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Author SHA1 Message Date
0853bf3ac4 Add basic unit test and noop config
Tidy tests:

Adding initial config option

lintrunner

Minor renaming
2025-04-08 10:10:40 -07:00
3834 changed files with 59918 additions and 167472 deletions

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@ -27,7 +27,6 @@ if [ "$DESIRED_CUDA" = "cpu" ]; then
USE_PRIORITIZED_TEXT_FOR_LD=1 python /pytorch/.ci/aarch64_linux/aarch64_wheel_ci_build.py --enable-mkldnn
else
echo "BASE_CUDA_VERSION is set to: $DESIRED_CUDA"
export USE_SYSTEM_NCCL=1
#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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@ -31,47 +31,33 @@ def build_ArmComputeLibrary() -> None:
"build=native",
]
acl_install_dir = "/acl"
acl_checkout_dir = os.getenv("ACL_SOURCE_DIR", "ComputeLibrary")
if os.path.isdir(acl_install_dir):
shutil.rmtree(acl_install_dir)
if not os.path.isdir(acl_checkout_dir) or not len(os.listdir(acl_checkout_dir)):
check_call(
[
"git",
"clone",
"https://github.com/ARM-software/ComputeLibrary.git",
"-b",
"v25.02",
"--depth",
"1",
"--shallow-submodules",
]
)
acl_checkout_dir = "ComputeLibrary"
os.makedirs(acl_install_dir)
check_call(
[
"git",
"clone",
"https://github.com/ARM-software/ComputeLibrary.git",
"-b",
"v25.02",
"--depth",
"1",
"--shallow-submodules",
]
)
check_call(
["scons", "Werror=1", f"-j{os.cpu_count()}"] + acl_build_flags,
["scons", "Werror=1", "-j8", f"build_dir=/{acl_install_dir}/build"]
+ acl_build_flags,
cwd=acl_checkout_dir,
)
for d in ["arm_compute", "include", "utils", "support", "src", "build"]:
for d in ["arm_compute", "include", "utils", "support", "src"]:
shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
def replace_tag(filename) -> None:
with open(filename) as f:
lines = f.readlines()
for i, line in enumerate(lines):
if line.startswith("Tag:"):
lines[i] = line.replace("-linux_", "-manylinux_2_28_")
print(f"Updated tag from {line} to {lines[i]}")
break
with open(filename, "w") as f:
f.writelines(lines)
def package_cuda_wheel(wheel_path, desired_cuda) -> None:
def update_wheel(wheel_path, desired_cuda) -> None:
"""
Package the cuda wheel libraries
Update the cuda wheel libraries
"""
folder = os.path.dirname(wheel_path)
wheelname = os.path.basename(wheel_path)
@ -102,19 +88,30 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
"/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",
]
if "128" in desired_cuda:
if enable_cuda:
libs_to_copy += [
"/usr/local/cuda/lib64/libnvrtc-builtins.so.12.8",
"/usr/local/cuda/lib64/libcufile.so.0",
"/usr/local/cuda/lib64/libcufile_rdma.so.1",
"/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",
]
if "126" in desired_cuda:
libs_to_copy += [
"/usr/local/cuda/lib64/libnvrtc-builtins.so.12.6",
"/usr/local/cuda/lib64/libcufile.so.0",
"/usr/local/cuda/lib64/libcufile_rdma.so.1",
]
elif "128" in desired_cuda:
libs_to_copy += [
"/usr/local/cuda/lib64/libnvrtc-builtins.so.12.8",
"/usr/local/cuda/lib64/libcufile.so.0",
"/usr/local/cuda/lib64/libcufile_rdma.so.1",
]
else:
libs_to_copy += [
"/opt/OpenBLAS/lib/libopenblas.so.0",
]
# Copy libraries to unzipped_folder/a/lib
for lib_path in libs_to_copy:
lib_name = os.path.basename(lib_path)
@ -123,13 +120,6 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
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/"):
if f.is_dir() and f.name.endswith(".dist-info"):
replace_tag(f"{f.path}/WHEEL")
break
os.mkdir(f"{folder}/cuda_wheel")
os.system(f"cd {folder}/tmp/; zip -r {folder}/cuda_wheel/{wheelname} *")
shutil.move(
@ -146,9 +136,6 @@ def complete_wheel(folder: str) -> str:
"""
wheel_name = list_dir(f"/{folder}/dist")[0]
# Please note for cuda we don't run auditwheel since we use custom script to package
# the cuda dependencies to the wheel file using update_wheel() method.
# However we need to make sure filename reflects the correct Manylinux platform.
if "pytorch" in folder and not enable_cuda:
print("Repairing Wheel with AuditWheel")
check_call(["auditwheel", "repair", f"dist/{wheel_name}"], cwd=folder)
@ -160,14 +147,7 @@ def complete_wheel(folder: str) -> str:
f"/{folder}/dist/{repaired_wheel_name}",
)
else:
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}",
)
repaired_wheel_name = wheel_name
print(f"Copying {repaired_wheel_name} to artifacts")
shutil.copy2(
@ -204,10 +184,8 @@ if __name__ == "__main__":
).decode()
print("Building PyTorch wheel")
build_vars = "CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000 "
# MAX_JOB=5 is not required for CPU backend (see commit 465d98b)
if enable_cuda:
build_vars = "MAX_JOBS=5 " + build_vars
build_vars = "MAX_JOBS=5 CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000 "
os.system("cd /pytorch; python setup.py clean")
override_package_version = os.getenv("OVERRIDE_PACKAGE_VERSION")
desired_cuda = os.getenv("DESIRED_CUDA")
@ -254,6 +232,6 @@ if __name__ == "__main__":
print("Updating Cuda Dependency")
filename = os.listdir("/pytorch/dist/")
wheel_path = f"/pytorch/dist/{filename[0]}"
package_cuda_wheel(wheel_path, desired_cuda)
update_wheel(wheel_path, desired_cuda)
pytorch_wheel_name = complete_wheel("/pytorch/")
print(f"Build Complete. Created {pytorch_wheel_name}..")

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@ -10,3 +10,5 @@ example: `py2-cuda9.0-cudnn7-ubuntu16.04`. The Docker images that are
built on Jenkins and are used in triggered builds already have this
environment variable set in their manifest. Also see
`./docker/jenkins/*/Dockerfile` and search for `BUILD_ENVIRONMENT`.
Our Jenkins installation is located at https://ci.pytorch.org/jenkins/.

View File

@ -13,6 +13,10 @@ if [[ "${BUILD_ENVIRONMENT}" == *-android* ]]; then
echo 'Skipping tests'
exit 0
fi
if [[ "${BUILD_ENVIRONMENT}" == *-rocm* ]]; then
# temporary to locate some kernel issues on the CI nodes
export HSAKMT_DEBUG_LEVEL=4
fi
# These additional packages are needed for circleci ROCm builds.
if [[ $BUILD_ENVIRONMENT == *rocm* ]]; then
# Need networkx 2.0 because bellmand_ford was moved in 2.1 . Scikit-image by

View File

@ -34,5 +34,5 @@ See `build.sh` for valid build environments (it's the giant switch).
