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4 Commits

Author SHA1 Message Date
3f85e2baa3 ditch const 2025-09-10 10:38:18 -07:00
339fe1a29d lint 2025-09-03 22:03:20 -07:00
8fdf326e85 Default return for unreachable case in module shim 2025-09-03 21:47:14 -07:00
1cd74387af shim interface and nativeRT impl 2025-09-03 20:43:57 -07:00
1045 changed files with 10381 additions and 27333 deletions

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@ -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
@ -28,7 +27,7 @@ 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 [ "$DESIRED_CUDA" = "cpu" ]; then
echo "BASE_CUDA_VERSION is not set. Building cpu wheel."
#USE_PRIORITIZED_TEXT_FOR_LD for enable linker script optimization https://github.com/pytorch/pytorch/pull/121975/files
@ -36,16 +35,6 @@ if [ "$DESIRED_CUDA" = "cpu" ]; then
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
#USE_PRIORITIZED_TEXT_FOR_LD for enable linker script optimization https://github.com/pytorch/pytorch/pull/121975/files
USE_PRIORITIZED_TEXT_FOR_LD=1 python /pytorch/.ci/aarch64_linux/aarch64_wheel_ci_build.py --enable-mkldnn --enable-cuda
fi

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@ -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(
@ -322,16 +232,6 @@ if __name__ == "__main__":
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:

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@ -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

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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

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@ -1 +0,0 @@
7fe50dc3da2069d6645d9deb8c017a876472a977

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@ -1 +1 @@
1b0418a9a454b2b93ab8d71f40e59d2297157fae
d0e80f39c562c70986fc548fa6e5852ad86e16e7

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@ -1 +1 @@
5ae38bdb0dc066c5823e34dc9797afb9de42c866
f7888497a1eb9e98d4c07537f0d0bcfe180d1363

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

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

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@ -1 +1 @@
3.5.0
3.4.0

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@ -1 +1 @@
3.5.0
3.4.0

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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

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@ -76,6 +76,7 @@ def sample_vllm_test_library():
),
"pytest -v -s entrypoints/llm/test_lazy_outlines.py",
"pytest -v -s entrypoints/llm/test_generate.py ",
"pytest -v -s entrypoints/llm/test_generate_multiple_loras.py",
"VLLM_USE_V1=0 pytest -v -s entrypoints/offline_mode",
],
},
@ -96,24 +97,14 @@ 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": {
@ -124,15 +115,6 @@ 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",
@ -147,28 +129,6 @@ 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

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

View File

@ -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

@ -199,7 +199,7 @@ torchbench_setup_macos() {
git checkout "$(cat ../.github/ci_commit_pins/vision.txt)"
git submodule update --init --recursive
python setup.py clean
python -m pip install -e . -v --no-build-isolation
python setup.py develop
popd
pushd torchaudio
@ -208,7 +208,7 @@ torchbench_setup_macos() {
git submodule update --init --recursive
python setup.py clean
#TODO: Remove me, when figure out how to make TorchAudio find brew installed openmp
USE_OPENMP=0 python -m pip install -e . -v --no-build-isolation
USE_OPENMP=0 python setup.py develop
popd
checkout_install_torchbench

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

@ -1721,6 +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

View File

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

View File

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

View File

@ -85,7 +85,7 @@ mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
# Create an isolated directory to store this builds pytorch checkout and conda
# installation
if [[ -z "$MAC_PACKAGE_WORK_DIR" ]]; then
MAC_PACKAGE_WORK_DIR="$(pwd)/tmp_wheel_${DESIRED_PYTHON}_$(date +%H%M%S)"
MAC_PACKAGE_WORK_DIR="$(pwd)/tmp_wheel_conda_${DESIRED_PYTHON}_$(date +%H%M%S)"
fi
mkdir -p "$MAC_PACKAGE_WORK_DIR" || true
if [[ -n ${GITHUB_ACTIONS} ]]; then
@ -96,11 +96,11 @@ fi
whl_tmp_dir="${MAC_PACKAGE_WORK_DIR}/dist"
mkdir -p "$whl_tmp_dir"
mac_version='macosx-11_0-arm64'
mac_version='macosx_11_0_arm64'
libtorch_arch='arm64'
# Create a consistent wheel package name to rename the wheel to
wheel_filename_new="${TORCH_PACKAGE_NAME}-${build_version}${build_number_prefix}-cp${python_nodot}-none-${mac_version//[-,]/_}.whl"
wheel_filename_new="${TORCH_PACKAGE_NAME}-${build_version}${build_number_prefix}-cp${python_nodot}-none-${mac_version}.whl"
###########################################################
@ -124,57 +124,93 @@ popd
export TH_BINARY_BUILD=1
export INSTALL_TEST=0 # dont install test binaries into site-packages
export MACOSX_DEPLOYMENT_TARGET=11.0
export MACOSX_DEPLOYMENT_TARGET=10.15
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
SETUPTOOLS_PINNED_VERSION="==70.1.0"
PYYAML_PINNED_VERSION="==5.3"
EXTRA_CONDA_INSTALL_FLAGS=""
CONDA_ENV_CREATE_FLAGS=""
RENAME_WHEEL=true
case $desired_python in
3.14t)
echo "Using 3.14 deps"
mac_version='macosx-11.0-arm64'
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.1.0"
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
RENAME_WHEEL=false
;;
3.14)
echo "Using 3.14t deps"
mac_version='macosx-11.0-arm64'
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.1.0"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
desired_python="3.14.0rc1"
RENAME_WHEEL=false
;;
3.13t)
echo "Using 3.13 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.1.0"
CONDA_ENV_CREATE_FLAGS="python-freethreading"
EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
desired_python="3.13"
RENAME_WHEEL=false
;;
3.13)
echo "Using 3.13 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.1.0"
;;
3.12)
echo "Using 3.12 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=6.0.1"
NUMPY_PINNED_VERSION="==2.0.2"
;;
3.11)
echo "Using 3.11 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="==2.0.2"
;;
3.10)
echo "Using 3.10 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="==2.0.2"
;;
3.9)
echo "Using 3.9 deps"
SETUPTOOLS_PINNED_VERSION=">=70.1.0"
PYYAML_PINNED_VERSION=">=5.3"
NUMPY_PINNED_VERSION="==2.0.2"
;;
*)
echo "Unsupported version $desired_python"
exit 1
echo "Using default deps"
NUMPY_PINNED_VERSION="==1.11.3"
;;
esac
# Install into a fresh env
tmp_env_name="wheel_py$python_nodot"
conda create ${EXTRA_CONDA_INSTALL_FLAGS} -yn "$tmp_env_name" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS}
source activate "$tmp_env_name"
PINNED_PACKAGES=(
"setuptools${SETUPTOOLS_PINNED_VERSION}"
"pyyaml${PYYAML_PINNED_VERSION}"
"numpy${NUMPY_PINNED_VERSION}"
)
python -mvenv ~/${desired_python}-build
source ~/${desired_python}-build/bin/activate
retry pip install "${PINNED_PACKAGES[@]}" -r "${pytorch_rootdir}/requirements.txt"
retry pip install "${PINNED_PACKAGES[@]}" -r "${pytorch_rootdir}/requirements-build.txt"
pip install requests ninja typing-extensions
retry pip install -r "${pytorch_rootdir}/requirements.txt" || true
retry brew install libomp
# For USE_DISTRIBUTED=1 on macOS, this enables gloo, which needs libuv, which
@ -188,7 +224,7 @@ 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"
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

@ -12,9 +12,7 @@ self-hosted-runner:
- linux.9xlarge.ephemeral
- am2.linux.9xlarge.ephemeral
- linux.12xlarge
- linux.12xlarge.memory
- linux.24xlarge
- linux.24xlarge.memory
- linux.24xlarge.ephemeral
- linux.24xlarge.amd
- linux.arm64.2xlarge

View File

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

View File

@ -1 +1 @@
caba63f0fa29ef9e3d566699f32f11c07c8bda4e
0757bbb660855272f7dd8d31cc84e7c631522805

View File

@ -1 +1 @@
08ae0af1395c8d8471f4025deb6af9aef90b342f
7f1de94a4c2d14f59ad4ca84538c36084ea6b2c8

View File

@ -1 +1 @@
f510715882304796a96e33028b4f6de1b026c2c7
862f2ef893d9751db0a92bd2d4ae0e3d9677872f

View File

@ -1 +1 @@
6c5478ff7c3d50dd1e3047d72ec5909bea474073
763e5b78d4fcd74a9e812256656c075f99d9a781

