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Author SHA1 Message Date
aa7e793a8e Update (base update)
[ghstack-poisoned]
2025-08-27 19:17:52 -07:00
2281 changed files with 54883 additions and 113989 deletions

View File

@ -3,20 +3,8 @@ set -eux -o pipefail
GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
# Set CUDA architecture lists to match x86 build_cuda.sh
if [[ "$GPU_ARCH_VERSION" == *"12.6"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0"
elif [[ "$GPU_ARCH_VERSION" == *"12.8"* ]]; then
if [[ "$GPU_ARCH_VERSION" == *"12.9"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;12.0"
elif [[ "$GPU_ARCH_VERSION" == *"13.0"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;11.0;12.0+PTX"
fi
# Compress the fatbin with -compress-mode=size for CUDA 13
if [[ "$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 "$0")" >/dev/null 2>&1 ; pwd -P )"
@ -30,22 +18,14 @@ cd /
# on the mounted pytorch repo
git config --global --add safe.directory /pytorch
pip install -r /pytorch/requirements.txt
pip install auditwheel==6.2.0 wheel
pip install auditwheel==6.2.0
if [ "$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: $DESIRED_CUDA"
export USE_SYSTEM_NCCL=1
# Check if we should use NVIDIA libs from PyPI (similar to x86 build_cuda.sh logic)
if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
echo "Bundling CUDA libraries with wheel for aarch64."
else
echo "Using nvidia libs from pypi for aarch64."
echo "Updated PYTORCH_EXTRA_INSTALL_REQUIREMENTS for aarch64: $PYTORCH_EXTRA_INSTALL_REQUIREMENTS"
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

View File

@ -69,186 +69,62 @@ def replace_tag(filename) -> None:
f.writelines(lines)
def patch_library_rpath(
folder: str,
lib_name: str,
use_nvidia_pypi_libs: bool = False,
desired_cuda: str = "",
) -> None:
"""Apply patchelf to set RPATH for a library in torch/lib"""
lib_path = f"{folder}/tmp/torch/lib/{lib_name}"
if use_nvidia_pypi_libs:
# For PyPI NVIDIA libraries, construct CUDA RPATH
cuda_rpaths = [
"$ORIGIN/../../nvidia/cudnn/lib",
"$ORIGIN/../../nvidia/nvshmem/lib",
"$ORIGIN/../../nvidia/nccl/lib",
"$ORIGIN/../../nvidia/cusparselt/lib",
]
if "130" in desired_cuda:
cuda_rpaths.append("$ORIGIN/../../nvidia/cu13/lib")
else:
cuda_rpaths.extend(
[
"$ORIGIN/../../nvidia/cublas/lib",
"$ORIGIN/../../nvidia/cuda_cupti/lib",
"$ORIGIN/../../nvidia/cuda_nvrtc/lib",
"$ORIGIN/../../nvidia/cuda_runtime/lib",
"$ORIGIN/../../nvidia/cufft/lib",
"$ORIGIN/../../nvidia/curand/lib",
"$ORIGIN/../../nvidia/cusolver/lib",
"$ORIGIN/../../nvidia/cusparse/lib",
"$ORIGIN/../../nvidia/nvtx/lib",
"$ORIGIN/../../nvidia/cufile/lib",
]
)
# Add $ORIGIN for local torch libs
rpath = ":".join(cuda_rpaths) + ":$ORIGIN"
else:
# For bundled libraries, just use $ORIGIN
rpath = "$ORIGIN"
if os.path.exists(lib_path):
os.system(
f"cd {folder}/tmp/torch/lib/; "
f"patchelf --set-rpath '{rpath}' --force-rpath {lib_name}"
)
def copy_and_patch_library(
src_path: str,
folder: str,
use_nvidia_pypi_libs: bool = False,
desired_cuda: str = "",
) -> None:
"""Copy a library to torch/lib and patch its RPATH"""
if os.path.exists(src_path):
lib_name = os.path.basename(src_path)
shutil.copy2(src_path, f"{folder}/tmp/torch/lib/{lib_name}")
patch_library_rpath(folder, lib_name, use_nvidia_pypi_libs, desired_cuda)
def package_cuda_wheel(wheel_path, desired_cuda) -> None:
"""
Package the cuda wheel libraries
"""
folder = os.path.dirname(wheel_path)
wheelname = os.path.basename(wheel_path)
os.mkdir(f"{folder}/tmp")
os.system(f"unzip {wheel_path} -d {folder}/tmp")
# Delete original wheel since it will be repackaged
os.system(f"rm {wheel_path}")
libs_to_copy = [
"/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12",
"/usr/local/cuda/extras/CUPTI/lib64/libnvperf_host.so",
"/usr/local/cuda/lib64/libcudnn.so.9",
"/usr/local/cuda/lib64/libcublas.so.12",
"/usr/local/cuda/lib64/libcublasLt.so.12",
"/usr/local/cuda/lib64/libcudart.so.12",
"/usr/local/cuda/lib64/libcufft.so.11",
"/usr/local/cuda/lib64/libcusparse.so.12",
"/usr/local/cuda/lib64/libcusparseLt.so.0",
"/usr/local/cuda/lib64/libcusolver.so.11",
"/usr/local/cuda/lib64/libcurand.so.10",
"/usr/local/cuda/lib64/libnccl.so.2",
"/usr/local/cuda/lib64/libnvJitLink.so.12",
"/usr/local/cuda/lib64/libnvrtc.so.12",
"/usr/local/cuda/lib64/libnvshmem_host.so.3",
"/usr/local/cuda/lib64/libcudnn_adv.so.9",
"/usr/local/cuda/lib64/libcudnn_cnn.so.9",
"/usr/local/cuda/lib64/libcudnn_graph.so.9",
"/usr/local/cuda/lib64/libcudnn_ops.so.9",
"/usr/local/cuda/lib64/libcudnn_engines_runtime_compiled.so.9",
"/usr/local/cuda/lib64/libcudnn_engines_precompiled.so.9",
"/usr/local/cuda/lib64/libcudnn_heuristic.so.9",
"/lib64/libgomp.so.1",
"/usr/lib64/libgfortran.so.5",
"/acl/build/libarm_compute.so",
"/acl/build/libarm_compute_graph.so",
"/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
"/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
"/usr/local/lib/libnvpl_lapack_core.so.0",
"/usr/local/lib/libnvpl_blas_core.so.0",
]
# Check if we should use PyPI NVIDIA libraries or bundle system libraries
use_nvidia_pypi_libs = os.getenv("USE_NVIDIA_PYPI_LIBS", "0") == "1"
if use_nvidia_pypi_libs:
print("Using nvidia libs from pypi - skipping CUDA library bundling")
# For PyPI approach, we don't bundle CUDA libraries - they come from PyPI packages
# We only need to bundle non-NVIDIA libraries
minimal_libs_to_copy = [
"/lib64/libgomp.so.1",
"/usr/lib64/libgfortran.so.5",
"/acl/build/libarm_compute.so",
"/acl/build/libarm_compute_graph.so",
"/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
"/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
"/usr/local/lib/libnvpl_lapack_core.so.0",
"/usr/local/lib/libnvpl_blas_core.so.0",
]
# Copy minimal libraries to unzipped_folder/torch/lib
for lib_path in minimal_libs_to_copy:
copy_and_patch_library(lib_path, folder, use_nvidia_pypi_libs, desired_cuda)
# Patch torch libraries used for searching libraries
torch_libs_to_patch = [
"libtorch.so",
"libtorch_cpu.so",
"libtorch_cuda.so",
"libtorch_cuda_linalg.so",
"libtorch_global_deps.so",
"libtorch_python.so",
"libtorch_nvshmem.so",
"libc10.so",
"libc10_cuda.so",
"libcaffe2_nvrtc.so",
"libshm.so",
]
for lib_name in torch_libs_to_patch:
patch_library_rpath(folder, lib_name, use_nvidia_pypi_libs, desired_cuda)
else:
print("Bundling CUDA libraries with wheel")
# Original logic for bundling system CUDA libraries
# Common libraries for all CUDA versions
common_libs = [
# Non-NVIDIA system libraries
"/lib64/libgomp.so.1",
"/usr/lib64/libgfortran.so.5",
"/acl/build/libarm_compute.so",
"/acl/build/libarm_compute_graph.so",
# Common CUDA libraries (same for all versions)
"/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
"/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
"/usr/local/lib/libnvpl_lapack_core.so.0",
"/usr/local/lib/libnvpl_blas_core.so.0",
"/usr/local/cuda/extras/CUPTI/lib64/libnvperf_host.so",
"/usr/local/cuda/lib64/libcudnn.so.9",
"/usr/local/cuda/lib64/libcusparseLt.so.0",
"/usr/local/cuda/lib64/libcurand.so.10",
"/usr/local/cuda/lib64/libnccl.so.2",
"/usr/local/cuda/lib64/libnvshmem_host.so.3",
"/usr/local/cuda/lib64/libcudnn_adv.so.9",
"/usr/local/cuda/lib64/libcudnn_cnn.so.9",
"/usr/local/cuda/lib64/libcudnn_graph.so.9",
"/usr/local/cuda/lib64/libcudnn_ops.so.9",
"/usr/local/cuda/lib64/libcudnn_engines_runtime_compiled.so.9",
"/usr/local/cuda/lib64/libcudnn_engines_precompiled.so.9",
"/usr/local/cuda/lib64/libcudnn_heuristic.so.9",
if "129" in desired_cuda:
libs_to_copy += [
"/usr/local/cuda/lib64/libnvrtc-builtins.so.12.9",
"/usr/local/cuda/lib64/libcufile.so.0",
"/usr/local/cuda/lib64/libcufile_rdma.so.1",
"/usr/local/cuda/lib64/libcusparse.so.12",
]
# CUDA version-specific libraries
if "13" in desired_cuda:
minor_version = desired_cuda[-1]
version_specific_libs = [
"/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.13",
"/usr/local/cuda/lib64/libcublas.so.13",
"/usr/local/cuda/lib64/libcublasLt.so.13",
"/usr/local/cuda/lib64/libcudart.so.13",
"/usr/local/cuda/lib64/libcufft.so.12",
"/usr/local/cuda/lib64/libcusolver.so.12",
"/usr/local/cuda/lib64/libnvJitLink.so.13",
"/usr/local/cuda/lib64/libnvrtc.so.13",
f"/usr/local/cuda/lib64/libnvrtc-builtins.so.13.{minor_version}",
]
elif "12" in desired_cuda:
# Get the last character for libnvrtc-builtins version (e.g., "129" -> "9")
minor_version = desired_cuda[-1]
version_specific_libs = [
"/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12",
"/usr/local/cuda/lib64/libcublas.so.12",
"/usr/local/cuda/lib64/libcublasLt.so.12",
"/usr/local/cuda/lib64/libcudart.so.12",
"/usr/local/cuda/lib64/libcufft.so.11",
"/usr/local/cuda/lib64/libcusolver.so.11",
"/usr/local/cuda/lib64/libnvJitLink.so.12",
"/usr/local/cuda/lib64/libnvrtc.so.12",
f"/usr/local/cuda/lib64/libnvrtc-builtins.so.12.{minor_version}",
]
else:
raise ValueError(f"Unsupported CUDA version: {desired_cuda}.")
# Combine all libraries
libs_to_copy = common_libs + version_specific_libs
# Copy libraries to unzipped_folder/torch/lib
for lib_path in libs_to_copy:
copy_and_patch_library(lib_path, folder, use_nvidia_pypi_libs, desired_cuda)
# Copy libraries to unzipped_folder/a/lib
for lib_path in libs_to_copy:
lib_name = os.path.basename(lib_path)
shutil.copy2(lib_path, f"{folder}/tmp/torch/lib/{lib_name}")
os.system(
f"cd {folder}/tmp/torch/lib/; "
f"patchelf --set-rpath '$ORIGIN' --force-rpath {folder}/tmp/torch/lib/{lib_name}"
)
# Make sure the wheel is tagged with manylinux_2_28
for f in os.scandir(f"{folder}/tmp/"):
@ -256,8 +132,14 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
replace_tag(f"{f.path}/WHEEL")
break
os.system(f"wheel pack {folder}/tmp/ -d {folder}")
os.system(f"rm -rf {folder}/tmp/")
os.mkdir(f"{folder}/cuda_wheel")
os.system(f"cd {folder}/tmp/; zip -r {folder}/cuda_wheel/{wheelname} *")
shutil.move(
f"{folder}/cuda_wheel/{wheelname}",
f"{folder}/{wheelname}",
copy_function=shutil.copy2,
)
os.system(f"rm -rf {folder}/tmp/ {folder}/cuda_wheel/")
def complete_wheel(folder: str) -> str:
@ -280,7 +162,14 @@ def complete_wheel(folder: str) -> str:
f"/{folder}/dist/{repaired_wheel_name}",
)
else:
repaired_wheel_name = list_dir(f"/{folder}/dist")[0]
repaired_wheel_name = wheel_name.replace(
"linux_aarch64", "manylinux_2_28_aarch64"
)
print(f"Renaming {wheel_name} wheel to {repaired_wheel_name}")
os.rename(
f"/{folder}/dist/{wheel_name}",
f"/{folder}/dist/{repaired_wheel_name}",
)
print(f"Copying {repaired_wheel_name} to artifacts")
shutil.copy2(
@ -317,21 +206,11 @@ 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 "
# Handle PyPI NVIDIA libraries vs bundled libraries
use_nvidia_pypi_libs = os.getenv("USE_NVIDIA_PYPI_LIBS", "0") == "1"
if use_nvidia_pypi_libs:
print("Configuring build for PyPI NVIDIA libraries")
# Configure for dynamic linking (matching x86 logic)
build_vars += "ATEN_STATIC_CUDA=0 USE_CUDA_STATIC_LINK=0 USE_CUPTI_SO=1 "
else:
print("Configuring build for bundled NVIDIA libraries")
# Keep existing static linking approach - already configured above
override_package_version = os.getenv("OVERRIDE_PACKAGE_VERSION")
desired_cuda = os.getenv("DESIRED_CUDA")
if override_package_version is not None:
@ -372,7 +251,7 @@ if __name__ == "__main__":
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)
@ -442,7 +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))
@ -497,7 +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))
@ -553,7 +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))
@ -614,7 +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]
@ -726,7 +726,7 @@ def start_build(
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":
@ -747,8 +747,7 @@ def start_build(
print("build pytorch with mkldnn+acl backend")
build_vars += " USE_MKLDNN=ON USE_MKLDNN_ACL=ON"
host.run_cmd(
f"cd $HOME/pytorch && export ACL_ROOT_DIR=$HOME/ComputeLibrary && "
f"{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]
@ -764,7 +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")
@ -1005,7 +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