./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
# Set flags (see build.sh) and build image
sudo bash -c 'TRITON=1 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
sudo bash -c 'PROTOBUF=1 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
```

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@ -1,7 +1,6 @@
ARG CUDA_VERSION=12.4
ARG BASE_TARGET=cuda${CUDA_VERSION}
ARG ROCM_IMAGE=rocm/dev-almalinux-8:6.3-complete
FROM amd64/almalinux:8.10-20250519 as base
FROM amd64/almalinux:8 as base
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
@ -9,10 +8,12 @@ ENV LANGUAGE en_US.UTF-8
ARG DEVTOOLSET_VERSION=11
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
RUN yum -y update
RUN yum -y install epel-release
# install glibc-langpack-en make sure en_US.UTF-8 locale is available
RUN yum -y install glibc-langpack-en
RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel openssl-devel yum-utils autoconf automake make gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
# Just add everything as a safe.directory for git since these will be used in multiple places with git
RUN git config --global --add safe.directory '*'
@ -40,12 +41,11 @@ RUN bash ./install_conda.sh && rm install_conda.sh
# Install CUDA
FROM base as cuda
ARG CUDA_VERSION=12.6
ARG CUDA_VERSION=12.4
RUN rm -rf /usr/local/cuda-*
ADD ./common/install_cuda.sh install_cuda.sh
COPY ./common/install_nccl.sh install_nccl.sh
COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
COPY ./common/install_cusparselt.sh install_cusparselt.sh
ENV CUDA_HOME=/usr/local/cuda-${CUDA_VERSION}
# Preserve CUDA_VERSION for the builds
ENV CUDA_VERSION=${CUDA_VERSION}
@ -56,20 +56,18 @@ FROM cuda as cuda11.8
RUN bash ./install_cuda.sh 11.8
ENV DESIRED_CUDA=11.8
FROM cuda as cuda12.1
RUN bash ./install_cuda.sh 12.1
ENV DESIRED_CUDA=12.1
FROM cuda as cuda12.4
RUN bash ./install_cuda.sh 12.4
ENV DESIRED_CUDA=12.4
FROM cuda as cuda12.6
RUN bash ./install_cuda.sh 12.6
ENV DESIRED_CUDA=12.6
FROM cuda as cuda12.8
RUN bash ./install_cuda.sh 12.8
ENV DESIRED_CUDA=12.8
FROM ${ROCM_IMAGE} as rocm
ENV PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
ENV MKLROOT /opt/intel
# Install MNIST test data
FROM base as mnist
ADD ./common/install_mnist.sh install_mnist.sh
@ -77,8 +75,9 @@ RUN bash ./install_mnist.sh
FROM base as all_cuda
COPY --from=cuda11.8 /usr/local/cuda-11.8 /usr/local/cuda-11.8
COPY --from=cuda12.1 /usr/local/cuda-12.1 /usr/local/cuda-12.1
COPY --from=cuda12.4 /usr/local/cuda-12.4 /usr/local/cuda-12.4
COPY --from=cuda12.6 /usr/local/cuda-12.6 /usr/local/cuda-12.6
COPY --from=cuda12.8 /usr/local/cuda-12.8 /usr/local/cuda-12.8
# Final step
FROM ${BASE_TARGET} as final

View File

@ -1,70 +1,82 @@
#!/usr/bin/env bash
# Script used only in CD pipeline
set -exou pipefail
set -eou pipefail
image="$1"
shift
if [ -z "${image}" ]; then
echo "Usage: $0 IMAGENAME:ARCHTAG"
echo "Usage: $0 IMAGE"
exit 1
fi
# Go from imagename:tag to tag
DOCKER_TAG_PREFIX=$(echo "${image}" | awk -F':' '{print $2}')
DOCKER_IMAGE_NAME="pytorch/${image}"
CUDA_VERSION=""
ROCM_VERSION=""
EXTRA_BUILD_ARGS=""
if [[ "${DOCKER_TAG_PREFIX}" == cuda* ]]; then
# extract cuda version from image name and tag. e.g. manylinux2_28-builder:cuda12.8 returns 12.8
CUDA_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'cuda' '{print $2}')
EXTRA_BUILD_ARGS="--build-arg CUDA_VERSION=${CUDA_VERSION}"
elif [[ "${DOCKER_TAG_PREFIX}" == rocm* ]]; then
# extract rocm version from image name and tag. e.g. manylinux2_28-builder:rocm6.2.4 returns 6.2.4
ROCM_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'rocm' '{print $2}')
EXTRA_BUILD_ARGS="--build-arg ROCM_IMAGE=rocm/dev-almalinux-8:${ROCM_VERSION}-complete"
fi
case ${DOCKER_TAG_PREFIX} in
cpu)
BASE_TARGET=base
;;
cuda*)
BASE_TARGET=cuda${CUDA_VERSION}
;;
rocm*)
BASE_TARGET=rocm
;;
*)
echo "ERROR: Unknown docker tag ${DOCKER_TAG_PREFIX}"
exit 1
;;
esac
# TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
# is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
sudo systemctl daemon-reload
sudo systemctl restart docker
export DOCKER_BUILDKIT=1
TOPDIR=$(git rev-parse --show-toplevel)
tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
docker build \
--target final \
--progress plain \
--build-arg "BASE_TARGET=${BASE_TARGET}" \
--build-arg "DEVTOOLSET_VERSION=11" \
${EXTRA_BUILD_ARGS} \
-t ${tmp_tag} \
$@ \
-f "${TOPDIR}/.ci/docker/almalinux/Dockerfile" \
${TOPDIR}/.ci/docker/
CUDA_VERSION=${CUDA_VERSION:-12.1}
if [ -n "${CUDA_VERSION}" ]; then
case ${CUDA_VERSION} in
cpu)
BASE_TARGET=base
DOCKER_TAG=cpu
;;
all)
BASE_TARGET=all_cuda
DOCKER_TAG=latest
;;
*)
BASE_TARGET=cuda${CUDA_VERSION}
DOCKER_TAG=cuda${CUDA_VERSION}
;;
esac
(
set -x
# TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
# is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
sudo systemctl daemon-reload
sudo systemctl restart docker
docker build \
--target final \
--progress plain \
--build-arg "BASE_TARGET=${BASE_TARGET}" \
--build-arg "CUDA_VERSION=${CUDA_VERSION}" \
--build-arg "DEVTOOLSET_VERSION=11" \
-t ${DOCKER_IMAGE_NAME} \
$@ \
-f "${TOPDIR}/.ci/docker/almalinux/Dockerfile" \
${TOPDIR}/.ci/docker/
)
if [[ "${DOCKER_TAG}" =~ ^cuda* ]]; then
# Test that we're using the right CUDA compiler
docker run --rm "${tmp_tag}" nvcc --version | grep "cuda_${CUDA_VERSION}"
(
set -x
docker run --rm "${DOCKER_IMAGE_NAME}" nvcc --version | grep "cuda_${CUDA_VERSION}"
)
fi
GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
GIT_BRANCH_NAME=${GITHUB_REF##*/}
GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE_NAME}-${GIT_BRANCH_NAME}
DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE_NAME}-${GIT_COMMIT_SHA}
if [[ "${WITH_PUSH:-}" == true ]]; then
(
set -x
docker push "${DOCKER_IMAGE_NAME}"
if [[ -n ${GITHUB_REF} ]]; then
docker tag ${DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_BRANCH_TAG}
docker tag ${DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_SHA_TAG}
docker push "${DOCKER_IMAGE_BRANCH_TAG}"
docker push "${DOCKER_IMAGE_SHA_TAG}"
fi
)
fi

View File

@ -50,21 +50,30 @@ if [[ "$image" == *xla* ]]; then
exit 0
fi
if [[ "$image" == *-jammy* ]]; then
if [[ "$image" == *-focal* ]]; then
UBUNTU_VERSION=20.04
elif [[ "$image" == *-jammy* ]]; then
UBUNTU_VERSION=22.04
elif [[ "$image" == *ubuntu* ]]; then
extract_version_from_image_name ubuntu UBUNTU_VERSION
elif [[ "$image" == *centos* ]]; then
extract_version_from_image_name centos CENTOS_VERSION
fi
if [ -n "${UBUNTU_VERSION}" ]; then
OS="ubuntu"
elif [ -n "${CENTOS_VERSION}" ]; then
OS="centos"
else
echo "Unable to derive operating system base..."
exit 1
fi
DOCKERFILE="${OS}/Dockerfile"
