PARENT_DIR%\Miniconda3
if errorlevel 1 exit /b
if not errorlevel 0 exit /b
)
:: Activate conda so that we can use its commands, i.e. conda, python, pip
call %CONDA_ROOT_DIR%\Scripts\activate.bat %CONDA_ROOT_DIR%
:: Activate conda so that we can use its commands, i.e. conda, python, pip
call conda activate py_tmp
call pip install -r .ci/docker/requirements-ci.txt
call %CONDA_PARENT_DIR%\Miniconda3\Scripts\activate.bat %CONDA_PARENT_DIR%\Miniconda3

View File

@ -14,7 +14,7 @@ if not errorlevel 0 exit /b
:: build\torch. Rather than changing all these references, making a copy of torch folder
:: from conda to the current workspace is easier. The workspace will be cleaned up after
:: the job anyway
xcopy /s %CONDA_ROOT_DIR%\envs\py_tmp\Lib\site-packages\torch %TMP_DIR_WIN%\build\torch\
xcopy /s %CONDA_PARENT_DIR%\Miniconda3\Lib\site-packages\torch %TMP_DIR_WIN%\build\torch\
pushd .
if "%VC_VERSION%" == "" (

View File

@ -25,7 +25,7 @@ echo Copying over test times file
robocopy /E "%PYTORCH_FINAL_PACKAGE_DIR_WIN%\.additional_ci_files" "%PROJECT_DIR_WIN%\.additional_ci_files"
echo Run nn tests
python run_test.py --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests --shard "%SHARD_NUMBER%" "%NUM_TEST_SHARDS%" --verbose
python run_test.py --exclude-jit-executor --exclude-distributed-tests --shard "%SHARD_NUMBER%" "%NUM_TEST_SHARDS%" --verbose
if ERRORLEVEL 1 goto fail
popd

View File

@ -37,8 +37,23 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
export PYTORCH_TESTING_DEVICE_ONLY_FOR="cuda"
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"
# TODO: Move both of them to Windows AMI
python -m pip install pytest-rerunfailures==10.3 pytest-cpp==2.3.0 tensorboard==2.13.0 protobuf==5.29.4 pytest-subtests==0.13.1
# Install Z3 optional dependency for Windows builds.
python -m pip install z3-solver==4.15.1.0
# Install tlparse for test\dynamo\test_structured_trace.py UTs.
python -m pip install tlparse==0.4.0
# Install parameterized
python -m pip install parameterized==0.8.1
# Install pulp for testing ilps under torch\distributed\_tools
python -m pip install pulp==2.9.0
# Install expecttest to merge https://github.com/pytorch/pytorch/pull/155308
python -m pip install expecttest==0.3.0
run_tests() {
# Run nvidia-smi if available

View File

@ -48,7 +48,7 @@ sccache --zero-stats
sccache --show-stats
:: Call PyTorch build script
python -m build --wheel --no-isolation --outdir "%PYTORCH_FINAL_PACKAGE_DIR%"
python setup.py bdist_wheel -d "%PYTORCH_FINAL_PACKAGE_DIR%"
:: show sccache stats
sccache --show-stats

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

@ -28,5 +28,5 @@ start /wait "" python-amd64.exe /quiet InstallAllUsers=1 PrependPath=0 Include_t
if errorlevel 1 exit /b 1
set "PATH=%CD%\Python\Scripts;%CD%\Python;%PATH%"
%PYTHON_EXEC% -m pip install --upgrade pip setuptools packaging wheel build
%PYTHON_EXEC% -m pip install --upgrade pip setuptools packaging wheel
if errorlevel 1 exit /b 1

View File

@ -86,7 +86,7 @@ copy /Y "%LIBTORCH_PREFIX%-%PYTORCH_BUILD_VERSION%.zip" "%PYTORCH_FINAL_PACKAGE_
goto build_end
:pytorch
%PYTHON_EXEC% -m build --wheel --no-isolation --outdir "%PYTORCH_FINAL_PACKAGE_DIR%"
%PYTHON_EXEC% setup.py bdist_wheel -d "%PYTORCH_FINAL_PACKAGE_DIR%"
:build_end
IF ERRORLEVEL 1 exit /b 1

View File

@ -63,7 +63,7 @@ if errorlevel 1 exit /b 1
call %CONDA_HOME%\condabin\activate.bat testenv
if errorlevel 1 exit /b 1
call conda install -y -q -c conda-forge libuv=1.51
call conda install -y -q -c conda-forge libuv=1.39
call conda install -y -q intel-openmp
echo "install and test libtorch"

View File

@ -18,7 +18,7 @@ if "%DESIRED_PYTHON%" == "3.9" %PYTHON_EXEC% -m pip install numpy==2.0.2 cmake
%PYTHON_EXEC% -m pip install pyyaml
%PYTHON_EXEC% -m pip install mkl-include mkl-static
%PYTHON_EXEC% -m pip install boto3 requests ninja typing_extensions setuptools==72.1.0
%PYTHON_EXEC% -m pip install boto3 ninja typing_extensions setuptools==72.1.0
where cmake.exe

View File

@ -143,8 +143,7 @@ case $desired_python in
RENAME_WHEEL=false
;;
3.13t)
echo "Using 3.13t deps"
mac_version='macosx-11.0-arm64'
echo "Using 3.13 deps"
NUMPY_PINNED_VERSION="==2.1.0"
RENAME_WHEEL=false
;;
@ -178,7 +177,8 @@ source ~/${desired_python}-build/bin/activate
retry pip install "${PINNED_PACKAGES[@]}" -r "${pytorch_rootdir}/requirements.txt"
retry brew install libomp
# For USE_DISTRIBUTED=1 on macOS, need libuv, which is build as part of tensorpipe submodule
# For USE_DISTRIBUTED=1 on macOS, this enables gloo, which needs libuv, which
# is build as part of tensorpipe submodule
export USE_DISTRIBUTED=1
export USE_MKLDNN=OFF
@ -186,11 +186,11 @@ export USE_QNNPACK=OFF
export BUILD_TEST=OFF
pushd "$pytorch_rootdir"
echo "Calling -m build --wheel --no-isolation at $(date)"
echo "Calling setup.py bdist_wheel at $(date)"
_PYTHON_HOST_PLATFORM=${mac_version} ARCHFLAGS="-arch arm64" python -m build --wheel --no-isolation --outdir "$whl_tmp_dir" -C--plat-name="${mac_version//[-.]/_}"
_PYTHON_HOST_PLATFORM=${mac_version} ARCHFLAGS="-arch arm64" python setup.py bdist_wheel -d "$whl_tmp_dir" --plat-name "${mac_version//[-.]/_}"
echo "Finished -m build --wheel --no-isolation at $(date)"
echo "Finished setup.py bdist_wheel at $(date)"
if [[ $package_type != 'libtorch' ]]; then
echo "delocating wheel dependencies"