View File

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

View File

@ -81,11 +81,11 @@ elif [[ "$image" == *riscv* ]]; then
DOCKERFILE="ubuntu-cross-riscv/Dockerfile"
fi
_UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152
_UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96
_UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
_UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
if [[ "$image" == *rocm* ]]; then
_UCX_COMMIT=29831d319e6be55cb8c768ca61de335c934ca39e
_UCC_COMMIT=9f4b242cbbd8b1462cbc732eb29316cdfa124b77
_UCX_COMMIT=cc312eaa4655c0cc5c2bcd796db938f90563bcf6
_UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d
fi
tag=$(echo $image | awk -F':' '{print $2}')
@ -114,19 +114,31 @@ case "$tag" in
UCC_COMMIT=${_UCC_COMMIT}
TRITON=yes
;;
pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11)
CUDA_VERSION=13.0.0
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
GCC_VERSION=9
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks)
pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
ANACONDA_PYTHON_VERSION=3.10
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.13-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
ANACONDA_PYTHON_VERSION=3.13
GCC_VERSION=9
VISION=yes
KATEX=yes
@ -175,6 +187,20 @@ case "$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 [[ $tag =~ "benchmarks" ]]; then
INDUCTOR_BENCHMARKS=yes
fi
;;
pytorch-linux-noble-rocm-alpha-py3)
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
VISION=yes
ROCM_VERSION=7.0
NINJA_VERSION=1.9.0
TRITON=yes
@ -182,28 +208,25 @@ case "$tag" in
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
PYTORCH_ROCM_ARCH="gfx90a;gfx942;gfx950"
if [[ $tag =~ "benchmarks" ]]; then
INDUCTOR_BENCHMARKS=yes
fi
;;
pytorch-linux-jammy-xpu-n-1-py3)
ANACONDA_PYTHON_VERSION=3.10
pytorch-linux-jammy-xpu-2025.0-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
VISION=yes
XPU_VERSION=2025.0
NINJA_VERSION=1.9.0
TRITON=yes
;;
pytorch-linux-jammy-xpu-2025.1-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
VISION=yes
XPU_VERSION=2025.1
NINJA_VERSION=1.9.0
TRITON=yes
;;
pytorch-linux-jammy-xpu-n-py3)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
VISION=yes
XPU_VERSION=2025.2
NINJA_VERSION=1.9.0
TRITON=yes
;;
pytorch-linux-jammy-py3-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.10
pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
VISION=yes
KATEX=yes
@ -251,10 +274,13 @@ case "$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)
@ -441,3 +467,12 @@ 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

View File

@ -56,13 +56,9 @@ ENV INSTALLED_VISION ${VISION}
# Install rocm
ARG ROCM_VERSION
RUN mkdir ci_commit_pins
COPY ./common/common_utils.sh common_utils.sh
COPY ./ci_commit_pins/rocm-composable-kernel.txt ci_commit_pins/rocm-composable-kernel.txt
COPY ./common/install_rocm.sh install_rocm.sh
RUN bash ./install_rocm.sh
RUN rm install_rocm.sh common_utils.sh
RUN rm -r ci_commit_pins
RUN rm install_rocm.sh
COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh ${ROCM_VERSION}
RUN rm install_rocm_magma.sh

View File

@ -1 +1 @@
e0dda9059d082537cee36be6c5e4fe3b18c880c0
56392aa978594cc155fa8af48cd949f5b5f1823a

View File

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

View File

@ -1 +1 @@
v2.28.3-1
v2.27.5-1

View File

@ -1 +1 @@
v2.28.3-1
v2.27.7-1

View File

@ -1 +0,0 @@
7fe50dc3da2069d6645d9deb8c017a876472a977

View File

@ -1 +1 @@
74a23feff57432129df84d8099e622773cf77925
e03a63be43e33596f7f0a43b0f530353785e4a59

View File

@ -1 +1 @@
1b0418a9a454b2b93ab8d71f40e59d2297157fae
a6572fb0be5b9b0a19b0641a0ce05810fa04e44c

View File

@ -1 +1 @@
bbb06c0334a6772b92d24bde54956e675c8c6604
f7888497a1eb9e98d4c07537f0d0bcfe180d1363

View File

@ -83,9 +83,9 @@ function build_cpython {
py_suffix=${py_ver::-1}
py_folder=$py_suffix
fi
# Update to rc2 due to https://github.com/python/cpython/commit/c72699086fe4
# Only b3 is available now
if [ "$py_suffix" == "3.14.0" ]; then
py_suffix="3.14.0rc2"
py_suffix="3.14.0b3"
fi
wget -q $PYTHON_DOWNLOAD_URL/$py_folder/Python-$py_suffix.tgz -O Python-$py_ver.tgz
do_cpython_build $py_ver Python-$py_suffix

View File

@ -147,7 +147,7 @@ function install_128 {
}
function install_130 {
CUDNN_VERSION=9.13.0.50
CUDNN_VERSION=9.12.0.46
echo "Installing CUDA 13.0 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
# install CUDA 13.0 in the same container
install_cuda 13.0.0 cuda_13.0.0_580.65.06_linux

View File

@ -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

@ -2,11 +2,6 @@
set -ex
# for pip_install function
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
ROCM_COMPOSABLE_KERNEL_VERSION="$(cat $(dirname $0)/../ci_commit_pins/rocm-composable-kernel.txt)"
ver() {
printf "%3d%03d%03d%03d" $(echo "$1" | tr '.' ' ');
}
@ -42,6 +37,12 @@ EOF
rocm_baseurl="http://repo.radeon.com/rocm/apt/${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} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
@ -112,8 +113,6 @@ EOF
rm -rf HIP clr
fi
pip_install "git+https://github.com/rocm/composable_kernel@$ROCM_COMPOSABLE_KERNEL_VERSION"
# Cleanup
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
@ -177,8 +176,6 @@ install_centos() {
sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
done
pip_install "git+https://github.com/rocm/composable_kernel@$ROCM_COMPOSABLE_KERNEL_VERSION"
# Cleanup
yum clean all
rm -rf /var/cache/yum

View File

@ -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"

View File

@ -57,7 +57,7 @@ if [ ! -f setup.py ]; then
cd python
fi
pip_install pybind11==3.0.1
pip_install pybind11==2.13.6
# TODO: remove patch setup.py once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
as_jenkins sed -i -e 's/https:\/\/tritonlang.blob.core.windows.net\/llvm-builds/https:\/\/oaitriton.blob.core.windows.net\/public\/llvm-builds/g' setup.py
@ -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

@ -44,12 +44,8 @@ function install_ucc() {
./autogen.sh
if [[ -n "$CUDA_VERSION" && $CUDA_VERSION == 13* ]]; then
NVCC_GENCODE="-gencode=arch=compute_86,code=compute_86"
else
# We only run distributed tests on Tesla M60 and A10G
NVCC_GENCODE="-gencode=arch=compute_52,code=sm_52 -gencode=arch=compute_86,code=compute_86"
fi
# We only run distributed tests on Tesla M60 and A10G
NVCC_GENCODE="-gencode=arch=compute_52,code=sm_52 -gencode=arch=compute_86,code=compute_86"
if [[ -n "$ROCM_VERSION" ]]; then
if [[ -n "$PYTORCH_ROCM_ARCH" ]]; then

View File

@ -65,14 +65,10 @@ function install_ubuntu() {
function install_rhel() {
. /etc/os-release
if [[ "${ID}" == "rhel" ]]; then
if [[ ! " 8.8 8.9 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
echo "RHEL version ${VERSION_ID} not supported"
exit
fi
elif [[ "${ID}" == "almalinux" ]]; then
# Workaround for almalinux8 which used by quay.io/pypa/manylinux_2_28_x86_64
VERSION_ID="8.8"
if [[ ! " 8.8 8.10 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
echo "RHEL version ${VERSION_ID} not supported"
exit
fi
dnf install -y 'dnf-command(config-manager)'
@ -150,11 +146,11 @@ if [[ "${XPU_DRIVER_TYPE,,}" == "lts" ]]; then
XPU_DRIVER_VERSION="/lts/2350"
fi
# Default use Intel® oneAPI Deep Learning Essentials 2025.1
if [[ "$XPU_VERSION" == "2025.2" ]]; then
XPU_PACKAGES="intel-deep-learning-essentials-2025.2"
else
# Default use Intel® oneAPI Deep Learning Essentials 2025.0
if [[ "$XPU_VERSION" == "2025.1" ]]; then
XPU_PACKAGES="intel-deep-learning-essentials-2025.1"
else
XPU_PACKAGES="intel-deep-learning-essentials-2025.0"
fi
# The installation depends on the base OS