if [[ "$image" == *rocm* ]]; then
# When using ubuntu - 22.04, start from Ubuntu docker image, instead of nvidia/cuda docker image.
if [[ "$image" == *cuda* && "$UBUNTU_VERSION" != "22.04" ]]; then
DOCKERFILE="${OS}-cuda/Dockerfile"
elif [[ "$image" == *rocm* ]]; then
DOCKERFILE="${OS}-rocm/Dockerfile"
elif [[ "$image" == *xpu* ]]; then
DOCKERFILE="${OS}-xpu/Dockerfile"
@ -76,6 +85,9 @@ elif [[ "$image" == *linter* ]]; then
DOCKERFILE="linter/Dockerfile"
fi
# CMake 3.18 is needed to support CUDA17 language variant
CMAKE_VERSION=3.18.5
_UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
_UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
if [[ "$image" == *rocm* ]]; then
@ -83,219 +95,260 @@ if [[ "$image" == *rocm* ]]; then
_UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d
fi
tag=$(echo $image | awk -F':' '{print $2}')
# It's annoying to rename jobs every time you want to rewrite a
# configuration, so we hardcode everything here rather than do it
# from scratch
case "$tag" in
pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc11)
case "$image" in
pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc11)
CUDA_VERSION=12.6.3
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.13-gcc9-inductor-benchmarks)
CUDA_VERSION=12.8.1
pytorch-linux-focal-cuda12.4-cudnn9-py3.13-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.13
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc9)
pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9)
CUDA_VERSION=12.6.3
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6
pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6.3
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6
pytorch-linux-focal-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6.3
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6
pytorch-linux-focal-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
CUDA_VERSION=12.6.3
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.13
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9)
CUDA_VERSION=12.8.1
pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
CUDA_VERSION=11.8.0
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3-clang12-onnx)
pytorch-linux-focal-py3-clang10-onnx)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=12
CLANG_VERSION=10
PROTOBUF=yes
VISION=yes
CONDA_CMAKE=yes
ONNX=yes
;;
pytorch-linux-jammy-py3.9-clang12)
pytorch-linux-focal-py3.9-clang10)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=12
CLANG_VERSION=10
PROTOBUF=yes
VISION=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3.11-clang12)
pytorch-linux-focal-py3.11-clang10)
ANACONDA_PYTHON_VERSION=3.11
CLANG_VERSION=12
CLANG_VERSION=10
PROTOBUF=yes
VISION=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3.9-gcc9)
pytorch-linux-focal-py3.9-gcc9)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=9
PROTOBUF=yes
VISION=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-rocm-n-1-py3)
pytorch-linux-focal-rocm-n-1-py3)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
PROTOBUF=yes
VISION=yes
ROCM_VERSION=6.2.4
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-rocm-n-py3)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
PROTOBUF=yes
VISION=yes
ROCM_VERSION=6.3
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-rocm-n-py3)
ANACONDA_PYTHON_VERSION=3.10
pytorch-linux-jammy-xpu-2024.0-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
VISION=yes
ROCM_VERSION=6.4
XPU_VERSION=0.5
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-xpu-2025.0-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
VISION=yes
XPU_VERSION=2025.0
NINJA_VERSION=1.9.0
TRITON=yes
;;
pytorch-linux-jammy-xpu-2025.1-py3)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
VISION=yes
XPU_VERSION=2025.1
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
VISION=yes
KATEX=yes
CONDA_CMAKE=yes
TRITON=yes
DOCS=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-clang12)
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-clang12)
ANACONDA_PYTHON_VERSION=3.9
CUDA_VERSION=12.8.1
CUDA_VERSION=11.8
CUDNN_VERSION=9
CLANG_VERSION=12
PROTOBUF=yes
VISION=yes
TRITON=yes
;;
pytorch-linux-jammy-py3-clang12-asan)
ANACONDA_PYTHON_VERSION=3.9
CLANG_VERSION=12
PROTOBUF=yes
VISION=yes
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-jammy-py3-clang15-asan)
ANACONDA_PYTHON_VERSION=3.10
CLANG_VERSION=15
CONDA_CMAKE=yes
VISION=yes
;;
pytorch-linux-jammy-py3-clang18-asan)
ANACONDA_PYTHON_VERSION=3.10
CLANG_VERSION=18
CONDA_CMAKE=yes
VISION=yes
;;
pytorch-linux-jammy-py3.9-gcc11)
ANACONDA_PYTHON_VERSION=3.9
GCC_VERSION=11
PROTOBUF=yes
VISION=yes
KATEX=yes
CONDA_CMAKE=yes
TRITON=yes
DOCS=yes
UNINSTALL_DILL=yes
@ -303,12 +356,14 @@ case "$tag" in
pytorch-linux-jammy-py3-clang12-executorch)
ANACONDA_PYTHON_VERSION=3.10
CLANG_VERSION=12
CONDA_CMAKE=yes
EXECUTORCH=yes
;;
pytorch-linux-jammy-py3.12-halide)
CUDA_VERSION=12.6
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
CONDA_CMAKE=yes
HALIDE=yes
TRITON=yes
;;
@ -316,23 +371,28 @@ case "$tag" in
CUDA_VERSION=12.6
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=11
CONDA_CMAKE=yes
TRITON_CPU=yes
;;
pytorch-linux-jammy-linter)
pytorch-linux-focal-linter)
# TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
# We will need to update mypy version eventually, but that's for another day. The task
# would be to upgrade mypy to 1.0.0 with Python 3.11
PYTHON_VERSION=3.9
PIP_CMAKE=yes
;;
pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-linter)
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
PYTHON_VERSION=3.9
CUDA_VERSION=12.8.1
CUDA_VERSION=11.8
PIP_CMAKE=yes
;;
pytorch-linux-jammy-aarch64-py3.10-gcc11)
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
ACL=yes
PROTOBUF=yes
VISION=yes
CONDA_CMAKE=yes
# snadampal: skipping llvm src build install because the current version
# from pytorch/llvm:9.0.1 is x86 specific
SKIP_LLVM_SRC_BUILD_INSTALL=yes
@ -341,7 +401,9 @@ case "$tag" in
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=11
ACL=yes
PROTOBUF=yes
VISION=yes
CONDA_CMAKE=yes
# snadampal: skipping llvm src build install because the current version
# from pytorch/llvm:9.0.1 is x86 specific
SKIP_LLVM_SRC_BUILD_INSTALL=yes
@ -349,6 +411,7 @@ case "$tag" in
;;
*)
# Catch-all for builds that are not hardcoded.
PROTOBUF=yes
VISION=yes
echo "image '$image' did not match an existing build configuration"
if [[ "$image" == *py* ]]; then
@ -364,7 +427,8 @@ case "$tag" in
TRITON=yes
# To ensure that any ROCm config will build using conda cmake
# and thus have LAPACK/MKL enabled
fi
CONDA_CMAKE=yes
fi
if [[ "$image" == *centos7* ]]; then
NINJA_VERSION=1.10.2
fi
@ -380,11 +444,22 @@ case "$tag" in
if [[ "$image" == *glibc* ]]; then
extract_version_from_image_name glibc GLIBC_VERSION
fi
if [[ "$image" == *cmake* ]]; then
extract_version_from_image_name cmake CMAKE_VERSION
fi
;;
esac
tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
#when using cudnn version 8 install it separately from cuda
if [[ "$image" == *cuda* && ${OS} == "ubuntu" ]]; then
IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
if [[ ${CUDNN_VERSION} == 9 ]]; then
IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
fi
fi
no_cache_flag=""
progress_flag=""
# Do not use cache and progress=plain when in CI
@ -398,9 +473,11 @@ docker build \
${no_cache_flag} \
${progress_flag} \
--build-arg "BUILD_ENVIRONMENT=${image}" \
--build-arg "PROTOBUF=${PROTOBUF:-}" \
--build-arg "LLVMDEV=${LLVMDEV:-}" \
--build-arg "VISION=${VISION:-}" \
--build-arg "UBUNTU_VERSION=${UBUNTU_VERSION}" \
--build-arg "CENTOS_VERSION=${CENTOS_VERSION}" \
--build-arg "DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}" \
--build-arg "GLIBC_VERSION=${GLIBC_VERSION}" \
--build-arg "CLANG_VERSION=${CLANG_VERSION}" \
@ -411,6 +488,7 @@ docker build \
--build-arg "CUDNN_VERSION=${CUDNN_VERSION}" \
--build-arg "TENSORRT_VERSION=${TENSORRT_VERSION}" \
--build-arg "GRADLE_VERSION=${GRADLE_VERSION}" \
--build-arg "CMAKE_VERSION=${CMAKE_VERSION:-}" \
--build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
--build-arg "KATEX=${KATEX:-}" \
--build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
@ -418,6 +496,8 @@ docker build \
--build-arg "IMAGE_NAME=${IMAGE_NAME}" \
--build-arg "UCX_COMMIT=${UCX_COMMIT}" \
--build-arg "UCC_COMMIT=${UCC_COMMIT}" \
--build-arg "CONDA_CMAKE=${CONDA_CMAKE}" \
--build-arg "PIP_CMAKE=${PIP_CMAKE}" \
--build-arg "TRITON=${TRITON}" \
--build-arg "TRITON_CPU=${TRITON_CPU}" \
--build-arg "ONNX=${ONNX}" \
@ -426,7 +506,6 @@ docker build \
--build-arg "EXECUTORCH=${EXECUTORCH}" \
--build-arg "HALIDE=${HALIDE}" \
--build-arg "XPU_VERSION=${XPU_VERSION}" \
--build-arg "UNINSTALL_DILL=${UNINSTALL_DILL}" \
--build-arg "ACL=${ACL:-}" \
--build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
--build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
@ -503,12 +582,3 @@ elif [ "$HAS_TRITON" = "yes" ]; then
echo "expecting triton to not be installed, but it is"