View File

@ -12,46 +12,54 @@ ARG BUILD_BASE_IMAGE=torch-nightly-base
# by default, it uses devel-ubuntu22.04 official image.
ARG FINAL_BASE_IMAGE=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04
# The logic is copied from https://github.com/vllm-project/vllm/blob/main/docker/Dockerfile
ARG GET_PIP_URL="https://bootstrap.pypa.io/get-pip.py"
#################### TORCH NIGHTLY BASE IMAGE ####################
#################### TORCH NIGHTLY BASE IMAGE ####################
# A base image for building vLLM with devel ubuntu 22.04, this is mainly used to build vllm in vllm builtkite ci
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 as torch-nightly-base
From nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04 as torch-nightly-base
ARG CUDA_VERSION=12.8.1
ARG PYTHON_VERSION=3.12
ARG TARGETPLATFORM
ENV DEBIAN_FRONTEND=noninteractive
ARG CUDA_VERSION
ARG PYTHON_VERSION
ARG GET_PIP_URL
RUN PYTHON_VERSION_STR=$(echo ${PYTHON_VERSION} | sed 's/\.//g') && \
echo "export PYTHON_VERSION_STR=${PYTHON_VERSION_STR}" >> /etc/environment
# Install Python and other dependencies
RUN apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim \
&& add-apt-repository -y ppa:deadsnakes/ppa \
&& apt-get update -y \
&& apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
&& update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS ${GET_PIP_URL} | python${PYTHON_VERSION} \
&& python3 --version && python3 -m pip --version
# Install Python and other dependencies if it does not existed
RUN if ! command -v python3 >/dev/null || ! python3 --version | grep -q "${PYTHON_VERSION}"; then \
echo "Installing Python ${PYTHON_VERSION}..." && \
echo 'tzdata tzdata/Areas select America' | debconf-set-selections && \
echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections && \
apt-get update -y && \
apt-get install -y ccache software-properties-common git curl sudo && \
for i in 1 2 3; do \
add-apt-repository -y ppa:deadsnakes/ppa && break || \
{ echo "Attempt $i failed, retrying in 5s..."; sleep 5; }; \
done && \
apt-get update -y && \
apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv && \
update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 && \
update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} && \
ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config && \
curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}; \
else \
echo "Python ${PYTHON_VERSION} already present, skipping setup."; \
fi \
&& python3 --version && python3 -m pip --version
# Upgrade to GCC 10 to avoid https://gcc.gnu.org/bugzilla/show_bug.cgi?id=92519
# as it was causing spam when compiling the CUTLASS kernels
# Ensure gcc >= 10 to avoid CUTLASS issues (bug 92519)
RUN current_gcc_version=$(gcc -dumpversion | cut -f1 -d.) && \
if command -v apt-get >/dev/null; then \
if [ "$current_gcc_version" -lt 10 ]; then \
echo "GCC version is $current_gcc_version, installing gcc-10..."; \
apt-get update \
&& apt-get install -y gcc-10 g++-10 \
&& update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 100 \
&& update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-10 100; \
else \
echo "GCC version is $current_gcc_version, no need to install gcc-10."; \
fi \
fi \
&& gcc --version && g++ --version
if [ "$current_gcc_version" -lt 10 ]; then \
echo "GCC version is $current_gcc_version, installing gcc-10..."; \
apt-get update && \
apt-get install -y gcc-10 g++-10 && \
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 100 && \
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-10 100; \
else \
echo "GCC version is $current_gcc_version, no need to install gcc-10."; \
fi && \
gcc --version && g++ --version
# install uv for faster pip installs
RUN --mount=type=cache,target=/root/.cache/uv \
@ -71,21 +79,6 @@ ENV UV_LINK_MODE=copy
FROM ${BUILD_BASE_IMAGE} AS base
USER root
ARG CUDA_VERSION
ARG PYTHON_VERSION
# TODO (huydhn): Only work with PyTorch manylinux builder
ENV PATH="/opt/python/cp312-cp312/bin:${PATH}"
# Install some system dependencies and double check python version
RUN if command -v apt-get >/dev/null; then \
apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim; \
else \
dnf install -y git curl wget sudo 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
@ -125,15 +118,17 @@ RUN --mount=type=bind,source=${TORCH_WHEELS_PATH},target=/dist \
if [ -n "$TORCH_WHEELS_PATH" ] && [ "$TORCH_WHEELS_PATH" != "./requirements" ] && [ -d "/dist" ] && ls /dist/torch*.whl >/dev/null 2>&1; then \
echo "[INFO] Installing torch wheels to build vllm"; \
torch_whl=$(find /dist -maxdepth 1 -name 'torch-*.whl' -print -quit); \
vision_whl=$(find /dist -name 'torchvision*.whl' | head -n1 | xargs); \
audio_whl=$(find /dist -name 'torchaudio*.whl' | head -n1 | xargs); \
uv pip install --system "${torch_whl}[opt-einsum]" "${vision_whl}" "${audio_whl}" /dist/*.whl; \
vision_whl=$(find /dist/vision -name 'torchvision*.whl' | head -n1 | xargs); \
audio_whl=$(find /dist/audio -name 'torchaudio*.whl' | head -n1 | xargs); \
uv pip install --system "${torch_whl}[opt-einsum]"; \
uv pip install --system "${vision_whl}"; \
uv pip install --system "${audio_whl}"; \
elif [ -n "$PINNED_TORCH_VERSION" ]; then \
echo "[INFO] Installing pinned torch nightly version to build vllm: $PINNED_TORCH_VERSION"; \
uv pip install --system "$PINNED_TORCH_VERSION" --index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.'); \
uv pip install --system "$PINNED_TORCH_VERSION" --index-url https://download.pytorch.org/whl/nightly/cu128; \
else \
echo "[INFO] Installing torch nightly with latest one to build vllm"; \
uv pip install --system torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.'); \
uv pip install --system torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128; \
fi
# Install numba 0.61.2 for cuda environment
@ -142,11 +137,12 @@ RUN --mount=type=cache,target=/root/.cache/uv \
# Install common dependencies from vllm common.txt
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/common.txt
uv pip install --system -r requirements/common.txt
# Must put before installing xformers, so it can install the correct version of xfomrers.
ARG xformers_cuda_arch_list='7.5;8.0+PTX;9.0a'
ENV TORCH_CUDA_ARCH_LIST=${xformers_cuda_arch_list}
ARG exformer_cuda_arch_list='7.5;8.0+PTX;9.0a'
ENV TORCH_CUDA_ARCH_LIST=${exformer_cuda_arch_list}
ARG max_jobs=16
ENV MAX_JOBS=${max_jobs}
@ -157,8 +153,8 @@ RUN pip freeze | grep -E 'ninja'
# Build xformers with cuda and torch nightly/wheel
# following official xformers guidance: https://github.com/facebookresearch/xformers#build
# sha for https://github.com/facebookresearch/xformers/tree/v0.0.32.post2
ARG XFORMERS_COMMIT=5d4b92a5e5a9c6c6d4878283f47d82e17995b468
# sha for https://github.com/facebookresearch/xformers/tree/v0.0.31
ARG XFORMERS_COMMIT=eb0946a363464da96ea40afd1a7f72a907c25497
ENV CCACHE_DIR=/root/.cache/ccache
RUN --mount=type=cache,target=/root/.cache/ccache \
@ -192,6 +188,11 @@ RUN pip freeze | grep -E 'torch|xformers|torchvision|torchaudio'
FROM base AS build
ARG TARGETPLATFORM
ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"
# Use copy mode to avoid hardlink failures with Docker cache mounts
ENV UV_LINK_MODE=copy
COPY . .
RUN python3 use_existing_torch.py
@ -250,9 +251,9 @@ RUN --mount=type=cache,target=/root/.cache/ccache \
python3 setup.py bdist_wheel --dist-dir=vllm-dist --py-limited-api=cp38; \
fi
RUN echo "[INFO] Listing current directory:" && \
RUN echo "[DEBUG] Listing current directory:" && \
ls -al && \
echo "[INFO] Showing torch_build_versions.txt content:" && \
echo "[DEBUG] Showing torch_build_versions.txt content:" && \
cat torch_build_versions.txt
#################### WHEEL BUILD IMAGE ####################
@ -262,40 +263,42 @@ RUN echo "[INFO] Listing current directory:" && \
# Setup clean environment for vLLM for test and api server using ubuntu22.04 with AOT flashinfer
FROM ${FINAL_BASE_IMAGE} AS vllm-base
USER root
ARG CUDA_VERSION
ARG PYTHON_VERSION
ARG GET_PIP_URL
# TODO (huydhn): Only work with PyTorch manylinux builder
ENV PATH="/opt/python/cp312-cp312/bin:${PATH}"
# prepare for environment starts
WORKDIR /workspace
# Install Python and other dependencies
RUN if command -v apt-get >/dev/null; then \
apt-get update -y \
&& apt-get install -y ccache software-properties-common git curl wget sudo vim \
&& add-apt-repository -y ppa:deadsnakes/ppa \
&& apt-get update -y \
&& apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
&& update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
&& ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
&& curl -sS ${GET_PIP_URL} | python${PYTHON_VERSION}; \
else \
dnf install -y git curl wget sudo vim; \
fi \
&& python3 --version && python3 -m pip --version
RUN PYTHON_VERSION_STR=$(echo ${PYTHON_VERSION} | sed 's/\.//g') && \
echo "export PYTHON_VERSION_STR=${PYTHON_VERSION_STR}" >> /etc/environment
# Install Python and other dependencies if it does not existed
RUN if ! command -v python3 >/dev/null || ! python3 --version | grep -q "${PYTHON_VERSION}"; then \
echo "Installing Python ${PYTHON_VERSION}..." && \
echo 'tzdata tzdata/Areas select America' | debconf-set-selections && \
echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections && \
apt-get update -y && \
apt-get install -y ccache software-properties-common git curl sudo && \
for i in 1 2 3; do \
add-apt-repository -y ppa:deadsnakes/ppa && break || \
{ echo "Attempt $i failed, retrying in 5s..."; sleep 5; }; \
done && \
apt-get update -y && \
apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv && \
update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 && \
update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} && \
ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config && \
curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}; \
else \
echo "Python ${PYTHON_VERSION} already present, skipping setup."; \
fi \
&& python3 --version && python3 -m pip --version
# Get the torch versions, and whls used in previous stagtes for consistency
COPY --from=base /workspace/torch_build_versions.txt ./torch_build_versions.txt
COPY --from=base /workspace/xformers-dist /wheels/xformers
COPY --from=build /workspace/vllm-dist /wheels/vllm
RUN echo "[INFO] Listing current directory before torch install step:" && \
RUN echo "[DEBUG] Listing current directory before torch install step:" && \
ls -al && \
echo "[INFO] Showing torch_build_versions.txt content:" && \
echo "[DEBUG] Showing torch_build_versions.txt content:" && \
cat torch_build_versions.txt
# Workaround for https://github.com/openai/triton/issues/2507 and
@ -304,6 +307,7 @@ RUN echo "[INFO] Listing current directory before torch install step:" && \
# or future versions of triton.
RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
# Install uv for faster pip installs if not existed
RUN --mount=type=cache,target=/root/.cache/uv \
if ! python3 -m uv --version > /dev/null 2>&1; then \
@ -323,13 +327,15 @@ RUN --mount=type=bind,source=${TORCH_WHEELS_PATH},target=/dist \
--mount=type=cache,target=/root/.cache/uv \
if [ -n "$TORCH_WHEELS_PATH" ] && [ "$TORCH_WHEELS_PATH" != "./requirements" ] && [ -d "/dist" ] && ls /dist/torch*.whl >/dev/null 2>&1; then \
torch_whl=$(find /dist -maxdepth 1 -name 'torch-*.whl' -print -quit); \
vision_whl=$(find /dist -name 'torchvision*.whl' | head -n1 | xargs); \
audio_whl=$(find /dist -name 'torchaudio*.whl' | head -n1 | xargs); \
vision_whl=$(find /dist/vision -name 'torchvision*.whl' | head -n1 | xargs); \
audio_whl=$(find /dist/audio -name 'torchaudio*.whl' | head -n1 | xargs); \
echo "[INFO] Use wheels to build : '${torch_whl}' '${audio_whl}' '${vision_whl}'"; \
uv pip install --system "${torch_whl}[opt-einsum]" "${vision_whl}" "${audio_whl}" /dist/*.whl; \
uv pip install --system "${torch_whl}[opt-einsum]"; \
uv pip install --system "${vision_whl}"; \
uv pip install --system "${audio_whl}"; \
else \
echo "[INFO] Installing torch versions from torch_build_versions.txt"; \
uv pip install --system $(cat torch_build_versions.txt | xargs) --index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.'); \
uv pip install --system $(cat torch_build_versions.txt | xargs) --index-url https://download.pytorch.org/whl/nightly/cu128; \
fi
# Install the vllm wheel from previous stage
@ -340,8 +346,9 @@ RUN --mount=type=cache,target=/root/.cache/uv \
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system /wheels/xformers/*.whl --verbose
# Build flashinfer from source.
ARG torch_cuda_arch_list='8.0;8.9;9.0a;10.0a;12.0'
ARG torch_cuda_arch_list='8.0;8.9;9.0a'
# install package for build flashinfer
# see issue: https://github.com/flashinfer-ai/flashinfer/issues/738
@ -409,6 +416,11 @@ RUN --mount=type=cache,target=/root/.cache/uv \
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system -r requirements/nightly_torch_test.txt
# Workaround for #17068
# pinned commit for v2.2.4
RUN --mount=type=cache,target=/root/.cache/uv \
uv pip install --system --no-build-isolation "git+https://github.com/state-spaces/mamba@95d8aba8a8c75aedcaa6143713b11e745e7cd0d9#egg=mamba-ssm"
# Logging to confirm the torch versions
RUN pip freeze | grep -E 'torch|xformers|vllm|flashinfer'

View File

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

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

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

View File

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

View File

@ -16,16 +16,18 @@ from typing import Optional
# NOTE: Please also update the CUDA sources in `PIP_SOURCES` in tools/nightly.py when changing this
CUDA_ARCHES = ["12.6", "12.8", "13.0"]
CUDA_ARCHES = ["12.6", "12.8", "12.9", "13.0"]
CUDA_STABLE = "12.8"
CUDA_ARCHES_FULL_VERSION = {
"12.6": "12.6.3",
"12.8": "12.8.1",
"12.9": "12.9.1",
"13.0": "13.0.0",
}
CUDA_ARCHES_CUDNN_VERSION = {
"12.6": "9",
"12.8": "9",
"12.9": "9",
"13.0": "9",
}
@ -38,60 +40,77 @@ CPU_AARCH64_ARCH = ["cpu-aarch64"]
CPU_S390X_ARCH = ["cpu-s390x"]
CUDA_AARCH64_ARCHES = ["12.6-aarch64", "12.8-aarch64", "13.0-aarch64"]
CUDA_AARCH64_ARCHES = ["12.9-aarch64", "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'"
),
"12.9": (
"nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
"13.0": (
"nvidia-cuda-nvrtc==13.0.48; platform_system == 'Linux' | "
"nvidia-cuda-runtime==13.0.48; platform_system == 'Linux' | "
"nvidia-cuda-cupti==13.0.48; platform_system == 'Linux' | "
"nvidia-cudnn-cu13==9.13.0.50; platform_system == 'Linux' | "
"nvidia-cublas==13.0.0.19; platform_system == 'Linux' | "
"nvidia-cufft==12.0.0.15; platform_system == 'Linux' | "
"nvidia-curand==10.4.0.35; platform_system == 'Linux' | "
"nvidia-cusolver==12.0.3.29; platform_system == 'Linux' | "
"nvidia-cusparse==12.6.2.49; platform_system == 'Linux' | "
"nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' | "
"nvidia-nccl-cu13==2.27.7; 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'"
),
"xpu": (
"intel-cmplr-lib-rt==2025.2.1 | "
@ -221,6 +240,8 @@ def generate_libtorch_matrix(
if os == "linux":
arches += CUDA_ARCHES
arches += ROCM_ARCHES
if "13.0" in arches:
arches.remove("13.0")
elif os == "windows":
arches += CUDA_ARCHES
if libtorch_variants is None:
@ -322,7 +343,7 @@ def generate_wheels_matrix(
# cuda linux wheels require PYTORCH_EXTRA_INSTALL_REQUIREMENTS to install
if (
arch_version in ["13.0", "12.8", "12.6"]
arch_version in ["13.0", "12.9", "12.8", "12.6"]
and os == "linux"
or arch_version in CUDA_AARCH64_ARCHES
):
@ -386,5 +407,6 @@ def generate_wheels_matrix(
validate_nccl_dep_consistency("13.0")
validate_nccl_dep_consistency("12.9")
validate_nccl_dep_consistency("12.8")
validate_nccl_dep_consistency("12.6")