View File

@ -74,14 +74,6 @@ RUN bash ./install_cuda.sh 13.0
RUN bash ./install_magma.sh 13.0
RUN ln -sf /usr/local/cuda-13.0 /usr/local/cuda
# Install libibverbs for libtorch and copy to CUDA directory
RUN apt-get update -y && \
apt-get install -y libibverbs-dev librdmacm-dev && \
cp /usr/lib/x86_64-linux-gnu/libmlx5.so* /usr/local/cuda/lib64/ && \
cp /usr/lib/x86_64-linux-gnu/librdmacm.so* /usr/local/cuda/lib64/ && \
cp /usr/lib/x86_64-linux-gnu/libibverbs.so* /usr/local/cuda/lib64/ && \
cp /usr/lib/x86_64-linux-gnu/libnl* /usr/local/cuda/lib64/
FROM cpu as rocm
ARG ROCM_VERSION
ARG PYTORCH_ROCM_ARCH

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:${GPU_ARCH_VERSION}-complete
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
# add gfx950 conditionally starting in ROCm 7.0
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950"
fi
DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg ROCM_VERSION=${GPU_ARCH_VERSION}"
;;
*)

View File

@ -175,6 +175,6 @@ ENV XPU_DRIVER_TYPE ROLLING
RUN python3 -m pip install --upgrade pip && \
python3 -mpip install cmake==3.28.4
ADD ./common/install_xpu.sh install_xpu.sh
ENV XPU_VERSION 2025.2
ENV XPU_VERSION 2025.1
RUN bash ./install_xpu.sh && rm install_xpu.sh
RUN pushd /opt/_internal && tar -xJf static-libs-for-embedding-only.tar.xz && popd

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

@ -43,6 +43,12 @@ case ${image} in
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
GPU_IMAGE=s390x/almalinux:8
@ -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 conditionally starting in ROCm 7.0
if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
PYTORCH_ROCM_ARCH="${PYTORCH_ROCM_ARCH};gfx950"
fi
DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
;;
manylinux2_28-builder:xpu)

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:
@ -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 != "Windows"
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
@ -111,12 +105,14 @@ 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
@ -137,7 +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"
@ -172,9 +168,9 @@ pillow==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
@ -329,6 +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
@ -378,10 +376,10 @@ 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
tlparse==0.3.30
#Description: required for log parsing
cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x"

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@722b7e6f9ca512fcc526ad07d62b3d28c50bb6cd#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

@ -1 +1 @@
3.5.0
3.4.0

View File

@ -1 +1 @@
3.5.0
3.4.0

View File

@ -52,13 +52,9 @@ ENV INSTALLED_VISION ${VISION}
# Install rocm
ARG ROCM_VERSION
RUN mkdir ci_commit_pins
COPY ./common/common_utils.sh common_utils.sh
COPY ./ci_commit_pins/rocm-composable-kernel.txt ci_commit_pins/rocm-composable-kernel.txt
COPY ./common/install_rocm.sh install_rocm.sh
RUN bash ./install_rocm.sh
RUN rm install_rocm.sh common_utils.sh
RUN rm -r ci_commit_pins
RUN rm install_rocm.sh
COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh ${ROCM_VERSION}
RUN rm install_rocm_magma.sh

View File

@ -66,7 +66,6 @@ ENV NCCL_LIB_DIR="/usr/local/cuda/lib64/"
# (optional) Install UCC
ARG UCX_COMMIT
ARG UCC_COMMIT
ARG CUDA_VERSION
ENV UCX_COMMIT $UCX_COMMIT
ENV UCC_COMMIT $UCC_COMMIT
ENV UCX_HOME /usr

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

@ -3,6 +3,7 @@ from __future__ import annotations
import logging
import os
import textwrap
import xml.etree.ElementTree as ET
from pathlib import Path
from typing import TYPE_CHECKING
@ -16,6 +17,23 @@ if TYPE_CHECKING:
logger = logging.getLogger(__name__)
# ---- Template (title + per-command failures) ----
_TPL_FAIL_BY_CMD = Template(
textwrap.dedent("""\
## {{ title }}
{%- for section in sections if section.failures %}
### Test Command: {{ section.label }}
{%- for f in section.failures %}
- {{ f }}
{%- endfor %}
{%- endfor %}
""")
)
_TPL_CONTENT = Template(
textwrap.dedent("""\
## {{ title }}
@ -141,3 +159,65 @@ def render_content(
tpl = _TPL_CONTENT
md = tpl.render(title=title, content=content, lang=lang)
return md
def summarize_failures_by_test_command(
xml_and_labels: Iterable[tuple[str | Path, str]],
*,
title: str = "Pytest Failures by Test Command",
dedupe_within_command: bool = True,
) -> bool:
"""
Render a single Markdown block summarizing failures grouped by test command.
Returns True if anything was written, False otherwise.
"""
sections: list[dict] = []
for xml_path, label in xml_and_labels:
xmlp = Path(xml_path)
if not xmlp.exists():
# optional: your logger
# logger.warning("XML %s not found, skipping", xmlp)
continue
failed = _parse_failed(xmlp)
if dedupe_within_command:
failed = sorted(set(failed))
# collect even if empty; we'll filter in the template render
sections.append({"label": label, "failures": failed})
# If *all* sections are empty or we collected nothing, skip writing.
if not sections or all(not s["failures"] for s in sections):
return False
md = _TPL_FAIL_BY_CMD.render(title=title, sections=sections).rstrip() + "\n"
return write_gh_step_summary(md)
def _to_name_from_testcase(tc: ET.Element) -> str:
name = tc.attrib.get("name", "")
file_attr = tc.attrib.get("file")
if file_attr:
return f"{file_attr}:{name}"
classname = tc.attrib.get("classname", "")
parts = classname.split(".") if classname else []
if len(parts) >= 1:
mod_parts = parts[:-1] if len(parts) >= 2 else parts
mod_path = "/".join(mod_parts) + ".py" if mod_parts else "unknown.py"
return f"{mod_path}:{name}"
return f"unknown.py:{name or 'unknown_test'}"
def _parse_failed(xml_path: Path) -> list[str]:
if not xml_path.exists():
return []
tree = ET.parse(xml_path)
root = tree.getroot()
failed: list[str] = []
for tc in root.iter("testcase"):
if any(x.tag in {"failure", "error"} for x in tc):
failed.append(_to_name_from_testcase(tc))
return failed

View File

@ -4,6 +4,7 @@ General Utility helpers for CLI tasks.
import logging
import os
import secrets
import shlex
import subprocess
import sys
@ -11,6 +12,8 @@ from contextlib import contextmanager
from pathlib import Path
from typing import Optional
from cli.lib.common.path_helper import ensure_dir_exists
logger = logging.getLogger(__name__)
@ -137,3 +140,42 @@ def get_wheels(
relpath = str((Path(dirpath) / fname).relative_to(root))
items.append({"pkg": pkg, "relpath": relpath})
return items
def attach_junitxml_if_pytest(
cmd: str,
dir: Optional[Path],
prefix: str,
*,
ensure_unique: bool = False,
resolve_xml: bool = False,
) -> tuple[str, Optional[Path]]:
"""
Append --junitxml=<ABS_PATH> to a pytest command string.
The XML filename is <prefix>_<random-hex>.xml.
- dir: target folder (will be created), if None, skip the junitxml attachment
- prefix: filename prefix (e.g., "junit" -> junit_ab12cd34.xml)
- ensure_unique: if True, regenerate a hash with 8 characters
Returns: (amended_cmd, abs_xml_path)
"""
if "pytest" not in cmd:
return cmd, None
if dir is None:
return cmd, None
ensure_dir_exists(dir)
file_name_prefix = f"{prefix}"
if ensure_unique:
file_name_prefix += f"_{unique_hex(8)}"
xml_path = dir / f"{file_name_prefix}_junit_pytest.xml"
if resolve_xml:
xml_path = xml_path.resolve()
return f"{cmd} --junitxml={xml_path.as_posix()}", xml_path
def unique_hex(length: int = 8) -> str:
"""Return a random hex string of `length` characters."""
return secrets.token_hex((length + 1) // 2)[:length]

View File

@ -1,12 +1,18 @@
import logging
import os
import textwrap
from typing import Any
from pathlib import Path
from typing import Any, Optional
from cli.lib.common.gh_summary import write_gh_step_summary
from cli.lib.common.git_helper import clone_external_repo
from cli.lib.common.pip_helper import pip_install_packages
from cli.lib.common.utils import run_command, temp_environ, working_directory
from cli.lib.common.utils import (
attach_junitxml_if_pytest,
run_command,
temp_environ,
working_directory,
)
from jinja2 import Template
@ -41,6 +47,7 @@ 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 +74,16 @@ 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 ",
"pytest -v -s entrypoints/llm/test_generate_multiple_loras.py",
"VLLM_USE_V1=0 pytest -v -s entrypoints/offline_mode",
],
},
"vllm_regression_test": {
@ -92,24 +103,14 @@ def sample_vllm_test_library():
"num_gpus": 4,
"steps": [
"pytest -v -s -x lora/test_chatglm3_tp.py",
"echo $VLLM_WORKER_MULTIPROC_METHOD",
"pytest -v -s -x lora/test_llama_tp.py",
"pytest -v -s -x lora/test_llm_with_multi_loras.py",
"pytest -v -s -x lora/test_multi_loras_with_tp.py",
],
},
"vllm_distributed_test_28_failure_test": {
"title": "Distributed Tests (2 GPUs) pytorch 2.8 release failure",
"id": "vllm_distributed_test_28_failure_test",
"env_vars": {
"VLLM_WORKER_MULTIPROC_METHOD": "spawn",
},
"num_gpus": 4,
"steps": [
"pytest -v -s distributed/test_sequence_parallel.py",
],
},
"vllm_lora_28_failure_test": {
"title": "LoRA pytorch 2.8 failure test",
"id": "vllm_lora_28_failure_test",
"vllm_lora_280_failure_test": {
"title": "LoRA 280 failure test",
"id": "vllm_lora_280_failure_test",
"steps": ["pytest -v lora/test_quant_model.py"],
},
"vllm_multi_model_processor_test": {
@ -120,15 +121,6 @@ def sample_vllm_test_library():
"pytest -v -s models/multimodal/processing --ignore models/multimodal/processing/test_tensor_schema.py",
],
},
"vllm_multi_model_test_28_failure_test": {
"title": "Multi-Model Test (Failed 2.8 release)",
"id": "vllm_multi_model_test_28_failure_test",
"package_install": ["git+https://github.com/TIGER-AI-Lab/Mantis.git"],
"steps": [
"pytest -v -s models/multimodal/generation/test_voxtral.py",
"pytest -v -s models/multimodal/pooling",
],
},
"vllm_pytorch_compilation_unit_tests": {
"title": "PyTorch Compilation Unit Tests",
"id": "vllm_pytorch_compilation_unit_tests",
@ -143,28 +135,6 @@ def sample_vllm_test_library():
"pytest -v -s compile/test_decorator.py",
],
},
"vllm_languagde_model_test_extended_generation_28_failure_test": {
"title": "Language Models Test (Extended Generation) 2.8 release failure",
"id": "vllm_languagde_model_test_extended_generation_28_failure_test",
"package_install": [
"--no-build-isolation",
"git+https://github.com/Dao-AILab/causal-conv1d@v1.5.0.post8",
],
"steps": [
"pytest -v -s models/language/generation/test_mistral.py",
],
},
"vllm_distributed_test_2_gpu_28_failure_test": {
"title": "Distributed Tests (2 GPUs) pytorch 2.8 release failure",
"id": "vllm_distributed_test_2_gpu_28_failure_test",
"env_vars": {
"VLLM_WORKER_MULTIPROC_METHOD": "spawn",
},
"num_gpus": 4,
"steps": [
"pytest -v -s distributed/test_sequence_parallel.py",
],
},
# TODO(elainewy):need to add g6 with 4 gpus to run this test
"vllm_lora_test": {
"title": "LoRA Test %N",
@ -222,6 +192,9 @@ def run_test_plan(
tests_map: dict[str, Any],
shard_id: int = 0,
num_shards: int = 0,
*,
test_summary_path: Optional[Path] = None,
test_summary_result: Optional[list[tuple[str, str]]] = None,
):
"""
a method to run list of tests based on the test plan.
@ -234,7 +207,6 @@ def run_test_plan(
tests = tests_map[test_plan]
pkgs = tests.get("package_install", [])
title = tests.get("title", "unknown test")
is_parallel = check_parallelism(tests, title, shard_id, num_shards)
if is_parallel:
title = title.replace("%N", f"{shard_id}/{num_shards}")
@ -248,7 +220,15 @@ def run_test_plan(
temp_environ(tests.get("env_vars", {})),
):
failures = []
for step in tests["steps"]:
for idx, step in enumerate(tests["steps"]):
# generate xml report for each test for test summary if needed
step, xml_file_path = attach_junitxml_if_pytest(
cmd=step, dir=test_summary_path, prefix=f"{test_plan}_{idx}"
)
if xml_file_path and xml_file_path.exists() and test_summary_result:
test_summary_result.append((title, str(xml_file_path)))
else:
logger.info("No test report will be generate for %s", step)
logger.info("Running step: %s", step)
if is_parallel:
step = replace_buildkite_placeholders(step, shard_id, num_shards)

