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13 Commits

Author SHA1 Message Date
9c701f03ee update json 2025-09-08 22:16:33 -07:00
c193ed6c84 Merge remote-tracking branch 'origin/main' into add_compile_benchmarking 2025-09-08 12:42:06 -07:00
eab7bd0d4c Remove mm_bwd_test.py 2025-09-08 11:34:58 -07:00
199318f978 Remove cpu benchmarking 2025-09-08 11:28:30 -07:00
9b226b2ce4 Add cpu memory calculation 2025-09-08 00:10:10 -07:00
6357d4e05a Add cpu memory calculation 2025-09-08 00:03:50 -07:00
162e7d3c20 Updates 2025-09-07 22:02:53 -07:00
ada9c165dd Lint fixes 2025-09-04 13:12:34 -07:00
461c7ad698 Enable bwd pass 2025-09-03 21:51:42 -07:00
819159610d Add fixes 2025-09-03 20:47:09 -07:00
d257ebf9c7 Add peak memory calculation 2025-09-03 11:10:16 -07:00
aab478833d Make jit and compile mutually exclusive 2025-08-27 14:21:37 -07:00
ba1319f414 Update the op benchmarking, to benchmark using torch.compile 2025-08-25 00:15:50 -07:00
1406 changed files with 12193 additions and 42866 deletions

View File

@ -3,13 +3,12 @@ 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 [[ "$GPU_ARCH_VERSION" == *"13.0"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;11.0;12.0+PTX"
fi
if [[ "$GPU_ARCH_VERSION" == *"13.0"* ]]; then
export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;11.0;12.0"
fi
# Compress the fatbin with -compress-mode=size for CUDA 13
@ -28,22 +27,14 @@ 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 +69,83 @@ 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}")
# 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",
"/usr/local/cuda/lib64/libcufile.so.0",
"/usr/local/cuda/lib64/libcufile_rdma.so.1",
"/usr/local/cuda/lib64/libcusparse.so.12",
]
# 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",
# CUDA version-specific libraries
if "130" in desired_cuda:
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",
"/usr/local/cuda/lib64/libnvrtc-builtins.so.13.0",
]
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}",
]
# 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)
# Combine all libraries
libs_to_copy = common_libs + version_specific_libs
# 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",
"/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 +153,14 @@ 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 +183,14 @@ 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 +227,11 @@ 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:

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)

View File

@ -214,7 +214,8 @@ case "$tag" in
TRITON=yes
;;
pytorch-linux-jammy-py3-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.10
# TODO (huydhn): Upgrade this to Python >= 3.10
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
VISION=yes
KATEX=yes
@ -262,10 +263,13 @@ case "$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)

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@ -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

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@ -1 +0,0 @@
7fe50dc3da2069d6645d9deb8c017a876472a977

View File

@ -1 +1 @@
bbb06c0334a6772b92d24bde54956e675c8c6604
fccfc522864cf8bc172abe0cd58ae5581e2d44b9

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

View File

@ -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 "$1" | tr '.' ' ');
}
@ -118,8 +113,6 @@ EOF
rm -rf HIP clr
fi
pip_install "git+https://github.com/rocm/composable_kernel@$ROCM_COMPOSABLE_KERNEL_VERSION"
# Cleanup
apt-get autoclean && apt-get clean
rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
@ -183,8 +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

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@ -93,9 +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

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@ -1,7 +1,7 @@
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@d53b0ffb9b1cda68260693ea98f3483823c88d8e#egg=pytorch_sphinx_theme2
-e git+https://github.com/pytorch/pytorch_sphinx_theme.git@1657ad2fc1acdc98aa719eebecbb0128a7c13ce4#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

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@ -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

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

View File

@ -41,6 +41,7 @@ def sample_vllm_test_library():
"pytest -v -s basic_correctness/test_cumem.py",
"pytest -v -s basic_correctness/test_basic_correctness.py",
"pytest -v -s basic_correctness/test_cpu_offload.py",
"VLLM_TEST_ENABLE_ARTIFICIAL_PREEMPT=1 pytest -v -s basic_correctness/test_preemption.py",
],
},
"vllm_basic_models_test": {
@ -67,12 +68,15 @@ def sample_vllm_test_library():
"-v",
"-s",
"entrypoints/llm",
"--ignore=entrypoints/llm/test_lazy_outlines.py",
"--ignore=entrypoints/llm/test_generate.py",
"--ignore=entrypoints/llm/test_generate_multiple_loras.py",
"--ignore=entrypoints/llm/test_collective_rpc.py",
]
),
"pytest -v -s entrypoints/llm/test_generate.py",
"pytest -v -s entrypoints/offline_mode",
"pytest -v -s entrypoints/llm/test_lazy_outlines.py",
"pytest -v -s entrypoints/llm/test_generate.py ",
"VLLM_USE_V1=0 pytest -v -s entrypoints/offline_mode",
],
},
"vllm_regression_test": {
@ -92,24 +96,14 @@ 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 +114,6 @@ 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 +128,6 @@ 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",

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

@ -11,7 +11,7 @@ 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.path_helper import copy, remove_dir
from cli.lib.common.pip_helper import (
pip_install_first_match,
pip_install_packages,
@ -43,10 +43,6 @@ 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")
@ -96,13 +92,11 @@ class VllmTestRunner(BaseRunner):
self._set_envs(params)
clone_vllm(dst=self.work_directory)
self.cp_torch_cleaning_script(params)
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()
def run(self):
@ -110,31 +104,20 @@ class VllmTestRunner(BaseRunner):
main function to run vllm test
"""
self.prepare()
try:
with working_directory(self.work_directory):
if self.test_type == TestInpuType.TEST_PLAN:
if self.num_shards > 1:
run_test_plan(
self.test_plan,
"vllm",
sample_vllm_test_library(),
self.shard_id,
self.num_shards,
)
else:
run_test_plan(
self.test_plan, "vllm", sample_vllm_test_library()
)
with working_directory(self.work_directory):
if self.test_type == TestInpuType.TEST_PLAN:
if self.num_shards > 1:
run_test_plan(
self.test_plan,
"vllm",
sample_vllm_test_library(),
self.shard_id,
self.num_shards,
)
else:
raise ValueError(f"Unknown test type {self.test_type}")
finally:
# double check the torches are not overridden by other packages
check_versions()
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)
run_test_plan(self.test_plan, "vllm", sample_vllm_test_library())
else:
raise ValueError(f"Unknown test type {self.test_type}")
def _install_wheels(self, params: VllmTestParameters):
logger.info("Running vllm test with inputs: %s", params)

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

@ -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

@ -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
@ -334,17 +324,11 @@ test_python() {
}
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 $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
@ -1556,10 +1540,14 @@ test_executorch() {
install_torchvision
install_torchaudio
INSTALL_SCRIPT="$(pwd)/.ci/docker/common/install_executorch.sh"
pushd /executorch
"${INSTALL_SCRIPT}" setup_executorch
export PYTHON_EXECUTABLE=python
export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
# NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
# from the PR
bash .ci/scripts/setup-linux.sh --build-tool cmake
echo "Run ExecuTorch unit tests"
pytest -v -n auto
@ -1573,6 +1561,10 @@ test_executorch() {
popd
# Test torchgen generated code for Executorch.
echo "Testing ExecuTorch op registration"
"$BUILD_BIN_DIR"/test_edge_op_registration
assert_git_not_dirty
}
@ -1580,7 +1572,6 @@ 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 \
distributed/elastic/timer/api_test distributed/elastic/timer/local_timer_example distributed/elastic/timer/local_timer_test \
--shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
# Dynamo tests
@ -1730,6 +1721,11 @@ 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 [[ "${TEST_CONFIG}" == *dynamo_wrapped* ]]; then
@ -1779,8 +1775,6 @@ elif [[ "${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

View File

@ -137,7 +137,7 @@ 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

@ -38,14 +38,7 @@ 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
@ -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

@ -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

@ -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-${mac_version}.whl"
###########################################################
@ -125,6 +125,7 @@ popd
export TH_BINARY_BUILD=1
export INSTALL_TEST=0 # dont install test binaries into site-packages
export MACOSX_DEPLOYMENT_TARGET=11.0
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
@ -132,19 +133,25 @@ RENAME_WHEEL=true
case $desired_python in
3.14t)
echo "Using 3.14 deps"
mac_version='macosx-11.0-arm64'
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'
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 3.13 deps"
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)
@ -169,12 +176,17 @@ case $desired_python in
;;
esac
# Install into a fresh env
tmp_env_name="wheel_py$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=(
"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, this enables gloo, which needs libuv, which
@ -188,7 +200,7 @@ export BUILD_TEST=OFF
pushd "$pytorch_rootdir"
echo "Calling setup.py bdist_wheel at $(date)"
_PYTHON_HOST_PLATFORM=${mac_version} ARCHFLAGS="-arch arm64" python setup.py bdist_wheel -d "$whl_tmp_dir" --plat-name "${mac_version//[-.]/_}"
python setup.py bdist_wheel -d "$whl_tmp_dir" --plat-name ${mac_version}
echo "Finished setup.py bdist_wheel at $(date)"

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

@ -21,7 +21,6 @@ self-hosted-runner:
- linux.arm64.2xlarge.ephemeral
- linux.arm64.m7g.4xlarge
- linux.arm64.m7g.4xlarge.ephemeral
- linux.arm64.r7g.12xlarge.memory
- linux.4xlarge.nvidia.gpu
- linux.8xlarge.nvidia.gpu
- linux.16xlarge.nvidia.gpu

View File

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

View File

@ -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
PYTHON3=$(${CONDA_RUN} -n py_tmp which python3)
PYTHON3=$(${CONDA_RUN} which python3)
EXIT_CODE=$?
if [[ "${EXIT_CODE}" == "0" ]]; then
@ -74,7 +62,7 @@ runs:
# installation, which is Python 3 based. Its Python is default to Python 3. Further, there
# is also the Miniconda installation that is Python 2 based, and both can be installed if
# needed. In both cases, Python binary is just called python
PYTHON=$(${CONDA_RUN} -n py_tmp which python)
PYTHON=$(${CONDA_RUN} which python)
EXIT_CODE=$?
if [[ "${EXIT_CODE}" == "0" ]]; then

View File

@ -1 +1 @@
87ff22e49ed0e92576c4935ccb8c143daac4a3cd
3f90600fc287b276979ff2c8550a61d5d896bb8d

View File

@ -1 +1 @@
08ae0af1395c8d8471f4025deb6af9aef90b342f
7f1de94a4c2d14f59ad4ca84538c36084ea6b2c8

View File

@ -1 +1 @@
090197034faf3b193c4467cedeb9281e3078892d
4172235ab78b09989fb56edaf734dbee283dda3e

View File

@ -1 +1 @@
c77852e117bdf056c8e9a087e51d6f65cf6ba53d
6c5478ff7c3d50dd1e3047d72ec5909bea474073

View File

@ -82,10 +82,16 @@ RUN if command -v apt-get >/dev/null; then \
apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim; \
else \
dnf install -y git curl wget sudo; \
dnf install -y git curl wget sudo vim; \
fi \
&& python3 --version && python3 -m pip --version
# Workaround for https://github.com/openai/triton/issues/2507 and
# https://github.com/pytorch/pytorch/issues/107960 -- hopefully
# this won't be needed for future versions of this docker image
# or future versions of triton.
RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
# Install uv for faster pip installs if not existed
RUN --mount=type=cache,target=/root/.cache/uv \
if ! python3 -m uv --version >/dev/null 2>&1; then \
@ -214,16 +220,11 @@ ARG SCCACHE_S3_NO_CREDENTIALS=0
RUN --mount=type=cache,target=/root/.cache/uv \
--mount=type=bind,source=.git,target=.git \
if [ "$USE_SCCACHE" = "1" ]; then \
echo "Installing sccache..."; \
if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
SCCACHE_ARCHIVE="sccache-v0.8.1-aarch64-unknown-linux-musl"; \
else \
SCCACHE_ARCHIVE="sccache-v0.8.1-x86_64-unknown-linux-musl"; \
fi; \
curl -L -o sccache.tar.gz "https://github.com/mozilla/sccache/releases/download/v0.8.1/${SCCACHE_ARCHIVE}.tar.gz" \
echo "Installing sccache..." \
&& curl -L -o sccache.tar.gz https://github.com/mozilla/sccache/releases/download/v0.8.1/sccache-v0.8.1-x86_64-unknown-linux-musl.tar.gz \
&& tar -xzf sccache.tar.gz \
&& sudo mv "${SCCACHE_ARCHIVE}"/sccache /usr/bin/sccache \
&& rm -rf sccache.tar.gz "${SCCACHE_ARCHIVE}" \
&& sudo mv sccache-v0.8.1-x86_64-unknown-linux-musl/sccache /usr/bin/sccache \
&& rm -rf sccache.tar.gz sccache-v0.8.1-x86_64-unknown-linux-musl \
&& export SCCACHE_BUCKET=${SCCACHE_BUCKET_NAME} \
&& export SCCACHE_REGION=${SCCACHE_REGION_NAME} \
&& export SCCACHE_S3_NO_CREDENTIALS=${SCCACHE_S3_NO_CREDENTIALS} \
@ -284,7 +285,7 @@ RUN if command -v apt-get >/dev/null; then \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS ${GET_PIP_URL} | python${PYTHON_VERSION}; \
else \
dnf install -y git curl wget sudo; \
dnf install -y git curl wget sudo vim; \
fi \
&& python3 --version && python3 -m pip --version
@ -297,6 +298,12 @@ RUN echo "[INFO] Listing current directory before torch install step:" && \
echo "[INFO] 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 \