View File

@ -22,7 +22,7 @@ LABEL_CIFLOW_BINARIES = "ciflow/binaries"
LABEL_CIFLOW_PERIODIC = "ciflow/periodic"
LABEL_CIFLOW_BINARIES_LIBTORCH = "ciflow/binaries_libtorch"
LABEL_CIFLOW_BINARIES_WHEEL = "ciflow/binaries_wheel"
LABEL_CIFLOW_ROCM = "ciflow/rocm"
LABEL_CIFLOW_ROCM = "ciflow/rocm-mi300"
@dataclass
@ -139,8 +139,6 @@ ROCM_SMOKE_WORKFLOWS = [
),
ciflow_config=CIFlowConfig(
labels={
LABEL_CIFLOW_BINARIES,
LABEL_CIFLOW_BINARIES_WHEEL,
LABEL_CIFLOW_ROCM,
},
isolated_workflow=True,

View File

@ -1,91 +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
}
pushd externals/vllm/wheels
for package in xformers flashinfer-python vllm; do
repackage_wheel $package
done
popd

View File

@ -171,7 +171,7 @@ jobs:
- name: Teardown XPU
uses: ./.github/actions/teardown-xpu
{%- else %}
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: !{{ common.timeout_minutes }}
!{{ upload.binary_env(config) }}
steps:

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 +61,28 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
!{{ common.checkout(deep_clone=False, directory="pytorch") }}
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -94,6 +99,8 @@ jobs:
{%- if config["package_type"] == "wheel" %}
- name: Test PyTorch wheel
run: |
# shellcheck disable=SC1091
source "${RUNNER_TEMP}/anaconda/bin/activate"
set -eux -o pipefail
# shellcheck disable=SC1090
source "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -104,9 +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

View File

@ -33,7 +33,7 @@
{%- if is_windows %}
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
{%- endif %}
{%- else %}

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

@ -1,219 +0,0 @@
name: Build vLLM wheels
on:
push:
branches:
- main
paths:
- .github/workflows/build-vllm-wheel.yml
- .github/ci_commit_pins/vllm.txt
workflow_dispatch:
pull_request:
paths:
- .github/workflows/build-vllm-wheel.yml
- .github/ci_commit_pins/vllm.txt
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
cancel-in-progress: true
jobs:
build-wheel:
if: github.repository_owner == 'pytorch'
strategy:
fail-fast: false
matrix:
python-version: [ '3.12' ]
# TODO (huydhn): Add cu130 https://github.com/pytorch/pytorch/pull/162000#issuecomment-3261541554
device: [ 'cu128', 'cu129' ]
runner: [ 'linux.12xlarge.memory' ]
include:
- device: cu128
manylinux-image: 'pytorch/manylinux2_28-builder:cuda12.8'
- device: cu129
manylinux-image: 'pytorch/manylinux2_28-builder:cuda12.9'
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: 'manylinux_2_28_x86_64'
BUILD_DEVICE: ${{ matrix.device }}
steps:
- name: Setup SSH (Click me for login details)
uses: pytorch/test-infra/.github/actions/setup-ssh@main
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
with:
submodules: false
- name: Setup Linux
uses: ./.github/actions/setup-linux
- name: Get latest PyTorch nightly
shell: bash
run: |
set -eux
# Determine python executable for given version (copied from build-triton-wheel)
case $PY_VERS in
3.10)
PYTHON_EXECUTABLE=/opt/python/cp310-cp310/bin/python
;;
3.11)
PYTHON_EXECUTABLE=/opt/python/cp311-cp311/bin/python
;;
3.12)
PYTHON_EXECUTABLE=/opt/python/cp312-cp312/bin/python
;;
3.13)
PYTHON_EXECUTABLE=/opt/python/cp313-cp313/bin/python
;;
3.13t)
PYTHON_EXECUTABLE=/opt/python/cp313-cp313t/bin/python
;;
3.14)
PYTHON_EXECUTABLE=/opt/python/cp314-cp314/bin/python
;;
3.14t)
PYTHON_EXECUTABLE=/opt/python/cp314-cp314t/bin/python
;;
*)
echo "Unsupported python version ${PY_VERS}"
exit 1
;;
esac
# Keep PyTorch nightly wheel here so that we can install it later during
# vLLM build process
mkdir -p "${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}"
# I wonder if there is a command to both download and install the wheels
# in one go
docker exec -t "${container_name}" "${PYTHON_EXECUTABLE}" -mpip download \
--pre torch torchvision torchaudio \
--index-url "https://download.pytorch.org/whl/nightly/${BUILD_DEVICE}"
# Save this for later
echo "container_name=${container_name}" >> "$GITHUB_ENV"
- name: Build vLLM wheel
uses: ./.github/actions/build-external-packages
with:
build-targets: vllm
docker-image: ${{ env.MANYLINUX_IMAGE }}
cuda-arch-list: '8.0;8.9;9.0;10.0;12.0'
torch-wheel-dir: ${{ runner.temp }}/artifacts
output-dir: ${{ runner.temp }}/artifacts/externals
- name: Prepare vLLM wheel
shell: bash
run: |
set -eux
# Get these wheels ready, the vllm renaming logic is copied from its .buildkite/scripts/upload-wheels.sh
docker exec -t "${container_name}" bash -c /pytorch/.github/scripts/prepare_vllm_wheels.sh
docker exec -t "${container_name}" chown -R 1000:1000 /artifacts
- uses: actions/upload-artifact@50769540e7f4bd5e21e526ee35c689e35e0d6874 # v4.4.0
with:
name: vllm-wheel-${{ matrix.device }}-${{ matrix.python-version }}-${{ env.PLATFORM }}
if-no-files-found: error
path: ${{ runner.temp }}/artifacts/externals/vllm/wheels/*.whl
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
if: always()
# Copied from build-triton-wheel workflow (mostly)
upload-wheel:
name: "Upload ${{ matrix.device }} vLLM wheel"
needs:
- build-wheel
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
device: [ 'cu128', 'cu129' ]
env:
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') && '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' }}
uses: aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722 # v4.1.0
with:
role-to-assume: arn:aws:iam::749337293305:role/gha_workflow_nightly_build_wheels
aws-region: us-east-1
- name: Configure AWS credentials(PyTorch account) for RC builds
if: ${{ github.event_name == 'push' && (startsWith(github.event.ref, 'refs/tags/') && !startsWith(github.event.ref, 'refs/tags/ciflow/')) }}
uses: aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722 # v4.1.0
with:
role-to-assume: arn:aws:iam::749337293305:role/gha_workflow_test_build_wheels
aws-region: us-east-1
- name: Download Build Artifacts
uses: actions/download-artifact@65a9edc5881444af0b9093a5e628f2fe47ea3b2e # v4.1.7
with:
# Download all available artifacts
path: ${{ runner.temp }}/artifacts-all
- name: Select Wheel Artifacts
shell: bash
run: |
set -eux
mkdir -p "${RUNNER_TEMP}/artifacts/"
mv "${RUNNER_TEMP}"/artifacts-all/vllm-wheel-"${BUILD_DEVICE}"-*/* "${RUNNER_TEMP}/artifacts/"
- 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 (only for tagged pushes)
if: ${{ github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags/v') }}
shell: bash
run: |
set -ex
if [[ "${GITHUB_REF_NAME}" = *-rc[0-9]* ]]; then
echo "UPLOAD_CHANNEL=test" >> "$GITHUB_ENV"
fi
- name: Upload binaries
env:
PACKAGE_TYPE: wheel
UPLOAD_SUBFOLDER: ${{ env.BUILD_DEVICE }}
PKG_DIR: ${{ runner.temp }}/artifacts
shell: bash
run: |
set -ex
bash .circleci/scripts/binary_upload.sh

View File

@ -112,7 +112,7 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda-aarch64-12_6-build:
manywheel-py3_10-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -121,85 +121,39 @@ jobs:
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
runner_prefix: "${{ 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_name: manywheel-py3_10-cuda-aarch64-12_9
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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda-aarch64-12_6-upload: # Uploading
manywheel-py3_10-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_10-cuda-aarch64-12_6-build
needs: manywheel-py3_10-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
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
build_name: manywheel-py3_10-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
@ -224,7 +178,7 @@ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -315,7 +269,7 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda-aarch64-12_6-build:
manywheel-py3_11-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -324,85 +278,39 @@ jobs:
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
runner_prefix: "${{ 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_name: manywheel-py3_11-cuda-aarch64-12_9
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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda-aarch64-12_6-upload: # Uploading
manywheel-py3_11-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_11-cuda-aarch64-12_6-build
needs: manywheel-py3_11-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
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
build_name: manywheel-py3_11-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
@ -427,7 +335,7 @@ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -518,7 +426,7 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda-aarch64-12_6-build:
manywheel-py3_12-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -527,85 +435,39 @@ jobs:
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
runner_prefix: "${{ 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_name: manywheel-py3_12-cuda-aarch64-12_9
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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda-aarch64-12_6-upload: # Uploading
manywheel-py3_12-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-cuda-aarch64-12_6-build
needs: manywheel-py3_12-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
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
build_name: manywheel-py3_12-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
@ -630,7 +492,7 @@ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -721,7 +583,7 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda-aarch64-12_6-build:
manywheel-py3_13-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -730,85 +592,39 @@ jobs:
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
runner_prefix: "${{ 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_name: manywheel-py3_13-cuda-aarch64-12_9
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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda-aarch64-12_6-upload: # Uploading
manywheel-py3_13-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13-cuda-aarch64-12_6-build
needs: manywheel-py3_13-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
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
build_name: manywheel-py3_13-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
@ -833,7 +649,7 @@ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -924,7 +740,7 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda-aarch64-12_6-build:
manywheel-py3_13t-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -933,85 +749,39 @@ jobs:
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
runner_prefix: "${{ 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_name: manywheel-py3_13t-cuda-aarch64-12_9
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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda-aarch64-12_6-upload: # Uploading
manywheel-py3_13t-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13t-cuda-aarch64-12_6-build
needs: manywheel-py3_13t-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
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
build_name: manywheel-py3_13t-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
@ -1036,7 +806,7 @@ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1127,7 +897,7 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda-aarch64-12_6-build:
manywheel-py3_14-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -1136,85 +906,39 @@ jobs:
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
runner_prefix: "${{ 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_name: manywheel-py3_14-cuda-aarch64-12_9
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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda-aarch64-12_6-upload: # Uploading
manywheel-py3_14-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14-cuda-aarch64-12_6-build
needs: manywheel-py3_14-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
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
build_name: manywheel-py3_14-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
@ -1239,7 +963,7 @@ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -1330,7 +1054,7 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda-aarch64-12_6-build:
manywheel-py3_14t-cuda-aarch64-12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -1339,85 +1063,39 @@ jobs:
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
runner_prefix: "${{ 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_name: manywheel-py3_14t-cuda-aarch64-12_9
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'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda-aarch64-12_6-upload: # Uploading
manywheel-py3_14t-cuda-aarch64-12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14t-cuda-aarch64-12_6-build
needs: manywheel-py3_14t-cuda-aarch64-12_9-build
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu126
GPU_ARCH_VERSION: "12.6-aarch64"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9-aarch64"
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: manylinuxaarch64-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.6
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
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
build_name: manywheel-py3_14t-cuda-aarch64-12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
@ -1442,7 +1120,7 @@ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

View File

@ -248,7 +248,7 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
libtorch-cuda13_0-shared-with-deps-release-build:
libtorch-cuda12_9-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
@ -257,22 +257,22 @@ jobs:
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu130
GPU_ARCH_VERSION: "13.0"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: libtorch-cxx11-builder
DOCKER_IMAGE_TAG_PREFIX: cuda13.0
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: libtorch-cuda13_0-shared-with-deps-release
build_name: libtorch-cuda12_9-shared-with-deps-release
build_environment: linux-binary-libtorch
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
libtorch-cuda13_0-shared-with-deps-release-test: # Testing
libtorch-cuda12_9-shared-with-deps-release-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- libtorch-cuda13_0-shared-with-deps-release-build
- libtorch-cuda12_9-shared-with-deps-release-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
@ -280,38 +280,38 @@ jobs:
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu130
GPU_ARCH_VERSION: "13.0"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: libtorch-cxx11-builder
DOCKER_IMAGE_TAG_PREFIX: cuda13.0
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
build_name: libtorch-cuda13_0-shared-with-deps-release
build_name: libtorch-cuda12_9-shared-with-deps-release
build_environment: linux-binary-libtorch
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
libtorch-cuda13_0-shared-with-deps-release-upload: # Uploading
libtorch-cuda12_9-shared-with-deps-release-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: libtorch-cuda13_0-shared-with-deps-release-test
needs: libtorch-cuda12_9-shared-with-deps-release-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu130
GPU_ARCH_VERSION: "13.0"
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: libtorch-cxx11-builder
DOCKER_IMAGE_TAG_PREFIX: cuda13.0
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
build_name: libtorch-cuda13_0-shared-with-deps-release
build_name: libtorch-cuda12_9-shared-with-deps-release
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
@ -342,7 +342,7 @@ jobs:
needs:
- libtorch-rocm6_3-shared-with-deps-release-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -456,7 +456,7 @@ jobs:
needs:
- libtorch-rocm6_4-shared-with-deps-release-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch

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
@ -241,6 +241,72 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_10-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_10-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_10-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -259,7 +325,7 @@ jobs:
runner_prefix: "${{ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda13_0-test: # Testing
@ -332,7 +398,7 @@ jobs:
needs:
- manywheel-py3_10-rocm6_3-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -443,7 +509,7 @@ jobs:
needs:
- manywheel-py3_10-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -719,7 +785,7 @@ jobs:
runner_prefix: "${{ 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: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_6-test: # Testing
@ -785,7 +851,7 @@ jobs:
runner_prefix: "${{ 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
@ -833,6 +899,72 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_11-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_11-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_11-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -851,7 +983,7 @@ jobs:
runner_prefix: "${{ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda13_0-test: # Testing
@ -924,7 +1056,7 @@ jobs:
needs:
- manywheel-py3_11-rocm6_3-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -1035,7 +1167,7 @@ jobs:
needs:
- manywheel-py3_11-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -1311,7 +1443,7 @@ jobs:
runner_prefix: "${{ 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: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_6-test: # Testing
@ -1377,7 +1509,7 @@ jobs:
runner_prefix: "${{ 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
@ -1425,6 +1557,72 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_12-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_12-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -1443,7 +1641,7 @@ jobs:
runner_prefix: "${{ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda13_0-test: # Testing
@ -1516,7 +1714,7 @@ jobs:
needs:
- manywheel-py3_12-rocm6_3-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -1627,7 +1825,7 @@ jobs:
needs:
- manywheel-py3_12-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -1903,7 +2101,7 @@ jobs:
runner_prefix: "${{ 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: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_6-test: # Testing
@ -1969,7 +2167,7 @@ jobs:
runner_prefix: "${{ 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
@ -2017,6 +2215,72 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_13-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
build_name: manywheel-py3_13-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13"
build_name: manywheel-py3_13-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -2035,7 +2299,7 @@ jobs:
runner_prefix: "${{ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13-cuda13_0-test: # Testing
@ -2108,7 +2372,7 @@ jobs:
needs:
- manywheel-py3_13-rocm6_3-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -2219,7 +2483,7 @@ jobs:
needs:
- manywheel-py3_13-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -2495,7 +2759,7 @@ jobs:
runner_prefix: "${{ 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: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_6-test: # Testing
@ -2561,7 +2825,7 @@ jobs:
runner_prefix: "${{ 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
@ -2609,6 +2873,72 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_13t-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_13t-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
build_name: manywheel-py3_13t-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_13t-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.13t"
build_name: manywheel-py3_13t-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_13t-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -2627,7 +2957,7 @@ jobs:
runner_prefix: "${{ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_13t-cuda13_0-test: # Testing
@ -2700,7 +3030,7 @@ jobs:
needs:
- manywheel-py3_13t-rocm6_3-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -2811,7 +3141,7 @@ jobs:
needs:
- manywheel-py3_13t-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -3087,7 +3417,7 @@ jobs:
runner_prefix: "${{ 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: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_6-test: # Testing
@ -3153,7 +3483,7 @@ jobs:
runner_prefix: "${{ 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
@ -3201,6 +3531,72 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_14-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
build_name: manywheel-py3_14-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14"
build_name: manywheel-py3_14-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -3219,7 +3615,7 @@ jobs:
runner_prefix: "${{ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14-cuda13_0-test: # Testing
@ -3292,7 +3688,7 @@ jobs:
needs:
- manywheel-py3_14-rocm6_3-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -3403,7 +3799,7 @@ jobs:
needs:
- manywheel-py3_14-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -3679,7 +4075,7 @@ jobs:
runner_prefix: "${{ 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: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_6-test: # Testing
@ -3745,7 +4141,7 @@ jobs:
runner_prefix: "${{ 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
@ -3793,6 +4189,72 @@ jobs:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda12_9-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
needs: get-label-type
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
build_name: manywheel-py3_14t-cuda12_9
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.10.2.21; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.9.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.4.1.4; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.10.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.7.5.82; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.5.10.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu12==0.7.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.27.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu12==3.3.20; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.9.79; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.9.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile-cu12==1.14.1.1; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_9-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- manywheel-py3_14t-cuda12_9-build
- get-label-type
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
build_name: manywheel-py3_14t-cuda12_9
build_environment: linux-binary-manywheel
runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
runs_on: linux.g4dn.4xlarge.nvidia.gpu # 12.8+ builds need sm_70+ runner
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda12_9-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_14t-cuda12_9-test
with:
PYTORCH_ROOT: /pytorch
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: manylinux2_28-builder
DOCKER_IMAGE_TAG_PREFIX: cuda12.9
DESIRED_PYTHON: "3.14t"
build_name: manywheel-py3_14t-cuda12_9
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_14t-cuda13_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -3811,7 +4273,7 @@ jobs:
runner_prefix: "${{ 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==9.12.0.46; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas==13.0.0.19; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft==12.0.0.15; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand==10.4.0.35; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver==12.0.3.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse==12.6.2.49; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparselt-cu13==0.8.0; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu13==2.27.7; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvshmem-cu13==3.3.24; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink==13.0.39; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufile==1.15.0.42; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_14t-cuda13_0-test: # Testing
@ -3884,7 +4346,7 @@ jobs:
needs:
- manywheel-py3_14t-rocm6_3-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
@ -3995,7 +4457,7 @@ jobs:
needs:
- manywheel-py3_14t-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch

View File

@ -10,9 +10,7 @@ on:
branches:
- main
tags:
- 'ciflow/binaries/*'
- 'ciflow/binaries_wheel/*'
- 'ciflow/rocm/*'
- 'ciflow/rocm-mi300/*'
workflow_dispatch:
permissions:
@ -69,7 +67,7 @@ jobs:
needs:
- manywheel-py3_9-rocm6_4-build
- get-label-type
runs-on: linux.rocm.gpu.mi250
runs-on: linux.rocm.gpu.gfx942.1
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch

View File

@ -46,7 +46,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -60,13 +60,18 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -81,9 +86,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 +56,18 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -77,9 +82,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -95,6 +104,8 @@ jobs:
"${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 +116,33 @@ 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 +201,18 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -187,9 +227,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -205,6 +249,8 @@ jobs:
"${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 +261,33 @@ 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 +346,18 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -297,9 +372,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -315,6 +394,8 @@ jobs:
"${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 +406,33 @@ 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 +491,18 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -407,9 +517,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -425,6 +539,8 @@ jobs:
"${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 +551,33 @@ 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 +636,18 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -517,9 +662,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -535,6 +684,8 @@ jobs:
"${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 +696,33 @@ 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 +781,18 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -627,9 +807,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -645,6 +829,8 @@ jobs:
"${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 +841,33 @@ 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 +926,18 @@ 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" >> "${GITHUB_PATH}"
if [ -d "/Applications/Xcode_14.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_14.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
elif [ -d "/Applications/Xcode_13.3.1.app" ]; then
echo "DEVELOPER_DIR=/Applications/Xcode_13.3.1.app/Contents/Developer" >> "${GITHUB_ENV}"
fi
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
@ -737,9 +952,13 @@ jobs:
working-directory: pytorch
- name: Populate binary env
run: |
# shellcheck disable=SC1091
source "${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 "${BINARY_ENV_FILE:-/Users/distiller/project/env}"
@ -755,6 +974,8 @@ jobs:
"${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 +986,33 @@ 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

@ -64,7 +64,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Populate binary env
shell: cmd
@ -141,7 +141,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Populate binary env
shell: cmd
@ -201,7 +201,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cpu-shared-with-deps-debug
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

View File

@ -64,7 +64,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Populate binary env
shell: cmd
@ -141,7 +141,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Populate binary env
shell: cmd
@ -201,7 +201,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cpu-shared-with-deps-release
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

View File

@ -51,7 +51,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -166,7 +166,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash

View File

@ -58,7 +58,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -173,7 +173,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
@ -283,7 +283,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cpu-shared-with-deps-debug
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -306,7 +306,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -422,7 +422,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
@ -533,7 +533,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cuda12_6-shared-with-deps-debug
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -556,7 +556,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -672,7 +672,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
@ -783,11 +783,261 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cuda12_8-shared-with-deps-debug
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
libtorch-cuda12_9-shared-with-deps-debug-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
LIBTORCH_CONFIG: debug
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
# runner.temp variable, which we need.
- name: Populate binary env
shell: bash
run: |
echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
- name: Display EC2 information
shell: bash
run: |
set -euo pipefail
function get_ec2_metadata() {
# Pulled from instance metadata endpoint for EC2
# see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html
category=$1
curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}"
}
echo "ami-id: $(get_ec2_metadata ami-id)"
echo "instance-id: $(get_ec2_metadata instance-id)"
echo "instance-type: $(get_ec2_metadata instance-type)"
echo "system info $(uname -a)"
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
uses: pytorch/test-infra/.github/actions/setup-ssh@main
continue-on-error: true
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
- name: Enable git long paths and symlinks on Windows and disable fsmonitor daemon
shell: bash
run: |
git config --global core.longpaths true
git config --global core.symlinks true
# https://git-scm.com/docs/git-fsmonitor--daemon. The daemon could lock
# the directory on Windows and prevent GHA from checking out as reported
# in https://github.com/actions/checkout/issues/1018
git config --global core.fsmonitor false
# Needed for binary builds, see: https://github.com/pytorch/pytorch/issues/73339#issuecomment-1058981560
- name: Enable long paths on Windows
shell: powershell
run: |
Set-ItemProperty -Path "HKLM:\\SYSTEM\CurrentControlSet\Control\FileSystem" -Name "LongPathsEnabled" -Value 1
# Since it's just a defensive command, the workflow should continue even the command fails. This step can be
# removed once Windows Defender is removed from the AMI
- name: Disables Windows Defender scheduled and real-time scanning for files in directories used by PyTorch
continue-on-error: true
shell: powershell
run: |
Add-MpPreference -ExclusionPath $(Get-Location).tostring(),$Env:TEMP -ErrorAction Ignore
# Let's both exclude the path and disable Windows Defender completely just to be sure
# that it doesn't interfere
Set-MpPreference -DisableRealtimeMonitoring $True -ErrorAction Ignore
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
show-progress: false
- name: Clean PyTorch checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: pytorch
- name: Populate binary env
shell: bash
run: |
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
shell: bash
run: |
"${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
- uses: actions/upload-artifact@v4.4.0
if: always()
with:
name: libtorch-cuda12_9-shared-with-deps-debug
retention-days: 14
if-no-files-found: error
path: "${{ env.PYTORCH_FINAL_PACKAGE_DIR }}"
- name: Wait until all sessions have drained
shell: powershell
working-directory: pytorch
if: always()
timeout-minutes: 120
run: |
.github\scripts\wait_for_ssh_to_drain.ps1
- name: Kill active ssh sessions if still around (Useful if workflow was cancelled)
shell: powershell
working-directory: pytorch
if: always()
run: |
.github\scripts\kill_active_ssh_sessions.ps1
libtorch-cuda12_9-shared-with-deps-debug-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- libtorch-cuda12_9-shared-with-deps-debug-build
- get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
LIBTORCH_CONFIG: debug
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
run: |
set -euo pipefail
function get_ec2_metadata() {
# Pulled from instance metadata endpoint for EC2
# see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html
category=$1
curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}"
}
echo "ami-id: $(get_ec2_metadata ami-id)"
echo "instance-id: $(get_ec2_metadata instance-id)"
echo "instance-type: $(get_ec2_metadata instance-type)"
echo "system info $(uname -a)"
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
uses: pytorch/test-infra/.github/actions/setup-ssh@main
continue-on-error: true
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
- name: Enable git long paths and symlinks on Windows and disable fsmonitor daemon
shell: bash
run: |
git config --global core.longpaths true
git config --global core.symlinks true
# https://git-scm.com/docs/git-fsmonitor--daemon. The daemon could lock
# the directory on Windows and prevent GHA from checking out as reported
# in https://github.com/actions/checkout/issues/1018
git config --global core.fsmonitor false
# Needed for binary builds, see: https://github.com/pytorch/pytorch/issues/73339#issuecomment-1058981560
- name: Enable long paths on Windows
shell: powershell
run: |
Set-ItemProperty -Path "HKLM:\\SYSTEM\CurrentControlSet\Control\FileSystem" -Name "LongPathsEnabled" -Value 1
# Since it's just a defensive command, the workflow should continue even the command fails. This step can be
# removed once Windows Defender is removed from the AMI
- name: Disables Windows Defender scheduled and real-time scanning for files in directories used by PyTorch
continue-on-error: true
shell: powershell
run: |
Add-MpPreference -ExclusionPath $(Get-Location).tostring(),$Env:TEMP -ErrorAction Ignore
# Let's both exclude the path and disable Windows Defender completely just to be sure
# that it doesn't interfere
Set-MpPreference -DisableRealtimeMonitoring $True -ErrorAction Ignore
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
show-progress: false
- name: Clean PyTorch checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: pytorch
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
# runner.temp variable, which we need.
- name: Populate binary env
shell: bash
run: |
echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
- uses: actions/download-artifact@v4.1.7
name: Download Build Artifacts
with:
name: libtorch-cuda12_9-shared-with-deps-debug
path: "${{ env.PYTORCH_FINAL_PACKAGE_DIR }}"
- name: Populate binary env
shell: bash
run: |
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Test PyTorch binary
shell: bash
run: |
"${PYTORCH_ROOT}/.circleci/scripts/binary_windows_test.sh"
- name: Wait until all sessions have drained
shell: powershell
working-directory: pytorch
if: always()
timeout-minutes: 120
run: |
.github\scripts\wait_for_ssh_to_drain.ps1
- name: Kill active ssh sessions if still around (Useful if workflow was cancelled)
shell: powershell
working-directory: pytorch
if: always()
run: |
.github\scripts\kill_active_ssh_sessions.ps1
libtorch-cuda12_9-shared-with-deps-debug-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: libtorch-cuda12_9-shared-with-deps-debug-test
with:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
LIBTORCH_CONFIG: debug
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.9"
build_name: libtorch-cuda12_9-shared-with-deps-debug
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
libtorch-cuda13_0-shared-with-deps-debug-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
@ -806,7 +1056,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -922,7 +1172,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
@ -1033,7 +1283,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cuda13_0-shared-with-deps-debug
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