View File

@ -66,11 +66,6 @@ class VllmBuildParameters:
"DOCKERFILE_PATH", ".github/ci_configs/vllm/Dockerfile.tmp_vllm"
)
# the cleaning script to remove torch dependencies from pip
cleaning_script: Path = env_path_field(
"cleaning_script", ".github/ci_configs/vllm/use_existing_torch.py"
)
# OUTPUT_DIR: where docker buildx (local exporter) will write artifacts
output_dir: Path = env_path_field("OUTPUT_DIR", "external/vllm")
@ -165,7 +160,6 @@ class VllmBuildRunner(BaseRunner):
logger.info("Running vllm build with inputs: %s", inputs)
vllm_commit = clone_vllm()
self.cp_torch_cleaning_script(inputs)
self.cp_dockerfile_if_exist(inputs)
# cp torch wheels from root direct to vllm workspace if exist
self.cp_torch_whls_if_exist(inputs)
@ -211,11 +205,6 @@ class VllmBuildRunner(BaseRunner):
copy(inputs.torch_whls_path, tmp_dir)
return tmp_dir
def cp_torch_cleaning_script(self, inputs: VllmBuildParameters):
script = get_path(inputs.cleaning_script, resolve=True)
vllm_script = Path(f"./{self.work_directory}/use_existing_torch.py")
copy(script, vllm_script)
def cp_dockerfile_if_exist(self, inputs: VllmBuildParameters):
if not inputs.use_local_dockerfile:
logger.info("using vllm default dockerfile.torch_nightly for build")

View File

@ -11,15 +11,20 @@ from typing import Any
from cli.lib.common.cli_helper import BaseRunner
from cli.lib.common.envs_helper import env_path_field, env_str_field, get_env
from cli.lib.common.path_helper import copy, get_path, remove_dir
from cli.lib.common.gh_summary import (
gh_summary_path,
summarize_failures_by_test_command,
write_gh_step_summary,
)
from cli.lib.common.path_helper import copy, remove_dir
from cli.lib.common.pip_helper import (
pip_install_first_match,
pip_install_packages,
pkg_exists,
run_python,
)
from cli.lib.common.utils import run_command, working_directory
from cli.lib.core.vllm.lib import clone_vllm, run_test_plan, sample_vllm_test_library
from cli.lib.common.utils import ensure_dir_exists, run_command, working_directory
from cli.lib.core.vllm.lib import clone_vllm, run_test_plan, sample_vllm_test_library, summarize_build_info
logger = logging.getLogger(__name__)
@ -43,10 +48,6 @@ class VllmTestParameters:
torch_cuda_arch_list: str = env_str_field("TORCH_CUDA_ARCH_LIST", "8.9")
cleaning_script: Path = env_path_field(
"cleaning_script", ".github/ci_configs/vllm/use_existing_torch.py"
)
def __post_init__(self):
if not self.torch_whls_path.exists():
raise ValueError("missing torch_whls_path")
@ -95,21 +96,26 @@ class VllmTestRunner(BaseRunner):
logger.info("Display VllmTestParameters %s", params)
self._set_envs(params)
clone_vllm(dst=self.work_directory)
self.cp_torch_cleaning_script(params)
vllm_commit = clone_vllm(dst=self.work_directory)
with working_directory(self.work_directory):
remove_dir(Path("vllm"))
self._install_wheels(params)
self._install_dependencies()
# verify the torches are not overridden by test dependencies
check_versions()
return vllm_commit
def run(self):
"""
main function to run vllm test
"""
self.prepare()
vllm_commit = self.prepare()
# prepare test summary
test_summary_path = Path("tmp_pytest_report").resolve()
ensure_dir_exists(test_summary_path)
test_summary_result = []
try:
with working_directory(self.work_directory):
if self.test_type == TestInpuType.TEST_PLAN:
@ -120,21 +126,24 @@ class VllmTestRunner(BaseRunner):
sample_vllm_test_library(),
self.shard_id,
self.num_shards,
)
else:
run_test_plan(
self.test_plan, "vllm", sample_vllm_test_library()
test_summary_path=test_summary_path,
test_summary_result=test_summary_result,
)
else:
raise ValueError(f"Unknown test type {self.test_type}")
except Exception as e:
logger.error("Failed to run vllm test: %s", e)
finally:
# double check the torches are not overridden by other packages
check_versions()
self.vllm_test_gh_summary(vllm_commit, test_summary_result)
def cp_torch_cleaning_script(self, params: VllmTestParameters):
script = get_path(params.cleaning_script, resolve=True)
vllm_script = Path(f"./{self.work_directory}/use_existing_torch.py")
copy(script, vllm_script)
def vllm_test_gh_summary(
self, vllm_commit: str, test_summary_results: list[tuple[str, str]]
):
if not gh_summary_path():
return logger.info("Skipping, not detect GH Summary env var....")
logger.info("Generate GH Summary ...")
summarize_build_info(vllm_commit)
summarize_failures_by_test_command(test_summary_results)
def _install_wheels(self, params: VllmTestParameters):
logger.info("Running vllm test with inputs: %s", params)

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;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 \
@ -16,7 +16,6 @@ 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
@ -25,11 +24,6 @@ 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:

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

@ -124,7 +124,6 @@ if [[ $CUDA_VERSION == 12* || $CUDA_VERSION == 13* ]]; then
fi
if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
echo "Bundling with cudnn and cublas."
DEPS_LIST+=(
"/usr/local/cuda/lib64/libcudnn_adv.so.9"
"/usr/local/cuda/lib64/libcudnn_cnn.so.9"
@ -134,11 +133,16 @@ if [[ $CUDA_VERSION == 12* || $CUDA_VERSION == 13* ]]; then
"/usr/local/cuda/lib64/libcudnn_engines_precompiled.so.9"
"/usr/local/cuda/lib64/libcudnn_heuristic.so.9"
"/usr/local/cuda/lib64/libcudnn.so.9"
"/usr/local/cuda/lib64/libcublas.so.12"
"/usr/local/cuda/lib64/libcublasLt.so.12"
"/usr/local/cuda/lib64/libcusparseLt.so.0"
"/usr/local/cuda/lib64/libcudart.so.12"
"/usr/local/cuda/lib64/libnvrtc.so.12"
"/usr/local/cuda/lib64/libnvrtc-builtins.so"
"/usr/local/cuda/lib64/libcufile.so.0"
"/usr/local/cuda/lib64/libcufile_rdma.so.1"
"/usr/local/cuda/lib64/libnvshmem_host.so.3"
"/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12"
"/usr/local/cuda/extras/CUPTI/lib64/libnvperf_host.so"
)
DEPS_SONAME+=(
@ -150,56 +154,22 @@ if [[ $CUDA_VERSION == 12* || $CUDA_VERSION == 13* ]]; then
"libcudnn_engines_precompiled.so.9"
"libcudnn_heuristic.so.9"
"libcudnn.so.9"
"libcublas.so.12"
"libcublasLt.so.12"
"libcusparseLt.so.0"
"libcudart.so.12"
"libnvrtc.so.12"
"libnvrtc-builtins.so"
"libnvshmem_host.so.3"
"libcufile.so.0"
"libcufile_rdma.so.1"
"libcupti.so.12"
"libnvperf_host.so"
)
# Add libnvToolsExt only if CUDA version is not 12.9
if [[ $CUDA_VERSION == 13* ]]; then
DEPS_LIST+=(
"/usr/local/cuda/lib64/libcublas.so.13"
"/usr/local/cuda/lib64/libcublasLt.so.13"
"/usr/local/cuda/lib64/libcudart.so.13"
"/usr/local/cuda/lib64/libnvrtc.so.13"
"/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.13"
"/usr/local/cuda/lib64/libibverbs.so.1"
"/usr/local/cuda/lib64/librdmacm.so.1"
"/usr/local/cuda/lib64/libmlx5.so.1"
"/usr/local/cuda/lib64/libnl-3.so.200"
"/usr/local/cuda/lib64/libnl-route-3.so.200")
DEPS_SONAME+=(
"libcublas.so.13"
"libcublasLt.so.13"
"libcudart.so.13"
"libnvrtc.so.13"
"libcupti.so.13"
"libibverbs.so.1"
"librdmacm.so.1"
"libmlx5.so.1"
"libnl-3.so.200"
"libnl-route-3.so.200")
export USE_CUPTI_SO=1
export ATEN_STATIC_CUDA=0
export USE_CUDA_STATIC_LINK=0
export USE_CUFILE=0
else
DEPS_LIST+=(
"/usr/local/cuda/lib64/libnvToolsExt.so.1"
"/usr/local/cuda/lib64/libcublas.so.12"
"/usr/local/cuda/lib64/libcublasLt.so.12"
"/usr/local/cuda/lib64/libcudart.so.12"
"/usr/local/cuda/lib64/libnvrtc.so.12"
"/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12")
DEPS_SONAME+=(
"libnvToolsExt.so.1"
"libcublas.so.12"
"libcublasLt.so.12"
"libcudart.so.12"
"libnvrtc.so.12"
"libcupti.so.12")
if [[ $CUDA_VERSION != 12.9* ]]; then
DEPS_LIST+=("/usr/local/cuda/lib64/libnvToolsExt.so.1")
DEPS_SONAME+=("libnvToolsExt.so.1")
fi
else
echo "Using nvidia libs from pypi."