exit 1
fi
# Sanity check cmake version. Executorch reinstalls cmake and I'm not sure if
# they support 4.0.0 yet, so exclude them from this check.
CMAKE_VERSION=$(drun cmake --version)
if [[ "$EXECUTORCH" != *yes* && "$CMAKE_VERSION" != *4.* ]]; then
echo "CMake version is not 4.0.0:"
drun cmake --version
exit 1
fi

View File

@ -17,8 +17,9 @@ RUN bash ./install_base.sh && rm install_base.sh
# Update CentOS git version
RUN yum -y remove git
RUN yum -y remove git-*
RUN yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
sed -i 's/packages.endpoint/packages.endpointdev/' /etc/yum.repos.d/endpoint.repo
RUN yum -y install https://packages.endpoint.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm || \
(yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
sed -i "s/packages.endpoint/packages.endpointdev/" /etc/yum.repos.d/endpoint.repo)
RUN yum install -y git
# Install devtoolset
@ -39,6 +40,7 @@ RUN bash ./install_user.sh && rm install_user.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
@ -46,6 +48,13 @@ COPY ./common/install_conda.sh install_conda.sh
COPY ./common/common_utils.sh common_utils.sh
RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
# (optional) Install protobuf for ONNX
ARG PROTOBUF
COPY ./common/install_protobuf.sh install_protobuf.sh
RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
RUN rm install_protobuf.sh
ENV INSTALLED_PROTOBUF ${PROTOBUF}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@ -73,6 +82,12 @@ ENV MAGMA_HOME /opt/rocm/magma
ENV LANG en_US.utf8
ENV LC_ALL en_US.utf8
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
RUN rm install_cmake.sh
# (optional) Install non-default Ninja version
ARG NINJA_VERSION
COPY ./common/install_ninja.sh install_ninja.sh

View File

@ -1 +1 @@
f50bfa92602b45dca884a9e511e5d9ddbe8ba314
7e487c24e1c20c3f4606c2d8aca2778873b00b4c

View File

@ -1 +1 @@
v2.26.5-1
v2.26.2-1

View File

@ -1 +1 @@
b0e26b7359c147b8aa0af686c20510fb9b15990a
0bcc8265e677e5321606a3311bf71470f14456a8

View File

@ -1 +1 @@
c8757738a7418249896224430ce84888e8ecdd79
96316ce50fade7e209553aba4898cd9b82aab83b

View File

@ -36,6 +36,8 @@ install_ubuntu() {
# See https://github.com/pytorch/pytorch/issues/144768
if [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "11.8"* ]]; then
maybe_libnccl_dev="libnccl2=2.15.5-1+cuda11.8 libnccl-dev=2.15.5-1+cuda11.8 --allow-downgrades --allow-change-held-packages"
elif [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "12.4"* ]]; then
maybe_libnccl_dev="libnccl2=2.26.2-1+cuda12.4 libnccl-dev=2.26.2-1+cuda12.4 --allow-downgrades --allow-change-held-packages"
else
maybe_libnccl_dev=""
fi
@ -97,6 +99,9 @@ install_centos() {
ccache_deps="asciidoc docbook-dtds docbook-style-xsl libxslt"
numpy_deps="gcc-gfortran"
# Note: protobuf-c-{compiler,devel} on CentOS are too old to be used
# for Caffe2. That said, we still install them to make sure the build
# system opts to build/use protoc and libprotobuf from third-party.
yum install -y \
$ccache_deps \
$numpy_deps \

View File

@ -9,7 +9,7 @@ install_ubuntu() {
# Instead use lib and headers from OpenSSL1.1 installed in `install_openssl.sh``
apt-get install -y cargo
echo "Checking out sccache repo"
git clone https://github.com/mozilla/sccache -b v0.10.0
git clone https://github.com/mozilla/sccache -b v0.9.1
cd sccache
echo "Building sccache"
cargo build --release

View File

@ -0,0 +1,31 @@
#!/bin/bash
set -ex
[ -n "$CMAKE_VERSION" ]
# Remove system cmake install so it won't get used instead
ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
case "$ID" in
ubuntu)
apt-get remove cmake -y
;;
centos)
yum remove cmake -y
;;
*)
echo "Unable to determine OS..."
exit 1
;;
esac
# Turn 3.6.3 into v3.6
path=$(echo "${CMAKE_VERSION}" | sed -e 's/\([0-9].[0-9]\+\).*/v\1/')
file="cmake-${CMAKE_VERSION}-Linux-x86_64.tar.gz"
# Download and install specific CMake version in /usr/local
pushd /tmp
curl -Os --retry 3 "https://cmake.org/files/${path}/${file}"
tar -C /usr/local --strip-components 1 --no-same-owner -zxf cmake-*.tar.gz
rm -f cmake-*.tar.gz
popd

View File

@ -7,7 +7,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
BASE_URL="https://repo.anaconda.com/miniconda"
CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
if [[ $(uname -m) == "aarch64" ]] || [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download" # @lint-ignore
BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"
CONDA_FILE="Miniforge3-Linux-$(uname -m).sh"
fi
@ -75,11 +75,19 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
# and libpython-static for torch deploy
conda_install llvmdev=8.0.0 "libpython-static=${ANACONDA_PYTHON_VERSION}"
# Use conda cmake in some cases. Conda cmake will be newer than our supported
# min version (3.5 for xenial and 3.10 for bionic), so we only do it in those
# following builds that we know should use conda. Specifically, Ubuntu bionic
# and focal cannot find conda mkl with stock cmake, so we need a cmake from conda
if [ -n "${CONDA_CMAKE}" ]; then
conda_install cmake
fi
# Magma package names are concatenation of CUDA major and minor ignoring revision
# I.e. magma-cuda102 package corresponds to CUDA_VERSION=10.2 and CUDA_VERSION=10.2.89
# Magma is installed from a tarball in the ossci-linux bucket into the conda env
if [ -n "$CUDA_VERSION" ]; then
conda_run ${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION})
${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION}) ${ANACONDA_PYTHON_VERSION}
fi
# Install some other packages, including those needed for Python test reporting

View File

@ -3,7 +3,7 @@
set -uex -o pipefail
PYTHON_DOWNLOAD_URL=https://www.python.org/ftp/python
PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads # @lint-ignore
PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads
GET_PIP_URL=https://bootstrap.pypa.io/get-pip.py
# Python versions to be installed in /opt/$VERSION_NO

View File

@ -2,68 +2,117 @@
set -ex
arch_path=''
targetarch=${TARGETARCH:-$(uname -m)}
if [ ${targetarch} = 'amd64' ] || [ "${targetarch}" = 'x86_64' ]; then
arch_path='x86_64'
else
arch_path='sbsa'
fi
CUDNN_VERSION=9.5.1.17
function install_cuda {
version=$1
runfile=$2
major_minor=${version%.*}
rm -rf /usr/local/cuda-${major_minor} /usr/local/cuda
if [[ ${arch_path} == 'sbsa' ]]; then
runfile="${runfile}_sbsa"
fi
runfile="${runfile}.run"
wget -q https://developer.download.nvidia.com/compute/cuda/${version}/local_installers/${runfile} -O ${runfile}
chmod +x ${runfile}
./${runfile} --toolkit --silent
rm -f ${runfile}
rm -f /usr/local/cuda && ln -s /usr/local/cuda-${major_minor} /usr/local/cuda
function install_cusparselt_040 {
# cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && pushd tmp_cusparselt
wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.4.0.7-archive.tar.xz
tar xf libcusparse_lt-linux-x86_64-0.4.0.7-archive.tar.xz
cp -a libcusparse_lt-linux-x86_64-0.4.0.7-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-x86_64-0.4.0.7-archive/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cusparselt
}
function install_cudnn {
cuda_major_version=$1
cudnn_version=$2
mkdir tmp_cudnn && cd tmp_cudnn
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
filepath="cudnn-linux-${arch_path}-${cudnn_version}_cuda${cuda_major_version}-archive"
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-${arch_path}/${filepath}.tar.xz
tar xf ${filepath}.tar.xz
cp -a ${filepath}/include/* /usr/local/cuda/include/
cp -a ${filepath}/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
function install_cusparselt_062 {
# cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && pushd tmp_cusparselt
wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
tar xf libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cusparselt
}
function install_cusparselt_063 {
# cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && pushd tmp_cusparselt
wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.3.2-archive.tar.xz
tar xf libcusparse_lt-linux-x86_64-0.6.3.2-archive.tar.xz
cp -a libcusparse_lt-linux-x86_64-0.6.3.2-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-x86_64-0.6.3.2-archive/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cusparselt
}
function install_118 {
CUDNN_VERSION=9.1.0.70
echo "Installing CUDA 11.8 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.4.0"
install_cuda 11.8.0 cuda_11.8.0_520.61.05_linux