View File

@ -51,7 +51,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -166,7 +166,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash

View File

@ -58,7 +58,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -173,7 +173,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
@ -283,7 +283,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cpu-shared-with-deps-release
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -306,7 +306,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -422,7 +422,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
@ -533,7 +533,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cuda12_6-shared-with-deps-release
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
@ -556,7 +556,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -672,7 +672,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
@ -783,11 +783,261 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cuda12_8-shared-with-deps-release
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
libtorch-cuda12_9-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
# runner.temp variable, which we need.
- name: Populate binary env
shell: bash
run: |
echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
- name: Display EC2 information
shell: bash
run: |
set -euo pipefail
function get_ec2_metadata() {
# Pulled from instance metadata endpoint for EC2
# see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html
category=$1
curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}"
}
echo "ami-id: $(get_ec2_metadata ami-id)"
echo "instance-id: $(get_ec2_metadata instance-id)"
echo "instance-type: $(get_ec2_metadata instance-type)"
echo "system info $(uname -a)"
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
uses: pytorch/test-infra/.github/actions/setup-ssh@main
continue-on-error: true
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
- name: Enable git long paths and symlinks on Windows and disable fsmonitor daemon
shell: bash
run: |
git config --global core.longpaths true
git config --global core.symlinks true
# https://git-scm.com/docs/git-fsmonitor--daemon. The daemon could lock
# the directory on Windows and prevent GHA from checking out as reported
# in https://github.com/actions/checkout/issues/1018
git config --global core.fsmonitor false
# Needed for binary builds, see: https://github.com/pytorch/pytorch/issues/73339#issuecomment-1058981560
- name: Enable long paths on Windows
shell: powershell
run: |
Set-ItemProperty -Path "HKLM:\\SYSTEM\CurrentControlSet\Control\FileSystem" -Name "LongPathsEnabled" -Value 1
# Since it's just a defensive command, the workflow should continue even the command fails. This step can be
# removed once Windows Defender is removed from the AMI
- name: Disables Windows Defender scheduled and real-time scanning for files in directories used by PyTorch
continue-on-error: true
shell: powershell
run: |
Add-MpPreference -ExclusionPath $(Get-Location).tostring(),$Env:TEMP -ErrorAction Ignore
# Let's both exclude the path and disable Windows Defender completely just to be sure
# that it doesn't interfere
Set-MpPreference -DisableRealtimeMonitoring $True -ErrorAction Ignore
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
show-progress: false
- name: Clean PyTorch checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: pytorch
- name: Populate binary env
shell: bash
run: |
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Build PyTorch binary
shell: bash
run: |
"${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
- uses: actions/upload-artifact@v4.4.0
if: always()
with:
name: libtorch-cuda12_9-shared-with-deps-release
retention-days: 14
if-no-files-found: error
path: "${{ env.PYTORCH_FINAL_PACKAGE_DIR }}"
- name: Wait until all sessions have drained
shell: powershell
working-directory: pytorch
if: always()
timeout-minutes: 120
run: |
.github\scripts\wait_for_ssh_to_drain.ps1
- name: Kill active ssh sessions if still around (Useful if workflow was cancelled)
shell: powershell
working-directory: pytorch
if: always()
run: |
.github\scripts\kill_active_ssh_sessions.ps1
libtorch-cuda12_9-shared-with-deps-release-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs:
- libtorch-cuda12_9-shared-with-deps-release-build
- get-label-type
runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
timeout-minutes: 360
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
run: |
set -euo pipefail
function get_ec2_metadata() {
# Pulled from instance metadata endpoint for EC2
# see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html
category=$1
curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}"
}
echo "ami-id: $(get_ec2_metadata ami-id)"
echo "instance-id: $(get_ec2_metadata instance-id)"
echo "instance-type: $(get_ec2_metadata instance-type)"
echo "system info $(uname -a)"
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
uses: pytorch/test-infra/.github/actions/setup-ssh@main
continue-on-error: true
with:
github-secret: ${{ secrets.GITHUB_TOKEN }}
- name: Enable git long paths and symlinks on Windows and disable fsmonitor daemon
shell: bash
run: |
git config --global core.longpaths true
git config --global core.symlinks true
# https://git-scm.com/docs/git-fsmonitor--daemon. The daemon could lock
# the directory on Windows and prevent GHA from checking out as reported
# in https://github.com/actions/checkout/issues/1018
git config --global core.fsmonitor false
# Needed for binary builds, see: https://github.com/pytorch/pytorch/issues/73339#issuecomment-1058981560
- name: Enable long paths on Windows
shell: powershell
run: |
Set-ItemProperty -Path "HKLM:\\SYSTEM\CurrentControlSet\Control\FileSystem" -Name "LongPathsEnabled" -Value 1
# Since it's just a defensive command, the workflow should continue even the command fails. This step can be
# removed once Windows Defender is removed from the AMI
- name: Disables Windows Defender scheduled and real-time scanning for files in directories used by PyTorch
continue-on-error: true
shell: powershell
run: |
Add-MpPreference -ExclusionPath $(Get-Location).tostring(),$Env:TEMP -ErrorAction Ignore
# Let's both exclude the path and disable Windows Defender completely just to be sure
# that it doesn't interfere
Set-MpPreference -DisableRealtimeMonitoring $True -ErrorAction Ignore
- name: Checkout PyTorch
uses: actions/checkout@v4
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
show-progress: false
- name: Clean PyTorch checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: pytorch
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
# runner.temp variable, which we need.
- name: Populate binary env
shell: bash
run: |
echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
- uses: actions/download-artifact@v4.1.7
name: Download Build Artifacts
with:
name: libtorch-cuda12_9-shared-with-deps-release
path: "${{ env.PYTORCH_FINAL_PACKAGE_DIR }}"
- name: Populate binary env
shell: bash
run: |
"${PYTORCH_ROOT}/.circleci/scripts/binary_populate_env.sh"
- name: Test PyTorch binary
shell: bash
run: |
"${PYTORCH_ROOT}/.circleci/scripts/binary_windows_test.sh"
- name: Wait until all sessions have drained
shell: powershell
working-directory: pytorch
if: always()
timeout-minutes: 120
run: |
.github\scripts\wait_for_ssh_to_drain.ps1
- name: Kill active ssh sessions if still around (Useful if workflow was cancelled)
shell: powershell
working-directory: pytorch
if: always()
run: |
.github\scripts\kill_active_ssh_sessions.ps1
libtorch-cuda12_9-shared-with-deps-release-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: libtorch-cuda12_9-shared-with-deps-release-test
with:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
PACKAGE_TYPE: libtorch
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu129
GPU_ARCH_VERSION: "12.9"
GPU_ARCH_TYPE: cuda
LIBTORCH_CONFIG: release
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.9"
build_name: libtorch-cuda12_9-shared-with-deps-release
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
uses: ./.github/workflows/_binary-upload.yml
libtorch-cuda13_0-shared-with-deps-release-build:
if: ${{ github.repository_owner == 'pytorch' }}
needs: get-label-type
@ -806,7 +1056,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
# NOTE: These environment variables are put here so that they can be applied on every job equally
# They are also here because setting them at a workflow level doesn't give us access to the
@ -922,7 +1172,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
steps:
- name: Display EC2 information
shell: bash
@ -1033,7 +1283,7 @@ jobs:
LIBTORCH_VARIANT: shared-with-deps
# This is a dummy value for libtorch to work correctly with our batch scripts
# without this value pip does not get installed for some reason
DESIRED_PYTHON: "3.10"
DESIRED_PYTHON: "3.9"
build_name: libtorch-cuda13_0-shared-with-deps-release
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

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@ -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

@ -75,7 +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: [
@ -101,7 +101,7 @@ 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
docker-image: ${{ needs.inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.inductor-build.outputs.test-matrix }}
@ -118,7 +118,7 @@ jobs:
needs: inductor-build
if: github.event_name == 'workflow_dispatch'
with:
build-environment: linux-jammy-py3.10-gcc11-build
build-environment: linux-jammy-py3.9-gcc11-build
dashboard-tag: training-${{ inputs.training }}-inference-${{ inputs.inference }}-default-${{ inputs.default }}-dynamic-${{ inputs.dynamic }}-cppwrapper-${{ inputs.cppwrapper }}-aotinductor-${{ inputs.aotinductor }}
docker-image: ${{ needs.inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.inductor-build.outputs.test-matrix }}

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

@ -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

@ -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

@ -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

@ -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: [
@ -255,7 +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

View File

@ -2,9 +2,6 @@ name: vllm-test
on:
push:
branches:
- main
- release/*
tags:
- ciflow/vllm/*
workflow_dispatch:
@ -48,18 +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

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/**',
@ -1568,6 +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

@ -1,15 +0,0 @@
# Testing
Use our test class and test runner:
```
from torch.testing._internal.common_utils import run_tests, TestCase
class TestFeature(TestCase):
...
if __name__ == "__main__":
run_tests()
```
To test Tensor equality, use assertEqual.