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

@ -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

@ -300,3 +300,24 @@ except RuntimeError as e:
exit 1
fi
fi
###############################################################################
# Check for C++ ABI compatibility to GCC-11 - GCC 13
###############################################################################
if [[ "$(uname)" == 'Linux' && "$PACKAGE_TYPE" == 'manywheel' ]]; then
pushd /tmp
# Per https://gcc.gnu.org/onlinedocs/gcc/C_002b_002b-Dialect-Options.html
# gcc-11 is ABI16, gcc-13 is ABI18, gcc-14 is ABI19
# gcc 11 - CUDA 11.8, xpu, rocm
# gcc 13 - CUDA 12.6, 12.8 and cpu
# Please see issue for reference: https://github.com/pytorch/pytorch/issues/152426
if [[ "$(uname -m)" == "s390x" ]]; then
cxx_abi="19"
elif [[ "$DESIRED_CUDA" != 'xpu' && "$DESIRED_CUDA" != 'rocm'* ]]; then
cxx_abi="18"
else
cxx_abi="16"
fi
python -c "import torch; exit(0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi10${cxx_abi}' else 1)"
popd
fi

View File

@ -258,19 +258,11 @@ function install_torchrec_and_fbgemm() {
git clone --recursive https://github.com/pytorch/fbgemm
pushd fbgemm/fbgemm_gpu
git checkout "${fbgemm_commit}" --recurse-submodules
# until the fbgemm_commit includes the tbb patch
patch <<'EOF'
--- a/FbgemmGpu.cmake
+++ b/FbgemmGpu.cmake
@@ -184,5 +184,6 @@ gpu_cpp_library(
fbgemm_gpu_tbe_cache
fbgemm_gpu_tbe_optimizers
fbgemm_gpu_tbe_utils
+ tbb
DESTINATION
fbgemm_gpu)
EOF
python setup.py bdist_wheel --build-variant=rocm
python setup.py bdist_wheel \
--build-variant=rocm \
-DHIP_ROOT_DIR="${ROCM_PATH}" \
-DCMAKE_C_FLAGS="-DTORCH_USE_HIP_DSA" \
-DCMAKE_CXX_FLAGS="-DTORCH_USE_HIP_DSA"
popd
# Save the wheel before cleaning up

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

@ -36,11 +36,11 @@ 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_DISTRIBUTED=1 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
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

@ -55,7 +55,7 @@ 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
}
@ -195,7 +195,7 @@ torchbench_setup_macos() {
git checkout "$(cat ../.github/ci_commit_pins/vision.txt)"
git submodule update --init --recursive
python setup.py clean
python -m pip install -e . -v --no-build-isolation
python setup.py develop
popd
pushd torchaudio
@ -204,7 +204,7 @@ torchbench_setup_macos() {
git submodule update --init --recursive
python setup.py clean
#TODO: Remove me, when figure out how to make TorchAudio find brew installed openmp
USE_OPENMP=0 python -m pip install -e . -v --no-build-isolation
USE_OPENMP=0 python setup.py develop
popd
checkout_install_torchbench
@ -302,47 +302,6 @@ test_torchbench_smoketest() {
fi
done
echo "Pytorch benchmark on mps device completed"
}
test_aoti_torchbench_smoketest() {
print_cmake_info
echo "Launching AOTInductor torchbench setup"
pip_benchmark_deps
# shellcheck disable=SC2119,SC2120
torchbench_setup_macos
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
local device=mps
local dtypes=(undefined float16 bfloat16 notset)
local dtype=${dtypes[$1]}
local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor timm_resnet timm_vovnet vgg16)
echo "Launching torchbench inference performance run for AOT Inductor and dtype ${dtype}"
local dtype_arg="--${dtype}"
if [ "$dtype" == notset ]; then
dtype_arg="--float32"
fi
touch "$TEST_REPORTS_DIR/aot_inductor_torchbench_${dtype}_inference_${device}_performance.csv"
for model in "${models[@]}"; do
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
--performance --only "$model" --export-aot-inductor --inference --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/aot_inductor_torchbench_${dtype}_inference_${device}_performance.csv" || true
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
--accuracy --only "$model" --export-aot-inductor --inference --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/aot_inductor_torchbench_${dtype}_inference_${device}_accuracy.csv" || true
done
echo "Launching HuggingFace inference performance run for AOT Inductor and dtype ${dtype}"
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/huggingface.py \
--performance --export-aot-inductor --inference --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/aot_inductor_huggingface_${dtype}_inference_${device}_performance.csv" || true
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/huggingface.py \
--accuracy --export-aot-inductor --inference --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/aot_inductor_huggingface_${dtype}_inference_${device}_accuracy.csv" || true
echo "Pytorch benchmark on mps device completed"
}
@ -391,8 +350,6 @@ elif [[ $TEST_CONFIG == *"perf_timm"* ]]; then
test_timm_perf
elif [[ $TEST_CONFIG == *"perf_smoketest"* ]]; then
test_torchbench_smoketest "${SHARD_NUMBER}"
elif [[ $TEST_CONFIG == *"aot_inductor_perf_smoketest"* ]]; then
test_aoti_torchbench_smoketest "${SHARD_NUMBER}"
elif [[ $TEST_CONFIG == *"mps"* ]]; then
test_python_mps
elif [[ $NUM_TEST_SHARDS -gt 1 ]]; then

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

@ -386,8 +386,8 @@ def smoke_test_compile(device: str = "cpu") -> None:
def smoke_test_nvshmem() -> None:
if not torch.cuda.is_available() or target_os == "windows":
print("Windows platform or CUDA is not available, skipping NVSHMEM test")
if not torch.cuda.is_available():
print("CUDA is not available, skipping NVSHMEM test")
return
# Check if NVSHMEM is compiled in current build
@ -396,9 +396,7 @@ def smoke_test_nvshmem() -> None:
except ImportError:
# Not built with NVSHMEM support.
# torch is not compiled with NVSHMEM prior to 2.9
from torch.torch_version import TorchVersion
if TorchVersion(torch.__version__) < (2, 9):
if torch.__version__ < "2.9":
return
else:
# After 2.9: NVSHMEM is expected to be compiled in current build

View File

@ -32,16 +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
NUMBA_CUDA_DIR=$(python -c "import os;import numba.cuda; print(os.path.dirname(numba.cuda.__file__))" 2>/dev/null || true)
if [ -n "$NUMBA_CUDA_DIR" ]; then
NUMBA_PATCH="$(dirname "$(realpath "${BASH_SOURCE[0]}")")/numba-cuda-13.patch"
pushd "$NUMBA_CUDA_DIR"
patch -p4 <"$NUMBA_PATCH"
popd
fi
echo "Environment variables:"
env
@ -322,29 +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
@ -390,7 +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
@ -435,7 +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
}
@ -513,14 +496,6 @@ test_inductor_cpp_wrapper_shard() {
-k 'take' \
--shard "$1" "$NUM_TEST_SHARDS" \
--verbose
if [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
python test/run_test.py \
--include inductor/test_mkldnn_pattern_matcher \
-k 'xpu' \
--shard "$1" "$NUM_TEST_SHARDS" \
--verbose
fi
}
# "Global" flags for inductor benchmarking controlled by TEST_CONFIG
@ -1163,12 +1138,6 @@ 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
@ -1415,7 +1384,7 @@ 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::"
@ -1563,10 +1532,14 @@ 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
@ -1580,14 +1553,17 @@ 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" "$NUM_TEST_SHARDS" --verbose
# Dynamo tests
@ -1617,7 +1593,7 @@ test_operator_benchmark() {
test_inductor_set_cpu_affinity
cd benchmarks/operator_benchmark/pt_extension
python -m pip install . -v --no-build-isolation
python -m pip install .
cd "${TEST_DIR}"/benchmarks/operator_benchmark
$TASKSET python -m benchmark_all_test --device "$1" --tag-filter "$2" \
@ -1630,25 +1606,6 @@ test_operator_benchmark() {
--expected "expected_ci_operator_benchmark_eager_float32_cpu.csv"
}
test_operator_microbenchmark() {
TEST_REPORTS_DIR=$(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())")
@ -1681,8 +1638,6 @@ 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"
@ -1705,8 +1660,6 @@ 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
@ -1760,6 +1713,11 @@ elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper* ]]; then
elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
install_torchvision
test_inductor_shard "${SHARD_NUMBER}"
if [[ "${SHARD_NUMBER}" == 1 ]]; then
if [[ "${BUILD_ENVIRONMENT}" != linux-jammy-py3.9-gcc11-build ]]; then
test_inductor_distributed
fi
fi
elif [[ "${TEST_CONFIG}" == *einops* ]]; then
test_einops
elif [[ "${TEST_CONFIG}" == *dynamo_wrapped* ]]; then
@ -1809,14 +1767,10 @@ elif [[ "${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

@ -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

@ -130,14 +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

@ -38,20 +38,13 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
fi
# TODO: Move both of them to Windows AMI
python -m pip install tensorboard==2.13.0 protobuf==5.29.4 pytest-subtests==0.13.1
# Copied from https://github.com/pytorch/test-infra/blob/be01a40157c36cd5a48391fdf44a7bc3ebd4c7e3/aws/ami/windows/scripts/Installers/Install-Pip-Dependencies.ps1#L16 with some adjustments
# pytest-rerunfailures==10.3 as 10.2 fails with INTERNALERROR> pluggy._manager.PluginValidationError: unknown hook 'pytest_configure_node'
# scipy from 1.6.3 to 1.10
# expecttest from 0.1.3 to 0.3.0
# xdoctest from 1.0.2 to 1.3.0
python -m pip install "future==0.18.2" "hypothesis==5.35.1" "expecttest==0.3.0" "librosa>=0.6.2" "scipy==1.10.1" "psutil==5.9.1" "pynvml==11.4.1" "pillow==9.2.0" "unittest-xml-reporting<=3.2.0,>=2.0.0" "pytest==7.1.3" "pytest-xdist==2.5.0" "pytest-flakefinder==1.1.0" "pytest-rerunfailures==10.3" "pytest-shard==0.1.2" "sympy==1.11.1" "xdoctest==1.3.0" "pygments==2.12.0" "opt-einsum>=3.3" "networkx==2.8.8" "mpmath==1.2.1" "pytest-cpp==2.3.0" "boto3==1.35.42"
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
python -m pip install tlparse==0.3.30
# Install parameterized
python -m pip install parameterized==0.8.1
@ -59,6 +52,9 @@ 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
for path in '/c/Program Files/NVIDIA Corporation/NVSMI/nvidia-smi.exe' /c/Windows/System32/nvidia-smi.exe; do

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

@ -1,20 +1,12 @@
if %CUDA_VERSION% geq 130 (
set "dll_path=bin\x64"
) else (
set "dll_path=bin"
)
copy "%CUDA_PATH%\%dll_path%\cusparse*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\%dll_path%\cublas*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\%dll_path%\cudart*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\%dll_path%\curand*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\%dll_path%\cufft*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\%dll_path%\cusolver*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\%dll_path%\nvrtc*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\%dll_path%\nvJitLink_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\bin\cusparse*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\bin\cublas*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\bin\cudart*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\bin\curand*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\bin\cufft*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\bin\cusolver*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\bin\cudnn*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\bin\nvrtc*64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\extras\CUPTI\lib64\cupti64_*.dll*" pytorch\torch\lib
copy "%CUDA_PATH%\extras\CUPTI\lib64\nvperf_host*.dll*" pytorch\torch\lib
@ -28,3 +20,8 @@ copy "%libuv_ROOT%\bin\uv.dll" pytorch\torch\lib
if exist "C:\Windows\System32\zlibwapi.dll" (
copy "C:\Windows\System32\zlibwapi.dll" pytorch\torch\lib
)
::copy nvJitLink dll is requires for cuda 12+
if exist "%CUDA_PATH%\bin\nvJitLink_*.dll*" (
copy "%CUDA_PATH%\bin\nvJitLink_*.dll*" pytorch\torch\lib
)