rm -rf /usr/local/cuda-11.8 /usr/local/cuda
# install CUDA 11.8.0 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
chmod +x cuda_11.8.0_520.61.05_linux.run
./cuda_11.8.0_520.61.05_linux.run --toolkit --silent
rm -f cuda_11.8.0_520.61.05_linux.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-11.8 /usr/local/cuda
install_cudnn 11 $CUDNN_VERSION
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
CUDA_VERSION=11.8 bash install_nccl.sh
CUDA_VERSION=11.8 bash install_cusparselt.sh
install_cusparselt_040
ldconfig
}
function install_126 {
CUDNN_VERSION=9.5.1.17
echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.7.1"
install_cuda 12.6.3 cuda_12.6.3_560.35.05_linux
function install_124 {
CUDNN_VERSION=9.1.0.70
echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.2"
rm -rf /usr/local/cuda-12.4 /usr/local/cuda
# install CUDA 12.4.1 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run
chmod +x cuda_12.4.1_550.54.15_linux.run
./cuda_12.4.1_550.54.15_linux.run --toolkit --silent
rm -f cuda_12.4.1_550.54.15_linux.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
install_cudnn 12 $CUDNN_VERSION
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
CUDA_VERSION=12.4 bash install_nccl.sh
install_cusparselt_062
ldconfig
}
function install_126 {
echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
rm -rf /usr/local/cuda-12.6 /usr/local/cuda
# install CUDA 12.6.3 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run
chmod +x cuda_12.6.3_560.35.05_linux.run
./cuda_12.6.3_560.35.05_linux.run --toolkit --silent
rm -f cuda_12.6.3_560.35.05_linux.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.6 /usr/local/cuda
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
CUDA_VERSION=12.6 bash install_nccl.sh
CUDA_VERSION=12.6 bash install_cusparselt.sh
install_cusparselt_063
ldconfig
}
@ -99,6 +148,40 @@ function prune_118 {
rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.3.0 $CUDA_BASE/nsight-systems-2022.4.2/
}
function prune_124 {
echo "Pruning CUDA 12.4"
#####################################################################################
# CUDA 12.4 prune static libs
#####################################################################################
export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
if [[ -n "$OVERRIDE_GENCODE" ]]; then
export GENCODE=$OVERRIDE_GENCODE
fi
if [[ -n "$OVERRIDE_GENCODE_CUDNN" ]]; then
export GENCODE_CUDNN=$OVERRIDE_GENCODE_CUDNN
fi
# all CUDA libs except CuDNN and CuBLAS
ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis" \
| xargs -I {} bash -c \
"echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
# prune CuDNN and CuBLAS
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
$NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
#####################################################################################
# CUDA 12.4 prune visual tools
#####################################################################################
export CUDA_BASE="/usr/local/cuda-12.4/"
rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.1.0 $CUDA_BASE/nsight-systems-2023.4.4/
}
function prune_126 {
echo "Pruning CUDA 12.6"
#####################################################################################
@ -135,16 +218,27 @@ function prune_126 {
function install_128 {
CUDNN_VERSION=9.8.0.87
echo "Installing CUDA 12.8.1 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.7.1"
# install CUDA 12.8.1 in the same container
install_cuda 12.8.1 cuda_12.8.1_570.124.06_linux
echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
rm -rf /usr/local/cuda-12.8 /usr/local/cuda
# install CUDA 12.8.0 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux.run
chmod +x cuda_12.8.0_570.86.10_linux.run
./cuda_12.8.0_570.86.10_linux.run --toolkit --silent
rm -f cuda_12.8.0_570.86.10_linux.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.8 /usr/local/cuda
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
install_cudnn 12 $CUDNN_VERSION
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
CUDA_VERSION=12.8 bash install_nccl.sh
CUDA_VERSION=12.8 bash install_cusparselt.sh
install_cusparselt_063
ldconfig
}
@ -155,9 +249,11 @@ do
case "$1" in
11.8) install_118; prune_118
;;
12.6|12.6.*) install_126; prune_126
12.4) install_124; prune_124
;;
12.8|12.8.*) install_128;
12.6) install_126; prune_126
;;
12.8) install_128;
;;
*) echo "bad argument $1"; exit 1
;;

View File

@ -0,0 +1,55 @@
#!/bin/bash
# Script used only in CD pipeline
set -ex
CUDNN_VERSION=9.8.0.87
function install_cusparselt_063 {
# cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && pushd tmp_cusparselt
wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-sbsa/libcusparse_lt-linux-sbsa-0.6.3.2-archive.tar.xz
tar xf libcusparse_lt-linux-sbsa-0.6.3.2-archive.tar.xz
cp -a libcusparse_lt-linux-sbsa-0.6.3.2-archive/include/* /usr/local/cuda/include/
cp -a libcusparse_lt-linux-sbsa-0.6.3.2-archive/lib/* /usr/local/cuda/lib64/
popd
rm -rf tmp_cusparselt
}
function install_128 {
echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
rm -rf /usr/local/cuda-12.8 /usr/local/cuda
# install CUDA 12.8.0 in the same container
wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux_sbsa.run
chmod +x cuda_12.8.0_570.86.10_linux_sbsa.run
./cuda_12.8.0_570.86.10_linux_sbsa.run --toolkit --silent
rm -f cuda_12.8.0_570.86.10_linux_sbsa.run
rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.8 /usr/local/cuda
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn && cd tmp_cudnn
wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-sbsa/cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
tar xf cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
cd ..
rm -rf tmp_cudnn
CUDA_VERSION=12.8 bash install_nccl.sh
install_cusparselt_063
ldconfig
}
# idiomatic parameter and option handling in sh
while test $# -gt 0
do
case "$1" in
12.8) install_128;
;;
*) echo "bad argument $1"; exit 1
;;
esac
shift
done

View File

@ -8,6 +8,8 @@ if [[ -n "${CUDNN_VERSION}" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.8.0.87_cuda12-archive"
elif [[ ${CUDA_VERSION:0:4} == "12.6" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.5.1.17_cuda12-archive"
elif [[ ${CUDA_VERSION:0:2} == "12" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda12-archive"
elif [[ ${CUDA_VERSION:0:2} == "11" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda11-archive"
else

View File

@ -11,7 +11,15 @@ if [[ ${CUDA_VERSION:0:4} =~ ^12\.[5-8]$ ]]; then
if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
arch_path='x86_64'
fi
CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.7.1.0-archive"
CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.3.2-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
elif [[ ${CUDA_VERSION:0:4} == "12.4" ]]; then
arch_path='sbsa'
export TARGETARCH=${TARGETARCH:-$(uname -m)}
if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
arch_path='x86_64'
fi
CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.2.3-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.4.0.7-archive"

View File

@ -13,7 +13,7 @@ clone_executorch() {
# and fetch the target commit
pushd executorch
git checkout "${EXECUTORCH_PINNED_COMMIT}"
git submodule update --init --recursive
git submodule update --init
popd
chown -R jenkins executorch

View File

@ -17,7 +17,7 @@ if [ -n "${UBUNTU_VERSION}" ];then
libopenblas-dev libeigen3-dev libatlas-base-dev libzstd-dev
fi
pip_install numpy scipy imageio cmake ninja
conda_install numpy scipy imageio cmake ninja
git clone --depth 1 --branch release/16.x --recursive https://github.com/llvm/llvm-project.git
cmake -DCMAKE_BUILD_TYPE=Release \

View File

@ -14,9 +14,16 @@ function install_timm() {
local commit
commit=$(get_pinned_commit timm)
# TODO (huydhn): There is no torchvision release on 3.13 when I write this, so
# I'm using nightly here instead. We just need to package to be able to install
# TIMM. Removing this once vision has a release on 3.13
if [[ "${ANACONDA_PYTHON_VERSION}" == "3.13" ]]; then
pip_install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu124
fi
pip_install "git+https://github.com/huggingface/pytorch-image-models@${commit}"
# Clean up
conda_run pip uninstall -y torch torchvision triton
conda_run pip uninstall -y cmake torch torchvision triton
}
# Pango is needed for weasyprint which is needed for doctr

View File