View File

@ -0,0 +1,47 @@
#!/bin/bash
# =================== The following code **should** be executed inside Docker container ===================
# Install dependencies
sudo apt-get -y update
sudo apt-get -y install expect-dev
# This is where the local pytorch install in the docker image is located
pt_checkout="/var/lib/jenkins/workspace"
source "$pt_checkout/.ci/pytorch/common_utils.sh"
echo "functorch_doc_push_script.sh: Invoked with $*"
set -ex
version=${DOCS_VERSION:-nightly}
echo "version: $version"
# Build functorch docs
pushd $pt_checkout/functorch/docs
pip -q install -r requirements.txt
make html
popd
git clone https://github.com/pytorch/functorch -b gh-pages --depth 1 functorch_ghpages
pushd functorch_ghpages
if [ $version == "main" ]; then
version=nightly
fi
git rm -rf "$version" || true
mv "$pt_checkout/functorch/docs/build/html" "$version"
git add "$version" || true
git status
git config user.email "soumith+bot@pytorch.org"
git config user.name "pytorchbot"
# If there aren't changes, don't make a commit; push is no-op
git commit -m "Generate Python docs from pytorch/pytorch@${GITHUB_SHA}" || true
git status
if [[ "${WITH_PUSH:-}" == true ]]; then
git push -u origin gh-pages
fi
popd
# =================== The above code **should** be executed inside Docker container ===================

View File

@ -59,19 +59,16 @@ 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: '*'
LineFilter:
- name: '/usr/include/.*'
CheckOptions:
cppcoreguidelines-special-member-functions.AllowSoleDefaultDtor: true
cppcoreguidelines-special-member-functions.AllowImplicitlyDeletedCopyOrMove: true

View File

@ -1,10 +1,6 @@
---
name: "⚠️ CI SEV"
about: Tracking incidents for PyTorch's CI infra.
title: ''
labels: ''
assignees: ''
---
> NOTE: Remember to label this issue with "`ci: sev`"

View File

@ -1,18 +0,0 @@
---
name: DISABLE AUTOREVERT
about: Disables autorevert when open
title: "❌​\U0001F519 [DISABLE AUTOREVERT]"
labels: 'ci: disable-autorevert'
assignees: ''
---
This issue, while open, disables the autorevert functionality.
More details can be found [here](https://github.com/pytorch/test-infra/blob/main/aws/lambda/pytorch-auto-revert/README.md)
## Why are you disabling autorevert?
## Links to any issues/commits/errors that shows the source of problem

View File

@ -1,10 +1,8 @@
---
name: Disable CI jobs (PyTorch Dev Infra only)
about: Use this template to disable CI jobs
title: DISABLED [WORKFLOW_NAME] / [PLATFORM_NAME] / [JOB_NAME]
labels: 'module: ci'
assignees: ''
title: "DISABLED [WORKFLOW_NAME] / [PLATFORM_NAME] / [JOB_NAME]"
labels: "module: ci"
---
> For example, DISABLED pull / win-vs2022-cpu-py3 / test (default). Once

View File

@ -21,10 +21,6 @@ self-hosted-runner:
- linux.arm64.2xlarge.ephemeral
- linux.arm64.m7g.4xlarge
- linux.arm64.m7g.4xlarge.ephemeral
- linux.arm64.r7g.12xlarge.memory
- linux.aws.h100
- linux.aws.h100.4
- linux.aws.h100.8
- linux.4xlarge.nvidia.gpu
- linux.8xlarge.nvidia.gpu
- linux.16xlarge.nvidia.gpu

View File

@ -264,7 +264,7 @@ def unzip_artifact_and_replace_files() -> None:
change_content_to_new_version(f"artifacts/dist/{old_stem}/torch/version.py")
for file in Path(f"artifacts/dist/{old_stem}").glob(
"*.dist-info/*",
"*.dist-info/**",
):
change_content_to_new_version(file)

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

@ -6,12 +6,6 @@ inputs:
cuda-version:
description: which cuda version to install, 'cpu' for none
required: true
python-version:
required: false
type: string
default: "3.10"
description: |
The python version to be used. Will be 3.10 by default
runs:
using: composite
@ -44,24 +38,18 @@ runs:
CONDA="C:\Jenkins\Miniconda3\condabin\conda.bat"
{
echo "CONDA=${CONDA}";
echo "CONDA_RUN=${CONDA} run --no-capture-output";
echo "CONDA_BUILD=${CONDA} run conda-build";
echo "CONDA_INSTALL=${CONDA} install";
} >> "${GITHUB_ENV}"
- name: Setup Python3
env:
PYTHON_VERSION: ${{ inputs.python-version }}
shell: bash
run: |
set +e
set -x
# Create new py_tmp env with python-version
${CONDA} create -y -n py_tmp python=${PYTHON_VERSION} intel-openmp libuv
PYTHON3=$(${CONDA_RUN} -n py_tmp which python3)
PYTHON3=$(${CONDA_RUN} which python3)
EXIT_CODE=$?
if [[ "${EXIT_CODE}" == "0" ]]; then
@ -74,7 +62,7 @@ runs:
# installation, which is Python 3 based. Its Python is default to Python 3. Further, there
# is also the Miniconda installation that is Python 2 based, and both can be installed if
# needed. In both cases, Python binary is just called python
PYTHON=$(${CONDA_RUN} -n py_tmp which python)
PYTHON=$(${CONDA_RUN} which python)
EXIT_CODE=$?
if [[ "${EXIT_CODE}" == "0" ]]; then