View File

@ -234,7 +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)
@ -874,28 +873,17 @@ 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 OR USE_ROCM"
"USE_CUDA OR USE_ROCM;NOT MSVC"
OFF)
cmake_dependent_option(
USE_FBGEMM_GENAI
"Whether to build FBGEMM GenAI quantized GEMM kernels.\
Will be disabled if not supported by the platform"
ON
"USE_ROCM"
OFF
"USE_CUDA OR USE_ROCM"
OFF)
IF(USE_FBGEMM_GENAI AND USE_ROCM AND NOT "gfx942" IN_LIST PYTORCH_ROCM_ARCH)
message(WARNING "Unsupported ROCM arch for FBGEMM GenAI, will set USE_FBGEMM_GENAI to OFF")
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)
message(STATUS "Setting USE_FBGEMM_GENAI to ON, doing CUDA build for SM100a")
set(USE_FBGEMM_GENAI ON)
endif()
# CAVEAT: Again, Flash Attention2 will error while building for sm52 while Mem
# Eff Attention won't
cmake_dependent_option(
@ -909,7 +897,7 @@ 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()

View File

@ -88,13 +88,13 @@ source venv/bin/activate # or `& .\venv\Scripts\Activate.ps1` on Windows
* If you want to have no-op incremental rebuilds (which are fast), see [Make no-op build fast](#make-no-op-build-fast) below.
* When installing with `python -m pip install -e . -v --no-build-isolation` (in contrast to `python -m pip install . -v --no-build-isolation`) Python runtime will use
* When installing with `python -m pip install -e .` (in contrast to `python -m pip install .`) Python runtime will use
the current local source-tree when importing `torch` package. (This is done by creating [`.egg-link`](https://wiki.python.org/moin/PythonPackagingTerminology#egg-link) file in `site-packages` folder)
This way you do not need to repeatedly install after modifying Python files (`.py`).
However, you would need to reinstall if you modify Python interface (`.pyi`, `.pyi.in`) or non-Python files (`.cpp`, `.cc`, `.cu`, `.h`, ...).
One way to avoid running `python -m pip install -e . -v --no-build-isolation` every time one makes a change to C++/CUDA/ObjectiveC files on Linux/Mac,
One way to avoid running `python -m pip install -e .` every time one makes a change to C++/CUDA/ObjectiveC files on Linux/Mac,
is to create a symbolic link from `build` folder to `torch/lib`, for example, by issuing following:
```bash
pushd torch/lib; sh -c "ln -sf ../../build/lib/libtorch_cpu.* ."; popd
@ -116,7 +116,7 @@ source venv/bin/activate # or `& .\venv\Scripts\Activate.ps1` on Windows
Next run `python setup.py clean`. After that, you can install in editable mode again.
* If you run into errors when running `python -m pip install -e . -v --no-build-isolation`, here are some debugging steps:
* If you run into errors when running `python -m pip install -e .`, here are some debugging steps:
1. Run `printf '#include <stdio.h>\nint main() { printf("Hello World");}'|clang -x c -; ./a.out` to make sure
your CMake works and can compile this simple Hello World program without errors.
2. Nuke your `build` directory. The `setup.py` script compiles binaries into the `build` folder and caches many
@ -129,10 +129,10 @@ source venv/bin/activate # or `& .\venv\Scripts\Activate.ps1` on Windows
git clean -xdf
python setup.py clean
git submodule update --init --recursive
python -m pip install --group dev
python -m pip install -r requirements.txt
python -m pip install --no-build-isolation -v -e .
```
4. The main step within `python -m pip install -e . -v --no-build-isolation` is running `make` from the `build` directory. If you want to
4. The main step within `python -m pip install -e .` is running `cmake --build build` from the `build` directory. If you want to
experiment with some environment variables, you can pass them into the command:
```bash
ENV_KEY1=ENV_VAL1[, ENV_KEY2=ENV_VAL2]* CMAKE_FRESH=1 python -m pip install --no-build-isolation -v -e .
@ -259,7 +259,6 @@ dependencies as well as the nightly binaries into the repo directory.
support for PyTorch.
* [tools](tools) - Code generation scripts for the PyTorch library.
See [README](tools/README.md) of this directory for more details.
* [torchgen](torchgen) - contains the logic and tooling for generating PyTorch's low-level C++ and Python bindings from operator definitions, typically specified in native_functions.yaml
* [test](test) - Python unit tests for PyTorch Python frontend.
* [test_torch.py](test/test_torch.py) - Basic tests for PyTorch
functionality.
@ -295,7 +294,7 @@ The following packages should be installed with `pip`:
- `pytest` - recommended to run tests more selectively
Running
```
pip install --group dev
pip install -r requirements.txt
```
will install these dependencies for you.
@ -646,9 +645,9 @@ can be selected interactively with your mouse to zoom in on a particular part of
the program execution timeline. The `--native` command-line option tells
`py-spy` to record stack frame entries for PyTorch C++ code. To get line numbers
for C++ code it may be necessary to compile PyTorch in debug mode by prepending
your `python -m pip install -e . -v --no-build-isolation` call to compile
PyTorch with `DEBUG=1`. Depending on your operating system it may also be
necessary to run `py-spy` with root privileges.
your `python -m pip install -e .` call to compile PyTorch with `DEBUG=1`.
Depending on your operating system it may also be necessary to run `py-spy` with
root privileges.
`py-spy` can also work in an `htop`-like "live profiling" mode and can be
tweaked to adjust the stack sampling rate, see the `py-spy` readme for more
@ -656,10 +655,10 @@ details.
## Managing multiple build trees
One downside to using `python -m pip install -e . -v --no-build-isolation` is
that your development version of PyTorch will be installed globally on your
account (e.g., if you run `import torch` anywhere else, the development version
will be used).
One downside to using `python -m pip install -e .` is that your development
version of PyTorch will be installed globally on your account (e.g., if
you run `import torch` anywhere else, the development version will be
used).
If you want to manage multiple builds of PyTorch, you can make use of
[venv environments](https://docs.python.org/3/library/venv.html) to maintain
@ -720,7 +719,7 @@ options.
### Code completion and IDE support
When using `python -m pip install -e . -v --no-build-isolation`, PyTorch will generate
When using `python -m pip install -e .`, PyTorch will generate
a `compile_commands.json` file that can be used by many editors
to provide command completion and error highlighting for PyTorch's
C++ code. You need to `pip install ninja` to generate accurate

View File

@ -243,7 +243,7 @@ git submodule update --init --recursive
```bash
# Run this command from the PyTorch directory after cloning the source code using the “Get the PyTorch Source“ section above
pip install --group dev
pip install -r requirements.txt
```
**On Linux**
@ -394,7 +394,7 @@ On macOS
```bash
export CMAKE_PREFIX_PATH="${CONDA_PREFIX:-'$(dirname $(which conda))/../'}:${CMAKE_PREFIX_PATH}"
MACOSX_DEPLOYMENT_TARGET=11.0 CMAKE_ONLY=1 python setup.py build
MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ CMAKE_ONLY=1 python setup.py build
ccmake build # or cmake-gui build
```

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

@ -252,88 +252,47 @@ if(USE_MEM_EFF_ATTENTION)
list(APPEND ATen_ATTENTION_KERNEL_SRCS ${mem_eff_attention_cuda_kernels_cu})
endif()
IF(USE_FBGEMM_GENAI AND USE_ROCM AND NOT "gfx942" IN_LIST PYTORCH_ROCM_ARCH)
message(WARNING "Unsupported ROCM arch for FBGEMM GenAI, will set USE_FBGEMM_GENAI to OFF")
set(USE_FBGEMM_GENAI off)
endif()
# FBGEMM GenAI
IF(USE_FBGEMM_GENAI)
set(FBGEMM_THIRD_PARTY ${PROJECT_SOURCE_DIR}/third_party/fbgemm/external/)
set(FBGEMM_GENAI_SRCS ${PROJECT_SOURCE_DIR}/third_party/fbgemm/fbgemm_gpu/experimental/gen_ai/src/quantize)
if(USE_CUDA)
# To avoid increasing the build time/binary size unnecessarily, use an allow-list of kernels to build.
# If you want to integrate a kernel from FBGEMM into torch, you have to add it here.
set(FBGEMM_CUTLASS_KERNELS_REGEX ".*mx8mx8bf16_grouped.*")
file(GLOB_RECURSE fbgemm_genai_native_cuda_cu
"${FBGEMM_GENAI_SRCS}/cutlass_extensions/*.cu"
"${FBGEMM_GENAI_SRCS}/cutlass_extensions/**/*.cu")
list(FILTER fbgemm_genai_native_cuda_cu INCLUDE REGEX ${FBGEMM_CUTLASS_KERNELS_REGEX})
set(FBGEMM_GENAI_DIR ${PROJECT_SOURCE_DIR}/third_party/fbgemm/fbgemm_gpu/experimental/gen_ai/src/quantize)
# 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()
if(USE_ROCM)
# Only include the kernels we want to build to avoid increasing binary size.
file(GLOB_RECURSE fbgemm_genai_native_rocm_hip
"${FBGEMM_GENAI_DIR}/ck_extensions/fp8_rowwise_grouped/kernels/fp8_rowwise_grouped*.hip"
"${FBGEMM_GENAI_DIR}/ck_extensions/fp8_rowwise_grouped/fp8_rowwise_grouped_gemm.hip")
set_source_files_properties(${fbgemm_genai_native_rocm_hip} PROPERTIES HIP_SOURCE_PROPERTY_FORMAT 1)
file(GLOB_RECURSE fbgemm_genai_native_cuda_cpp
"${FBGEMM_GENAI_SRCS}/common/*.cpp"
)
# Combine all source files into a single list
list(APPEND fbgemm_genai_all_sources
${fbgemm_genai_native_cuda_cu}
${fbgemm_genai_native_cuda_cpp}
)
# Now, create the library and provide the sources at the same time
add_library(fbgemm_genai OBJECT ${fbgemm_genai_all_sources})
# Add additional HIPCC compiler flags for performance
set(FBGEMM_GENAI_EXTRA_HIPCC_FLAGS
-mllvm
-amdgpu-coerce-illegal-types=1
-mllvm
-enable-post-misched=0
-mllvm
-greedy-reverse-local-assignment=1
-fhip-new-launch-api)
hip_add_library(
fbgemm_genai STATIC
${fbgemm_genai_native_rocm_hip}
HIPCC_OPTIONS ${HIP_HCC_FLAGS} ${FBGEMM_GENAI_EXTRA_HIPCC_FLAGS})
set_target_properties(fbgemm_genai PROPERTIES POSITION_INDEPENDENT_CODE ON)
set(fbgemm_genai_mx8mx8bf16_grouped
"${FBGEMM_GENAI_SRCS}/cutlass_extensions/mx8mx8bf16_grouped/"
)
target_compile_definitions(fbgemm_genai PRIVATE FBGEMM_GENAI_NO_EXTENDED_SHAPES)
target_include_directories(fbgemm_genai PUBLIC
${FBGEMM_THIRD_PARTY}/cutlass/include
${FBGEMM_THIRD_PARTY}/cutlass/tools/util/include
${fbgemm_genai_mx8mx8bf16_grouped}
${FBGEMM_GENAI_SRCS}/common/include/ # includes fbgemm_gpu/quantize/utils.h, fbgemm_gpu/quantize/tuning_cache.hpp
${FBGEMM_GENAI_SRCS}/include/ # includes fbgemm_gpu/torch_ops.h
# FBGEMM version of Composable Kernel is used due to some customizations
${FBGEMM_THIRD_PARTY}/composable_kernel/include
${FBGEMM_THIRD_PARTY}/composable_kernel/library/include
${FBGEMM_GENAI_DIR}/include/
${FBGEMM_GENAI_DIR}/common/include/
)
else()
if(USE_ROCM)
# Only include the kernels we want to build to avoid increasing binary size.
file(GLOB_RECURSE fbgemm_genai_native_rocm_hip
"${FBGEMM_GENAI_SRCS}/ck_extensions/fp8_rowwise_grouped/kernels/fp8_rowwise_grouped*.hip"
"${FBGEMM_GENAI_SRCS}/ck_extensions/fp8_rowwise_grouped/fp8_rowwise_grouped_gemm.hip")
set_source_files_properties(${fbgemm_genai_native_rocm_hip} PROPERTIES HIP_SOURCE_PROPERTY_FORMAT 1)
# Add additional HIPCC compiler flags for performance
set(FBGEMM_GENAI_EXTRA_HIPCC_FLAGS
-mllvm
-amdgpu-coerce-illegal-types=1
-mllvm
-enable-post-misched=0
-mllvm
-greedy-reverse-local-assignment=1
-fhip-new-launch-api)
hip_add_library(
fbgemm_genai STATIC
${fbgemm_genai_native_rocm_hip}
HIPCC_OPTIONS ${HIP_HCC_FLAGS} ${FBGEMM_GENAI_EXTRA_HIPCC_FLAGS})