@ -1,23 +1,26 @@
#!/usr/bin/env bash
# Script that installs magma from tarball inside conda environment.
# It replaces anaconda magma-cuda package which is no longer published.
# Execute it inside active conda environment.
# See issue: https://github.com/pytorch/pytorch/issues/138506
# Script that replaces the magma install from a conda package
set -eou pipefail
cuda_version_nodot=${1/./}
anaconda_dir=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
function do_install() {
cuda_version_nodot=${1/./}
anaconda_python_version=$2
MAGMA_VERSION="2.6.1"
magma_archive="magma-cuda${cuda_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
(
set -x
tmp_dir=$(mktemp -d)
pushd ${tmp_dir}
curl -OLs https://ossci-linux.s3.us-east-1.amazonaws.com/${magma_archive}
tar -xvf "${magma_archive}"
mv include/* "${anaconda_dir}/include/"
mv lib/* "${anaconda_dir}/lib"
popd
)
MAGMA_VERSION="2.6.1"
magma_archive="magma-cuda${cuda_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
anaconda_dir="/opt/conda/envs/py_${anaconda_python_version}"
(
set -x
tmp_dir=$(mktemp -d)
pushd ${tmp_dir}
curl -OLs https://ossci-linux.s3.us-east-1.amazonaws.com/${magma_archive}
tar -xvf "${magma_archive}"
mv include/* "${anaconda_dir}/include/"
mv lib/* "${anaconda_dir}/lib"
popd
)
}
do_install $1 $2

View File

@ -8,6 +8,16 @@ retry () {
"$@" || (sleep 10 && "$@") || (sleep 20 && "$@") || (sleep 40 && "$@")
}
# A bunch of custom pip dependencies for ONNX
pip_install \
beartype==0.15.0 \
filelock==3.9.0 \
flatbuffers==2.0 \
mock==5.0.1 \
ninja==1.10.2 \
networkx==2.5 \
numpy==1.24.2
# ONNXRuntime should be installed before installing
# onnx-weekly. Otherwise, onnx-weekly could be
# overwritten by onnx.
@ -19,8 +29,12 @@ pip_install \
transformers==4.36.2
pip_install coloredlogs packaging
pip_install onnxruntime==1.18.1
pip_install onnxscript==0.3.0
pip_install onnx==1.17.0
pip_install onnxscript==0.2.2 --no-deps
# required by onnxscript
pip_install ml_dtypes
# Cache the transformers model to be used later by ONNX tests. We need to run the transformers
# package to download the model. By default, the model is cached at ~/.cache/huggingface/hub/

View File

@ -4,7 +4,8 @@
set -ex
cd /
git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION:-v0.3.29}" --depth 1 --shallow-submodules
git clone https://github.com/OpenMathLib/OpenBLAS.git -b v0.3.29 --depth 1 --shallow-submodules
OPENBLAS_BUILD_FLAGS="
NUM_THREADS=128

View File

@ -0,0 +1,19 @@
#!/bin/bash
set -ex
pb_dir="/usr/temp_pb_install_dir"
mkdir -p $pb_dir
# On the nvidia/cuda:9-cudnn7-devel-centos7 image we need this symlink or
# else it will fail with
# g++: error: ./../lib64/crti.o: No such file or directory
ln -s /usr/lib64 "$pb_dir/lib64"
curl -LO "https://github.com/protocolbuffers/protobuf/releases/download/v3.17.3/protobuf-all-3.17.3.tar.gz" --retry 3
tar -xvz --no-same-owner -C "$pb_dir" --strip-components 1 -f protobuf-all-3.17.3.tar.gz
NPROC=$[$(nproc) - 2]
pushd "$pb_dir" && ./configure && make -j${NPROC} && make -j${NPROC} check && sudo make -j${NRPOC} install && sudo ldconfig
popd
rm -rf $pb_dir

View File

@ -13,3 +13,6 @@ source /var/lib/jenkins/ci_env/bin/activate
python -mpip install --upgrade pip
python -mpip install -r /opt/requirements-ci.txt
if [ -n "${PIP_CMAKE}" ]; then
python -mpip install cmake==3.31.6
fi

View File

@ -19,13 +19,6 @@ install_ubuntu() {
apt-get install -y libc++1
apt-get install -y libc++abi1
# Make sure rocm packages from repo.radeon.com have highest priority
cat << EOF > /etc/apt/preferences.d/rocm-pin-600
Package: *
Pin: release o=repo.radeon.com
Pin-Priority: 600
EOF
# Add amdgpu repository
UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
echo "deb [arch=amd64] https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
@ -66,25 +59,17 @@ EOF
done
# ROCm 6.3 had a regression where initializing static code objects had significant overhead
# ROCm 6.4 did not yet fix the regression, also HIP branch names are different
if [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]] || [[ $(ver $ROCM_VERSION) -eq $(ver 6.4) ]]; then
if [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]]; then
HIP_BRANCH=rocm-6.3.x
VER_STR=6.3
elif [[ $(ver $ROCM_VERSION) -eq $(ver 6.4) ]]; then
HIP_BRANCH=release/rocm-rel-6.4
VER_STR=6.4
fi
if [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]]; then
# clr build needs CppHeaderParser but can only find it using conda's python
/opt/conda/bin/python -m pip install CppHeaderParser
git clone https://github.com/ROCm/HIP -b $HIP_BRANCH
git clone https://github.com/ROCm/HIP -b rocm-6.3.x
HIP_COMMON_DIR=$(readlink -f HIP)
git clone https://github.com/jeffdaily/clr -b release/rocm-rel-${VER_STR}-statco-hotfix
git clone https://github.com/jeffdaily/clr -b release/rocm-rel-6.3-statco-hotfix
mkdir -p clr/build
pushd clr/build
cmake .. -DCLR_BUILD_HIP=ON -DHIP_COMMON_DIR=$HIP_COMMON_DIR
make -j
cp hipamd/lib/libamdhip64.so.${VER_STR}.* /opt/rocm/lib/libamdhip64.so.${VER_STR}.*
cp hipamd/lib/libamdhip64.so.6.3.* /opt/rocm/lib/libamdhip64.so.6.3.*
popd
rm -rf HIP clr
fi

View File

@ -25,7 +25,9 @@ python3 -m pip install meson ninja
###########################
### clone repo
###########################
GIT_SSL_NO_VERIFY=true git clone https://gitlab.freedesktop.org/mesa/drm.git
# TEMPORARY FIX: https://gitlab.freedesktop.org/mesa/drm.git is down until 2025/03/22
# GIT_SSL_NO_VERIFY=true git clone https://gitlab.freedesktop.org/mesa/drm.git
GIT_SSL_NO_VERIFY=true git clone git://anongit.freedesktop.org/mesa/drm
pushd drm
###########################

View File

@ -17,14 +17,10 @@ function do_install() {
tmp_dir=$(mktemp -d)
pushd ${tmp_dir}
curl -OLs https://ossci-linux.s3.us-east-1.amazonaws.com/${magma_archive}
if tar -xvf "${magma_archive}"
then
mkdir -p "${rocm_dir}/magma"
mv include "${rocm_dir}/magma/include"
mv lib "${rocm_dir}/magma/lib"
else
echo "${magma_archive} not found, skipping magma install"
fi
tar -xvf "${magma_archive}"
mkdir -p "${rocm_dir}/magma"
mv include "${rocm_dir}/magma/include"
mv lib "${rocm_dir}/magma/lib"
popd
)
}

View File

@ -10,8 +10,12 @@ fi
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
get_pip_version() {
conda_run pip list | grep -w $* | head -n 1 | awk '{print $2}'
get_conda_version() {
as_jenkins conda list -n py_$ANACONDA_PYTHON_VERSION | grep -w $* | head -n 1 | awk '{print $2}'
}
conda_reinstall() {
as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y --force-reinstall $*
}
if [ -n "${XPU_VERSION}" ]; then
@ -33,9 +37,11 @@ if [ -n "${UBUNTU_VERSION}" ];then
apt-get install -y gpg-agent
fi
# Keep the current cmake and numpy version here, so we can reinstall them later
CMAKE_VERSION=$(get_pip_version cmake)
NUMPY_VERSION=$(get_pip_version numpy)
if [ -n "${CONDA_CMAKE}" ]; then
# Keep the current cmake and numpy version here, so we can reinstall them later
CMAKE_VERSION=$(get_conda_version cmake)
NUMPY_VERSION=$(get_conda_version numpy)
fi
if [ -z "${MAX_JOBS}" ]; then
export MAX_JOBS=$(nproc)