View File

@ -23,6 +23,9 @@ runs:
run: |
.github\scripts\kill_active_ssh_sessions.ps1
- name: Clean up leftover processes on non-ephemeral Windows runner
uses: pytorch/test-infra/.github/actions/cleanup-runner@main
# Cleaning up Windows workspace sometimes fails flakily with device or resource busy
# error, meaning one or more processes haven't stopped completely yet. So trying to
# retry this step several time similar to how checkout-pytorch GHA does

View File

@ -1 +1 @@
87ff22e49ed0e92576c4935ccb8c143daac4a3cd
caba63f0fa29ef9e3d566699f32f11c07c8bda4e

View File

@ -1 +1 @@
0ad9951c416d33c5da4f7a504fb162cbe62386f5
f510715882304796a96e33028b4f6de1b026c2c7

View File

@ -1 +1 @@
2a9138a26ee257fef05310ad3fecf7c55fe80d73
6c5478ff7c3d50dd1e3047d72ec5909bea474073

View File

@ -82,10 +82,16 @@ RUN if command -v apt-get >/dev/null; then \
apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim; \
else \
dnf install -y git curl wget sudo; \
dnf install -y git curl wget sudo vim; \
fi \
&& python3 --version && python3 -m pip --version
# Workaround for https://github.com/openai/triton/issues/2507 and
# https://github.com/pytorch/pytorch/issues/107960 -- hopefully
# this won't be needed for future versions of this docker image
# or future versions of triton.
RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
# Install uv for faster pip installs if not existed
RUN --mount=type=cache,target=/root/.cache/uv \
if ! python3 -m uv --version >/dev/null 2>&1; then \
@ -202,7 +208,7 @@ ARG max_jobs=16
ENV MAX_JOBS=${max_jobs}
ARG nvcc_threads=4
ENV NVCC_THREADS=$nvcc_threads
ARG torch_cuda_arch_list='8.0 8.6 8.9 9.0'
ARG torch_cuda_arch_list='8.0;8.6;8.9;9.0'
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
ARG USE_SCCACHE
@ -214,16 +220,11 @@ ARG SCCACHE_S3_NO_CREDENTIALS=0
RUN --mount=type=cache,target=/root/.cache/uv \
--mount=type=bind,source=.git,target=.git \
if [ "$USE_SCCACHE" = "1" ]; then \
echo "Installing sccache..."; \
if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
SCCACHE_ARCHIVE="sccache-v0.8.1-aarch64-unknown-linux-musl"; \
else \
SCCACHE_ARCHIVE="sccache-v0.8.1-x86_64-unknown-linux-musl"; \
fi; \
curl -L -o sccache.tar.gz "https://github.com/mozilla/sccache/releases/download/v0.8.1/${SCCACHE_ARCHIVE}.tar.gz" \
echo "Installing sccache..." \
&& curl -L -o sccache.tar.gz https://github.com/mozilla/sccache/releases/download/v0.8.1/sccache-v0.8.1-x86_64-unknown-linux-musl.tar.gz \
&& tar -xzf sccache.tar.gz \
&& sudo mv "${SCCACHE_ARCHIVE}"/sccache /usr/bin/sccache \
&& rm -rf sccache.tar.gz "${SCCACHE_ARCHIVE}" \
&& sudo mv sccache-v0.8.1-x86_64-unknown-linux-musl/sccache /usr/bin/sccache \
&& rm -rf sccache.tar.gz sccache-v0.8.1-x86_64-unknown-linux-musl \
&& export SCCACHE_BUCKET=${SCCACHE_BUCKET_NAME} \
&& export SCCACHE_REGION=${SCCACHE_REGION_NAME} \
&& export SCCACHE_S3_NO_CREDENTIALS=${SCCACHE_S3_NO_CREDENTIALS} \
@ -284,7 +285,7 @@ RUN if command -v apt-get >/dev/null; then \
&& 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 curl wget sudo; \
dnf install -y git curl wget sudo vim; \
fi \
&& python3 --version && python3 -m pip --version
@ -297,28 +298,22 @@ RUN echo "[INFO] Listing current directory before torch install step:" && \
echo "[INFO] Showing torch_build_versions.txt content:" && \
cat torch_build_versions.txt
# 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
# Workaround for https://github.com/openai/triton/issues/2507 and
# https://github.com/pytorch/pytorch/issues/107960 -- hopefully
# this won't be needed for future versions of this docker image
# or future versions of triton.
RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
# Install uv for faster pip installs if not existed
RUN --mount=type=cache,target=/root/.cache/uv \
if ! python3 -m uv --version > /dev/null 2>&1; then \
python3 -m pip install uv==0.8.4; \
fi
ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"
# Use copy mode to avoid hardlink failures with Docker cache mounts
ENV UV_LINK_MODE=copy
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/build.txt
# Default mount file as placeholder, this just avoid the mount error
ARG TORCH_WHEELS_PATH="./requirements"
# Install torch, torchaudio and torchvision
@ -344,11 +339,13 @@ RUN --mount=type=cache,target=/root/.cache/uv \
# Install xformers wheel from previous stage
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system /wheels/xformers/*.whl --verbose
# Build flashinfer from source.
ARG torch_cuda_arch_list='8.0;8.9;9.0a;10.0a;12.0'
# install package for build flashinfer
# see issue: https://github.com/flashinfer-ai/flashinfer/issues/738
RUN pip install build==1.3.0
RUN pip freeze | grep -E 'setuptools|packaging|build'
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}

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()

3
.github/labeler.yml vendored
View File

@ -130,6 +130,3 @@
- torch/csrc/inductor/aoti_include/**
- torchgen/aoti/**
- torchgen/gen_aoti_c_shim.py
"ciflow/vllm":
- .github/ci_commit_pins/vllm.txt

View File

@ -525,21 +525,6 @@
- Lint
- pull
- name: typechecking
patterns:
- 'pyrefly.toml'
- 'mypy.ini'
- 'mypy-strict.ini'
approved_by:
- lolpack
- maggiemoss
- ndmitchell
- kinto0
mandatory_checks_name:
- EasyCLA
- Lint
- pull
- name: superuser
patterns:
- '*'