set_target_properties(fbgemm_genai PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_compile_definitions(fbgemm_genai PRIVATE FBGEMM_GENAI_NO_EXTENDED_SHAPES)
target_include_directories(fbgemm_genai PUBLIC
# FBGEMM version of Composable Kernel is used due to some customizations
${FBGEMM_THIRD_PARTY}/composable_kernel/include
${FBGEMM_THIRD_PARTY}/composable_kernel/library/include
${FBGEMM_THIRD_PARTY}/cutlass/include
${FBGEMM_THIRD_PARTY}/cutlass/tools/util/include
${FBGEMM_GENAI_SRCS}/common/include/ # includes fbgemm_gpu/quantize/utils.h, fbgemm_gpu/quantize/tuning_cache.hpp
${FBGEMM_GENAI_SRCS}/include/ # includes fbgemm_gpu/torch_ops.h
)
endif()
endif()
endif()
@ -676,26 +635,12 @@ if(USE_CUDA AND NOT USE_ROCM)
add_definitions(-DCUTE_SM90_EXTENDED_MMA_SHAPES_ENABLED)
list(APPEND ATen_CUDA_INCLUDE ${CMAKE_CURRENT_SOURCE_DIR}/../../../third_party/cutlass/include)
list(APPEND ATen_CUDA_INCLUDE ${CMAKE_CURRENT_SOURCE_DIR}/../../../third_party/cutlass/tools/util/include)
# Add FBGEMM_GENAI include directories for torch_ops.h
if(USE_FBGEMM_GENAI)
list(APPEND ATen_CUDA_INCLUDE ${CMAKE_CURRENT_SOURCE_DIR}/../../../third_party/fbgemm/fbgemm_gpu/experimental/gen_ai/src/quantize/include)
list(APPEND ATen_CUDA_INCLUDE ${CMAKE_CURRENT_SOURCE_DIR}/../../../third_party/fbgemm/fbgemm_gpu/experimental/gen_ai/src/quantize/common/include)
endif()
if($ENV{ATEN_STATIC_CUDA})
if(CUDA_VERSION VERSION_LESS_EQUAL 12.9)
list(APPEND ATen_CUDA_DEPENDENCY_LIBS
${CUDA_LIBRARIES}
CUDA::cusparse_static
CUDA::cufft_static_nocallback)
else()
list(APPEND ATen_CUDA_DEPENDENCY_LIBS
${CUDA_LIBRARIES}
CUDA::cusparse_static
CUDA::cufft_static)
endif()
list(APPEND ATen_CUDA_DEPENDENCY_LIBS
${CUDA_LIBRARIES}
CUDA::cusparse_static
CUDA::cufft_static_nocallback
)
if(NOT BUILD_LAZY_CUDA_LINALG)
list(APPEND ATen_CUDA_DEPENDENCY_LIBS
CUDA::cusolver_static

View File

@ -308,44 +308,17 @@ void fillVersion<DLManagedTensorVersioned>(
// constructed out of ATen tensor
template <class T>
T* toDLPackImpl(const Tensor& src) {
auto view = src;
// Detect whether there is need to normalize the strides
// Background: gh-83069
//
// However, normalizing strides can come at a high-cost
// to slow down toDLPack conversion 3x, so we
// only normalize if needed.
//
// 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 = 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;
// create a new tensor with possibly normalized strides
// gh-83069
auto shape = src.sizes();
auto strides = src.strides().vec();
for (int i = 0; i < src.dim(); i++) {
if (shape[i] < 2) {
strides[i] = 1;
}
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();
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());
}
auto view = src.as_strided(shape, strides, src.storage_offset());
ATenDLMTensor<T>* atDLMTensor(new ATenDLMTensor<T>);
atDLMTensor->handle = view;
atDLMTensor->tensor.manager_ctx = atDLMTensor;

View File

@ -1,17 +0,0 @@
#include <ATen/DTensorState.h>
namespace at {
namespace {
thread_local bool kDTensorAllowImplicitReplication = false;
}
bool get_dtensor_allow_implicit_replication() {
return kDTensorAllowImplicitReplication;
}
void set_dtensor_allow_implicit_replication(bool enabled) {
kDTensorAllowImplicitReplication = enabled;
}
} // namespace at

View File

@ -1,34 +0,0 @@
#pragma once
#include <c10/macros/Macros.h>
namespace at {
TORCH_API bool get_dtensor_allow_implicit_replication();
TORCH_API void set_dtensor_allow_implicit_replication(bool enabled);
struct DTensorAllowImplicitReplication {
DTensorAllowImplicitReplication()
: prev_dtensor_allow_implicit_replication_(
get_dtensor_allow_implicit_replication()) {
set_dtensor_allow_implicit_replication(true);
}
DTensorAllowImplicitReplication(const DTensorAllowImplicitReplication&) =
delete;
DTensorAllowImplicitReplication& operator=(
const DTensorAllowImplicitReplication&) = delete;
DTensorAllowImplicitReplication(DTensorAllowImplicitReplication&&) = delete;
DTensorAllowImplicitReplication& operator=(
DTensorAllowImplicitReplication&&) = delete;
~DTensorAllowImplicitReplication() {
set_dtensor_allow_implicit_replication(
prev_dtensor_allow_implicit_replication_);
}
private:
bool prev_dtensor_allow_implicit_replication_;
};
} // namespace at

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

@ -8,7 +8,6 @@
#include <ATen/record_function.h>
#include <ATen/SavedTensorHooks.h>
#include <ATen/FunctionalTensorWrapper.h>
#include <ATen/DTensorState.h>
namespace at {
@ -20,7 +19,6 @@ ThreadLocalState::ThreadLocalState()
torch_dispatch_mode_state_(c10::impl::TorchDispatchModeTLS::get_state()), python_dispatcher_state_(c10::impl::PythonDispatcherTLS::get_state()),
python_torch_function_state_(at::impl::PythonTorchFunctionTLS::get_state()),
saved_tensors_default_hooks_state_(at::SavedTensorDefaultHooks::get_tls_state()), functionalization_reapply_views_state_(at::functionalization::impl::getFunctionalizationReapplyViewsTLS()),
dtensor_allow_implicit_replication_(at::get_dtensor_allow_implicit_replication()),
saved_objects_(at::impl::ThreadLocalPythonObjects::get_state()) {
#if !defined(CAFFE2_IS_XPLAT_BUILD) && !defined(C10_MOBILE) && !defined(BUILD_LITE_INTERPRETER)
for(size_t i=0; i<autocast_dtypes_.size(); i++) {
@ -54,8 +52,6 @@ void ThreadLocalState::setThreadLocalState(
c10::impl::PythonDispatcherTLS::set_state(state.python_dispatcher_state_);
at::set_dtensor_allow_implicit_replication(state.dtensor_allow_implicit_replication_);
c10::ThreadLocalDebugInfo::_forceCurrentDebugInfo(state.debug_info_);
c10::impl::_force_tls_local_dispatch_key_set(state.dispatch_key_);

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@ -75,8 +75,6 @@ class TORCH_API ThreadLocalState {
bool functionalization_reapply_views_state_;
bool dtensor_allow_implicit_replication_;
// TLS for arbitrary python objects that is registered via hooks
at::impl::ThreadLocalPythonObjects saved_objects_;

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@ -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;

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@ -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,
@ -1941,11 +1937,11 @@ void scaled_gemm(
computeDesc.setAttribute(CUBLASLT_MATMUL_DESC_TRANSB, _cublasOpFromChar(transb));
cublasLtMatmulDescAttributes_t matmulDescA = CUBLASLT_MATMUL_DESC_A_SCALE_POINTER;
cublasLtMatmulDescAttributes_t matmulDescB = CUBLASLT_MATMUL_DESC_B_SCALE_POINTER;
#if defined(USE_ROCM) && !defined(HIPBLASLT_OUTER_VEC) && defined(HIPBLASLT_VEC_EXT)
// hipblaslt supported row-wise before cublas, and did so their own way (via
// the SCALE_POINTERSs), but then migrated to match how cublas does it (via
// the SCALE_MODEs). Here we check for this early custom mode.
bool use_rowwise = (mat1_scaling_type == ScalingType::RowWise && mat2_scaling_type == ScalingType::RowWise);
#if defined(USE_ROCM) && !defined(HIPBLASLT_OUTER_VEC) && defined(HIPBLASLT_VEC_EXT)
if (use_rowwise) {
matmulDescA = HIPBLASLT_MATMUL_DESC_A_SCALE_POINTER_VEC_EXT;
matmulDescB = HIPBLASLT_MATMUL_DESC_B_SCALE_POINTER_VEC_EXT;
@ -1960,12 +1956,8 @@ void scaled_gemm(
}
#endif
}
#elif (CUDA_VERSION < 12090) && !defined(USE_ROCM)
// hipblaslt supported row-wise before cublas, and did so their own way (via
// the SCALE_POINTERSs), but then migrated to match how cublas does it (via
// the SCALE_MODEs). Here we check for this early custom mode.
bool use_rowwise = (mat1_scaling_type == ScalingType::RowWise && mat2_scaling_type == ScalingType::RowWise);
// rowwise isn't supported using older cublaslt or older hipblaslt
#else
// rowwise isn't supported using cublaslt or older hipblaslt
TORCH_INTERNAL_ASSERT(use_rowwise == false, "rowwise scaled_gemm not supported with blaslt");
#endif // if defined(USE_ROCM) && !defined(HIPBLASLT_OUTER_VEC) && defined(HIPBLASLT_VEC_EXT)
computeDesc.setAttribute(matmulDescA, mat1_scale_ptr);

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@ -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;

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@ -117,8 +117,6 @@ namespace at::cuda {
_(nvrtcGetPTXSize) \
_(nvrtcGetPTX) \
_(cuModuleLoadData) \
_(cuModuleLoad) \
_(cuGetErrorString) \
_(cuModuleGetFunction) \
_(HIPOCCUPANCYMAXACTIVEBLOCKSPERMULTIPROCESSOR) \
_(nvrtcGetErrorString) \

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@ -7,7 +7,6 @@
#include <ATen/functorch/BatchRulesHelper.h>
#include <ATen/functorch/PlumbingHelper.h>
#include <ATen/core/dispatch/Dispatcher.h>
#include <ATen/DTensorState.h>
#include <utility>
@ -45,13 +44,8 @@ static std::tuple<Tensor, std::optional<int64_t>> embedding_batch_rule(
const auto weight_ = reshape_dim_into(*weight_bdim, 0, weight);
auto indices_ = moveBatchDimToFront(indices, indices_bdim);
{
// getStepTensor returns a regular Tensor. If indices_ is a DTensor
// we want to allow this mixed DTensor-Tensor operation.
at::DTensorAllowImplicitReplication guard;
const auto range = getStepTensor(indices, batch_size, num_embeddings);
indices_ = indices_ + range;
}
const auto range = getStepTensor(indices, batch_size, num_embeddings);
indices_ = indices_ + range;
auto result = at::embedding_symint(weight_, indices_, std::move(padding_idx), scale_grad_by_freq, sparse);
return std::make_tuple(std::move(result), 0);
}

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@ -9,7 +9,6 @@
#include <ATen/native/mkldnn/Matmul.h>
#include <ATen/native/mkldnn/Linear.h>
#include <ATen/native/Resize.h>
#include <ATen/native/GroupedMMUtils.h>
#if !defined(__s390x__) && !defined(__powerpc__)
#include <cpuinfo.h>
#endif
@ -333,23 +332,4 @@ _scaled_mm_cpu(const Tensor& mat_a, const Tensor& mat_b,
return _scaled_mm_out_cpu(mat_a, mat_b, scale_a, scale_b, bias, scale_result, out_dtype, use_fast_accum, out);
}
// TODO(vasiliy, future PR): figure out why we need to declare this function, when
// other functions that live in ATen/native/*.cpp without declarations
// or headers work just fine.
Tensor _grouped_mm(const Tensor& mat_a, const Tensor& mat_b,
const std::optional<at::Tensor>& offs,
const std::optional<at::Tensor>& bias,
std::optional<c10::ScalarType> out_dtype);
Tensor _grouped_mm(const Tensor& mat_a, const Tensor& mat_b,
const std::optional<at::Tensor>& offs,
const std::optional<at::Tensor>& bias,
std::optional<c10::ScalarType> out_dtype) {
_grouped_mm_validate_inputs(mat_a, mat_b, offs, bias, out_dtype);
const auto out_dtype_ = _resolve_grouped_mm_out_dtype(mat_a, mat_b, out_dtype);
Tensor out = create_grouped_gemm_output_tensor(mat_a, mat_b, offs, out_dtype_);
_grouped_mm_fallback(mat_a, mat_b, offs, bias, out_dtype, out);
return out;
}
} // namespace at::native

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@ -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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@ -1,167 +0,0 @@
#pragma once
#include <ATen/core/Tensor.h>
#include <ATen/TensorUtils.h>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/CPUFunctions.h>
#include <ATen/Functions.h>
#include <ATen/NativeFunctions.h>
#else
#include <ATen/ops/bmm.h>
#include <ATen/ops/empty.h>
#include <ATen/ops/empty_strided.h>
#include <ATen/ops/mm.h>
#endif
namespace at::native {
inline bool check_valid_strides_and_return_transposed(const Tensor& mat) {
IntArrayRef tensor_strides = mat.strides();
IntArrayRef tensor_sizes = mat.sizes();
int end_dim = mat.dim() - 1;