@ -51,12 +57,7 @@ as_jenkins git clone --recursive ${TRITON_REPO} triton
cd triton
as_jenkins git checkout ${TRITON_PINNED_COMMIT}
as_jenkins git submodule update --init --recursive
# Old versions of python have setup.py in ./python; newer versions have it in ./
if [ ! -f setup.py ]; then
cd python
fi
cd python
pip_install pybind11==2.13.6
# TODO: remove patch setup.py once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
@ -82,19 +83,17 @@ cp dist/*.whl /opt/triton
# Install the wheel for docker builds that don't use multi stage
pip_install dist/*.whl
# TODO: This is to make sure that the same cmake and numpy version from install conda
# script is used. Without this step, the newer cmake version (3.25.2) downloaded by
# triton build step via pip will fail to detect conda MKL. Once that issue is fixed,
# this can be removed.
#
# The correct numpy version also needs to be set here because conda claims that it
# causes inconsistent environment. Without this, conda will attempt to install the
# latest numpy version, which fails ASAN tests with the following import error: Numba
# needs NumPy 1.20 or less.
# Note that we install numpy with pip as conda might not have the version we want
if [ -n "${CMAKE_VERSION}" ]; then
pip_install "cmake==${CMAKE_VERSION}"
fi
if [ -n "${NUMPY_VERSION}" ]; then
pip_install "numpy==${NUMPY_VERSION}"
if [ -n "${CONDA_CMAKE}" ]; then
# TODO: This is to make sure that the same cmake and numpy version from install conda
# script is used. Without this step, the newer cmake version (3.25.2) downloaded by
# triton build step via pip will fail to detect conda MKL. Once that issue is fixed,
# this can be removed.
#
# The correct numpy version also needs to be set here because conda claims that it
# causes inconsistent environment. Without this, conda will attempt to install the
# latest numpy version, which fails ASAN tests with the following import error: Numba
# needs NumPy 1.20 or less.
conda_reinstall cmake="${CMAKE_VERSION}"
# Note that we install numpy with pip as conda might not have the version we want
pip_install --force-reinstall numpy=="${NUMPY_VERSION}"
fi

View File

@ -26,7 +26,7 @@ function install_ubuntu() {
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
| gpg --dearmor > /usr/share/keyrings/oneapi-archive-keyring.gpg.gpg
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg.gpg] \
https://apt.repos.intel.com/oneapi all main" \
https://apt.repos.intel.com/${XPU_REPO_NAME} all main" \
| tee /etc/apt/sources.list.d/oneAPI.list
# Update the packages list and repository index
@ -74,7 +74,7 @@ function install_rhel() {
tee > /etc/yum.repos.d/oneAPI.repo << EOF
[oneAPI]
name=Intel for Pytorch GPU dev repository
baseurl=https://yum.repos.intel.com/oneapi
baseurl=https://yum.repos.intel.com/${XPU_REPO_NAME}
enabled=1
gpgcheck=1
repo_gpgcheck=1
@ -118,7 +118,7 @@ function install_sles() {
https://repositories.intel.com/gpu/sles/${VERSION_SP}${XPU_DRIVER_VERSION}/unified/intel-gpu-${VERSION_SP}.repo
rpm --import https://repositories.intel.com/gpu/intel-graphics.key
# To add the online network network package repository for the Intel Support Packages
zypper addrepo https://yum.repos.intel.com/oneapi oneAPI
zypper addrepo https://yum.repos.intel.com/${XPU_REPO_NAME} oneAPI
rpm --import https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
# The xpu-smi packages
@ -141,10 +141,10 @@ if [[ "${XPU_DRIVER_TYPE,,}" == "rolling" ]]; then
XPU_DRIVER_VERSION=""
fi
# Default use Intel® oneAPI Deep Learning Essentials 2025.0
if [[ "$XPU_VERSION" == "2025.1" ]]; then
XPU_PACKAGES="intel-deep-learning-essentials-2025.1"
else
XPU_REPO_NAME="intel-for-pytorch-gpu-dev"
XPU_PACKAGES="intel-for-pytorch-gpu-dev-0.5 intel-pti-dev-0.9"
if [[ "$XPU_VERSION" == "2025.0" ]]; then
XPU_REPO_NAME="oneapi"
XPU_PACKAGES="intel-deep-learning-essentials-2025.0"
fi

View File

@ -51,7 +51,6 @@ ADD ./common/install_cuda.sh install_cuda.sh
ADD ./common/install_magma.sh install_magma.sh
COPY ./common/install_nccl.sh install_nccl.sh
COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
COPY ./common/install_cusparselt.sh install_cusparselt.sh
ENV CUDA_HOME /usr/local/cuda
FROM cuda as cuda11.8
@ -90,7 +89,7 @@ ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
# gfortran and python needed for building magma from source for ROCm
RUN apt-get update -y && \
apt-get install gfortran -y && \
apt-get install python3 python-is-python3 -y && \
apt-get install python -y && \
apt-get clean
RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh

View File

@ -1,63 +1,83 @@
#!/usr/bin/env bash
# Script used only in CD pipeline
set -eoux pipefail
set -eou pipefail
image="$1"
shift
if [ -z "${image}" ]; then
echo "Usage: $0 IMAGENAME:ARCHTAG"
echo "Usage: $0 IMAGE"
exit 1
fi
DOCKER_IMAGE="pytorch/${image}"
TOPDIR=$(git rev-parse --show-toplevel)
GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
WITH_PUSH=${WITH_PUSH:-}
DOCKER=${DOCKER:-docker}
# Go from imagename:tag to tag
DOCKER_TAG_PREFIX=$(echo "${image}" | awk -F':' '{print $2}')
GPU_ARCH_VERSION=""
if [[ "${DOCKER_TAG_PREFIX}" == cuda* ]]; then
# extract cuda version from image name. e.g. manylinux2_28-builder:cuda12.8 returns 12.8
GPU_ARCH_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'cuda' '{print $2}')
elif [[ "${DOCKER_TAG_PREFIX}" == rocm* ]]; then
# extract rocm version from image name. e.g. manylinux2_28-builder:rocm6.2.4 returns 6.2.4
GPU_ARCH_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'rocm' '{print $2}')
fi
case ${DOCKER_TAG_PREFIX} in
case ${GPU_ARCH_TYPE} in
cpu)
BASE_TARGET=cpu
DOCKER_TAG=cpu
GPU_IMAGE=ubuntu:20.04
DOCKER_GPU_BUILD_ARG=""
;;
cuda*)
cuda)
BASE_TARGET=cuda${GPU_ARCH_VERSION}
DOCKER_TAG=cuda${GPU_ARCH_VERSION}
GPU_IMAGE=ubuntu:20.04
DOCKER_GPU_BUILD_ARG=""
;;
rocm*)
rocm)
BASE_TARGET=rocm
GPU_IMAGE=rocm/dev-ubuntu-22.04:${GPU_ARCH_VERSION}-complete
DOCKER_TAG=rocm${GPU_ARCH_VERSION}
GPU_IMAGE=rocm/dev-ubuntu-20.04:${GPU_ARCH_VERSION}-complete
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg ROCM_VERSION=${GPU_ARCH_VERSION}"
;;
*)
echo "ERROR: Unrecognized DOCKER_TAG_PREFIX: ${DOCKER_TAG_PREFIX}"
echo "ERROR: Unrecognized GPU_ARCH_TYPE: ${GPU_ARCH_TYPE}"
exit 1
;;
esac
tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
DOCKER_BUILDKIT=1 ${DOCKER} build \
--target final \
${DOCKER_GPU_BUILD_ARG} \
--build-arg "GPU_IMAGE=${GPU_IMAGE}" \
--build-arg "BASE_TARGET=${BASE_TARGET}" \
-t "${tmp_tag}" \
$@ \
-f "${TOPDIR}/.ci/docker/libtorch/Dockerfile" \
"${TOPDIR}/.ci/docker/"
(
set -x
DOCKER_BUILDKIT=1 ${DOCKER} build \
--target final \
${DOCKER_GPU_BUILD_ARG} \
--build-arg "GPU_IMAGE=${GPU_IMAGE}" \
--build-arg "BASE_TARGET=${BASE_TARGET}" \
-t "${DOCKER_IMAGE}" \
$@ \
-f "${TOPDIR}/.ci/docker/libtorch/Dockerfile" \
"${TOPDIR}/.ci/docker/"
)
GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
GIT_BRANCH_NAME=${GITHUB_REF##*/}
GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE}-${GIT_BRANCH_NAME}
DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE}-${GIT_COMMIT_SHA}
if [[ "${WITH_PUSH}" == true ]]; then
(
set -x
${DOCKER} push "${DOCKER_IMAGE}"
if [[ -n ${GITHUB_REF} ]]; then
${DOCKER} tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_BRANCH_TAG}
${DOCKER} tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_SHA_TAG}
${DOCKER} push "${DOCKER_IMAGE_BRANCH_TAG}"
${DOCKER} push "${DOCKER_IMAGE_SHA_TAG}"
fi
)
fi

View File

@ -32,8 +32,7 @@ ARG CUDA_VERSION
COPY ./common/install_cuda.sh install_cuda.sh
COPY ./common/install_nccl.sh install_nccl.sh
COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
COPY ./common/install_cusparselt.sh install_cusparselt.sh
RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu* install_cusparselt.sh
RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu*
ENV DESIRED_CUDA ${CUDA_VERSION}
ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH

View File