View File

@ -1,44 +1,41 @@
tracking_issue: 24422
ciflow_tracking_issue: 64124
ciflow_push_tags:
- ciflow/b200
- ciflow/b200-symm-mem
- ciflow/binaries
- ciflow/binaries_libtorch
- ciflow/binaries_wheel
- ciflow/h100
- ciflow/h100-cutlass-backend
- ciflow/h100-distributed
- ciflow/h100-symm-mem
- ciflow/triton_binaries
- ciflow/inductor
- ciflow/inductor-cu126
- ciflow/inductor-micro-benchmark
- ciflow/inductor-micro-benchmark-cpu-x86
- ciflow/inductor-perf-compare
- ciflow/inductor-perf-test-nightly-rocm
- ciflow/inductor-perf-test-nightly-x86-zen
- ciflow/inductor-periodic
- ciflow/inductor-rocm
- ciflow/inductor-perf-test-nightly-rocm
- ciflow/inductor-perf-compare
- ciflow/inductor-micro-benchmark
- ciflow/inductor-micro-benchmark-cpu-x86
- ciflow/inductor-perf-test-nightly-x86-zen
- ciflow/inductor-cu126
- ciflow/linux-aarch64
- ciflow/mps
- ciflow/nightly
- ciflow/op-benchmark
- ciflow/periodic
- ciflow/periodic-rocm-mi300
- ciflow/pull
- ciflow/quantization-periodic
- ciflow/riscv64
- ciflow/rocm
- ciflow/rocm-mi300
- ciflow/s390
- ciflow/riscv64
- ciflow/slow
- ciflow/torchbench
- ciflow/triton_binaries
- ciflow/trunk
- ciflow/unstable
- ciflow/vllm
- ciflow/win-arm64
- ciflow/xpu
- ciflow/vllm
- ciflow/torchbench
- ciflow/op-benchmark
- ciflow/pull
- ciflow/h100
- ciflow/h100-distributed
- ciflow/win-arm64
- ciflow/h100-symm-mem
- ciflow/h100-cutlass-backend
retryable_workflows:
- pull
- trunk
@ -47,4 +44,4 @@ retryable_workflows:
- inductor-A100-perf-nightly
labeler_config: labeler.yml
label_to_label_config: label_to_label.yml
mergebot: true
mergebot: True

View File

@ -0,0 +1,36 @@
boto3==1.35.42
cmake==3.27.*
expecttest==0.3.0
fbscribelogger==0.1.7
filelock==3.18.0
hypothesis==6.56.4
librosa>=0.6.2
mpmath==1.3.0
networkx==2.8.7
ninja==1.10.2.4
numba==0.59.0
numpy==1.26.4
opt-einsum>=3.3
optree==0.13.0
packaging==23.1
parameterized==0.8.1
pillow==10.3.0
protobuf==5.29.5
psutil==5.9.8
pygments==2.15.0
pytest-cpp==2.3.0
pytest-flakefinder==1.1.0
pytest-rerunfailures==10.3
pytest-subtests==0.13.1
pytest-xdist==3.3.1
pytest==7.3.2
pyyaml==6.0.2
scipy==1.12.0
setuptools==78.1.1
sympy==1.13.3
tlparse==0.4.0
tensorboard==2.13.0
typing-extensions==4.12.2
unittest-xml-reporting<=3.2.0,>=2.0.0
xdoctest==1.1.0
z3-solver==4.15.1.0

Binary file not shown.

View File

@ -502,7 +502,6 @@ def perform_misc_tasks(
job_name: str,
pr_body: str,
branch: Optional[str] = None,
tag: Optional[str] = None,
) -> None:
"""
In addition to apply the filter logic, the script also does the following
@ -510,9 +509,7 @@ def perform_misc_tasks(
"""
set_output(
"keep-going",
branch == MAIN_BRANCH
or bool(tag and re.match(r"^trunk/[a-f0-9]{40}$", tag))
or check_for_setting(labels, pr_body, "keep-going"),
branch == MAIN_BRANCH or check_for_setting(labels, pr_body, "keep-going"),
)
set_output(
"ci-verbose-test-logs",
@ -637,7 +634,6 @@ def main() -> None:
job_name=args.job_name,
pr_body=pr_body if pr_body else "",
branch=args.branch,
tag=tag,
)
# Set the filtered test matrix as the output

View File

@ -30,7 +30,7 @@ CUDA_ARCHES_CUDNN_VERSION = {
}
# NOTE: Please also update the ROCm sources in `PIP_SOURCES` in tools/nightly.py when changing this
ROCM_ARCHES = ["6.4", "7.0"]
ROCM_ARCHES = ["6.3", "6.4"]
XPU_ARCHES = ["xpu"]