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

@ -36,7 +36,6 @@ ciflow_push_tags:
- ciflow/win-arm64
- ciflow/h100-symm-mem
- ciflow/h100-cutlass-backend
- ciflow/b200
retryable_workflows:
- pull
- trunk

View File

@ -15,7 +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
@ -26,7 +26,7 @@ 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
tensorboard==2.13.0

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

@ -38,60 +38,60 @@ 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 = ["13.0-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==2.27.5; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | "
"nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | "
"nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | "
"nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'"
"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==2.27.5; platform_system == 'Linux' | "
"nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | "
"nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | "
"nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | "
"nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'"
"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'"
),
"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==2.27.7; 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==9.13.0.50; 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 | "

View File

@ -135,7 +135,7 @@ ROCM_SMOKE_WORKFLOWS = [
build_configs=generate_binary_build_matrix.generate_wheels_matrix(
OperatingSystem.LINUX,
arches=["6.4"],
python_versions=["3.10"],
python_versions=["3.9"],
),
ciflow_config=CIFlowConfig(
labels={

View File

@ -1,94 +0,0 @@
#!/usr/bin/env bash
set -eux
torch_version=$(unzip -p torch-* '**/METADATA' | grep '^Version: ' | cut -d' ' -f2)
nightly=$(echo ${torch_version} | cut -d'.' -f4)
# Copied from .ci/manywheel/build_common.sh
make_wheel_record() {
fpath=$1
if echo $fpath | grep RECORD >/dev/null 2>&1; then
echo "$fpath,,"
else
fhash=$(openssl dgst -sha256 -binary $fpath | openssl base64 | sed -e 's/+/-/g' | sed -e 's/\//_/g' | sed -e 's/=//g')
fsize=$(ls -nl $fpath | awk '{print $5}')
echo "$fpath,sha256=$fhash,$fsize"
fi
}
change_wheel_version() {
local package=$1
local wheel=$2
local f_version=$3
local t_version=$4
# Extract the wheel
${PYTHON_EXECUTABLE} -mwheel unpack $wheel
mv "${package}-${f_version}" "${package}-${t_version}"
# Change the version from f_version to t_version in the dist-info dir
pushd "${package}-${t_version}"
mv "${package}-${f_version}.dist-info" "${package}-${t_version}.dist-info"
pushd "${package}-${t_version}.dist-info"
sed -i "s/${package}-${f_version}.dist-info/${package}-${t_version}.dist-info/g" RECORD
# Update the version in METADATA and its SHA256 hash
sed -i "s/Version: ${f_version}/Version: ${t_version}/g" METADATA
# then add PyTorch nightly dependency of vLLM
if [[ "${package}" == vllm ]] || [[ "${package}" == xformers ]]; then
sed -i "/License-File/a\Requires-Dist: torch==${torch_version}" METADATA
fi
sed -i '/METADATA,sha256/d' RECORD
popd
make_wheel_record "${package}-${t_version}.dist-info/METADATA" >> "${package}-${t_version}.dist-info/RECORD"
popd
# Repack the wheel
${PYTHON_EXECUTABLE} -mwheel pack "${package}-${t_version}"
# Clean up
rm -rf "${package}-${t_version}"
}
repackage_wheel() {
local package=$1
pushd $package
local orig_wheel=$(find . -name *${package//-/_}*)
local orig_version=$(unzip -p $orig_wheel '**/METADATA' | grep '^Version: ' | cut -d' ' -f2)
local version=""
if [[ "${package}" == vllm ]]; then
# Copied from vllm/.buildkite/scripts/upload-wheels.sh
version=1.0.0
else
version=$(echo $orig_version | tr '.+' '.' | cut -d'.' -f1-3)
fi
local nightly_version=$version.$nightly
# Use nightly version
change_wheel_version ${package//-/_} $orig_wheel $orig_version $nightly_version
# Clean up
rm "${orig_wheel}"
auditwheel repair --plat $PLATFORM *.whl \
--exclude libc10* --exclude libtorch* --exclude libcu* --exclude libnv*
local repair_wheel=$(find wheelhouse -name *${PLATFORM}*)
local repair_wheel=$(basename ${repair_wheel})
popd
cp ${package}/wheelhouse/${repair_wheel} .
rm -rf $package
}
# Require to re-package the wheel
${PYTHON_EXECUTABLE} -mpip install wheel==0.45.1
pushd externals/vllm/wheels
for package in xformers flashinfer-python vllm; do
repackage_wheel $package
done
popd

View File

@ -22,16 +22,6 @@ name: !{{ build_environment }}
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
{%- endmacro %}
{%- macro setup_python(py_ver) -%}
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "!{{ (py_ver.strip('t') + '.4') if '3.14' not in py_ver else '3.14.0-rc.2' }}"
freethreaded: !{{ "true" if py_ver.endswith('t') else "false" }}
{%- endmacro %}
on:
# TODO: Migrate to new ciflow trigger, reference https://github.com/pytorch/pytorch/pull/70321
push:
@ -71,13 +61,23 @@ jobs:
{%- endif %}
steps:
!{{ set_runner_specific_vars() }}
!{{ setup_python(config.get("python_version", "3.10")) }}
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
!{{ common.checkout(deep_clone=False, directory="pytorch") }}
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -94,6 +94,8 @@ jobs:
{%- if config["package_type"] == "wheel" %}
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -104,9 +106,33 @@ jobs:
SMOKE_TEST_PARAMS=""
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
# shellcheck disable=SC2153
case $DESIRED_PYTHON in
3.14t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.14)
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.13t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
;;
*)
# shellcheck disable=SC2153
desired_python=${DESIRED_PYTHON}
;;
esac
# shellcheck disable=SC2086
python -mvenv test_venv
source test_venv/bin/activate
conda create -yn "test_conda_env" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS} ${EXTRA_CONDA_INSTALL_FLAGS}
conda activate test_conda_env
pip install "$PYTORCH_FINAL_PACKAGE_DIR"/*.whl numpy -v
# shellcheck disable=SC2086

View File

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

View File

@ -75,6 +75,10 @@ jobs:
runner: ${{ inputs.runner_prefix }}linux.2xlarge
# It takes less than 30m to finish python docs unless there are issues
timeout-minutes: 30
- docs_type: functorch
runner: ${{ inputs.runner_prefix }}linux.2xlarge
# It takes less than 15m to finish functorch docs unless there are issues
timeout-minutes: 15
# Set a fixed name for this job instead of using the current matrix-generated name, i.e. build-docs (cpp, linux.12xlarge, 180)
# The current name requires updating the database last docs push query from test-infra every time the matrix is updated
name: build-docs-${{ matrix.docs_type }}-${{ inputs.push }}
@ -207,6 +211,16 @@ jobs:
path: cppdocs/
s3-prefix: pytorch/pytorch/${{ github.event.pull_request.number }}/cppdocs
- name: Upload functorch Docs Preview
uses: seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a # v5.1.0
if: ${{ github.event_name == 'pull_request' && matrix.docs_type == 'functorch' && steps.build-docs.outcome == 'success' }}
with:
retention-days: 14
s3-bucket: doc-previews
if-no-files-found: error
path: functorch_ghpages/nightly/
s3-prefix: pytorch/pytorch/${{ github.event.pull_request.number }}/functorchdocs
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
if: always()

View File

@ -2,12 +2,6 @@ name: Get Changed Files
on:
workflow_call:
inputs:
all_files:
description: "Whether to return all files instead of just changed files"
required: false
type: boolean
default: false
outputs:
changed-files:
description: "List of changed files (space-separated) or '*' if not in a PR"
@ -32,23 +26,17 @@ jobs:
# Get the PR number from the github context
PR_NUMBER="${{ github.event.number }}"
# Check if all_files is requested
if [ "${{ inputs.all_files }}" = "true" ]; then
echo "all_files input is true, returning all files"
echo "changed-files=*" >> "$GITHUB_OUTPUT"
else
# Use gh CLI to get changed files in the PR with explicit repo
CHANGED_FILES=$(gh api repos/${{ github.repository }}/pulls/$PR_NUMBER/files --paginate --jq '.[] | select(.status != "removed") | .filename' | tr '\n' ' ' | sed 's/ $//')
# Use gh CLI to get changed files in the PR with explicit repo
CHANGED_FILES=$(gh api repos/${{ github.repository }}/pulls/$PR_NUMBER/files --paginate --jq '.[] | select(.status != "removed") | .filename' | tr '\n' ' ' | sed 's/ $//')
if [ -z "$CHANGED_FILES" ]; then
echo "No changed files found, setting to '*'"
CHANGED_FILES="*"
fi
echo "Changed files: $CHANGED_FILES"
echo "changed-files=$CHANGED_FILES" >> "$GITHUB_OUTPUT"
if [ -z "$CHANGED_FILES" ]; then
echo "No changed files found, setting to '*'"
CHANGED_FILES="*"
fi
echo "Changed files: $CHANGED_FILES"
echo "changed-files=$CHANGED_FILES" >> "$GITHUB_OUTPUT"
else
echo "Not in PR context, setting changed files to '*'"
echo "changed-files=*" >> "$GITHUB_OUTPUT"

View File

@ -169,7 +169,7 @@ jobs:
id: install-nvidia-driver
uses: pytorch/test-infra/.github/actions/setup-nvidia@main
with:
driver-version: ${{ matrix.config == 'legacy_nvidia_driver' && '525.105.17' || '580.82.07' }}
driver-version: ${{ matrix.config == 'legacy_nvidia_driver' && '525.105.17' || '570.133.07' }}
if: ${{ contains(inputs.build-environment, 'cuda') && !contains(matrix.config, 'nogpu') && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' && !contains(matrix.runner, 'b200') }}
- name: Setup GPU_FLAG for docker run

View File

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

View File

@ -151,7 +151,7 @@ jobs:
BUILD_WHEEL: 1
MAX_JOBS: 8
CUDA_VERSION: ${{ inputs.cuda-version }}
PYTHON_VERSION: "3.10"
PYTHON_VERSION: "3.9"
SCCACHE_BUCKET: "ossci-compiler-cache"
SCCACHE_S3_KEY_PREFIX: ${{ github.workflow }}
SCCACHE_REGION: us-east-1

View File

@ -184,7 +184,7 @@ jobs:
env:
USE_CUDA: ${{ inputs.cuda-version != 'cpu' && '1' || '0' }}
INSTALL_WINDOWS_SDK: 1
PYTHON_VERSION: "3.10"
PYTHON_VERSION: 3.9
CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
VERBOSE_TEST_LOGS: ${{ steps.keep-going.outputs.ci-verbose-test-logs }}
TEST_SHOWLOCALS: ${{ steps.keep-going.outputs.ci-test-showlocals }}

View File

@ -47,11 +47,12 @@ jobs:
matrix:
include: [
{ name: "manylinux2_28-builder", tag: "cuda13.0", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "cuda12.9", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "cuda12.8", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "cuda12.6", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinuxaarch64-builder", tag: "cuda13.0", runner: "linux.arm64.2xlarge.ephemeral" },
{ name: "manylinuxaarch64-builder", tag: "cuda12.9", runner: "linux.arm64.2xlarge.ephemeral" },
{ name: "manylinuxaarch64-builder", tag: "cuda12.8", runner: "linux.arm64.2xlarge.ephemeral" },
{ name: "manylinuxaarch64-builder", tag: "cuda12.6", runner: "linux.arm64.2xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "rocm6.3", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "rocm6.4", runner: "linux.9xlarge.ephemeral" },
{ name: "manylinux2_28-builder", tag: "cpu", runner: "linux.9xlarge.ephemeral" },