View File

@ -1,9 +1,9 @@
set WIN_DRIVER_VN=580.88
set "DRIVER_DOWNLOAD_LINK=https://ossci-windows.s3.amazonaws.com/%WIN_DRIVER_VN%-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe" & REM @lint-ignore
curl --retry 3 -kL %DRIVER_DOWNLOAD_LINK% --output %WIN_DRIVER_VN%-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe
set WIN_DRIVER_VN=528.89
set "DRIVER_DOWNLOAD_LINK=https://ossci-windows.s3.amazonaws.com/%WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe" & REM @lint-ignore
curl --retry 3 -kL %DRIVER_DOWNLOAD_LINK% --output %WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe
if errorlevel 1 exit /b 1
start /wait %WIN_DRIVER_VN%-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe -s -noreboot
start /wait %WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe -s -noreboot
if errorlevel 1 exit /b 1
del %WIN_DRIVER_VN%-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe || ver > NUL
del %WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe || ver > NUL

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

@ -13,9 +13,9 @@ if not exist "%SRC_DIR%\temp_build" mkdir "%SRC_DIR%\temp_build"
:xpu_bundle_install_start
set XPU_BUNDLE_PARENT_DIR=C:\Program Files (x86)\Intel\oneAPI
set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/75d4eb97-914a-4a95-852c-7b9733d80f74/intel-deep-learning-essentials-2025.1.3.8_offline.exe
set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/9d6d6c17-ca2d-4735-9331-99447e4a1280/intel-deep-learning-essentials-2025.0.1.28_offline.exe
set XPU_BUNDLE_PRODUCT_NAME=intel.oneapi.win.deep-learning-essentials.product
set XPU_BUNDLE_VERSION=2025.1.3+5
set XPU_BUNDLE_VERSION=2025.0.1+20
set XPU_BUNDLE_INSTALLED=0
set XPU_BUNDLE_UNINSTALL=0
set XPU_EXTRA_URL=NULL
@ -24,9 +24,9 @@ set XPU_EXTRA_VERSION=2025.0.1+1226
set XPU_EXTRA_INSTALLED=0
set XPU_EXTRA_UNINSTALL=0
if not [%XPU_VERSION%]==[] if [%XPU_VERSION%]==[2025.2] (
set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/24751ead-ddc5-4479-b9e6-f9fe2ff8b9f2/intel-deep-learning-essentials-2025.2.1.25_offline.exe
set XPU_BUNDLE_VERSION=2025.2.1+20
if not [%XPU_VERSION%]==[] if [%XPU_VERSION%]==[2025.1] (
set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/75d4eb97-914a-4a95-852c-7b9733d80f74/intel-deep-learning-essentials-2025.1.3.8_offline.exe
set XPU_BUNDLE_VERSION=2025.1.3+5
)
:: Check if XPU bundle is target version or already installed
@ -90,3 +90,14 @@ if errorlevel 1 exit /b 1
del xpu_extra.exe
:xpu_install_end
if not "%XPU_ENABLE_KINETO%"=="1" goto install_end
:: Install Level Zero SDK
set XPU_EXTRA_LZ_URL=https://github.com/oneapi-src/level-zero/releases/download/v1.14.0/level-zero-sdk_1.14.0.zip
curl -k -L %XPU_EXTRA_LZ_URL% --output "%SRC_DIR%\temp_build\level_zero_sdk.zip"
echo "Installing level zero SDK..."
7z x "%SRC_DIR%\temp_build\level_zero_sdk.zip" -o"%SRC_DIR%\temp_build\level_zero"
set "INCLUDE=%SRC_DIR%\temp_build\level_zero\include;%INCLUDE%"
del "%SRC_DIR%\temp_build\level_zero_sdk.zip"
:install_end

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

@ -85,7 +85,7 @@ mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
# Create an isolated directory to store this builds pytorch checkout and conda
# installation
if [[ -z "$MAC_PACKAGE_WORK_DIR" ]]; then
MAC_PACKAGE_WORK_DIR="$(pwd)/tmp_wheel_${DESIRED_PYTHON}_$(date +%H%M%S)"
MAC_PACKAGE_WORK_DIR="$(pwd)/tmp_wheel_conda_${DESIRED_PYTHON}_$(date +%H%M%S)"
fi
mkdir -p "$MAC_PACKAGE_WORK_DIR" || true
if [[ -n ${GITHUB_ACTIONS} ]]; then
@ -96,11 +96,11 @@ fi
whl_tmp_dir="${MAC_PACKAGE_WORK_DIR}/dist"
mkdir -p "$whl_tmp_dir"
mac_version='macosx-11_0-arm64'
mac_version='macosx_11_0_arm64'
libtorch_arch='arm64'
# Create a consistent wheel package name to rename the wheel to
wheel_filename_new="${TORCH_PACKAGE_NAME}-${build_version}${build_number_prefix}-cp${python_nodot}-none-${mac_version//[-,]/_}.whl"
wheel_filename_new="${TORCH_PACKAGE_NAME}-${build_version}${build_number_prefix}-cp${python_nodot}-none-${mac_version}.whl"
###########################################################
@ -124,58 +124,93 @@ popd
export TH_BINARY_BUILD=1
export INSTALL_TEST=0 # dont install test binaries into site-packages
export MACOSX_DEPLOYMENT_TARGET=11.0
export MACOSX_DEPLOYMENT_TARGET=10.15
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
SETUPTOOLS_PINNED_VERSION="==70.1.0"
PYYAML_PINNED_VERSION="==5.3"
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
RENAME_WHEEL=true
case $desired_python in
3.14t)
echo "Using 3.14 deps"
mac_version='macosx-11.0-arm64'
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.1.0"
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
RENAME_WHEEL=false
;;
3.14)
echo "Using 3.14t deps"
mac_version='macosx-11.0-arm64'
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.1.0"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
RENAME_WHEEL=false
;;
3.13t)
echo "Using 3.13t deps"
mac_version='macosx-11.0-arm64'
echo "Using 3.13 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.1.0"
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
RENAME_WHEEL=false
;;
3.13)
echo "Using 3.13 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.1.0"
;;
3.12)
echo "Using 3.12 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.0.2"
;;
3.11)
echo "Using 3.11 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="==2.0.2"
;;
3.10)
echo "Using 3.10 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="==2.0.2"
;;
3.9)
echo "Using 3.9 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="==2.0.2"
;;
*)
echo "Unsupported version $desired_python"
exit 1
echo "Using default deps"
NUMPY_PINNED_VERSION="==1.11.3"
;;
esac
# Install into a fresh env
tmp_env_name="wheel_py$python_nodot"
conda create ${EXTRA_CONDA_INSTALL_FLAGS} -yn "$tmp_env_name" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS}
source activate "$tmp_env_name"
PINNED_PACKAGES=(
"setuptools${SETUPTOOLS_PINNED_VERSION}"
"pyyaml${PYYAML_PINNED_VERSION}"
"numpy${NUMPY_PINNED_VERSION}"
)
python -mvenv ~/${desired_python}-build
source ~/${desired_python}-build/bin/activate
retry pip install "${PINNED_PACKAGES[@]}" -r "${pytorch_rootdir}/requirements.txt"
retry pip install "${PINNED_PACKAGES[@]}" -r "${pytorch_rootdir}/requirements-build.txt"
pip install requests ninja typing-extensions
retry pip install -r "${pytorch_rootdir}/requirements.txt" || true
retry brew install libomp
# For USE_DISTRIBUTED=1 on macOS, need libuv, which is build as part of tensorpipe submodule
@ -186,11 +221,11 @@ 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 setup.py bdist_wheel -d "$whl_tmp_dir"
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

@ -75,8 +75,8 @@ TRITON_VERSION=$(cat $PYTORCH_ROOT/.ci/docker/triton_version.txt)
# Here PYTORCH_EXTRA_INSTALL_REQUIREMENTS is already set for the all the wheel builds hence append TRITON_CONSTRAINT
TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64'"
# CUDA 12.9/13.0 builds have triton for Linux and Linux aarch64 binaries.
if [[ "$DESIRED_CUDA" == "cu129" ]] || [[ "$DESIRED_CUDA" == "cu130" ]]; then
# CUDA 12.9 builds have triton for Linux and Linux aarch64 binaries.
if [[ "$DESIRED_CUDA" == "cu129" ]]; then
TRITON_CONSTRAINT="platform_system == 'Linux'"
fi

View File

@ -15,7 +15,8 @@ fi
if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
export VC_YEAR=2022
export USE_SCCACHE=0
export XPU_VERSION=2025.2
export XPU_VERSION=2025.1
export XPU_ENABLE_KINETO=1
fi
echo "Free space on filesystem before build:"

View File

@ -8,7 +8,7 @@ export VC_YEAR=2022
if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
export VC_YEAR=2022
export XPU_VERSION=2025.2
export XPU_VERSION=2025.1
fi
pushd "$PYTORCH_ROOT/.ci/pytorch/"

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

@ -69,8 +69,6 @@ readability-string-compare,
'
HeaderFilterRegex: '^(aten/|c10/|torch/).*$'
WarningsAsErrors: '*'
LineFilter:
- name: '/usr/include/.*'
CheckOptions:
cppcoreguidelines-special-member-functions.AllowSoleDefaultDtor: true
cppcoreguidelines-special-member-functions.AllowImplicitlyDeletedCopyOrMove: true

View File

@ -73,7 +73,7 @@ exclude =
./docs/src,
./functorch/docs,
./functorch/examples,
./functorch/docs/source/tutorials,
./functorch/notebooks,
./scripts,
./test/generated_type_hints_smoketest.py,
./third_party,

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

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@ -12,19 +12,13 @@ self-hosted-runner:
- linux.9xlarge.ephemeral
- am2.linux.9xlarge.ephemeral
- linux.12xlarge
- linux.12xlarge.memory
- linux.24xlarge
- linux.24xlarge.memory
- linux.24xlarge.ephemeral
- linux.24xlarge.amd
- linux.arm64.2xlarge
- 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

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@ -4,11 +4,6 @@ name: Build External packages
description: build external packages for PyTorch
inputs:
cuda-version:
description: CUDA version to use
type: string
required: true
default: '12.8.1'
cuda-arch-list:
description: TORCH_CUDA_ARCH_LIST (e.g., "8.0;8.9;9.0")
type: string
@ -49,12 +44,11 @@ runs:
env:
SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
SCCACHE_REGION: us-east-1
CUDA_VERSION: ${{ inputs.cuda-version }}
TORCH_CUDA_ARCH_LIST: ${{ inputs.cuda-arch-list }}
BASE_IMAGE: ${{ inputs.docker-image }}
BUILD_TARGETS: ${{ inputs.build-targets }}
PARENT_OUTPUT_DIR: ${{ inputs.output-dir }}
TORCH_WHEELS_PATH: ${{ inputs.torch-wheel-dir }}
PARENT_OUTPUT_DIR: ${{ inputs.output-dir}}
shell: bash
run: |
set -euo pipefail
@ -75,6 +69,7 @@ runs:
export OUTPUT_DIR
echo "Building external package: $target in directory $OUTPUT_DIR"
python3 -m cli.run build external "$target"
done
END_TIME=$(date +%s)

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@ -57,21 +57,6 @@ runs:
submodules: ${{ inputs.submodules }}
show-progress: false
- name: Clean submodules post checkout
id: clean-submodules
if: ${{ steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' }}
shell: bash
env:
NO_SUDO: ${{ inputs.no-sudo }}
run: |
cd "${GITHUB_WORKSPACE}"
# Clean stale submodule dirs
if [ -z "${NO_SUDO}" ]; then
sudo git submodule foreach --recursive git clean -ffdx
else
git submodule foreach --recursive git clean -ffdx
fi
- name: Clean workspace (try again)
if: ${{ steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' &&
(steps.first-clean.outcome != 'success' || steps.first-checkout-attempt.outcome != 'success') }}