View File

@ -127,6 +127,53 @@ LINUX_BINARY_BUILD_WORFKLOWS = [
),
]
ROCM_SMOKE_WORKFLOWS = [
BinaryBuildWorkflow(
os=OperatingSystem.LINUX,
package_type="manywheel",
build_variant="rocm",
build_configs=generate_binary_build_matrix.generate_wheels_matrix(
OperatingSystem.LINUX,
arches=["6.4"],
python_versions=["3.9"],
),
ciflow_config=CIFlowConfig(
labels={
LABEL_CIFLOW_BINARIES,
LABEL_CIFLOW_BINARIES_WHEEL,
LABEL_CIFLOW_ROCM,
},
isolated_workflow=True,
),
branches="main",
),
]
LINUX_BINARY_SMOKE_WORKFLOWS = [
BinaryBuildWorkflow(
os=OperatingSystem.LINUX,
package_type="manywheel",
build_configs=generate_binary_build_matrix.generate_wheels_matrix(
OperatingSystem.LINUX,
arches=["12.8"],
python_versions=["3.12"],
),
branches="main",
),
BinaryBuildWorkflow(
os=OperatingSystem.LINUX,
package_type="libtorch",
build_variant=generate_binary_build_matrix.RELEASE,
build_configs=generate_binary_build_matrix.generate_libtorch_matrix(
OperatingSystem.LINUX,
generate_binary_build_matrix.RELEASE,
arches=["cpu"],
libtorch_variants=["shared-with-deps"],
),
branches="main",
),
]
WINDOWS_BINARY_BUILD_WORKFLOWS = [
BinaryBuildWorkflow(
os=OperatingSystem.WINDOWS,
@ -212,6 +259,39 @@ WINDOWS_BINARY_BUILD_WORKFLOWS = [
),
]
WINDOWS_BINARY_SMOKE_WORKFLOWS = [
BinaryBuildWorkflow(
os=OperatingSystem.WINDOWS,
package_type="libtorch",
build_variant=generate_binary_build_matrix.RELEASE,
build_configs=generate_binary_build_matrix.generate_libtorch_matrix(
OperatingSystem.WINDOWS,
generate_binary_build_matrix.RELEASE,
arches=["cpu"],
libtorch_variants=["shared-with-deps"],
),
branches="main",
ciflow_config=CIFlowConfig(
isolated_workflow=True,
),
),
BinaryBuildWorkflow(
os=OperatingSystem.WINDOWS,
package_type="libtorch",
build_variant=generate_binary_build_matrix.DEBUG,
build_configs=generate_binary_build_matrix.generate_libtorch_matrix(
OperatingSystem.WINDOWS,
generate_binary_build_matrix.DEBUG,
arches=["cpu"],
libtorch_variants=["shared-with-deps"],
),
branches="main",
ciflow_config=CIFlowConfig(
isolated_workflow=True,
),
),
]
MACOS_BINARY_BUILD_WORKFLOWS = [
BinaryBuildWorkflow(
os=OperatingSystem.MACOS_ARM64,
@ -292,10 +372,23 @@ def main() -> None:
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
S390X_BINARY_BUILD_WORKFLOWS,
),
(
# Give rocm it's own workflow file
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
ROCM_SMOKE_WORKFLOWS,
),
(
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
LINUX_BINARY_SMOKE_WORKFLOWS,
),
(
jinja_env.get_template("windows_binary_build_workflow.yml.j2"),
WINDOWS_BINARY_BUILD_WORKFLOWS,
),
(
jinja_env.get_template("windows_binary_build_workflow.yml.j2"),
WINDOWS_BINARY_SMOKE_WORKFLOWS,
),
(
jinja_env.get_template("macos_binary_build_workflow.yml.j2"),
MACOS_BINARY_BUILD_WORKFLOWS,

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

@ -84,9 +84,6 @@ repackage_wheel() {
rm -rf $package
}
# Require to re-package the wheel
${PYTHON_EXECUTABLE} -mpip install wheel==0.45.1
pushd externals/vllm/wheels
for package in xformers flashinfer-python vllm; do
repackage_wheel $package

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 {
@ -1094,7 +1093,6 @@ class GitHubPR:
body_text=node["bodyText"],
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"],
@ -2031,11 +2029,6 @@ 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 "

View File

@ -71,15 +71,12 @@ jobs:
with:!{{ upload.binary_env_as_input(config) }}
{%- if "aarch64" in build_environment %}
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.r7g.12xlarge.memory
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
{%- elif "s390x" in build_environment %}
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
timeout-minutes: 420
{%- elif config["gpu_arch_type"] == "rocm" %}
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
timeout-minutes: 300
{%- elif "conda" in build_environment and config["gpu_arch_type"] == "cuda" %}
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.24xlarge.ephemeral

View File

@ -187,6 +187,8 @@ jobs:
- name: Install nvidia driver, nvidia-docker runtime, set GPU_FLAG
uses: pytorch/test-infra/.github/actions/setup-nvidia@main
with:
driver-version: ${{ startsWith(inputs.GPU_ARCH_VERSION, '13') && '580.65.06' || '570.133.07' }}
if: ${{ inputs.GPU_ARCH_TYPE == 'cuda' && steps.filter.outputs.is-test-matrix-empty == 'False' }}
- name: configure aws credentials

View File

@ -67,7 +67,7 @@ jobs:
# an OOM issue when running the job, so this upgrades the runner from 4xlarge
# to the next available tier of 12xlarge. So much memory just to generate cpp
# doc
runner: ${{ inputs.runner_prefix }}linux.12xlarge.memory
runner: ${{ inputs.runner_prefix }}linux.12xlarge
# TODO: Nightly cpp docs take longer and longer to finish (more than 3h now)
# Let's try to figure out how this can be improved
timeout-minutes: 360
@ -75,6 +75,10 @@ jobs:
runner: ${{ inputs.runner_prefix }}linux.2xlarge
# It takes less than 30m to finish python docs unless there are issues
timeout-minutes: 30
- docs_type: functorch
runner: ${{ inputs.runner_prefix }}linux.2xlarge
# It takes less than 15m to finish functorch docs unless there are issues
timeout-minutes: 15
# Set a fixed name for this job instead of using the current matrix-generated name, i.e. build-docs (cpp, linux.12xlarge, 180)
# The current name requires updating the database last docs push query from test-infra every time the matrix is updated
name: build-docs-${{ matrix.docs_type }}-${{ inputs.push }}
@ -207,6 +211,16 @@ jobs:
path: cppdocs/
s3-prefix: pytorch/pytorch/${{ github.event.pull_request.number }}/cppdocs
- name: Upload functorch Docs Preview
uses: seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a # v5.1.0
if: ${{ github.event_name == 'pull_request' && matrix.docs_type == 'functorch' && steps.build-docs.outcome == 'success' }}
with:
retention-days: 14
s3-bucket: doc-previews
if-no-files-found: error
path: functorch_ghpages/nightly/
s3-prefix: pytorch/pytorch/${{ github.event.pull_request.number }}/functorchdocs
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
if: always()

View File

@ -2,12 +2,6 @@ name: Get Changed Files
on:
workflow_call:
inputs:
all_files:
description: "Whether to return all files instead of just changed files"
required: false
type: boolean
default: false
outputs:
changed-files:
description: "List of changed files (space-separated) or '*' if not in a PR"
@ -32,32 +26,17 @@ jobs:
# Get the PR number from the github context
PR_NUMBER="${{ github.event.number }}"
# Check if all_files is requested
if [ "${{ inputs.all_files }}" = "true" ]; then
echo "all_files input is true, returning all files"
echo "changed-files=*" >> "$GITHUB_OUTPUT"
else
# Use gh CLI to get changed files in the PR with explicit repo
CHANGED_FILES=$(gh api repos/${{ github.repository }}/pulls/$PR_NUMBER/files --paginate --jq '.[] | select(.status != "removed") | .filename' | tr '\n' ' ' | sed 's/ $//')
# Use gh CLI to get changed files in the PR with explicit repo
CHANGED_FILES=$(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="*"
fi
echo "Changed files: $CHANGED_FILES"
echo "changed-files=$CHANGED_FILES" >> "$GITHUB_OUTPUT"
if [ -z "$CHANGED_FILES" ]; then
echo "No changed files found, setting to '*'"
CHANGED_FILES="*"
fi
echo "Changed files: $CHANGED_FILES"
echo "changed-files=$CHANGED_FILES" >> "$GITHUB_OUTPUT"
else
echo "Not in PR context, setting changed files to '*'"
echo "changed-files=*" >> "$GITHUB_OUTPUT"