View File

@ -12,9 +12,6 @@ on:
paths:
- .github/workflows/build-vllm-wheel.yml
- .github/ci_commit_pins/vllm.txt
schedule:
# every morning at 01:30PM UTC, 9:30AM EST, 6:30AM PST
- cron: 30 13 * * *
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
@ -27,33 +24,21 @@ jobs:
fail-fast: false
matrix:
python-version: [ '3.12' ]
# TODO (huydhn): Add cu130 after https://github.com/vllm-project/vllm/issues/24464 is resolved
platform: [ 'manylinux_2_28_x86_64', 'manylinux_2_28_aarch64' ]
# TODO (huydhn): Add cu130 https://github.com/pytorch/pytorch/pull/162000#issuecomment-3261541554
device: [ 'cu128', 'cu129' ]
runner: [ 'linux.12xlarge.memory' ]
include:
- platform: manylinux_2_28_x86_64
device: cu128
- device: cu128
manylinux-image: 'pytorch/manylinux2_28-builder:cuda12.8'
runner: linux.12xlarge.memory
- platform: manylinux_2_28_x86_64
device: cu129
- device: cu129
manylinux-image: 'pytorch/manylinux2_28-builder:cuda12.9'
runner: linux.12xlarge.memory
- platform: manylinux_2_28_aarch64
device: cu128
manylinux-image: 'pytorch/manylinuxaarch64-builder:cuda12.8'
runner: linux.arm64.r7g.12xlarge.memory
- platform: manylinux_2_28_aarch64
device: cu129
manylinux-image: 'pytorch/manylinuxaarch64-builder:cuda12.9'
runner: linux.arm64.r7g.12xlarge.memory
name: "Build ${{ matrix.device }} vLLM wheel on ${{ matrix.platform }}"
name: "Build ${{ matrix.device }} vLLM wheel"
runs-on: ${{ matrix.runner }}
timeout-minutes: 480
env:
PY_VERS: ${{ matrix.python-version }}
MANYLINUX_IMAGE: ${{ matrix.manylinux-image }}
PLATFORM: ${{ matrix.platform }}
PLATFORM: 'manylinux_2_28_x86_64'
BUILD_DEVICE: ${{ matrix.device }}
steps:
- name: Setup SSH (Click me for login details)
@ -74,6 +59,20 @@ jobs:
run: |
set -eux
# Keep PyTorch nightly wheel here so that we can install it later during
# vLLM build process
mkdir -p "${RUNNER_TEMP}/artifacts/"
container_name=$(docker run \
--tty \
--detach \
-e PLATFORM \
-v "${GITHUB_WORKSPACE}:/pytorch" \
-v "${RUNNER_TEMP}/artifacts:/artifacts" \
-w /artifacts/ \
"${MANYLINUX_IMAGE}"
)
# Determine python executable for given version (copied from build-triton-wheel)
case $PY_VERS in
3.10)
@ -103,21 +102,6 @@ jobs:
;;
esac
# Keep PyTorch nightly wheel here so that we can install it later during
# vLLM build process
mkdir -p "${RUNNER_TEMP}/artifacts/"
container_name=$(docker run \
--tty \
--detach \
-e PLATFORM \
-e PYTHON_EXECUTABLE="${PYTHON_EXECUTABLE}" \
-v "${GITHUB_WORKSPACE}:/pytorch" \
-v "${RUNNER_TEMP}/artifacts:/artifacts" \
-w /artifacts/ \
"${MANYLINUX_IMAGE}"
)
docker exec -t "${container_name}" "${PYTHON_EXECUTABLE}" -mpip install \
--pre torch torchvision torchaudio \
--index-url "https://download.pytorch.org/whl/nightly/${BUILD_DEVICE}"
@ -129,6 +113,7 @@ jobs:
--index-url "https://download.pytorch.org/whl/nightly/${BUILD_DEVICE}"
# Save this for later
echo "PYTHON_EXECUTABLE=${PYTHON_EXECUTABLE}" >> "$GITHUB_ENV"
echo "container_name=${container_name}" >> "$GITHUB_ENV"
- name: Build vLLM wheel
@ -146,12 +131,41 @@ jobs:
set -eux
# Get these wheels ready, the vllm renaming logic is copied from its .buildkite/scripts/upload-wheels.sh
docker exec -t "${container_name}" bash -c /pytorch/.github/scripts/prepare_vllm_wheels.sh
docker exec -t "${container_name}" bash -c "
set -eux
nightly=\$(unzip -p torch-* '**/METADATA' | grep '^Version: ' | cut -d' ' -f2 | cut -d'.' -f4)
pushd externals/vllm/wheels
for package in xformers flashinfer-python vllm; do
pushd \$package
auditwheel repair --plat \$PLATFORM *.whl \
--exclude libc10* --exclude libtorch* --exclude libcu* --exclude libnv*
repair_wheel=\$(find wheelhouse -name *\${PLATFORM}*)
repair_wheel=\$(basename \${repair_wheel})
popd
cp \${package}/wheelhouse/\${repair_wheel} .
version=\$(unzip -p \$repair_wheel '**/METADATA' | grep '^Version: ' | cut -d' ' -f2)
if [[ \$package == vllm ]]; then
new_wheel=\${repair_wheel/\$version/1.0.0.\$nightly}
else
major_version=\$(echo \$version | tr '.+' '.' | cut -d'.' -f1-3)
new_wheel=\${repair_wheel/\$version/\$major_version.\$nightly}
fi
mv -- \$repair_wheel \$new_wheel
rm -rf \$package
done
popd
"
docker exec -t "${container_name}" chown -R 1000:1000 /artifacts
- uses: actions/upload-artifact@50769540e7f4bd5e21e526ee35c689e35e0d6874 # v4.4.0
with:
name: vllm-wheel-${{ matrix.device }}-${{ matrix.platform }}-${{ matrix.python-version }}
name: vllm-wheel-${{ matrix.device }}-${{ matrix.python-version }}-${{ env.PLATFORM }}
if-no-files-found: error
path: ${{ runner.temp }}/artifacts/externals/vllm/wheels/*.whl
@ -161,29 +175,27 @@ jobs:
# Copied from build-triton-wheel workflow (mostly)
upload-wheel:
name: "Upload ${{ matrix.device }} vLLM wheel on ${{ matrix.platform }}"
name: "Upload ${{ matrix.device }} vLLM wheel"
needs:
- build-wheel
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
platform: [ 'manylinux_2_28_x86_64', 'manylinux_2_28_aarch64' ]
device: [ 'cu128', 'cu129' ]
env:
PLATFORM: ${{ matrix.platform }}
BUILD_DEVICE: ${{ matrix.device }}
permissions:
id-token: write
contents: read
container:
image: continuumio/miniconda3:4.12.0
environment: ${{ ((github.event_name == 'push' && github.event.ref == 'refs/heads/main') || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && 'nightly-wheel-upload' || '' }}
environment: ${{ (github.event_name == 'push' && github.event.ref == 'refs/heads/main') && 'nightly-wheel-upload' || '' }}
steps:
- uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
- name: Configure AWS credentials(PyTorch account) for main
if: ${{ (github.event_name == 'push' && github.event.ref == 'refs/heads/main') || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch' }}
if: ${{ github.event_name == 'push' && github.event.ref == 'refs/heads/main' }}
uses: aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722 # v4.1.0
with:
role-to-assume: arn:aws:iam::749337293305:role/gha_workflow_nightly_build_wheels
@ -207,15 +219,15 @@ jobs:
run: |
set -eux
mkdir -p "${RUNNER_TEMP}/artifacts/"
mv "${RUNNER_TEMP}"/artifacts-all/vllm-wheel-"${BUILD_DEVICE}"-"${PLATFORM}"-*/* "${RUNNER_TEMP}/artifacts/"
mv "${RUNNER_TEMP}"/artifacts-all/vllm-wheel-"${BUILD_DEVICE}"-*/* "${RUNNER_TEMP}/artifacts/"
- name: Set DRY_RUN
if: ${{ (github.event_name == 'push' && (github.event.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v'))) || github.event_name == 'schedule' || github.event_name == 'workflow_dispatch' }}
- name: Set DRY_RUN (only for tagged pushes)
if: ${{ github.event_name == 'push' && (github.event.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) }}
shell: bash
run: |
echo "DRY_RUN=disabled" >> "$GITHUB_ENV"
- name: Set UPLOAD_CHANNEL
- name: Set UPLOAD_CHANNEL (only for tagged pushes)
if: ${{ github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v') }}
shell: bash
run: |

View File

@ -70,8 +70,9 @@ jobs:
pytorch-linux-jammy-py3-clang18-asan,
pytorch-linux-jammy-py3-clang12-onnx,
pytorch-linux-jammy-linter,
pytorch-linux-jammy-cuda12.8-cudnn9-py3.10-linter,
pytorch-linux-jammy-py3-clang12-executorch,
pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-linter,
# Executorch pin needs update
# pytorch-linux-jammy-py3-clang12-executorch,
pytorch-linux-jammy-py3.12-triton-cpu,
pytorch-linux-noble-riscv64-py3.12-gcc14
]

View File

@ -112,98 +112,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda-aarch64-12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.10"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda-aarch64-12_6-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_10-cuda-aarch64-12_6-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda-aarch64-12_6
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda-aarch64-12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.10"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda-aarch64-12_8-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_10-cuda-aarch64-12_8-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda-aarch64-12_8
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -224,7 +132,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -315,98 +223,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda-aarch64-12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.11"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda-aarch64-12_6-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_11-cuda-aarch64-12_6-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda-aarch64-12_6
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda-aarch64-12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.11"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda-aarch64-12_8-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_11-cuda-aarch64-12_8-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda-aarch64-12_8
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -427,7 +243,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -518,98 +334,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda-aarch64-12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.12"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda-aarch64-12_6-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-cuda-aarch64-12_6-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda-aarch64-12_6
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda-aarch64-12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.12"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda-aarch64-12_8-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-cuda-aarch64-12_8-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda-aarch64-12_8
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -630,7 +354,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -721,98 +445,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda-aarch64-12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.13"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda-aarch64-12_6-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13-cuda-aarch64-12_6-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.13"
build_name: manywheel-py3_13-cuda-aarch64-12_6
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda-aarch64-12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.13"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda-aarch64-12_8-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13-cuda-aarch64-12_8-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.13"
build_name: manywheel-py3_13-cuda-aarch64-12_8
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -833,7 +465,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -924,98 +556,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda-aarch64-12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.13t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13t-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda-aarch64-12_6-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13t-cuda-aarch64-12_6-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.13t"
build_name: manywheel-py3_13t-cuda-aarch64-12_6
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda-aarch64-12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.13t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13t-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda-aarch64-12_8-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13t-cuda-aarch64-12_8-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.13t"
build_name: manywheel-py3_13t-cuda-aarch64-12_8
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1036,7 +576,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_13t-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1127,98 +667,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda-aarch64-12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.14"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda-aarch64-12_6-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14-cuda-aarch64-12_6-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.14"
build_name: manywheel-py3_14-cuda-aarch64-12_6
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda-aarch64-12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.14"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda-aarch64-12_8-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14-cuda-aarch64-12_8-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.14"
build_name: manywheel-py3_14-cuda-aarch64-12_8
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1239,7 +687,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1330,98 +778,6 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda-aarch64-12_6-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.14t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14t-cuda-aarch64-12_6
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.6.77; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.6.85; platform_system == 'Linux' | nvidia-cufile-cu12==1.11.1.6; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda-aarch64-12_6-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14t-cuda-aarch64-12_6-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DESIRED_PYTHON: "3.14t"
build_name: manywheel-py3_14t-cuda-aarch64-12_6
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda-aarch64-12_8-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.14t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.arm64.m7g.4xlarge.ephemeral
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14t-cuda-aarch64-12_8
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; platform_system == 'Linux' | nvidia-nvtx-cu12==12.8.90; platform_system == 'Linux' | nvidia-nvjitlink-cu12==12.8.93; platform_system == 'Linux' | nvidia-cufile-cu12==1.13.1.3; platform_system == 'Linux'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda-aarch64-12_8-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14t-cuda-aarch64-12_8-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu128
GPU_ARCH_VERSION: "12.8-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.8
DESIRED_PYTHON: "3.14t"
build_name: manywheel-py3_14t-cuda-aarch64-12_8
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda-aarch64-13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1442,7 +798,7 @@ jobs:
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_14t-cuda-aarch64-13_0
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

View File

@ -60,7 +60,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_8-test: # Testing

View File

@ -127,7 +127,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_6-test: # Testing
@ -193,7 +193,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_8-test: # Testing
@ -259,7 +259,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda13_0-test: # Testing
@ -719,7 +719,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_6-test: # Testing
@ -785,7 +785,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_8-test: # Testing
@ -851,7 +851,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda13_0-test: # Testing
@ -1311,7 +1311,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_6-test: # Testing
@ -1377,7 +1377,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_8-test: # Testing
@ -1443,7 +1443,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda13_0-test: # Testing
@ -1903,7 +1903,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_6-test: # Testing
@ -1969,7 +1969,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_8-test: # Testing
@ -2035,7 +2035,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda13_0-test: # Testing
@ -2495,7 +2495,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_6-test: # Testing
@ -2561,7 +2561,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_8-test: # Testing
@ -2627,7 +2627,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda13_0-test: # Testing
@ -3087,7 +3087,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_6-test: # Testing
@ -3153,7 +3153,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_8-test: # Testing
@ -3219,7 +3219,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda13_0-test: # Testing
@ -3679,7 +3679,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14t-cuda12_6
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.6.77; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.6.80; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.6.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.0.4; platform_system == 'Linux' | nvidia-curand-cu12==10.3.7.77; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.1.2; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.4.2; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_6-test: # Testing
@ -3745,7 +3745,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14t-cuda12_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.8.93; platform_system == 'Linux' | nvidia-cuda-runtime-cu12==12.8.90; platform_system == 'Linux' | nvidia-cuda-cupti-cu12==12.8.90; platform_system == 'Linux' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' | nvidia-cublas-cu12==12.8.4.1; platform_system == 'Linux' | nvidia-cufft-cu12==11.3.3.83; platform_system == 'Linux' | nvidia-curand-cu12==10.3.9.90; platform_system == 'Linux' | nvidia-cusolver-cu12==11.7.3.90; platform_system == 'Linux' | nvidia-cusparse-cu12==12.5.8.93; platform_system == 'Linux' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' | nvidia-nvshmem-cu12==3.3.24; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_8-test: # Testing
@ -3811,7 +3811,7 @@ jobs:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14t-cuda13_0
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' | nvidia-curand==10.4.0.35; platform_system == 'Linux' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | nvidia-nccl-cu13==2.27.7; 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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: 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==9.13.0.50; 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'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda13_0-test: # Testing

View File

@ -44,7 +44,7 @@ jobs:
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
manywheel-py3_10-rocm6_4-build:
manywheel-py3_9-rocm6_4-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -58,16 +58,16 @@ jobs:
GPU_ARCH_TYPE: rocm
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-rocm6_4
build_name: manywheel-py3_9-rocm6_4
build_environment: linux-binary-manywheel-rocm
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-rocm6_4-test: # Testing
manywheel-py3_9-rocm6_4-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_10-rocm6_4-build
- manywheel-py3_9-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
timeout-minutes: 240
@ -82,14 +82,14 @@ jobs:
SKIP_ALL_TESTS: 1
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: rocm6.4
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
- uses: actions/download-artifact@v4.1.7
name: Download Build Artifacts
with:
name: manywheel-py3_10-rocm6_4
name: manywheel-py3_9-rocm6_4
path: "${{ runner.temp }}/artifacts/"
- name: Checkout PyTorch
uses: actions/checkout@v4