int alignment = 16 / mat.element_size();
TORCH_CHECK(uint64_t(mat.data_ptr()) % 16 ==0, "expected data_ptr to be aligned to 16 bytes\n");
if ((tensor_strides[end_dim - 1] == 1) && (tensor_strides[end_dim] >= std::max<int64_t>(1, tensor_sizes[end_dim - 1]))) {
TORCH_CHECK(tensor_strides[end_dim] % alignment == 0, "strides should be multiple of 16 bytes");
return true;
} else if ((tensor_strides[end_dim] == 1) && (tensor_strides[end_dim - 1] >= std::max<int64_t>(1, tensor_sizes[end_dim]))) {
TORCH_CHECK(tensor_strides[end_dim - 1] % alignment == 0, "strides should be multiple of 16 bytes");
return false;
} else {
TORCH_CHECK(false, "Invalid strides/sizes, got ", mat.strides(), " for strides and ", mat.sizes(), " for sizes");
}
}
inline at::Tensor create_grouped_gemm_output_tensor(const Tensor& mat_a,
const Tensor& mat_b,
const std::optional<at::Tensor>& offs,
c10::ScalarType out_dtype
) {
c10::SmallVector<int64_t, 3> out_size;
const bool a_is_2d = mat_a.dim() == 2;
const bool b_is_2d = mat_b.dim() == 2;
if (a_is_2d) {
if (b_is_2d) {
out_size = {offs->size(0), mat_a.size(0), mat_b.size(1)};
} else {
TORCH_CHECK(offs->size(0) == mat_b.size(0), "matrix batch sizes have to match");
out_size = {mat_a.size(0), mat_b.size(-1)};
}
} else {
if (b_is_2d) {
// this case is not actually encountered for MoE gemms
TORCH_CHECK(offs->size(0) == mat_a.size(0), "matrix batch sizes have to match");
out_size = {mat_a.size(1), mat_b.size(1)};
} else { // regular bmm
TORCH_CHECK(mat_a.size(0) == mat_b.size(0), "batched dimension has to match");
out_size = {mat_a.size(0), mat_a.size(1), mat_b.size(-1)};
}
}
#ifndef USE_ROCM
// For TMA transfers, strides of output tensor have to be either
// 1, or aligned to 16 bytes.
const auto last_dim = out_size.size() - 1;
const auto alignment = 16 / c10::elementSize(out_dtype);
const int64_t size_padded = (out_size[last_dim] + alignment - 1) / alignment * alignment;
std::vector<int64_t> out_stride;
if (a_is_2d != b_is_2d) {
out_stride = {size_padded, 1};
} else {
out_stride = {out_size[1] * size_padded, size_padded, 1};
}
return at::empty_strided(out_size, out_stride, mat_a.options().dtype(out_dtype));
#else
return at::empty(out_size, mat_a.options().dtype(out_dtype));
#endif
}
inline void _grouped_mm_validate_inputs(const Tensor& mat_a, const Tensor& mat_b,
const std::optional<at::Tensor>& offs,
const std::optional<at::Tensor>& bias,
std::optional<c10::ScalarType> out_dtype) {
TORCH_CHECK((mat_a.dtype() == at::kBFloat16) || (mat_a.dtype() == at::kFloat) || (mat_a.dtype() == at::kHalf), "Expected mat_a to be Float32, BFloat16 or Float16 matrix, got ", mat_a.scalar_type());
TORCH_CHECK((mat_b.dtype() == at::kBFloat16) || (mat_b.dtype() == at::kFloat) || (mat_b.dtype() == at::kHalf), "Expected mat_b to be Float32, BFloat16 or Float16 matrix, got ", mat_b.scalar_type());
TORCH_CHECK(mat_a.dim() == 2 || mat_a.dim() == 3, "mat_a has to be 2 or 3d");
TORCH_CHECK(mat_b.dim() == 2 || mat_b.dim() == 3, "mat_b has to be 2 or 3d");
const bool a_is_2d = mat_a.dim() == 2;
const bool b_is_2d = mat_b.dim() == 2;
if (!a_is_2d || !b_is_2d) {
TORCH_CHECK(mat_a.size(-1) == mat_b.size(-2), "contraction dimension of mat_a and mat_b must match");
}
// check that the strides are valid, the fn will throw an error if not
check_valid_strides_and_return_transposed(mat_a);
check_valid_strides_and_return_transposed(mat_b);
TORCH_CHECK(offs.has_value() == (a_is_2d || b_is_2d), "Have to provide offsets if there is a 2d matrix, or no offset if both matrices are 3d");
if (offs.has_value()) {
TORCH_CHECK(offs->dim() == 1, "offs has to be 1D");
TORCH_CHECK(offs->dtype() == at::kInt, "Offsets have to be int32");
}
TORCH_CHECK(!bias.has_value(), "Bias not supported yet");
}
inline c10::ScalarType _resolve_grouped_mm_out_dtype(const Tensor& mat_a, const Tensor& mat_b,
std::optional<c10::ScalarType> out_dtype) {
const auto out_dtype_ = out_dtype.value_or(mat_a.scalar_type());
// TODO(future PR): enable float32 output dtype for bfloat16 and float16 inputs
TORCH_CHECK(out_dtype_ == mat_a.dtype(), "Grouped gemm output dtype must match `mat_a` dtype");
return out_dtype_;
}
inline void _grouped_mm_fallback(const Tensor& mat_a, const Tensor& mat_b,
const std::optional<at::Tensor>& offs,
const std::optional<at::Tensor>& bias,
std::optional<c10::ScalarType> out_dtype,
Tensor out) {
LOG(INFO) << "fallback path for `torch._grouped_mm`, performance may not be optimal";
const bool a_is_2d = mat_a.dim() == 2;
const bool b_is_2d = mat_b.dim() == 2;
if (a_is_2d && !b_is_2d) {
// 2d x 3d with offsets
int group_start_idx = 0;
auto offs_cpu = offs.value().cpu();
for (int group_idx = 0; group_idx < offs_cpu.size(0); group_idx++) {
int group_end_idx = offs_cpu[group_idx].item<int>();
auto mat_a_slice = mat_a.slice(0, group_start_idx, group_end_idx);
auto out_slice = out.slice(0, group_start_idx, group_end_idx);
at::mm_out(out_slice, mat_a_slice, mat_b[group_idx]);
group_start_idx = group_end_idx;
}
} else if (!a_is_2d && b_is_2d) {
// 3d x 2d with offsets
int group_start_idx = 0;
auto offs_cpu = offs.value().cpu();
for (int group_idx = 0; group_idx < offs_cpu.size(0); group_idx++) {
int group_end_idx = offs_cpu[group_idx].item<int>();
auto mat_b_slice = mat_b.slice(1, group_start_idx, group_end_idx);
auto out_slice = out.slice(1, group_start_idx, group_end_idx);
at::mm_out(out_slice, mat_a[group_idx], mat_b_slice);
group_start_idx = group_end_idx;
}
} else if (a_is_2d && b_is_2d) {
// 2d x 2d with offsets
int group_start_idx = 0;
auto offs_cpu = offs.value().cpu();
for (int group_idx = 0; group_idx < offs_cpu.size(0); group_idx++) {
int group_end_idx = offs_cpu[group_idx].item<int>();
auto mat_a_slice = mat_a.slice(1, group_start_idx, group_end_idx);
auto mat_b_slice = mat_b.slice(0, group_start_idx, group_end_idx);
auto out_slice = out[group_idx];
at::mm_out(out_slice, mat_a_slice, mat_b_slice);
group_start_idx = group_end_idx;
}
} else {
// 3d x 3d without offsets - regular bmm
at::bmm_out(out, mat_a, mat_b);
}
}
} // namespace at::native

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@ -1360,8 +1360,7 @@ Tensor outer(const Tensor& self, const Tensor& vec2) {
#endif
#if !defined(__aarch64__) || AT_MKLDNN_ACL_ENABLED()
// Used by default on x86 platforms and on AArch64+ACL
#if defined(__aarch64__) && AT_MKLDNN_ACL_ENABLED()
static inline int64_t get_mkldnn_matmul_min_dim() {
static auto value = [&] {
const int64_t default_min_dim = [&] {
@ -1396,6 +1395,8 @@ static inline bool apply_mkldnn_matmul_heur(int64_t m, int64_t k, int64_t n) {
return at::globalContext().userEnabledMkldnn() && m > min_dim && k > min_dim && n > min_dim && m * k * n > min_size;
}
#endif
static void addmm_impl_cpu_(
Tensor &result, const Tensor &self, Tensor m1, Tensor m2, const Scalar& beta, const Scalar& alpha) {
TORCH_INTERNAL_ASSERT(self.dim() == 2 && m1.dim() == 2 && m2.dim() == 2);
@ -1771,8 +1772,8 @@ static inline void bmm_out_or_baddbmm_(const Tensor& self_or_result_, const Tens
return (strides[2] == 1 && (sizes[1] == 1 || strides[1] >= sizes[2])) ||
(strides[1] == 1 && (sizes[2] == 1 || strides[2] >= sizes[1]));
};
#if !defined(__aarch64__) || AT_MKLDNN_ACL_ENABLED()
// Always apply mkldnn heuristic on x86 platform, but on ARM only if compiled with ACL
#if defined(__aarch64__) && AT_MKLDNN_ACL_ENABLED()
bool apply_heur = apply_mkldnn_matmul_heur(batch1.sizes()[1], batch1.sizes()[2], batch2.sizes()[2]);
if (apply_heur && use_mkldnn_matmul(batch1, batch2, self_or_result)) {
try {
@ -1784,6 +1785,7 @@ static inline void bmm_out_or_baddbmm_(const Tensor& self_or_result_, const Tens
}
}
#endif
if (contraction_size * res_rows * res_cols < 400) {
if (is_bmm_out) {
AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND2(kBFloat16, kHalf, batch1.scalar_type(), "bmm", [&] {

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@ -47,14 +47,10 @@ TORCH_META_FUNC(nll_loss_forward)
TORCH_CHECK(
target.dim() <= 1,
"0D or 1D target tensor expected, multi-target not supported");
if (self.dim() == 1 && target.dim() == 1) {
TORCH_CHECK_VALUE(
target.size(0) == 1,
"For 1D input, 1D target must have size 1, but got target size: ",
target.size(0));
}
auto no_batch_dim = self.dim() == 1 && target.dim() == 0;
TORCH_CHECK(
self.dim() == 1 || (self.size(0) == target.size(0)),
no_batch_dim || (self.size(0) == target.size(0)),
"size mismatch (got input: ",
self.sizes(),
", target: ",

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@ -624,9 +624,7 @@ std::tuple<Tensor, Tensor, Tensor, Tensor, int64_t> _batch_norm_impl_index(
if (backend == BatchNormBackend::Miopen) {
return std::tuple_cat(
at::miopen_batch_norm(
input.contiguous(input.suggest_memory_format()),
weight.contiguous(),
bias.contiguous(),
input.contiguous(), weight.contiguous(), bias.contiguous(),
running_mean.defined() ? running_mean.contiguous() : running_mean,
running_var.defined() ? running_var.contiguous() : running_var,
training, momentum, eps),

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@ -1,6 +1,5 @@
#define TORCH_ASSERT_ONLY_METHOD_OPERATORS
#include <ATen/core/Tensor.h>
#include <ATen/DTensorState.h>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/Functions.h>
@ -25,13 +24,8 @@ Tensor one_hot(const Tensor &self, int64_t num_classes) {
if (num_classes == -1) {
num_classes = self.max().item().toLong() + 1;
}
{
// If `self` is a DTensor, then allow implicit replication
// of the `index` Tensor.
at::DTensorAllowImplicitReplication guard;
at::Tensor index = at::arange(num_classes, self.options());
return at::eq(self.unsqueeze(-1), index).to(kLong);
}
at::Tensor index = at::arange(num_classes, self.options());
return at::eq(self.unsqueeze(-1), index).to(kLong);
}
auto shape = self.sizes().vec();

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@ -1640,9 +1640,6 @@ Tensor zeros_symint(
std::optional<Layout> layout,
std::optional<Device> device,
std::optional<bool> pin_memory) {
for (const auto& dim_size : size) {
TORCH_CHECK(dim_size >= 0, "zeros: Dimension size must be non-negative.");
}
Layout layout_ = layout.value_or(Layout::Strided);
if (at::sparse_csr::is_sparse_compressed(layout_)) {
return zeros_sparse_compressed_symint(

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@ -18,7 +18,6 @@
#include <ATen/ops/is_set_to_native.h>
#include <ATen/ops/size_native.h>
#include <ATen/ops/stride_native.h>
#include <ATen/ops/sym_is_contiguous_native.h>
#include <ATen/ops/sym_numel_native.h>
#include <ATen/ops/sym_size_native.h>
#include <ATen/ops/sym_storage_offset_native.h>
@ -58,12 +57,6 @@ c10::SymInt sym_size(const Tensor& self, int64_t dim) {
return self.sym_size(dim);
}
c10::SymBool sym_is_contiguous(
const Tensor& self,
c10::MemoryFormat memory_format) {
return self.sym_is_contiguous(memory_format);
}
c10::SymInt sym_stride(const Tensor& self, int64_t dim) {
return self.sym_stride(dim);
}

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@ -36,7 +36,7 @@ void hardsigmoid_kernel(TensorIteratorBase& iter) {
[zero, one_sixth, three, six] GPU_LAMBDA(
scalar_t self_val) -> scalar_t {
opmath_t x = static_cast<opmath_t>(self_val);
return std::min<opmath_t>(std::max<opmath_t>(x + three, zero), six) * one_sixth;
return std::min(std::max(x + three, zero), six) * one_sixth;
});
});
}

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