View File

@ -1,255 +0,0 @@
# The point of this workflow is to test that a FA3 wheel that was built based off the
# stable ABI as of torch nightly 20250830 can still run on the newer torch.
#
# This workflow is very similar to the _linux-test.yml workflow, with the following
# differences:
# 1. It is simpler (there is no test matrix)
# 2. It pulls flash-attention as a secondary repository in order to access the tests.
# Note that it does not BUILD anything from flash-attention, as we have a prebuilt
# wheel. We pull flash-attention only to run a few tests.
# 3. It runs only FA3 tests. No PyTorch tests are run.
name: linux-test-stable-fa3
on:
workflow_call:
inputs:
build-environment:
required: true
type: string
description: Top-level label for what's being built/tested.
docker-image:
required: true
type: string
description: Docker image to run in.
timeout-minutes:
required: false
type: number
default: 30
description: |
Set the maximum (in minutes) how long the workflow should take to finish
s3-bucket:
description: S3 bucket to download artifact
required: false
type: string
default: "gha-artifacts"
secrets:
HUGGING_FACE_HUB_TOKEN:
required: false
description: |
HF Auth token to avoid rate limits when downloading models or datasets from hub
VLLM_TEST_HUGGING_FACE_TOKEN:
required: false
description: |
HF Auth token to test vllm
SCRIBE_GRAPHQL_ACCESS_TOKEN:
required: false
description: |
FB app token to write to scribe endpoint
env:
GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
jobs:
test:
# Don't run on forked repos
if: github.repository_owner == 'pytorch'
runs-on: linux.aws.h100
timeout-minutes: ${{ inputs.timeout-minutes || 30 }}
permissions:
id-token: write
contents: read
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
with:
no-sudo: true
- name: Checkout flash-attention as a secondary repository
uses: actions/checkout@v4
with:
repository: Dao-AILab/flash-attention
path: flash-attention
- name: Setup Linux
uses: ./.github/actions/setup-linux
- name: Calculate docker image
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
with:
docker-image-name: ${{ inputs.docker-image }}
- name: Use following to pull public copy of the image
id: print-ghcr-mirror
env:
ECR_DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
shell: bash
run: |
tag=${ECR_DOCKER_IMAGE##*:}
echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}"
- name: Pull docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
- name: Check if in a container runner
shell: bash
id: check_container_runner
run: echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
- name: Setup GPU_FLAG for docker run
id: setup-gpu-flag
run: echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}"
- name: Setup SCCACHE_SERVER_PORT environment for docker run when on container
id: setup-sscache-port-flag
run: echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}"
if: ${{ steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'true' }}
- name: Get workflow job id
id: get-job-id
uses: ./.github/actions/get-workflow-job-id
if: always()
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
- name: Download build artifacts
uses: ./.github/actions/download-build-artifacts
with:
name: ${{ inputs.build-environment }}
s3-bucket: ${{ inputs.s3-bucket }}
- name: Parse ref
id: parse-ref
run: .github/scripts/parse_ref.py
- name: Set Test step time
id: test-timeout
shell: bash
env:
JOB_TIMEOUT: ${{ inputs.timeout-minutes }}
run: |
echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
- name: Preserve github env variables for use in docker
shell: bash
run: |
env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
- name: Test
id: test
timeout-minutes: ${{ fromJson(steps.test-timeout.outputs.timeout) }}
env:
BUILD_ENVIRONMENT: ${{ inputs.build-environment }}
PR_NUMBER: ${{ github.event.pull_request.number }}
GITHUB_REPOSITORY: ${{ github.repository }}
GITHUB_WORKFLOW: ${{ github.workflow }}
GITHUB_JOB: ${{ github.job }}
GITHUB_RUN_ID: ${{ github.run_id }}
GITHUB_RUN_NUMBER: ${{ github.run_number }}
GITHUB_RUN_ATTEMPT: ${{ github.run_attempt }}
JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
JOB_NAME: ${{ steps.get-job-id.outputs.job-name }}
BRANCH: ${{ steps.parse-ref.outputs.branch }}
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
BASE_SHA: ${{ github.event.pull_request.base.sha || github.sha }}
SHM_SIZE: '2g'
DOCKER_IMAGE: ${{ inputs.docker-image }}
VLLM_TEST_HUGGING_FACE_TOKEN: ${{ secrets.VLLM_TEST_HUGGING_FACE_TOKEN }}
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.SCRIBE_GRAPHQL_ACCESS_TOKEN }}
ARTIFACTS_FILE_SUFFIX: ${{ github.job }}-${{ steps.get-job-id.outputs.job-id }}
run: |
set -x
TEST_COMMAND=.ci/pytorch/test_fa3_abi_stable.sh
# Leaving 1GB for the runner and other things
TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo)
# https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap
# comes from https://github.com/pytorch/test-infra/pull/6058
TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3))
SHM_OPTS="--shm-size=${SHM_SIZE}"
JENKINS_USER="--user jenkins"
DOCKER_SHELL_CMD=
# detached container should get cleaned up by teardown_ec2_linux
# TODO: Stop building test binaries as part of the build phase
# Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice
# shellcheck disable=SC2086,SC2090
container_name=$(docker run \
${GPU_FLAG:-} \
${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \
-e BUILD_ENVIRONMENT \
-e PR_NUMBER \
-e GITHUB_ACTIONS \
-e GITHUB_REPOSITORY \
-e GITHUB_WORKFLOW \
-e GITHUB_JOB \
-e GITHUB_RUN_ID \
-e GITHUB_RUN_NUMBER \
-e GITHUB_RUN_ATTEMPT \
-e JOB_ID \
-e JOB_NAME \
-e BASE_SHA \
-e BRANCH \
-e SHA1 \
-e MAX_JOBS="$(nproc --ignore=2)" \
-e HUGGING_FACE_HUB_TOKEN \
-e VLLM_TEST_HUGGING_FACE_TOKEN \
-e SCRIBE_GRAPHQL_ACCESS_TOKEN \
-e ARTIFACTS_FILE_SUFFIX \
--memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \
--memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
--security-opt seccomp=unconfined \
--cap-add=SYS_PTRACE \
--ipc=host \
${SHM_OPTS} \
--tty \
--detach \
--name="${container_name}" \
${JENKINS_USER} \
-v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \
-w /var/lib/jenkins/workspace \
"${DOCKER_IMAGE}" \
${DOCKER_SHELL_CMD}
)
echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}"
docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}"
- name: Collect backtraces from coredumps (if any)
if: always()
run: |
# shellcheck disable=SC2156
find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \;
- name: Store Core dumps on S3
uses: seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a # v5.1.0
if: failure()
with:
name: coredumps-fa3-stable-abi-smoke-tests
retention-days: 14
if-no-files-found: ignore
path: ./**/core.[1-9]*
- name: Upload utilization stats
if: ${{ always() && steps.test.conclusion && steps.test.conclusion != 'skipped' }}
continue-on-error: true
uses: ./.github/actions/upload-utilization-stats
with:
job_id: ${{ steps.get-job-id.outputs.job-id }}
job_name: ${{ steps.get-job-id.outputs.job-name }}
workflow_name: ${{ github.workflow }}
workflow_run_id: ${{github.run_id}}
workflow_attempt: ${{github.run_attempt}}
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
if: always() && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false'