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

@ -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

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@ -1 +1 @@
87ff22e49ed0e92576c4935ccb8c143daac4a3cd
10a5002c6195bd95e34df8fe28ff8a2d55a2a922

View File

@ -1 +1 @@
08ae0af1395c8d8471f4025deb6af9aef90b342f
7f1de94a4c2d14f59ad4ca84538c36084ea6b2c8

View File

@ -1 +1 @@
78a47f87ce259a48f0391fa9ae15add05ea7432b
add1adfec742dfb13e614dab3372b5aafd1ff046

View File

@ -1 +1 @@
0fc62aa26a30ed7ca419d285f285cb5ba02c4394
a1c6ee92c85e8b0955c20892ed68f032a6015c09

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@ -12,46 +12,54 @@ ARG BUILD_BASE_IMAGE=torch-nightly-base
# by default, it uses devel-ubuntu22.04 official image.
ARG FINAL_BASE_IMAGE=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04
# The logic is copied from https://github.com/vllm-project/vllm/blob/main/docker/Dockerfile
ARG GET_PIP_URL="https://bootstrap.pypa.io/get-pip.py"
#################### TORCH NIGHTLY BASE IMAGE ####################
#################### TORCH NIGHTLY BASE IMAGE ####################
# A base image for building vLLM with devel ubuntu 22.04, this is mainly used to build vllm in vllm builtkite ci
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 as torch-nightly-base
From nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 as torch-nightly-base
ARG CUDA_VERSION=12.8.1
ARG PYTHON_VERSION=3.12
ARG TARGETPLATFORM
ENV DEBIAN_FRONTEND=noninteractive
ARG CUDA_VERSION
ARG PYTHON_VERSION
ARG GET_PIP_URL
RUN PYTHON_VERSION_STR=$(echo ${PYTHON_VERSION} | sed 's/\.//g') && \
echo "export PYTHON_VERSION_STR=${PYTHON_VERSION_STR}" >> /etc/environment
# Install Python and other dependencies
RUN apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim \
&& add-apt-repository -y ppa:deadsnakes/ppa \
&& apt-get update -y \
&& apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
&& update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS ${GET_PIP_URL} | python${PYTHON_VERSION} \
&& python3 --version && python3 -m pip --version
# Install Python and other dependencies if it does not existed
RUN if ! command -v python3 >/dev/null || ! python3 --version | grep -q "${PYTHON_VERSION}"; then \
echo "Installing Python ${PYTHON_VERSION}..." && \
echo 'tzdata tzdata/Areas select America' | debconf-set-selections && \
echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections && \
apt-get update -y && \
apt-get install -y ccache software-properties-common git curl sudo && \
for i in 1 2 3; do \
add-apt-repository -y ppa:deadsnakes/ppa && break || \
{ echo "Attempt $i failed, retrying in 5s..."; sleep 5; }; \
done && \
apt-get update -y && \
apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv && \
update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 && \
update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} && \
ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config && \
curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}; \
else \
echo "Python ${PYTHON_VERSION} already present, skipping setup."; \
fi \
&& python3 --version && python3 -m pip --version
# Upgrade to GCC 10 to avoid https://gcc.gnu.org/bugzilla/show_bug.cgi?id=92519
# as it was causing spam when compiling the CUTLASS kernels
# Ensure gcc >= 10 to avoid CUTLASS issues (bug 92519)
RUN current_gcc_version=$(gcc -dumpversion | cut -f1 -d.) && \
if command -v apt-get >/dev/null; then \
if [ "$current_gcc_version" -lt 10 ]; then \
echo "GCC version is $current_gcc_version, installing gcc-10..."; \
apt-get update \
&& apt-get install -y gcc-10 g++-10 \
&& update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 100 \
&& update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-10 100; \
else \
echo "GCC version is $current_gcc_version, no need to install gcc-10."; \
fi \
fi \
&& gcc --version && g++ --version
if [ "$current_gcc_version" -lt 10 ]; then \
echo "GCC version is $current_gcc_version, installing gcc-10..."; \
apt-get update && \
apt-get install -y gcc-10 g++-10 && \
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 100 && \
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-10 100; \
else \
echo "GCC version is $current_gcc_version, no need to install gcc-10."; \
fi && \
gcc --version && g++ --version
# install uv for faster pip installs
RUN --mount=type=cache,target=/root/.cache/uv \
@ -71,20 +79,11 @@ ENV UV_LINK_MODE=copy
FROM ${BUILD_BASE_IMAGE} AS base
USER root
ARG CUDA_VERSION
ARG PYTHON_VERSION
# TODO (huydhn): Only work with PyTorch manylinux builder
ENV PATH="/opt/python/cp312-cp312/bin:${PATH}"
# Install some system dependencies and double check python version
RUN if command -v apt-get >/dev/null; then \
apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim; \
else \
dnf install -y git curl wget sudo; \
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 $CUDA_VERSION | cut -d. -f1,2)/compat/
# Install uv for faster pip installs if not existed
RUN --mount=type=cache,target=/root/.cache/uv \
@ -119,15 +118,17 @@ RUN --mount=type=bind,source=${TORCH_WHEELS_PATH},target=/dist \
if [ -n "$TORCH_WHEELS_PATH" ] && [ "$TORCH_WHEELS_PATH" != "./requirements" ] && [ -d "/dist" ] && ls /dist/torch*.whl >/dev/null 2>&1; then \
echo "[INFO] Installing torch wheels to build vllm"; \
torch_whl=$(find /dist -maxdepth 1 -name 'torch-*.whl' -print -quit); \
vision_whl=$(find /dist -name 'torchvision*.whl' | head -n1 | xargs); \
audio_whl=$(find /dist -name 'torchaudio*.whl' | head -n1 | xargs); \
uv pip install --system "${torch_whl}[opt-einsum]" "${vision_whl}" "${audio_whl}" /dist/*.whl; \
vision_whl=$(find /dist/vision -name 'torchvision*.whl' | head -n1 | xargs); \
audio_whl=$(find /dist/audio -name 'torchaudio*.whl' | head -n1 | xargs); \
uv pip install --system "${torch_whl}[opt-einsum]"; \
uv pip install --system "${vision_whl}"; \
uv pip install --system "${audio_whl}"; \
elif [ -n "$PINNED_TORCH_VERSION" ]; then \
echo "[INFO] Installing pinned torch nightly version to build vllm: $PINNED_TORCH_VERSION"; \
uv pip install --system "$PINNED_TORCH_VERSION" --index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.'); \
uv pip install --system "$PINNED_TORCH_VERSION" --index-url https://download.pytorch.org/whl/nightly/cu128; \
else \
echo "[INFO] Installing torch nightly with latest one to build vllm"; \
uv pip install --system torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.'); \
uv pip install --system torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128; \
fi
# Install numba 0.61.2 for cuda environment
@ -136,11 +137,12 @@ RUN --mount=type=cache,target=/root/.cache/uv \
# Install common dependencies from vllm common.txt
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/common.txt
uv pip install --system -r requirements/common.txt
# Must put before installing xformers, so it can install the correct version of xfomrers.
ARG xformers_cuda_arch_list='7.5;8.0+PTX;9.0a'
ENV TORCH_CUDA_ARCH_LIST=${xformers_cuda_arch_list}
ARG exformer_cuda_arch_list='7.5;8.0+PTX;9.0a'
ENV TORCH_CUDA_ARCH_LIST=${exformer_cuda_arch_list}
ARG max_jobs=16
ENV MAX_JOBS=${max_jobs}
@ -151,8 +153,8 @@ RUN pip freeze | grep -E 'ninja'
# Build xformers with cuda and torch nightly/wheel
# following official xformers guidance: https://github.com/facebookresearch/xformers#build
# sha for https://github.com/facebookresearch/xformers/tree/v0.0.32.post2
ARG XFORMERS_COMMIT=5d4b92a5e5a9c6c6d4878283f47d82e17995b468
# sha for https://github.com/facebookresearch/xformers/tree/v0.0.31
ARG XFORMERS_COMMIT=eb0946a363464da96ea40afd1a7f72a907c25497
ENV CCACHE_DIR=/root/.cache/ccache
RUN --mount=type=cache,target=/root/.cache/ccache \
@ -186,6 +188,11 @@ RUN pip freeze | grep -E 'torch|xformers|torchvision|torchaudio'
FROM base AS build
ARG TARGETPLATFORM
ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"
# Use copy mode to avoid hardlink failures with Docker cache mounts
ENV UV_LINK_MODE=copy
COPY . .
RUN python3 use_existing_torch.py
@ -214,16 +221,11 @@ 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} \
@ -249,9 +251,9 @@ RUN --mount=type=cache,target=/root/.cache/ccache \
python3 setup.py bdist_wheel --dist-dir=vllm-dist --py-limited-api=cp38; \
fi
RUN echo "[INFO] Listing current directory:" && \
RUN echo "[DEBUG] Listing current directory:" && \
ls -al && \
echo "[INFO] Showing torch_build_versions.txt content:" && \
echo "[DEBUG] Showing torch_build_versions.txt content:" && \
cat torch_build_versions.txt
#################### WHEEL BUILD IMAGE ####################
@ -261,42 +263,51 @@ RUN echo "[INFO] Listing current directory:" && \
# Setup clean environment for vLLM for test and api server using ubuntu22.04 with AOT flashinfer
FROM ${FINAL_BASE_IMAGE} AS vllm-base
USER root
ARG CUDA_VERSION
ARG PYTHON_VERSION
ARG GET_PIP_URL
# TODO (huydhn): Only work with PyTorch manylinux builder
ENV PATH="/opt/python/cp312-cp312/bin:${PATH}"
# prepare for environment starts
WORKDIR /workspace
# Install Python and other dependencies
RUN if command -v apt-get >/dev/null; then \
apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim \
&& add-apt-repository -y ppa:deadsnakes/ppa \
&& apt-get update -y \
&& apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
&& update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS ${GET_PIP_URL} | python${PYTHON_VERSION}; \
else \
dnf install -y git curl wget sudo; \
fi \
&& python3 --version && python3 -m pip --version
RUN PYTHON_VERSION_STR=$(echo ${PYTHON_VERSION} | sed 's/\.//g') && \
echo "export PYTHON_VERSION_STR=${PYTHON_VERSION_STR}" >> /etc/environment
# Install Python and other dependencies if it does not existed
RUN if ! command -v python3 >/dev/null || ! python3 --version | grep -q "${PYTHON_VERSION}"; then \
echo "Installing Python ${PYTHON_VERSION}..." && \
echo 'tzdata tzdata/Areas select America' | debconf-set-selections && \
echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections && \
apt-get update -y && \
apt-get install -y ccache software-properties-common git curl sudo && \
for i in 1 2 3; do \
add-apt-repository -y ppa:deadsnakes/ppa && break || \
{ echo "Attempt $i failed, retrying in 5s..."; sleep 5; }; \
done && \
apt-get update -y && \
apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv && \
update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 && \
update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} && \
ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config && \
curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}; \
else \
echo "Python ${PYTHON_VERSION} already present, skipping setup."; \
fi \
&& python3 --version && python3 -m pip --version
# Get the torch versions, and whls used in previous stagtes for consistency
COPY --from=base /workspace/torch_build_versions.txt ./torch_build_versions.txt
COPY --from=base /workspace/xformers-dist /wheels/xformers
COPY --from=build /workspace/vllm-dist /wheels/vllm
RUN echo "[INFO] Listing current directory before torch install step:" && \
RUN echo "[DEBUG] Listing current directory before torch install step:" && \
ls -al && \
echo "[INFO] Showing torch_build_versions.txt content:" && \
echo "[DEBUG] Showing torch_build_versions.txt content:" && \
cat torch_build_versions.txt
# Workaround for https://github.com/openai/triton/issues/2507 and
# https://github.com/pytorch/pytorch/issues/107960 -- hopefully
# this won't be needed for future versions of this docker image
# or future versions of triton.
RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
# Install uv for faster pip installs if not existed
RUN --mount=type=cache,target=/root/.cache/uv \
if ! python3 -m uv --version > /dev/null 2>&1; then \
@ -316,13 +327,15 @@ RUN --mount=type=bind,source=${TORCH_WHEELS_PATH},target=/dist \
--mount=type=cache,target=/root/.cache/uv \
if [ -n "$TORCH_WHEELS_PATH" ] && [ "$TORCH_WHEELS_PATH" != "./requirements" ] && [ -d "/dist" ] && ls /dist/torch*.whl >/dev/null 2>&1; then \
torch_whl=$(find /dist -maxdepth 1 -name 'torch-*.whl' -print -quit); \
vision_whl=$(find /dist -name 'torchvision*.whl' | head -n1 | xargs); \
audio_whl=$(find /dist -name 'torchaudio*.whl' | head -n1 | xargs); \
vision_whl=$(find /dist/vision -name 'torchvision*.whl' | head -n1 | xargs); \
audio_whl=$(find /dist/audio -name 'torchaudio*.whl' | head -n1 | xargs); \
echo "[INFO] Use wheels to build : '${torch_whl}' '${audio_whl}' '${vision_whl}'"; \
uv pip install --system "${torch_whl}[opt-einsum]" "${vision_whl}" "${audio_whl}" /dist/*.whl; \
uv pip install --system "${torch_whl}[opt-einsum]"; \
uv pip install --system "${vision_whl}"; \
uv pip install --system "${audio_whl}"; \
else \
echo "[INFO] Installing torch versions from torch_build_versions.txt"; \
uv pip install --system $(cat torch_build_versions.txt | xargs) --index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.'); \
uv pip install --system $(cat torch_build_versions.txt | xargs) --index-url https://download.pytorch.org/whl/nightly/cu128; \
fi
# Install the vllm wheel from previous stage
@ -333,8 +346,9 @@ RUN --mount=type=cache,target=/root/.cache/uv \
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system /wheels/xformers/*.whl --verbose
# Build flashinfer from source.
ARG torch_cuda_arch_list='8.0;8.9;9.0a;10.0a;12.0'
ARG torch_cuda_arch_list='8.0;8.9;9.0a'
# install package for build flashinfer
# see issue: https://github.com/flashinfer-ai/flashinfer/issues/738
@ -402,6 +416,11 @@ RUN --mount=type=cache,target=/root/.cache/uv \
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/nightly_torch_test.txt
# Workaround for #17068
# pinned commit for v2.2.4
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system --no-build-isolation "git+https://github.com/state-spaces/mamba@95d8aba8a8c75aedcaa6143713b11e745e7cd0d9#egg=mamba-ssm"
# Logging to confirm the torch versions
RUN pip freeze | grep -E 'torch|xformers|vllm|flashinfer'