View File

@ -60,13 +60,13 @@ jobs:
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
# shellcheck disable=SC2129
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.10.4"
freethreaded: false
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -81,9 +81,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"

View File

@ -56,13 +56,13 @@ jobs:
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
# shellcheck disable=SC2129
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.10.4"
freethreaded: false
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -77,9 +77,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -95,6 +99,8 @@ jobs:
"${PYTORCH_ROOT}/.ci/wheel/build_wheel.sh"
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -105,9 +111,33 @@ jobs:
SMOKE_TEST_PARAMS=""
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
# shellcheck disable=SC2153
case $DESIRED_PYTHON in
3.14t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.14)
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.13t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
;;
*)
# shellcheck disable=SC2153
desired_python=${DESIRED_PYTHON}
;;
esac
# shellcheck disable=SC2086
python -mvenv test_venv
source test_venv/bin/activate
conda create -yn "test_conda_env" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS} ${EXTRA_CONDA_INSTALL_FLAGS}
conda activate test_conda_env
pip install "$PYTORCH_FINAL_PACKAGE_DIR"/*.whl numpy -v
# shellcheck disable=SC2086
@ -166,13 +196,13 @@ jobs:
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
# shellcheck disable=SC2129
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.11.4"
freethreaded: false
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -187,9 +217,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -205,6 +239,8 @@ jobs:
"${PYTORCH_ROOT}/.ci/wheel/build_wheel.sh"
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -215,9 +251,33 @@ jobs:
SMOKE_TEST_PARAMS=""
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
# shellcheck disable=SC2153
case $DESIRED_PYTHON in
3.14t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.14)
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.13t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
;;
*)
# shellcheck disable=SC2153
desired_python=${DESIRED_PYTHON}
;;
esac
# shellcheck disable=SC2086
python -mvenv test_venv
source test_venv/bin/activate
conda create -yn "test_conda_env" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS} ${EXTRA_CONDA_INSTALL_FLAGS}
conda activate test_conda_env
pip install "$PYTORCH_FINAL_PACKAGE_DIR"/*.whl numpy -v
# shellcheck disable=SC2086
@ -276,13 +336,13 @@ jobs:
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
# shellcheck disable=SC2129
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.12.4"
freethreaded: false
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -297,9 +357,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -315,6 +379,8 @@ jobs:
"${PYTORCH_ROOT}/.ci/wheel/build_wheel.sh"
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -325,9 +391,33 @@ jobs:
SMOKE_TEST_PARAMS=""
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
# shellcheck disable=SC2153
case $DESIRED_PYTHON in
3.14t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.14)
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.13t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
;;
*)
# shellcheck disable=SC2153
desired_python=${DESIRED_PYTHON}
;;
esac
# shellcheck disable=SC2086
python -mvenv test_venv
source test_venv/bin/activate
conda create -yn "test_conda_env" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS} ${EXTRA_CONDA_INSTALL_FLAGS}
conda activate test_conda_env
pip install "$PYTORCH_FINAL_PACKAGE_DIR"/*.whl numpy -v
# shellcheck disable=SC2086
@ -386,13 +476,13 @@ jobs:
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
# shellcheck disable=SC2129
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.13.4"
freethreaded: false
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -407,9 +497,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -425,6 +519,8 @@ jobs:
"${PYTORCH_ROOT}/.ci/wheel/build_wheel.sh"
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -435,9 +531,33 @@ jobs:
SMOKE_TEST_PARAMS=""
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
# shellcheck disable=SC2153
case $DESIRED_PYTHON in
3.14t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.14)
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.13t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
;;
*)
# shellcheck disable=SC2153
desired_python=${DESIRED_PYTHON}
;;
esac
# shellcheck disable=SC2086
python -mvenv test_venv
source test_venv/bin/activate
conda create -yn "test_conda_env" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS} ${EXTRA_CONDA_INSTALL_FLAGS}
conda activate test_conda_env
pip install "$PYTORCH_FINAL_PACKAGE_DIR"/*.whl numpy -v
# shellcheck disable=SC2086
@ -496,13 +616,13 @@ jobs:
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
# shellcheck disable=SC2129
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.13.4"
freethreaded: true
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -517,9 +637,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -535,6 +659,8 @@ jobs:
"${PYTORCH_ROOT}/.ci/wheel/build_wheel.sh"
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -545,9 +671,33 @@ jobs:
SMOKE_TEST_PARAMS=""
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
# shellcheck disable=SC2153
case $DESIRED_PYTHON in
3.14t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.14)
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.13t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
;;
*)
# shellcheck disable=SC2153
desired_python=${DESIRED_PYTHON}
;;
esac
# shellcheck disable=SC2086
python -mvenv test_venv
source test_venv/bin/activate
conda create -yn "test_conda_env" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS} ${EXTRA_CONDA_INSTALL_FLAGS}
conda activate test_conda_env
pip install "$PYTORCH_FINAL_PACKAGE_DIR"/*.whl numpy -v
# shellcheck disable=SC2086
@ -606,13 +756,13 @@ jobs:
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
# shellcheck disable=SC2129
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.14.0-rc.2"
freethreaded: false
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -627,9 +777,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -645,6 +799,8 @@ jobs:
"${PYTORCH_ROOT}/.ci/wheel/build_wheel.sh"
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -655,9 +811,33 @@ jobs:
SMOKE_TEST_PARAMS=""
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
# shellcheck disable=SC2153
case $DESIRED_PYTHON in
3.14t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.14)
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.13t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
;;
*)
# shellcheck disable=SC2153
desired_python=${DESIRED_PYTHON}
;;
esac
# shellcheck disable=SC2086
python -mvenv test_venv
source test_venv/bin/activate
conda create -yn "test_conda_env" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS} ${EXTRA_CONDA_INSTALL_FLAGS}
conda activate test_conda_env
pip install "$PYTORCH_FINAL_PACKAGE_DIR"/*.whl numpy -v
# shellcheck disable=SC2086
@ -716,13 +896,13 @@ jobs:
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
# shellcheck disable=SC2129
echo "MAC_PACKAGE_WORK_DIR=${RUNNER_TEMP}" >> "${GITHUB_ENV}"
- name: Setup Python
uses: actions/setup-python@v6
with:
# TODO: Removeme once 3.14 is out
# .4 version is min minor for 3.10, and also no-gil version of 3.13 needs at least 3.13.3
python-version: "3.14.0-rc.2"
freethreaded: true
- name: Install conda and dependencies
run: |
# Install conda, setup-miniconda messes with the path that messes with the ruby stuff we do later on
curl --retry 3 --retry-all-errors -o "${RUNNER_TEMP}/conda.sh" "https://repo.anaconda.com/miniconda/Miniconda3-py310_23.5.2-0-MacOSX-$(uname -m).sh"
chmod +x "${RUNNER_TEMP}/conda.sh"
/bin/bash "${RUNNER_TEMP}/conda.sh" -b -p "${RUNNER_TEMP}/anaconda"
echo "${RUNNER_TEMP}/anaconda/bin" >> "${GITHUB_PATH}"
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -737,9 +917,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -755,6 +939,8 @@ jobs:
"${PYTORCH_ROOT}/.ci/wheel/build_wheel.sh"
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -765,9 +951,33 @@ jobs:
SMOKE_TEST_PARAMS=""
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
# shellcheck disable=SC2153
case $DESIRED_PYTHON in
3.14t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.14)
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
;;
3.13t)
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
;;
*)
# shellcheck disable=SC2153
desired_python=${DESIRED_PYTHON}
;;
esac
# shellcheck disable=SC2086
python -mvenv test_venv
source test_venv/bin/activate
conda create -yn "test_conda_env" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS} ${EXTRA_CONDA_INSTALL_FLAGS}
conda activate test_conda_env
pip install "$PYTORCH_FINAL_PACKAGE_DIR"/*.whl numpy -v
# shellcheck disable=SC2086

View File

@ -37,7 +37,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
needs: get-default-label-prefix
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
runner_prefix: "${{ needs.get-default-label-prefix.outputs.label-type }}"
test-matrix: |
@ -56,7 +56,7 @@ jobs:
uses: ./.github/workflows/_linux-test.yml
needs: nightly-dynamo-benchmarks-build
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image: ${{ needs.nightly-dynamo-benchmarks-build.outputs.docker-image }}
test-matrix: ${{ needs.nightly-dynamo-benchmarks-build.outputs.test-matrix }}
timeout-minutes: 720

View File

@ -43,11 +43,6 @@ on:
required: false
type: boolean
default: false
freezing:
description: Run freezing?
required: false
type: boolean
default: true
benchmark_configs:
description: The list of configs used the benchmark
required: false
@ -80,7 +75,7 @@ jobs:
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
test-matrix: |
{ include: [
@ -106,8 +101,8 @@ jobs:
needs: inductor-build
if: github.event.schedule == '0 7 * * *'
with:
build-environment: linux-jammy-py3.10-gcc11-build
dashboard-tag: training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true-freezing-true
build-environment: linux-jammy-py3.9-gcc11-build
dashboard-tag: training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true
docker-image: ${{ needs.inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.inductor-build.outputs.test-matrix }}
timeout-minutes: 720
@ -121,9 +116,10 @@ jobs:
name: inductor-test
uses: ./.github/workflows/_linux-test.yml
needs: inductor-build
if: github.event_name == 'workflow_dispatch'
with:
build-environment: linux-jammy-py3.10-gcc11-build
dashboard-tag: training-${{ inputs.training || 'false' }}-inference-${{ inputs.inference || 'true' }}-default-${{ inputs.default || 'true' }}-dynamic-${{ inputs.dynamic || 'true' }}-cppwrapper-${{ inputs.cppwrapper || 'true' }}-aotinductor-${{ inputs.aotinductor || 'true' }}-freezing-${{ inputs.freezing || 'true' }}
build-environment: linux-jammy-py3.9-gcc11-build
dashboard-tag: training-${{ inputs.training }}-inference-${{ inputs.inference }}-default-${{ inputs.default }}-dynamic-${{ inputs.dynamic }}-cppwrapper-${{ inputs.cppwrapper }}-aotinductor-${{ inputs.aotinductor }}
docker-image: ${{ needs.inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.inductor-build.outputs.test-matrix }}
timeout-minutes: 720

View File

@ -80,7 +80,7 @@ jobs:
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
test-matrix: |
{ include: [
@ -107,7 +107,7 @@ jobs:
needs: inductor-build
if: github.event.schedule == '0 7 * * *'
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
dashboard-tag: training-false-inference-true-default-true-dynamic-true-cppwrapper-true-aotinductor-true-freezing-true
docker-image: ${{ needs.inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.inductor-build.outputs.test-matrix }}
@ -124,7 +124,7 @@ jobs:
needs: inductor-build
if: github.event_name == 'workflow_dispatch'
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
dashboard-tag: training-${{ inputs.training }}-inference-${{ inputs.inference }}-default-${{ inputs.default }}-dynamic-${{ inputs.dynamic }}-cppwrapper-${{ inputs.cppwrapper }}-aotinductor-${{ inputs.aotinductor }}-freezing-${{ inputs.freezing }}
docker-image: ${{ needs.inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.inductor-build.outputs.test-matrix }}

View File

@ -39,7 +39,7 @@ jobs:
runner_prefix: "${{ needs.get-default-label-prefix.outputs.label-type }}"
build-environment: linux-jammy-cuda12.8-py3.10-gcc9-sm86
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0;8.6'
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "dynamo_eager_torchbench", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
@ -62,7 +62,7 @@ jobs:
{ config: "dynamic_inductor_timm", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "dynamic_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "dynamic_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.aws.a100" },
{ config: "aot_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_timm", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_timm", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
@ -154,7 +154,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
needs: get-default-label-prefix
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
runner_prefix: "${{ needs.get-default-label-prefix.outputs.label-type }}"
test-matrix: |
@ -200,7 +200,7 @@ jobs:
uses: ./.github/workflows/_linux-test.yml
needs: periodic-dynamo-benchmarks-cpu-build
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image: ${{ needs.periodic-dynamo-benchmarks-cpu-build.outputs.docker-image }}
test-matrix: ${{ needs.periodic-dynamo-benchmarks-cpu-build.outputs.test-matrix }}
secrets: inherit

View File

@ -3,10 +3,18 @@ name: inductor-rocm
on:
push:
branches:
- main
#- main
- release/*
tags:
- ciflow/inductor-rocm/*
schedule:
# We have several schedules so jobs can check github.event.schedule to activate only for a fraction of the runs.
# Also run less frequently on weekends.
- cron: 45 0,8,16 * * 1-5
- cron: 45 4 * * 0,6
- cron: 45 4,12,20 * * 1-5
- cron: 45 12 * * 0,6
- cron: 29 8 * * * # about 1:29am PDT, for mem leak check and rerun disabled tests
workflow_dispatch:
concurrency:

View File

@ -110,7 +110,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
test-matrix: |
@ -127,7 +127,7 @@ jobs:
uses: ./.github/workflows/_linux-test.yml
needs: inductor-cpu-build
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image: ${{ needs.inductor-cpu-build.outputs.docker-image }}
test-matrix: ${{ needs.inductor-cpu-build.outputs.test-matrix }}
secrets: inherit

View File

@ -79,7 +79,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
test-matrix: |
@ -101,7 +101,7 @@ jobs:
uses: ./.github/workflows/_linux-test.yml
needs: inductor-cpu-build
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image: ${{ needs.inductor-cpu-build.outputs.docker-image }}
test-matrix: ${{ needs.inductor-cpu-build.outputs.test-matrix }}
secrets: inherit