View File

@ -169,7 +169,7 @@ jobs:
id: install-nvidia-driver
uses: pytorch/test-infra/.github/actions/setup-nvidia@main
with:
driver-version: ${{ matrix.config == 'legacy_nvidia_driver' && '525.105.17' || '580.82.07' }}
driver-version: ${{ matrix.config == 'legacy_nvidia_driver' && '525.105.17' || '570.133.07' }}
if: ${{ contains(inputs.build-environment, 'cuda') && !contains(matrix.config, 'nogpu') && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' && !contains(matrix.runner, 'b200') }}
- name: Setup GPU_FLAG for docker run
@ -273,8 +273,6 @@ jobs:
TEST_CONFIG: ${{ matrix.config }}
SHARD_NUMBER: ${{ matrix.shard }}
NUM_TEST_SHARDS: ${{ matrix.num_shards }}
EXTRA_FLAGS: ${{ matrix.extra_flags || '' }}
OP_BENCHMARK_TESTS: ${{ matrix.op_benchmark_tests }}
REENABLED_ISSUES: ${{ steps.keep-going.outputs.reenabled-issues }}
CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
VERBOSE_TEST_LOGS: ${{ steps.keep-going.outputs.ci-verbose-test-logs }}

View File

@ -85,7 +85,7 @@ jobs:
uses: pytorch/test-infra/.github/actions/setup-python@main
with:
python-version: ${{ inputs.python-version }}
pip-requirements-file: .ci/docker/requirements-ci.txt
pip-requirements-file: .github/requirements/pip-requirements-macOS.txt
- name: Install sccache (only for non-forked PRs, and pushes to trunk)
uses: nick-fields/retry@7152eba30c6575329ac0576536151aca5a72780e # v3.0.0

View File

@ -122,7 +122,7 @@ jobs:
uses: pytorch/test-infra/.github/actions/setup-python@main
with:
python-version: ${{ inputs.python-version }}
pip-requirements-file: .ci/docker/requirements-ci.txt
pip-requirements-file: .github/requirements/pip-requirements-macOS.txt
- name: Start monitoring script
id: monitor-script

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@ -62,11 +62,6 @@ on:
required: false
type: number
default: 1
secrets:
HUGGING_FACE_HUB_TOKEN:
required: false
description: |
HF Auth token to avoid rate limits when downloading models or datasets from hub
env:
GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
@ -81,9 +76,10 @@ jobs:
strategy:
matrix: ${{ fromJSON(inputs.test-matrix) }}
fail-fast: false
runs-on: ${{ matrix.runner }}
timeout-minutes: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
runs-on: ${{ matrix.runner }}
steps:
# [see note: pytorch repo ref]
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
with:
@ -135,9 +131,6 @@ jobs:
- name: Start monitoring script
id: monitor-script
if: ${{ !inputs.disable-monitor }}
shell: bash
continue-on-error: true
env:
JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
JOB_NAME: ${{ steps.get-job-id.outputs.job-name }}
@ -145,6 +138,9 @@ jobs:
WORKFLOW_RUN_ID: ${{github.run_id}}
MONITOR_LOG_INTERVAL: ${{ inputs.monitor-log-interval }}
MONITOR_DATA_COLLECT_INTERVAL: ${{ inputs.monitor-data-collect-interval }}
if: ${{ !inputs.disable-monitor }}
shell: bash
continue-on-error: true
run: |
python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7
python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
@ -182,12 +178,6 @@ jobs:
run: |
echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
- name: Preserve github env variables for use in docker
shell: bash
run: |
env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
- name: Test
id: test
env:
@ -203,22 +193,20 @@ jobs:
JOB_NAME: ${{ steps.get-job-id.outputs.job-name }}
BRANCH: ${{ steps.parse-ref.outputs.branch }}
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
BASE_SHA: ${{ github.event.pull_request.base.sha || github.sha }}
TEST_CONFIG: ${{ matrix.config }}
SHARD_NUMBER: ${{ matrix.shard }}
NUM_TEST_SHARDS: ${{ matrix.num_shards }}
REENABLED_ISSUES: ${{ steps.keep-going.outputs.reenabled-issues }}
CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
VERBOSE_TEST_LOGS: ${{ steps.keep-going.outputs.ci-verbose-test-logs }}
TEST_SHOWLOCALS: ${{ steps.keep-going.outputs.ci-test-showlocals }}
NO_TEST_TIMEOUT: ${{ steps.keep-going.outputs.ci-no-test-timeout }}
NO_TD: ${{ steps.keep-going.outputs.ci-no-td }}
TEST_CONFIG: ${{ matrix.config }}
SHARD_NUMBER: ${{ matrix.shard }}
NUM_TEST_SHARDS: ${{ matrix.num_shards }}
REENABLED_ISSUES: ${{ steps.keep-going.outputs.reenabled-issues }}
DOCKER_IMAGE: ${{ inputs.docker-image }}
PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: ${{ matrix.mem_leak_check && '1' || '0' }}
PYTORCH_TEST_RERUN_DISABLED_TESTS: ${{ matrix.rerun_disabled_tests && '1' || '0' }}
TESTS_TO_INCLUDE: ${{ inputs.tests-to-include }}
DASHBOARD_TAG: ${{ inputs.dashboard-tag }}
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
timeout-minutes: ${{ fromJson(steps.test-timeout.outputs.timeout) }}
run: |
set -x
@ -248,7 +236,6 @@ jobs:
-e GITHUB_RUN_ATTEMPT \
-e JOB_ID \
-e JOB_NAME \
-e BASE_SHA \
-e BRANCH \
-e SHA1 \
-e AWS_DEFAULT_REGION \
@ -266,12 +253,10 @@ jobs:
-e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \
-e PYTORCH_TEST_RERUN_DISABLED_TESTS \
-e TESTS_TO_INCLUDE \
-e HUGGING_FACE_HUB_TOKEN \
-e DASHBOARD_TAG \
--env-file="${RUNNER_TEMP}/github_env_${GITHUB_RUN_ID}" \
--ulimit stack=10485760:83886080 \
--ulimit core=0 \
--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
--security-opt seccomp=unconfined \
--cap-add=SYS_PTRACE \
--shm-size="8g" \