View File

@ -1,17 +0,0 @@
import glob
requires_files = glob.glob("requirements/*.txt")
requires_files += ["pyproject.toml"]
for file in requires_files:
print(f">>> cleaning {file}")
with open(file) as f:
lines = f.readlines()
if "torch" in "".join(lines).lower():
print("removed:")
with open(file, "w") as f:
for line in lines:
if "torch" not in line.lower():
f.write(line)
print(f"<<< done cleaning {file}")
print()

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

@ -1,5 +1,4 @@
boto3==1.35.42
build==1.2.2.post1
cmake==3.27.*
expecttest==0.3.0
fbscribelogger==0.1.7
@ -16,7 +15,7 @@ optree==0.13.0
packaging==23.1
parameterized==0.8.1
pillow==10.3.0
protobuf==5.29.5
protobuf==5.29.4
psutil==5.9.8
pygments==2.15.0
pytest-cpp==2.3.0
@ -27,9 +26,9 @@ pytest-xdist==3.3.1
pytest==7.3.2
pyyaml==6.0.2
scipy==1.12.0
setuptools==78.1.1
setuptools==72.1.0
sympy==1.13.3
tlparse==0.4.0
tlparse==0.3.30
tensorboard==2.13.0
typing-extensions==4.12.2
unittest-xml-reporting<=3.2.0,>=2.0.0

View File

@ -84,7 +84,6 @@ def build_triton(
["git", "checkout", f"release/{ver}.{rev}.x"], cwd=triton_basedir
)
else:
check_call(["git", "fetch", "origin", commit_hash], cwd=triton_basedir)
check_call(["git", "checkout", commit_hash], cwd=triton_basedir)
# change built wheel name and version

View File

@ -39,9 +39,7 @@ def main() -> None:
pull_request_label_names = [label.name for label in pull_request_labels]
issue_label_names = [label.name for label in issue_labels]
labels_to_add = [
label
for label in issue_label_names
if label not in pull_request_label_names and label != "actionable"
label for label in issue_label_names if label not in pull_request_label_names
]
if not labels_to_add:
print("The pull request already has the same labels.")

View File

@ -16,21 +16,23 @@ from typing import Optional
# NOTE: Please also update the CUDA sources in `PIP_SOURCES` in tools/nightly.py when changing this
CUDA_ARCHES = ["12.6", "12.8", "13.0"]
CUDA_ARCHES = ["12.6", "12.8", "12.9", "13.0"]
CUDA_STABLE = "12.8"
CUDA_ARCHES_FULL_VERSION = {
"12.6": "12.6.3",
"12.8": "12.8.1",
"12.9": "12.9.1",
"13.0": "13.0.0",
}
CUDA_ARCHES_CUDNN_VERSION = {
"12.6": "9",
"12.8": "9",
"12.9": "9",
"13.0": "9",
}
# 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"]
@ -38,82 +40,99 @@ CPU_AARCH64_ARCH = ["cpu-aarch64"]
CPU_S390X_ARCH = ["cpu-s390x"]
CUDA_AARCH64_ARCHES = ["12.6-aarch64", "12.8-aarch64", "13.0-aarch64"]
CUDA_AARCH64_ARCHES = ["12.9-aarch64"]
PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"12.6": (
"nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | "
"nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | "
"nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | "
"nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | "
"nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | "
"nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | "
"nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | "
"nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | "
"nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | "
"nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | "
"nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | "
"nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | "
"nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'"
"nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
"12.8": (
"nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | "
"nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | "
"nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | "
"nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | "
"nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | "
"nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | "
"nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | "
"nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | "
"nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | "
"nvidia-nccl-cu12==2.28.3; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | "
"nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | "
"nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | "
"nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'"
"nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
"12.9": (
"nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
"13.0": (
"nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | "
"nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | "
"nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | "
"nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | "
"nvidia-cublas==13.0.0.19; platform_system == 'Linux' | "
"nvidia-cufft==12.0.0.15; platform_system == 'Linux' | "
"nvidia-curand==10.4.0.35; platform_system == 'Linux' | "
"nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | "
"nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | "
"nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | "
"nvidia-nccl-cu13==2.28.3; platform_system == 'Linux' | "
"nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' | "
"nvidia-nvtx==13.0.39; platform_system == 'Linux' | "
"nvidia-nvjitlink==13.0.39; platform_system == 'Linux' | "
"nvidia-cufile==1.15.0.42; platform_system == 'Linux'"
"nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu13==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
"xpu": (
"intel-cmplr-lib-rt==2025.2.1 | "
"intel-cmplr-lib-ur==2025.2.1 | "
"intel-cmplr-lic-rt==2025.2.1 | "
"intel-sycl-rt==2025.2.1 | "
"oneccl-devel==2021.16.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"oneccl==2021.16.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"impi-rt==2021.16.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"onemkl-sycl-blas==2025.2.0 | "
"onemkl-sycl-dft==2025.2.0 | "
"onemkl-sycl-lapack==2025.2.0 | "
"onemkl-sycl-rng==2025.2.0 | "
"onemkl-sycl-sparse==2025.2.0 | "
"dpcpp-cpp-rt==2025.2.1 | "
"intel-opencl-rt==2025.2.1 | "
"mkl==2025.2.0 | "
"intel-openmp==2025.2.1 | "
"tbb==2022.2.0 | "
"tcmlib==1.4.0 | "
"umf==0.11.0 | "
"intel-pti==0.13.1"
"intel-cmplr-lib-rt==2025.1.1 | "
"intel-cmplr-lib-ur==2025.1.1 | "
"intel-cmplr-lic-rt==2025.1.1 | "
"intel-sycl-rt==2025.1.1 | "
"oneccl-devel==2021.15.2; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"oneccl==2021.15.2; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"impi-rt==2021.15.0; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"onemkl-sycl-blas==2025.1.0 | "
"onemkl-sycl-dft==2025.1.0 | "
"onemkl-sycl-lapack==2025.1.0 | "
"onemkl-sycl-rng==2025.1.0 | "
"onemkl-sycl-sparse==2025.1.0 | "
"dpcpp-cpp-rt==2025.1.1 | "
"intel-opencl-rt==2025.1.1 | "
"mkl==2025.1.0 | "
"intel-openmp==2025.1.1 | "
"tbb==2022.1.0 | "
"tcmlib==1.3.0 | "
"umf==0.10.0 | "
"intel-pti==0.12.3"
),
}
@ -221,8 +240,12 @@ def generate_libtorch_matrix(
if os == "linux":
arches += CUDA_ARCHES
arches += ROCM_ARCHES
if "13.0" in arches:
arches.remove("13.0")
elif os == "windows":
arches += CUDA_ARCHES
if "13.0" in arches:
arches.remove("13.0")
if libtorch_variants is None:
libtorch_variants = [
"shared-with-deps",
@ -287,6 +310,8 @@ def generate_wheels_matrix(
arches += CUDA_ARCHES + ROCM_ARCHES + XPU_ARCHES
elif os == "windows":
arches += CUDA_ARCHES + XPU_ARCHES
if "13.0" in arches:
arches.remove("13.0")
elif os == "linux-aarch64":
# Separate new if as the CPU type is different and
# uses different build/test scripts
@ -309,20 +334,19 @@ def generate_wheels_matrix(
else arch_version
)
# TODO: Enable python 3.13t on cpu-s390x
if gpu_arch_type == "cpu-s390x" and python_version == "3.13t":
continue
# TODO: Enable python 3.14 for rest
if os not in [
"linux",
"linux-aarch64",
"linux-s390x",
"macos-arm64",
"windows",
] and (python_version == "3.14" or python_version == "3.14t"):
if os not in ["linux", "linux-aarch64", "macos-arm64", "windows"] and (
python_version == "3.14" or python_version == "3.14t"
):
continue
# cuda linux wheels require PYTORCH_EXTRA_INSTALL_REQUIREMENTS to install
if (
arch_version in ["13.0", "12.8", "12.6"]
arch_version in ["13.0", "12.9", "12.8", "12.6"]
and os == "linux"
or arch_version in CUDA_AARCH64_ARCHES
):
@ -386,5 +410,6 @@ def generate_wheels_matrix(
validate_nccl_dep_consistency("13.0")
validate_nccl_dep_consistency("12.9")
validate_nccl_dep_consistency("12.8")
validate_nccl_dep_consistency("12.6")

View File

@ -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,

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