View File

@ -31,8 +31,6 @@ jobs:
if: github.repository_owner == 'pytorch'
name: Get changed files
uses: ./.github/workflows/_get-changed-files.yml
with:
all_files: ${{ contains(github.event.pull_request.labels.*.name, 'lint-all-files') || contains(github.event.pull_request.labels.*.name, 'Reverted') }}
lintrunner-clang:
uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
@ -55,7 +53,7 @@ jobs:
with:
timeout: 120
runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
docker-image: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3.10-linter
docker-image: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-linter
# NB: A shallow checkout won't work here because calculate-docker-image requires a full checkout
# to run git rev-parse HEAD~:.ci/docker when a new image is needed
fetch-depth: 0
@ -266,10 +264,10 @@ jobs:
with:
submodules: false
fetch-depth: 1
- name: Setup Python 3.10
- name: Setup Python 3.9
uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0
with:
python-version: '3.10'
python-version: '3.9'
architecture: x64
cache: pip
- name: Install dependencies

View File

@ -54,7 +54,7 @@ jobs:
- get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3.10-gcc11
build-environment: linux-jammy-py3.9-gcc11
docker-image: ${{ needs.docs-build.outputs.docker-image }}
push: ${{ github.event_name == 'schedule' || github.event_name == 'workflow_dispatch' || startsWith(github.event.ref, 'refs/tags/v') }}
run-doxygen: true

View File

@ -14,10 +14,6 @@ on:
schedule:
# Run at 07:00 UTC every Sunday
- cron: 0 7 * * 0
pull_request:
paths:
- benchmarks/operator_benchmark/**
- .github/workflows/operator_benchmark.yml
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
@ -33,7 +29,7 @@ jobs:
name: opbenchmark-build
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
test-matrix: |
{ include: [
@ -46,7 +42,7 @@ jobs:
name: opbenchmark-on-demand-build
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
test-matrix: |
{ include: [
@ -59,7 +55,7 @@ jobs:
uses: ./.github/workflows/_linux-test.yml
needs: opbenchmark-build
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
docker-image: ${{ needs.opbenchmark-build.outputs.docker-image }}
test-matrix: ${{ needs.opbenchmark-build.outputs.test-matrix }}
secrets: inherit

View File

@ -316,6 +316,32 @@ jobs:
]}
secrets: inherit
linux-jammy-py3-clang12-executorch-build:
if: false # Docker build needs pin update
name: linux-jammy-py3-clang12-executorch
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3-clang12-executorch
docker-image-name: ci-image:pytorch-linux-jammy-py3-clang12-executorch
test-matrix: |
{ include: [
{ config: "executorch", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
]}
secrets: inherit
linux-jammy-py3-clang12-executorch-test:
name: linux-jammy-py3-clang12-executorch
uses: ./.github/workflows/_linux-test.yml
needs: linux-jammy-py3-clang12-executorch-build
if: false # Has been broken for a while
with:
build-environment: linux-jammy-py3-clang12-executorch
docker-image: ${{ needs.linux-jammy-py3-clang12-executorch-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-py3-clang12-executorch-build.outputs.test-matrix }}
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc9-inductor-build:
name: cuda12.8-py3.10-gcc9-sm75
uses: ./.github/workflows/_linux-build.yml

View File

@ -3,13 +3,19 @@ name: rocm
on:
push:
branches:
- main
# - main
- release/*
tags:
- ciflow/rocm/*
workflow_dispatch:
schedule:
- cron: 29 8 * * * # about 1:29am PDT
# We have several schedules so jobs can check github.event.schedule to activate only for a fraction of the runs.
# Also run less frequently on weekends.
- cron: 45 0,8,16 * * 1-5
- cron: 45 4 * * 0,6
- cron: 45 4,12,20 * * 1-5
- cron: 45 12 * * 0,6
- cron: 29 8 * * * # about 1:29am PDT, for mem leak check and rerun disabled tests
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}

View File

@ -1,76 +0,0 @@
# B200 Smoke Tests CI Workflow
#
# This workflow runs smoke tests on B200 hardware
#
# Flow:
# 1. Builds PyTorch with CUDA 12.8+ and sm100 architecture for B200
# 2. Runs smoke tests on linux.dgx.b200 runner
# 3. Tests executed are defined in .ci/pytorch/test.sh -> test_python_smoke() function
#
# Triggered by:
# - Pull requests modifying this workflow file
# - Manual dispatch
# - Schedule (every 6 hours)
# - Adding ciflow/b200 label to a PR (creates ciflow/b200/* tag)
name: B200 Smoke Tests
on:
pull_request:
paths:
- .github/workflows/test-b200.yml
workflow_dispatch:
schedule:
- cron: 0 4,10,16,22 * * * # every 6 hours
push:
tags:
- ciflow/b200/*
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
cancel-in-progress: true
permissions:
id-token: write
contents: read
jobs:
get-label-type:
if: github.repository_owner == 'pytorch'
name: get-label-type
uses: pytorch/pytorch/.github/workflows/_runner-determinator.yml@main
with:
triggering_actor: ${{ github.triggering_actor }}
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
linux-jammy-cuda12_8-py3_10-gcc11-sm100-build:
name: linux-jammy-cuda12.8-py3.10-gcc11-sm100
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runner: linux.12xlarge.memory
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-sm100
docker-image-name: ci-image:pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11
cuda-arch-list: '10.0'
test-matrix: |
{ include: [
{ config: "smoke_b200", shard: 1, num_shards: 1, runner: "linux.dgx.b200" },
]}
# config: "smoke_b200" maps to test_python_smoke_b200() in .ci/pytorch/test.sh
secrets: inherit
linux-jammy-cuda12_8-py3_10-gcc11-sm100-test:
name: linux-jammy-cuda12.8-py3.10-gcc11-sm100
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-jammy-cuda12_8-py3_10-gcc11-sm100-build
with:
build-environment: linux-jammy-cuda12.8-py3.10-gcc11-sm100
docker-image: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm100-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-cuda12_8-py3_10-gcc11-sm100-build.outputs.test-matrix }}
aws-role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_s3_and_ecr_read_only
secrets: inherit

View File

@ -240,7 +240,7 @@ jobs:
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3.10-gcc11
build-environment: linux-jammy-py3.9-gcc11
docker-image-name: ci-image:pytorch-linux-jammy-py3-gcc11-inductor-benchmarks
test-matrix: |
{ include: [
@ -255,31 +255,7 @@ jobs:
- verify-cachebench-cpu-build
- target-determination
with:
build-environment: linux-jammy-py3.10-gcc11
build-environment: linux-jammy-py3.9-gcc11
docker-image: ${{ needs.verify-cachebench-cpu-build.outputs.docker-image }}
test-matrix: ${{ needs.verify-cachebench-cpu-build.outputs.test-matrix }}
secrets: inherit
linux-jammy-py3-clang12-executorch-build:
name: linux-jammy-py3-clang12-executorch
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3-clang12-executorch
docker-image-name: ci-image:pytorch-linux-jammy-py3-clang12-executorch
test-matrix: |
{ include: [
{ config: "executorch", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge" },
]}
secrets: inherit
linux-jammy-py3-clang12-executorch-test:
name: linux-jammy-py3-clang12-executorch
uses: ./.github/workflows/_linux-test.yml
needs: linux-jammy-py3-clang12-executorch-build
with:
build-environment: linux-jammy-py3-clang12-executorch
docker-image: ${{ needs.linux-jammy-py3-clang12-executorch-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-py3-clang12-executorch-build.outputs.test-matrix }}
secrets: inherit

View File

@ -53,3 +53,27 @@ jobs:
issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
curr_branch: ${{ github.head_ref || github.ref_name }}
curr_ref_type: ${{ github.ref_type }}
linux-jammy-py3_9-clang9-xla-build:
name: linux-jammy-py3_9-clang9-xla
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build-environment: linux-jammy-py3.9-clang9-xla
docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/xla_base:v1.3-lite
test-matrix: |
{ include: [
{ config: "xla", shard: 1, num_shards: 1, runner: "${{ needs.get-label-type.outputs.label-type }}linux.12xlarge" },
]}
secrets: inherit
linux-jammy-py3_9-clang9-xla-test:
name: linux-jammy-py3_9-clang9-xla
uses: ./.github/workflows/_linux-test.yml
needs: linux-jammy-py3_9-clang9-xla-build
with:
build-environment: linux-jammy-py3.9-clang9-xla
docker-image: ${{ needs.linux-jammy-py3_9-clang9-xla-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-py3_9-clang9-xla-build.outputs.test-matrix }}
secrets: inherit

View File

@ -2,9 +2,6 @@ name: vllm-test
on:
push:
branches:
- main
- release/*
tags:
- ciflow/vllm/*
workflow_dispatch:
@ -36,8 +33,6 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
needs: get-label-type
with:
# When building vLLM, uv doesn't like that we rename wheel without changing the wheel metadata
allow-reuse-old-whl: false
build-additional-packages: "vision audio"
build-external-packages: "vllm"
build-environment: linux-jammy-cuda12.8-py3.12-gcc11
@ -50,18 +45,14 @@ jobs:
{ config: "vllm_basic_models_test", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_entrypoints_test", shard: 1, num_shards: 1,runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_regression_test", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_lora_280_failure_test", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_multi_model_processor_test", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_pytorch_compilation_unit_tests", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_lora_28_failure_test", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_multi_model_test_28_failure_test", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu"},
{ config: "vllm_languagde_model_test_extended_generation_28_failure_test", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu"},
{ config: "vllm_distributed_test_2_gpu_28_failure_test", shard: 1, num_shards: 1, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_lora_test", shard: 0, num_shards: 4, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_lora_test", shard: 1, num_shards: 4, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_lora_test", shard: 2, num_shards: 4, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_lora_test", shard: 3, num_shards: 4, runner: "linux.g6.4xlarge.experimental.nvidia.gpu" },
{ config: "vllm_lora_tp_test_distributed", shard: 1, num_shards: 1, runner: "linux.g6.12xlarge.nvidia.gpu"},
{ config: "vllm_distributed_test_28_failure_test", shard: 1, num_shards: 1, runner: "linux.g6.12xlarge.nvidia.gpu"}
{ config: "vllm_lora_tp_test_distributed", shard: 1, num_shards: 1, runner: "linux.aws.h100.4"},
]}
secrets: inherit

5
.gitignore vendored
View File

@ -259,9 +259,6 @@ gen
.pytest_cache
aten/build/*
# Linker scripts for prioritized text optimization
cmake/linker_script.ld
# Bram
plsdontbreak
@ -392,5 +389,3 @@ android/pytorch_android_torchvision/.cxx
# Claude Code local configuration
CLAUDE.local.md
/test_*.py
/debug_*.py

View File

@ -13,7 +13,7 @@ exclude_patterns = [
'**/fb/**',
'functorch/docs/**',
'functorch/examples/**',
'functorch/docs/source/tutorials/**',
'functorch/notebooks/**',
'torch/_inductor/fx_passes/serialized_patterns/**',
'torch/_inductor/autoheuristic/artifacts/**',
'scripts/**',
@ -123,7 +123,6 @@ is_formatter = true
code = 'MYPY'
include_patterns = [
'setup.py',
'functorch/dim/**/*.py',
'torch/**/*.py',
'torch/**/*.pyi',
'caffe2/**/*.py',
@ -196,7 +195,6 @@ exclude_patterns = [
'tools/test/gen_operators_yaml_test.py',
'tools/test/gen_oplist_test.py',
'tools/test/test_selective_build.py',
'tools/experimental/dynamic_shapes/torchfuzz/**',
]
command = [
'python3',
@ -966,6 +964,7 @@ exclude_patterns = [
'test/jit/**', # should be run through test/test_jit.py
'test/ao/sparsity/**', # should be run through test/test_ao_sparsity.py
'test/fx/**', # should be run through test/test_fx.py
'test/bottleneck_test/**', # excluded by test/run_test.py
'test/package/**', # excluded by test/run_test.py
'test/distributed/argparse_util_test.py',
'test/distributed/bin/test_script.py',
@ -1411,6 +1410,8 @@ exclude_patterns = [
'torch/utils/benchmark/utils/timer.py',
'torch/utils/benchmark/utils/valgrind_wrapper/__init__.py',
'torch/utils/benchmark/utils/valgrind_wrapper/timer_interface.py',
'torch/utils/bottleneck/__init__.py',
'torch/utils/bottleneck/__main__.py',
'torch/utils/bundled_inputs.py',
'torch/utils/checkpoint.py',
'torch/utils/collect_env.py',
@ -1567,6 +1568,7 @@ include_patterns = [
exclude_patterns = [
'caffe2/**',
'functorch/docs/**',
'functorch/notebooks/**',
'torch/_inductor/fx_passes/serialized_patterns/**',
'torch/_inductor/autoheuristic/artifacts/**',
'test/dynamo/cpython/**',

View File

@ -810,7 +810,7 @@ cc_library(
name = "torch_python",
srcs = libtorch_python_core_sources
+ if_cuda(libtorch_python_cuda_sources)
+ libtorch_python_distributed_sources
+ if_cuda(libtorch_python_distributed_sources)
+ GENERATED_AUTOGRAD_PYTHON,
hdrs = glob([
"torch/csrc/generic/*.cpp",