View File

@ -84,6 +84,9 @@ jobs:
# in https://github.com/actions/checkout/issues/1018
git config --global core.fsmonitor false
- name: Clean up leftover processes on non-ephemeral Windows runner
uses: pytorch/test-infra/.github/actions/cleanup-runner@main
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
with:
@ -148,7 +151,7 @@ jobs:
BUILD_WHEEL: 1
MAX_JOBS: 8
CUDA_VERSION: ${{ inputs.cuda-version }}
PYTHON_VERSION: "3.10"
PYTHON_VERSION: "3.9"
SCCACHE_BUCKET: "ossci-compiler-cache"
SCCACHE_S3_KEY_PREFIX: ${{ github.workflow }}
SCCACHE_REGION: us-east-1

View File

@ -77,6 +77,9 @@ jobs:
# in https://github.com/actions/checkout/issues/1018
git config --global core.fsmonitor false
- name: Clean up leftover processes on non-ephemeral Windows runner
uses: pytorch/test-infra/.github/actions/cleanup-runner@main
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
with:
@ -103,6 +106,18 @@ jobs:
with:
cuda-version: ${{ inputs.cuda-version }}
# TODO: Move to a requirements.txt file for windows
- name: Install pip dependencies
uses: nick-fields/retry@7152eba30c6575329ac0576536151aca5a72780e # v3.0.0
with:
shell: bash
timeout_minutes: 5
max_attempts: 5
retry_wait_seconds: 30
command: |
set -eu
python3 -m pip install 'xdoctest>=1.1.0'
- name: Get workflow job id
id: get-job-id
uses: ./.github/actions/get-workflow-job-id
@ -169,7 +184,7 @@ jobs:
env:
USE_CUDA: ${{ inputs.cuda-version != 'cpu' && '1' || '0' }}
INSTALL_WINDOWS_SDK: 1
PYTHON_VERSION: "3.10"
PYTHON_VERSION: 3.9
CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
VERBOSE_TEST_LOGS: ${{ steps.keep-going.outputs.ci-verbose-test-logs }}
TEST_SHOWLOCALS: ${{ steps.keep-going.outputs.ci-test-showlocals }}
@ -257,6 +272,15 @@ jobs:
shell: bash
run: python3 .github/scripts/parse_ref.py
- name: Uninstall PyTorch
if: always()
continue-on-error: true
shell: bash
run: |
# This step removes PyTorch installed by the test to give a clean slate
# to the next job
python3 -mpip uninstall -y torch
- name: Teardown Windows
uses: ./.github/actions/teardown-win
if: always()

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@ -1,60 +0,0 @@
name: Limited CI for symmetric memory tests on B200
on:
pull_request:
paths:
- .github/workflows/b200-symm-mem.yml
workflow_dispatch:
push:
tags:
- ciflow/b200-symm-mem/*
schedule:
- cron: 22 8 * * * # about 1:22am 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: ${{ github.ref_type }}
linux-jammy-cuda12_8-py3_10-gcc11-sm100-build-symm:
name: linux-jammy-cuda12.8-py3.10-gcc11-sm100-symm
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runner: linux.12xlarge.memory
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-sm100-symm
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11
cuda-arch-list: '10.0'
test-matrix: |
{ include: [
{ config: "b200-symm-mem", shard: 1, num_shards: 1, runner: "linux.dgx.b200.8" },
]}
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc11-sm100-test:
name: linux-jammy-cuda12.8-py3.10-gcc11-sm100-symm
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-jammy-cuda12_8-py3_10-gcc11-sm100-build-symm
with:
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-sm100-symm
docker-image: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm100-build-symm.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm100-build-symm.outputs.test-matrix }}
aws-role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
secrets: inherit

View File

@ -36,7 +36,7 @@ jobs:
runs-on: linux.9xlarge.ephemeral
strategy:
matrix:
tag: ["cuda12.6", "cuda12.8", "cuda12.9", "cuda13.0", "rocm6.4", "rocm7.0", "cpu"]
tag: ["cuda12.6", "cuda12.8", "cuda12.9", "cuda13.0", "rocm6.3", "rocm6.4", "cpu"]
steps:
- name: Build docker image
uses: pytorch/pytorch/.github/actions/binary-docker-build@main

View File

@ -52,8 +52,8 @@ jobs:
{ tag: "cuda12.9" },
{ tag: "cuda12.8" },
{ tag: "cuda12.6" },
{ tag: "rocm6.3" },
{ tag: "rocm6.4" },
{ tag: "rocm7.0" },
{ tag: "cpu" },
]
steps:

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