View File

@ -1,4 +1,5 @@
cmake_minimum_required(VERSION 3.27 FATAL_ERROR)
# cmake_policy(SET CMP0022 NEW) cmake_policy(SET CMP0023 NEW)
# Use compiler ID "AppleClang" instead of "Clang" for XCode. Not setting this
# sometimes makes XCode C compiler gets detected as "Clang", even when the C++
@ -233,7 +234,6 @@ cmake_dependent_option(INSTALL_TEST "Install test binaries if BUILD_TEST is on"
option(USE_CPP_CODE_COVERAGE "Compile C/C++ with code coverage flags" OFF)
option(USE_COLORIZE_OUTPUT "Colorize output during compilation" ON)
option(USE_ASAN "Use Address+Undefined Sanitizers" OFF)
option(USE_LSAN "Use Leak Sanitizer" OFF)
option(USE_TSAN "Use Thread Sanitizer" OFF)
option(USE_CUDA "Use CUDA" ON)
option(USE_XPU "Use XPU" ON)
@ -379,13 +379,6 @@ cmake_dependent_option(BUILD_BUNDLE_PTXAS "Bundle PTX into torch/bin fodler"
OFF "USE_CUDA" OFF)
cmake_dependent_option(USE_KLEIDIAI "Use KleidiAI for the ARM CPU & AARCH64 architecture." ON
"CPU_AARCH64" OFF)
# prioritized text linker, ON by default for AArch64+Linux, option visible to all AArch64, x86 and ppc64le.
set(USE_PRIORITIZED_TEXT_DEFAULT OFF)
if(LINUX AND CPU_AARCH64)
set(USE_PRIORITIZED_TEXT_DEFAULT ON)
endif()
cmake_dependent_option(USE_PRIORITIZED_TEXT_FOR_LD "Use prioritized text linker for ld."
"${USE_PRIORITIZED_TEXT_DEFAULT}" "CPU_INTEL OR CPU_AARCH64 OR CPU_POWER" OFF)
option(USE_MIMALLOC "Use mimalloc" OFF)
# Enable third party mimalloc library to improve memory allocation performance
@ -663,11 +656,6 @@ endif(MSVC)
string(APPEND CMAKE_CUDA_FLAGS " -Xfatbin -compress-all")
# Set linker max-page-size to 64KiB on AArch64 Linux
if(LINUX AND CPU_AARCH64)
add_link_options_if_supported("-z,max-page-size=0x10000")
endif()
# Set INTERN_BUILD_MOBILE for all mobile builds. Components that are not
# applicable to mobile are disabled by this variable. Setting
# `BUILD_PYTORCH_MOBILE_WITH_HOST_TOOLCHAIN` environment variable can force it
@ -885,7 +873,7 @@ cmake_dependent_option(
"Whether to build the flash_attention kernel for scaled dot product attention.\
Will be disabled if not supported by the platform"
ON
"(USE_CUDA AND NOT MSVC) OR USE_ROCM"
"USE_CUDA OR USE_ROCM;NOT MSVC"
OFF)
cmake_dependent_option(
@ -901,9 +889,9 @@ IF(USE_FBGEMM_GENAI AND USE_ROCM AND NOT "gfx942" IN_LIST PYTORCH_ROCM_ARCH)
set(USE_FBGEMM_GENAI off)
endif()
# Set USE_FBGEMM_GENAI to ON for CUDA build on SM100.
if(USE_CUDA AND "$ENV{TORCH_CUDA_ARCH_LIST}" MATCHES "10.0" AND CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL 12.8 AND NOT WIN32)
message(STATUS "Setting USE_FBGEMM_GENAI to ON, doing CUDA build for SM100a")
# Set USE_FBGEMM_GENAI to ON for CUDA build on SM100
if(USE_CUDA AND "$ENV{TORCH_CUDA_ARCH_LIST}" MATCHES "10.0a")
message(WARNING "Setting USE_FBGEMM_GENAI to ON for CUDA build on SM100")
set(USE_FBGEMM_GENAI ON)
endif()
@ -920,7 +908,7 @@ cmake_dependent_option(
# USE_FLASH_ATTENTION -> USE_ROCM -> Dependencies.cmake -> aotriton.cmake
#
if(USE_ROCM)
if(USE_FLASH_ATTENTION OR USE_MEM_EFF_ATTENTION)
if(UNIX AND (USE_FLASH_ATTENTION OR USE_MEM_EFF_ATTENTION))
include(cmake/External/aotriton.cmake)
endif()
endif()
@ -1432,57 +1420,3 @@ if(BUILD_BUNDLE_PTXAS AND USE_CUDA)
install(PROGRAMS "${PROJECT_BINARY_DIR}/ptxas"
DESTINATION "${CMAKE_INSTALL_BINDIR}")
endif()
if(USE_PRIORITIZED_TEXT_FOR_LD)
add_compile_options(
$<$<COMPILE_LANGUAGE:C,CXX>:-ffunction-sections>
$<$<COMPILE_LANGUAGE:C,CXX>:-fdata-sections>
)
set(LINKER_SCRIPT_FILE_OUT "${CMAKE_SOURCE_DIR}/cmake/linker_script.ld")
set(LINKER_SCRIPT_FILE_IN "${CMAKE_SOURCE_DIR}/cmake/prioritized_text.txt")
add_custom_command(
OUTPUT "${LINKER_SCRIPT_FILE_OUT}"
COMMAND ${Python_EXECUTABLE} ${CMAKE_SOURCE_DIR}/tools/setup_helpers/generate_linker_script.py --filein "${LINKER_SCRIPT_FILE_IN}" --fout "${LINKER_SCRIPT_FILE_OUT}"
DEPENDS ${CMAKE_SOURCE_DIR}/tools/setup_helpers/generate_linker_script.py "${LINKER_SCRIPT_FILE_IN}"
COMMENT "Generating prioritized text linker files"
VERBATIM
)
add_custom_target(generate_linker_script DEPENDS "${LINKER_SCRIPT_FILE_OUT}")
if(BUILD_PYTHON)
set(LINKER_OPT_TARGETS torch_python)
endif()
if(NOT BUILD_LIBTORCHLESS)
list(APPEND LINKER_OPT_TARGETS torch_cpu c10)
if(USE_CUDA)
list(APPEND LINKER_OPT_TARGETS torch_cuda c10_cuda)
endif()
if(USE_XPU)
list(APPEND LINKER_OPT_TARGETS torch_xpu c10_xpu)
endif()
if(USE_ROCM)
list(APPEND LINKER_OPT_TARGETS torch_hip c10_hip)
endif()
endif()
foreach(tgt IN LISTS LINKER_OPT_TARGETS)
if(TARGET ${tgt})
add_dependencies("${tgt}" generate_linker_script)
target_link_options_if_supported(${tgt} "-T,${LINKER_SCRIPT_FILE_OUT}")
set_property(TARGET ${tgt} APPEND PROPERTY LINK_DEPENDS "${LINKER_SCRIPT_FILE_OUT}")
else()
message(WARNING "Requested target '${tgt}' for linker script optimization was not found.")
endif()
endforeach()
else()
if(LINUX AND CPU_AARCH64)
message(WARNING [[
It is strongly recommend to enable linker script optimization for all AArch64 Linux builds.
To do so please export USE_PRIORITIZED_TEXT_FOR_LD=1
]])
endif()
endif()

View File

@ -50,7 +50,6 @@ Following is the Release Compatibility Matrix for PyTorch releases:
| PyTorch version | Python | C++ | Stable CUDA | Experimental CUDA | Stable ROCm |
| --- | --- | --- | --- | --- | --- |
| 2.9 | >=3.10, <=(3.14, 3.14t experimental) | C++17 | CUDA 12.6 (CUDNN 9.10.2.21), CUDA 12.8 (CUDNN 9.10.2.21) | CUDA 13.0 (CUDNN 9.13.0.50) | ROCm 6.4 |
| 2.8 | >=3.9, <=3.13, (3.13t experimental) | C++17 | CUDA 12.6 (CUDNN 9.10.2.21), CUDA 12.8 (CUDNN 9.10.2.21) | CUDA 12.9 (CUDNN 9.10.2.21) | ROCm 6.4 |
| 2.7 | >=3.9, <=3.13, (3.13t experimental) | C++17 | CUDA 11.8 (CUDNN 9.1.0.70), CUDA 12.6 (CUDNN 9.5.1.17) | CUDA 12.8 (CUDNN 9.7.1.26) | ROCm 6.3 |
| 2.6 | >=3.9, <=3.13, (3.13t experimental) | C++17 | CUDA 11.8, CUDA 12.4 (CUDNN 9.1.0.70) | CUDA 12.6 (CUDNN 9.5.1.17) | ROCm 6.2.4 |

View File

@ -16,8 +16,6 @@ However, if you believe you have found a security vulnerability in PyTorch, we e
Please report security issues using https://github.com/pytorch/pytorch/security/advisories/new
All reports submitted thru the security advisories mechanism would **either be made public or dismissed by the team within 90 days of the submission**. If advisory has been closed on the grounds that it is not a security issue, please do not hesitate to create an [new issue](https://github.com/pytorch/pytorch/issues/new?template=bug-report.yml) as it is still likely a valid issue within the framework.
Please refer to the following page for our responsible disclosure policy, reward guidelines, and those things that should not be reported:
https://www.facebook.com/whitehat

View File

@ -265,14 +265,6 @@ IF(USE_FBGEMM_GENAI)
"${FBGEMM_GENAI_SRCS}/cutlass_extensions/**/*.cu")
list(FILTER fbgemm_genai_native_cuda_cu INCLUDE REGEX ${FBGEMM_CUTLASS_KERNELS_REGEX})
# PyTorch is not built for 10.0a in CI, due to lack of portability,
# so we need to explicitly build these files for 10.0a.
foreach(cu_file ${fbgemm_genai_native_cuda_cu})
_BUILD_FOR_ADDITIONAL_ARCHS(
"${cu_file}"
"100a")
endforeach()
file(GLOB_RECURSE fbgemm_genai_native_cuda_cpp
"${FBGEMM_GENAI_SRCS}/common/*.cpp"
)
@ -317,20 +309,10 @@ IF(USE_FBGEMM_GENAI)
-greedy-reverse-local-assignment=1
-fhip-new-launch-api)
# Only compile for gfx942 for now.
# This is rather hacky, I could not figure out a clean solution :(
set(HIP_CLANG_FLAGS_ORIGINAL ${HIP_CLANG_FLAGS})
string(REGEX REPLACE "--offload-arch=[^ ]*" "" FILTERED_HIP_CLANG_FLAGS "${HIP_CLANG_FLAGS}")
if("gfx942" IN_LIST PYTORCH_ROCM_ARCH)
list(APPEND FILTERED_HIP_CLANG_FLAGS --offload-arch=gfx942;)
endif()
set(HIP_CLANG_FLAGS ${FILTERED_HIP_CLANG_FLAGS})
hip_add_library(
fbgemm_genai STATIC
${fbgemm_genai_native_rocm_hip}
HIPCC_OPTIONS ${HIP_HCC_FLAGS} ${FBGEMM_GENAI_EXTRA_HIPCC_FLAGS})
set(HIP_CLANG_FLAGS ${HIP_CLANG_FLAGS_ORIGINAL})
set_target_properties(fbgemm_genai PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_compile_definitions(fbgemm_genai PRIVATE FBGEMM_GENAI_NO_EXTENDED_SHAPES)

View File

@ -180,7 +180,7 @@ void Context::setUserEnabledNNPACK(bool e) {
}
bool Context::allowTF32CuDNN(const std::string& op) const {
if (op.empty()){
if (op.size() == 0){
bool allow_tf32_rnn = float32Precision("cuda", "rnn") == "tf32";
bool allow_tf32_conv = float32Precision("cuda", "conv") == "tf32";
TORCH_CHECK(
@ -281,6 +281,9 @@ bool Context::userEnabledOverrideableSDP() const {
static constexpr const auto cublas_config_var_name = "CUBLAS_WORKSPACE_CONFIG";
static constexpr const std::array<const char*, 2> cublas_deterministic_configs = {":4096:8", ":16:8"};
#ifdef USE_ROCM
static constexpr const auto hipblaslt_allow_tf32 = "HIPBLASLT_ALLOW_TF32";
#endif
bool Context::checkCuBLASConfigDeterministic() {
// If using CUDA 10.2 or greater, need to make sure CuBLAS workspace config
@ -340,6 +343,12 @@ void Context::setImmediateMiopen(bool b) {
}
bool Context::allowTF32CuBLAS() const {
#ifdef USE_ROCM
const auto allow_tf32 = c10::utils::check_env(hipblaslt_allow_tf32);
if (allow_tf32 != true) {
return false;
}
#endif
bool legacy_allow_tf32 = float32_matmul_precision != at::Float32MatmulPrecision::HIGHEST;
bool allow_tf32_new = float32Precision("cuda", "matmul") == "tf32";
TORCH_CHECK(
@ -353,6 +362,14 @@ bool Context::allowTF32CuBLAS() const {
}
void Context::setAllowTF32CuBLAS(bool b) {
#ifdef USE_ROCM
const auto allow_tf32 = c10::utils::check_env(hipblaslt_allow_tf32);
if (allow_tf32 != true) {
C10_LOG_FIRST_N(INFO, 10) << "torch.backends.cuda.matmul.allow_tf32 is not supported on ROCm by default. "
<< "Please set environment variable HIPBLASLT_ALLOW_TF32=1 to enable it.";
return;
}
#endif
float32_matmul_precision = b ? at::Float32MatmulPrecision::HIGH : at::Float32MatmulPrecision::HIGHEST;
setFloat32Precision("cuda", "matmul", b ? "tf32" : "ieee");
}
@ -426,7 +443,7 @@ void Context::setFloat32Precision(const std::string& backend, const std::string&
std::string msg;
auto iterp = _fp32_precisions.find(backend);
TORCH_CHECK(iterp != _fp32_precisions.end());
for (const auto& p : iterp->second) {
for (auto p : iterp->second) {
msg += p;
msg += " ";
}

View File

@ -65,24 +65,14 @@ DLDataType getDLDataType(const Tensor& t) {
break;
// TODO(#146647): use macro here instead of spelling out each shell dtype
case ScalarType::Float8_e5m2:
dtype.code = DLDataTypeCode::kDLFloat8_e5m2;
break;
case ScalarType::Float8_e5m2fnuz:
dtype.code = DLDataTypeCode::kDLFloat8_e5m2fnuz;
break;
case ScalarType::Float8_e4m3fn:
dtype.code = DLDataTypeCode::kDLFloat8_e4m3fn;
break;
case ScalarType::Float8_e4m3fnuz:
dtype.code = DLDataTypeCode::kDLFloat8_e4m3fnuz;
break;
case ScalarType::Float8_e8m0fnu:
dtype.code = DLDataTypeCode::kDLFloat8_e8m0fnu;
TORCH_CHECK_BUFFER(false, "float8 types are not supported by dlpack");
break;
case ScalarType::Float4_e2m1fn_x2:
dtype.code = DLDataTypeCode::kDLFloat4_e2m1fn;
dtype.lanes = 2;
dtype.bits = 4;
TORCH_CHECK_BUFFER(false, "float4 types are not supported by dlpack");
break;
case ScalarType::QInt8:
case ScalarType::QUInt8:
@ -187,11 +177,7 @@ static Device getATenDevice(DLDeviceType type, c10::DeviceIndex index, void* dat
ScalarType toScalarType(const DLDataType& dtype) {
ScalarType stype = ScalarType::Undefined;
if (dtype.code != DLDataTypeCode::kDLFloat4_e2m1fn) {
TORCH_CHECK_BUFFER(
dtype.lanes == 1,
"ATen does not support lanes != 1 for dtype code", std::to_string(dtype.code));
}
TORCH_CHECK_BUFFER(dtype.lanes == 1, "ATen does not support lanes != 1");
switch (dtype.code) {
case DLDataTypeCode::kDLUInt:
switch (dtype.bits) {
@ -283,73 +269,6 @@ ScalarType toScalarType(const DLDataType& dtype) {
false, "Unsupported kDLBool bits ", std::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLFloat8_e5m2:
switch (dtype.bits) {
case 8:
stype = ScalarType::Float8_e5m2;
break;
default:
TORCH_CHECK_BUFFER(
false, "Unsupported kDLFloat8_e5m2 bits ", std::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLFloat8_e5m2fnuz:
switch (dtype.bits) {
case 8:
stype = ScalarType::Float8_e5m2fnuz;
break;
default:
TORCH_CHECK_BUFFER(
false, "Unsupported kDLFloat8_e5m2fnuz bits ", std::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLFloat8_e4m3fn:
switch (dtype.bits) {
case 8:
stype = ScalarType::Float8_e4m3fn;
break;
default:
TORCH_CHECK_BUFFER(
false, "Unsupported kDLFloat8_e4m3fn bits ", std::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLFloat8_e4m3fnuz:
switch (dtype.bits) {
case 8:
stype = ScalarType::Float8_e4m3fnuz;
break;
default:
TORCH_CHECK_BUFFER(
false, "Unsupported kDLFloat8_e4m3fnuz bits ", std::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLFloat8_e8m0fnu:
switch (dtype.bits) {
case 8:
stype = ScalarType::Float8_e8m0fnu;
break;
default:
TORCH_CHECK_BUFFER(
false, "Unsupported kDLFloat8_e8m0fnu bits ", std::to_string(dtype.bits));
}
break;
case DLDataTypeCode::kDLFloat4_e2m1fn:
switch (dtype.bits) {
case 4:
switch (dtype.lanes) {
case 2:
stype = ScalarType::Float4_e2m1fn_x2;
break;
default:
TORCH_CHECK_BUFFER(
false, "Unsupported kDLFloat4_e2m1fn lanes ", std::to_string(dtype.lanes));
}
break;
default:
TORCH_CHECK_BUFFER(
false, "Unsupported kDLFloat4_e2m1fn bits ", std::to_string(dtype.bits));
}
break;
default:
TORCH_CHECK_BUFFER(false, "Unsupported code ", std::to_string(dtype.code));
}
@ -401,13 +320,30 @@ T* toDLPackImpl(const Tensor& src) {
// The following code detects whether the src follows
// a continuous pattern. If the src follows such pattern (common-case)
// then we do not need to normalize the strides.
bool need_normalize_strides = src.dim() == 1 && src.size(0) == 1 && src.stride(0) != 1;
bool need_normalize_strides = false;
int64_t expected_stride = 1;
for (int i = src.dim() - 1; i >= 0; i--) {
// detect if we do not meet continuous pattern
// and the size is 1, so there is opportunity to normalize
if (src.stride(i) != expected_stride && src.size(i) == 1) {
need_normalize_strides = true;
break;
}
expected_stride *= src.size(i);
}
// less common case, try normalizing the strides
if (need_normalize_strides) {
// create a new tensor with possibly normalized strides
// gh-83069
auto shape = src.sizes();
view = src.as_strided(shape, {1}, src.storage_offset());
auto strides = src.strides().vec();
for (int i = 0; i < src.dim(); i++) {
if (shape[i] < 2) {
strides[i] = 1;
}
}
view = src.as_strided(shape, strides, src.storage_offset());
}
ATenDLMTensor<T>* atDLMTensor(new ATenDLMTensor<T>);
@ -418,8 +354,8 @@ T* toDLPackImpl(const Tensor& src) {
atDLMTensor->tensor.dl_tensor.device = torchDeviceToDLDevice(src.device());
atDLMTensor->tensor.dl_tensor.ndim = static_cast<int32_t>(src.dim());
atDLMTensor->tensor.dl_tensor.dtype = getDLDataType(src);
atDLMTensor->tensor.dl_tensor.shape = const_cast<int64_t*>(view.sizes().data());
atDLMTensor->tensor.dl_tensor.strides = const_cast<int64_t*>(view.strides().data());
atDLMTensor->tensor.dl_tensor.shape = view.sizes().data();
atDLMTensor->tensor.dl_tensor.strides = view.strides().data();
atDLMTensor->tensor.dl_tensor.byte_offset = 0;
fillVersion(&atDLMTensor->tensor);

View File

@ -102,7 +102,7 @@ FunctionalStorageImpl::FunctionalStorageImpl(const Tensor& base)
// SparseTensorImpl has no storage, so we cannot query its nbytes.
// (original_storage_size is only used for storage resizing in fsdp anyway, which does not apply to sparse)
// Same for XLA
if (base.unsafeGetTensorImpl()->has_storage() && data_ptr().device().type() != c10::DeviceType::XLA) {
if (base.unsafeGetTensorImpl()->has_storage() && base.device().type() != c10::DeviceType::XLA) {
original_storage_size_ = base.unsafeGetTensorImpl()->unsafe_storage().unsafeGetStorageImpl()->sym_nbytes();
} else {
original_storage_size_ = -1;

View File

@ -133,7 +133,7 @@ FunctionalTensorWrapper::FunctionalTensorWrapper(const Tensor& view_value, const
: c10::TensorImpl(
c10::DispatchKeySet(DispatchKey::Functionalize),
view_value.dtype(),
base->storage().data_ptr().device()
view_value.device()
),
value_(view_value),
is_multi_output_view_(base->is_multi_output_view_ || meta.is_multi_output),
@ -485,10 +485,7 @@ void FunctionalTensorWrapper::shallow_copy_from(const c10::intrusive_ptr<TensorI
c10::Device FunctionalTensorWrapper::device_custom() const {
// The storage pointer already uses the underlying tensor custom device (if
// applicable) to extract the device. So, we dont have to recurse again by
// doing value_.unsafeGetTensorImpl()->device().
return storage().data_ptr().device();
return value_.unsafeGetTensorImpl()->device();
}
at::IntArrayRef FunctionalTensorWrapper::sizes_custom() const {
return value_.unsafeGetTensorImpl()->sizes();

View File

@ -133,12 +133,12 @@ struct TORCH_API SparseTensorImpl : public TensorImpl {
"resize_ called on tensor with symbolic shape")
TORCH_CHECK(
sparse_dim + dense_dim == static_cast<int64_t>(size.size()),
"'len(size) == sparse_dim + dense_dim' is not satisfied: len(size) = ",
size.size(),
", sparse_dim = ",
"number of dimensions must be sparse_dim (",
sparse_dim,
", dense_dim = ",
dense_dim);
") + dense_dim (",
dense_dim,
"), but got ",
size.size());
if (nnz() > 0) {
[[maybe_unused]] auto constexpr alt_options_msg =
"You could try the following options:\n\
@ -254,12 +254,12 @@ struct TORCH_API SparseTensorImpl : public TensorImpl {
"resize_and_clear_ called on tensor with symbolic shape")
TORCH_CHECK(
sparse_dim + dense_dim == static_cast<int64_t>(size.size()),
"'len(size) == sparse_dim + dense_dim' is not satisfied: len(size) = ",
size.size(),
", sparse_dim = ",
"number of dimensions must be sparse_dim (",
sparse_dim,
", dense_dim = ",
dense_dim);
") + dense_dim (",
dense_dim,
"), but got ",
size.size());
set_sizes_and_strides(size, std::vector<int64_t>(size.size()));
sparse_dim_ = sparse_dim;

View File

@ -64,7 +64,6 @@ constexpr DynamicTypeBits kDynamicClassTypeBit = DYNAMIC_TYPE_BIT(10);
_(ScalarType, kDynamicIntTypeBit, 1) \
_(Layout, kDynamicIntTypeBit, 1) \
_(SymInt, kDynamicIntTypeBit, 1) \
_(SymBool, kDynamicIntTypeBit, 1) \
_(MemoryFormat, kDynamicIntTypeBit, 1)
#define FORWARD_DECL_TYPE(NAME, _, __) struct NAME ## Type;

View File

@ -644,8 +644,6 @@ inline void bgemm_internal_cublas_half_helper(CUDABLAS_BGEMM_ARGTYPES_AND_C_DTYP
void * beta_ptr = &fbeta;
#ifdef USE_ROCM
int flag = 0;
rocblas_datatype c_type = std::is_same<C_Dtype, float>::value ? rocblas_datatype_f32_r : rocblas_datatype_f16_r;
rocblas_datatype d_type = c_type;
#if USE_GEMM_FLAGS_FP16_ALT_IMPL
flag = at::ROCmBackwardPassGuard::is_backward_pass() ? rocblas_gemm_flags_fp16_alt_impl : 0;
#endif
@ -654,8 +652,8 @@ inline void bgemm_internal_cublas_half_helper(CUDABLAS_BGEMM_ARGTYPES_AND_C_DTYP
hipOperationToRocOperation(opb), (int)m, (int)n, (int)k,
(void*)alpha_ptr, a, rocblas_datatype_f16_r, (int)lda, stridea,
b, rocblas_datatype_f16_r, (int)ldb, strideb,
(void*)beta_ptr, c, c_type, (int)ldc, stridec,
c, d_type, (int)ldc, stridec,
(void*)beta_ptr, c, rocblas_datatype_f16_r, (int)ldc, stridec,
c, rocblas_datatype_f16_r, (int)ldc, stridec,
(int) num_batches, rocblas_datatype_f32_r, rocblas_gemm_algo_standard,
0, flag)));
#else
@ -1098,8 +1096,6 @@ inline void gemm_internal_cublas_half_helper(CUDABLAS_GEMM_ARGTYPES_AND_C_DTYPE(
GEMM_CHECK_ARGVALUES(at::Half);
#ifdef USE_ROCM
int flag = 0;
rocblas_datatype c_type = std::is_same<C_Dtype, float>::value ? rocblas_datatype_f32_r : rocblas_datatype_f16_r;
rocblas_datatype d_type = c_type;
#if USE_GEMM_FLAGS_FP16_ALT_IMPL
flag = at::ROCmBackwardPassGuard::is_backward_pass() ? rocblas_gemm_flags_fp16_alt_impl : 0;
#endif
@ -1119,10 +1115,10 @@ inline void gemm_internal_cublas_half_helper(CUDABLAS_GEMM_ARGTYPES_AND_C_DTYPE(
ldb,
beta_ptr,
c,
c_type,
rocblas_datatype_f16_r,
ldc,
c,
d_type,
rocblas_datatype_f16_r,
ldc,
rocblas_datatype_f32_r,
rocblas_gemm_algo_standard,
@ -1637,7 +1633,9 @@ bool gemm_and_bias(
if (activation == GEMMAndBiasActivationEpilogue::RELU) {
epilogue = CUBLASLT_EPILOGUE_RELU_BIAS;
} else if (activation == GEMMAndBiasActivationEpilogue::GELU) {
#if CUDA_VERSION >= 11040 || defined(USE_ROCM)
epilogue = CUBLASLT_EPILOGUE_GELU_BIAS;
#endif
}
if (bias != nullptr) {
@ -1929,6 +1927,7 @@ void scaled_gemm(
bool use_fast_accum) {
// Note: see `cublasCommonArgs` for various non-intuitive manupulations
// of input arguments to this function.
#if CUDA_VERSION >= 11080 || defined(USE_ROCM)
const auto computeType = CUBLAS_COMPUTE_32F;
const auto scaleType = CUDA_R_32F;
const float alpha_val = 1.0;
@ -1951,8 +1950,8 @@ void scaled_gemm(
#if ROCM_VERSION >= 70000
if (at::detail::getCUDAHooks().isGPUArch({"gfx950"})) {
// TODO: add constraints based on hipblaslt internals
TORCH_CHECK((m % 16 == 0) && (n % 16 == 0) && (k % 128 == 0),
"M, N must be multiples of 16 and K should be multiple of 128 for MX format. "
TORCH_CHECK((m % 32 == 0) && (n % 32 == 0) && (k % 32 == 0),
"Matrix dimensions must be multiples of 32 for MX format. "
"Got m=", m, ", n=", n, ", k=", k);
}
#endif
@ -2130,6 +2129,8 @@ void scaled_gemm(
" scaleType ",
scaleType);
return;
#endif // if CUDA_VERSION >= 11080 || defined(USE_ROCM)
TORCH_CHECK(false, "scaled_gemm is only supported for CUDA 11.8 and above");
}
void int8_gemm(

View File

@ -266,14 +266,11 @@ CUDAGeneratorImpl::CUDAGeneratorImpl(
* See Note [Acquire lock when using random generators]
*/
void CUDAGeneratorImpl::set_current_seed(uint64_t seed) {
if (C10_LIKELY(at::cuda::currentStreamCaptureStatus() == at::cuda::CaptureStatus::None)) {
state_->seed_ = seed;
state_->philox_offset_per_thread_ = 0;
no_reset_rnn_state_.clear();
} else {
TORCH_CHECK(state_->seed_ == seed, "CUDAGeneratorImpl::set_current_seed can be called during stream capture only if new seed is the same as the original seed.");
// no-op case
}
at::cuda::assertNotCapturing(
"Cannot call CUDAGeneratorImpl::set_current_seed");
state_->seed_ = seed;
state_->philox_offset_per_thread_ = 0;
no_reset_rnn_state_.clear();
}
/**
@ -302,6 +299,9 @@ uint64_t CUDAGeneratorImpl::get_offset() const {
* Gets the current seed of CUDAGeneratorImpl.
*/
uint64_t CUDAGeneratorImpl::current_seed() const {
// Debatable if current_seed() should be allowed in captured regions.
// Conservatively disallow it for now.
at::cuda::assertNotCapturing("Cannot call CUDAGeneratorImpl::current_seed");
return state_->seed_;
}
@ -346,6 +346,8 @@ c10::intrusive_ptr<c10::TensorImpl> CUDAGeneratorImpl::get_state() const {
* and size of the internal state.
*/
void CUDAGeneratorImpl::set_state(const c10::TensorImpl& new_state) {
at::cuda::assertNotCapturing(
"Please ensure to utilize the CUDAGeneratorImpl::set_state_index method during capturing.");
static const size_t seed_size = sizeof(uint64_t);
static const size_t offset_size = sizeof(int64_t);
static const size_t total_size = seed_size + offset_size;
@ -400,27 +402,15 @@ c10::intrusive_ptr<c10::GeneratorImpl> CUDAGeneratorImpl::graphsafe_get_state()
*/
void CUDAGeneratorImpl::set_philox_offset_per_thread(uint64_t offset) {
// see Note [Why enforce RNG offset % 4 == 0?]
// Note: If you use CUDNN RNN's, calling
// set_philox_offset_per_thread instead of set_offset will cause the
// cudnn RNN rng state to become stale.
TORCH_CHECK(offset % 4 == 0, "offset must be a multiple of 4");
if (C10_LIKELY(at::cuda::currentStreamCaptureStatus() == at::cuda::CaptureStatus::None)) {
state_->philox_offset_per_thread_ = offset;
} else {
state_->offset_intragraph_ = offset;
}
state_->philox_offset_per_thread_ = offset;
}
/**
* Gets the current philox_offset_per_thread_ of CUDAGeneratorImpl.
*/
uint64_t CUDAGeneratorImpl::philox_offset_per_thread() const {
if (C10_LIKELY(at::cuda::currentStreamCaptureStatus() == at::cuda::CaptureStatus::None)) {
return state_->philox_offset_per_thread_;
} else {
return state_->offset_intragraph_;
}
return state_->philox_offset_per_thread_;
}
/**

View File

@ -45,24 +45,6 @@ struct OffsetCalculator {
C10_HOST_DEVICE offset_type get(index_t linear_idx) const {
offset_type offsets;
#if defined(USE_ROCM)
if ((dims > 0) && (dims <= 2)) {
auto divmod = sizes_[0].divmod(linear_idx);
#pragma unroll
for (int arg = 0; arg < NARGS; arg++)
offsets[arg] = divmod.mod * strides_[0][arg];
if (dims >= 2) {
divmod = sizes_[1].divmod(divmod.div);
#pragma unroll
for (int arg = 0; arg < NARGS; arg++)
offsets[arg] += divmod.mod * strides_[1][arg];
}
// [...]
return offsets;
}
#endif
#pragma unroll
for (int arg = 0; arg < NARGS; arg++) {
offsets[arg] = 0;

View File

@ -19,7 +19,7 @@
#define DLPACK_MAJOR_VERSION 1
/*! \brief The current minor version of dlpack */
#define DLPACK_MINOR_VERSION 1
#define DLPACK_MINOR_VERSION 0
/*! \brief DLPACK_DLL prefix for windows */
#ifdef _WIN32
@ -32,7 +32,9 @@
#define DLPACK_DLL
#endif
// NOLINTNEXTLINE(modernize-deprecated-headers)
#include <stdint.h>
// NOLINTNEXTLINE(modernize-deprecated-headers)
#include <stddef.h>
#ifdef __cplusplus
@ -157,26 +159,6 @@ typedef enum {
kDLComplex = 5U,
/*! \brief boolean */
kDLBool = 6U,
/*! \brief FP8 data types */
kDLFloat8_e3m4 = 7U,
kDLFloat8_e4m3 = 8U,
kDLFloat8_e4m3b11fnuz = 9U,
kDLFloat8_e4m3fn = 10U,
kDLFloat8_e4m3fnuz = 11U,
kDLFloat8_e5m2 = 12U,
kDLFloat8_e5m2fnuz = 13U,
kDLFloat8_e8m0fnu = 14U,
/*! \brief FP6 data types
* Setting bits != 6 is currently unspecified, and the producer must ensure it is set
* while the consumer must stop importing if the value is unexpected.
*/
kDLFloat6_e2m3fn = 15U,
kDLFloat6_e3m2fn = 16U,
/*! \brief FP4 data types
* Setting bits != 4 is currently unspecified, and the producer must ensure it is set
* while the consumer must stop importing if the value is unexpected.
*/
kDLFloat4_e2m1fn = 17U,
} DLDataTypeCode;
/*!
@ -190,12 +172,6 @@ typedef enum {
* - int8: type_code = 0, bits = 8, lanes = 1
* - std::complex<float>: type_code = 5, bits = 64, lanes = 1
* - bool: type_code = 6, bits = 8, lanes = 1 (as per common array library convention, the underlying storage size of bool is 8 bits)
* - float8_e4m3: type_code = 8, bits = 8, lanes = 1 (packed in memory)
* - float6_e3m2fn: type_code = 16, bits = 6, lanes = 1 (packed in memory)
* - float4_e2m1fn: type_code = 17, bits = 4, lanes = 1 (packed in memory)
*
* When a sub-byte type is packed, DLPack requires the data to be in little bit-endian, i.e.,
* for a packed data set D ((D >> (i * bits)) && bit_mask) stores the i-th element.
*/
typedef struct {
/*!
@ -253,12 +229,12 @@ typedef struct {
/*! \brief The data type of the pointer*/
DLDataType dtype;
/*! \brief The shape of the tensor */
int64_t* shape;
const int64_t* shape;
/*!
* \brief strides of the tensor (in number of elements, not bytes)
* can be NULL, indicating tensor is compact and row-majored.
*/
int64_t* strides;
const int64_t* strides;
/*! \brief The offset in bytes to the beginning pointer to data */
uint64_t byte_offset;
} DLTensor;
@ -293,7 +269,7 @@ typedef struct DLManagedTensor {
void (*deleter)(struct DLManagedTensor * self);
} DLManagedTensor;
// bit masks used in the DLManagedTensorVersioned
// bit masks used in in the DLManagedTensorVersioned
/*! \brief bit mask to indicate that the tensor is read only. */
#define DLPACK_FLAG_BITMASK_READ_ONLY (1UL << 0UL)
@ -306,14 +282,6 @@ typedef struct DLManagedTensor {
*/
#define DLPACK_FLAG_BITMASK_IS_COPIED (1UL << 1UL)
/*
* \brief bit mask to indicate that whether a sub-byte type is packed or padded.
*
* The default for sub-byte types (ex: fp4/fp6) is assumed packed. This flag can
* be set by the producer to signal that a tensor of sub-byte type is padded.
*/
#define DLPACK_FLAG_BITMASK_IS_SUBBYTE_TYPE_PADDED (1UL << 2UL)
/*!
* \brief A versioned and managed C Tensor object, manage memory of DLTensor.
*

View File

@ -171,8 +171,6 @@ TORCH_LIBRARY_IMPL(aten, FuncTorchBatched, m) {
POINTWISE_BOXED(fill_.Scalar);
POINTWISE_BOXED(zero_);
// This is special because this op doesn't return anything
m.impl("_assert_tensor_metadata", native::_assert_tensor_metadata);
#undef UNARY_POINTWISE
#undef UNARY_POINTWISE_ALL

View File

@ -457,9 +457,24 @@ void gemm(
return;
}
#endif
// for the fallback path, first compute gemm with beta = 0,
// and then add c in full precision.
int64_t c_size = n * m;
std::vector<float> float_c(c_size, 0.f);
gemm_no_downcast_stub(
at::kCPU, at::kBFloat16,
transa, transb, m, n, k, alpha, a, lda, b, ldb, beta, c, ldc);
transa, transb, m, n, k, alpha, a, lda, b, ldb, 0.f, float_c.data(), m);
for (const auto j : c10::irange(n)) {
for (const auto i : c10::irange(m)) {
auto offset = j * ldc + i;
// beta == 0 won't propagate NaN from C
if (beta == 0.f) {
c[offset] = float_c[j * m + i];
} else {
c[offset] = beta * c[offset] + float_c[j * m + i];
}
}
}
}
void gemm(
@ -478,9 +493,24 @@ void gemm(
return;
}
#endif
// for the fallback path, first compute gemm with beta = 0,
// and then add c in full precision.
int64_t c_size = n * m;
std::vector<float> float_c(c_size, 0.f);
gemm_no_downcast_stub(
at::kCPU, at::kHalf,
transa, transb, m, n, k, alpha, a, lda, b, ldb, beta, c, ldc);
transa, transb, m, n, k, alpha, a, lda, b, ldb, 0.f, float_c.data(), m);
for (const auto j : c10::irange(n)) {
for (const auto i : c10::irange(m)) {
auto offset = j * ldc + i;
// beta == 0 won't propagate NaN from C
if (beta == 0.f) {
c[offset] = float_c[j * m + i];
} else {
c[offset] = beta * c[offset] + float_c[j * m + i];
}
}
}
}
void gemm(

View File

@ -81,7 +81,7 @@ Tensor math_channel_shuffle(const Tensor& self, int64_t groups) {
// TODO: contiguous can be made to preserve the memory format
// of the input. However since the above reshape clobbers h and w
// it may not be safe to do that, since channels_last contiguous
// may think oc and the last dim correspond to h,w?
// may think oc and and the last dim correspond to h,w?
// It is not clear, however from initial looking around it feels that
// this may not be correct.
// In this case channels last will likely require custom implementation

View File

@ -14,7 +14,6 @@
#include <c10/util/accumulate.h>
#include <c10/util/irange.h>
#include <c10/macros/Macros.h>
#include <algorithm>
#include <limits>
#include <utility>
@ -301,50 +300,67 @@ struct ConvParams {
bool allow_tf32{};
bool is_strided() const {
return std::any_of(
stride.cbegin(), stride.cend(), [](const T& s) { return s != 1; });
bool is_strided = false;
for (const auto& s : stride) {
is_strided |= (s != 1);
}
return is_strided;
}
bool is_dilated() const {
return std::any_of(
dilation.cbegin(), dilation.cend(), [](const T& d) { return d != 1; });
bool is_dilated = false;
for (const auto& d : dilation) {
is_dilated |= (d != 1);
}
return is_dilated;
}
bool is_padded() const {
return std::any_of(
padding.cbegin(), padding.cend(), [](const T& p) { return p != 0; });
bool is_padded = false;
for (auto p : padding) {
is_padded |= (p != 0);
}
return is_padded;
}
bool is_output_padding_neg() const {
return std::any_of(
output_padding.cbegin(),
output_padding.cend(),
[](const T& p) { return p < 0; });
bool is_non_neg = false;
for (const auto& p : output_padding) {
is_non_neg |= (p < 0);
}
return is_non_neg;
}
bool is_output_padding_big() const {
// Revisit this with std::views::zip at C++20.
bool is_big = false;
for (auto i: c10::irange(output_padding.size())) {
if (output_padding[i] >= stride[i]) {
return true;
}
is_big |= (output_padding[i] >= stride[i]);
}
return false;
return is_big;
}
bool is_padding_neg() const {
return std::any_of(
padding.cbegin(), padding.cend(), [](const T& p) { return p < 0; });
bool is_non_neg = false;
for (const auto& p : padding) {
is_non_neg |= (p < 0);
}
return is_non_neg;
}
bool is_dilation_neg() const {
return std::any_of(
dilation.cbegin(), dilation.cend(), [](const T& d) { return d < 0; });
bool is_non_neg = false;
for (const auto& p : dilation) {
is_non_neg |= (p < 0);
}
return is_non_neg;
}
bool is_stride_nonpos() const {
return std::any_of(
stride.cbegin(), stride.cend(), [](const T& s) { return s <= 0; });
bool is_nonpos = false;
for (const auto& s : stride) {
is_nonpos |= (s <= 0);
}
return is_nonpos;
}
void view1d_as_2d() {

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