@ -16,6 +16,7 @@ RUN bash ./install_user.sh && rm install_user.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG PYTHON_VERSION
ARG PIP_CMAKE
ENV PATH /var/lib/jenkins/ci_env/bin:$PATH
ENV VIRTUAL_ENV /var/lib/jenkins/ci_env
COPY requirements-ci.txt /opt/requirements-ci.txt

View File

@ -0,0 +1,202 @@
# syntax = docker/dockerfile:experimental
ARG ROCM_VERSION=3.7
ARG BASE_CUDA_VERSION=11.8
ARG GPU_IMAGE=centos:7
FROM centos:7 as base
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
ARG DEVTOOLSET_VERSION=9
# Note: This is required patch since CentOS have reached EOL
# otherwise any yum install setp will fail
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y wget curl perl util-linux xz bzip2 git patch which perl zlib-devel
# Just add everything as a safe.directory for git since these will be used in multiple places with git
RUN git config --global --add safe.directory '*'
RUN yum install -y yum-utils centos-release-scl
RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
# Note: After running yum-config-manager --enable rhel-server-rhscl-7-rpms
# patch is required once again. Somehow this steps adds mirror.centos.org
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
RUN yum --enablerepo=extras install -y epel-release
# cmake-3.18.4 from pip
RUN yum install -y python3-pip && \
python3 -mpip install cmake==3.18.4 && \
ln -s /usr/local/bin/cmake /usr/bin/cmake
RUN yum install -y autoconf aclocal automake make sudo
FROM base as openssl
# Install openssl (this must precede `build python` step)
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
# EPEL for cmake
FROM base as patchelf
# Install patchelf
ADD ./common/install_patchelf.sh install_patchelf.sh
RUN bash ./install_patchelf.sh && rm install_patchelf.sh
RUN cp $(which patchelf) /patchelf
FROM patchelf as python
# build python
COPY manywheel/build_scripts /build_scripts
ADD ./common/install_cpython.sh /build_scripts/install_cpython.sh
RUN bash build_scripts/build.sh && rm -r build_scripts
FROM base as cuda
ARG BASE_CUDA_VERSION=10.2
# Install CUDA
ADD ./common/install_cuda.sh install_cuda.sh
COPY ./common/install_nccl.sh install_nccl.sh
COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu*
FROM base as intel
# MKL
ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
FROM base as magma
ARG BASE_CUDA_VERSION=10.2
# Install magma
ADD ./common/install_magma.sh install_magma.sh
RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
FROM base as jni
# Install java jni header
ADD ./common/install_jni.sh install_jni.sh
ADD ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
FROM base as libpng
# Install libpng
ADD ./common/install_libpng.sh install_libpng.sh
RUN bash ./install_libpng.sh && rm install_libpng.sh
FROM ${GPU_IMAGE} as common
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
RUN yum install -y \
aclocal \
autoconf \
automake \
bison \
bzip2 \
curl \
diffutils \
file \
git \
make \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz \
yasm
RUN yum install -y \
https://repo.ius.io/ius-release-el7.rpm \
https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
RUN yum swap -y git git236-core
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
ENV SSL_CERT_FILE=/opt/_internal/certs.pem
# Install LLVM version
COPY --from=openssl /opt/openssl /opt/openssl
COPY --from=python /opt/python /opt/python
COPY --from=python /opt/_internal /opt/_internal
COPY --from=python /opt/python/cp39-cp39/bin/auditwheel /usr/local/bin/auditwheel
COPY --from=intel /opt/intel /opt/intel
COPY --from=patchelf /usr/local/bin/patchelf /usr/local/bin/patchelf
COPY --from=jni /usr/local/include/jni.h /usr/local/include/jni.h
COPY --from=libpng /usr/local/bin/png* /usr/local/bin/
COPY --from=libpng /usr/local/bin/libpng* /usr/local/bin/
COPY --from=libpng /usr/local/include/png* /usr/local/include/
COPY --from=libpng /usr/local/include/libpng* /usr/local/include/
COPY --from=libpng /usr/local/lib/libpng* /usr/local/lib/
COPY --from=libpng /usr/local/lib/pkgconfig /usr/local/lib/pkgconfig
FROM common as cpu_final
ARG BASE_CUDA_VERSION=10.1
ARG DEVTOOLSET_VERSION=9
# Install Anaconda
ADD ./common/install_conda_docker.sh install_conda.sh
RUN bash ./install_conda.sh && rm install_conda.sh
ENV PATH /opt/conda/bin:$PATH
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y yum-utils centos-release-scl
RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
# cmake is already installed inside the rocm base image, so remove if present
RUN rpm -e cmake || true
# cmake-3.18.4 from pip
RUN yum install -y python3-pip && \
python3 -mpip install cmake==3.18.4 && \
ln -s /usr/local/bin/cmake /usr/bin/cmake
# ninja
RUN yum install -y ninja-build
FROM cpu_final as cuda_final
RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=cuda /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
COPY --from=magma /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda-${BASE_CUDA_VERSION}
RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
ENV PATH=/usr/local/cuda/bin:$PATH
FROM cpu_final as rocm_final
ARG ROCM_VERSION=3.7
ARG PYTORCH_ROCM_ARCH
ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
# Adding ROCM_PATH env var so that LoadHip.cmake (even with logic updated for ROCm6.0)
# find HIP works for ROCm5.7. Not needed for ROCm6.0 and above.
# Remove below when ROCm5.7 is not in support matrix anymore.
ENV ROCM_PATH /opt/rocm
ENV MKLROOT /opt/intel
# No need to install ROCm as base docker image should have full ROCm install
#ADD ./common/install_rocm.sh install_rocm.sh
#RUN ROCM_VERSION=${ROCM_VERSION} bash ./install_rocm.sh && rm install_rocm.sh
ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
# cmake3 is needed for the MIOpen build
RUN ln -sf /usr/local/bin/cmake /usr/bin/cmake3
ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh ${ROCM_VERSION} && rm install_rocm_magma.sh
ADD ./common/install_miopen.sh install_miopen.sh
RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh

View File

@ -7,8 +7,8 @@ ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
ARG DEVTOOLSET_VERSION=13
RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel yum-utils gcc-toolset-${DEVTOOLSET_VERSION}-gcc gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran gcc-toolset-${DEVTOOLSET_VERSION}-gdb
ARG DEVTOOLSET_VERSION=11
RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel yum-utils gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
@ -33,13 +33,12 @@ RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
FROM base as cuda
ARG BASE_CUDA_VERSION=12.6
ARG BASE_CUDA_VERSION=11.8
# Install CUDA
ADD ./common/install_cuda.sh install_cuda.sh
COPY ./common/install_nccl.sh install_nccl.sh
COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
COPY ./common/install_cusparselt.sh install_cusparselt.sh
RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh ci_commit_pins/nccl-cu* install_cusparselt.sh
RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh ci_commit_pins/nccl-cu*
FROM base as intel
# MKL
@ -47,7 +46,7 @@ ADD ./common/install_mkl.sh install_mkl.sh
RUN bash ./install_mkl.sh && rm install_mkl.sh
FROM base as magma
ARG BASE_CUDA_VERSION=12.6
ARG BASE_CUDA_VERSION=10.2
# Install magma
ADD ./common/install_magma.sh install_magma.sh
RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
@ -64,7 +63,7 @@ ADD ./common/install_libpng.sh install_libpng.sh
RUN bash ./install_libpng.sh && rm install_libpng.sh
FROM ${GPU_IMAGE} as common
ARG DEVTOOLSET_VERSION=13
ARG DEVTOOLSET_VERSION=11
ENV LC_ALL en_US.UTF-8
ENV LANG en_US.UTF-8
ENV LANGUAGE en_US.UTF-8
@ -87,12 +86,13 @@ RUN yum install -y \
wget \
which \
xz \
glibc-langpack-en \
gcc-toolset-${DEVTOOLSET_VERSION}-gcc \
gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ \
gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
gcc-toolset-${DEVTOOLSET_VERSION}-gdb
gcc-toolset-${DEVTOOLSET_VERSION}-toolchain \
glibc-langpack-en
RUN yum install -y \
https://repo.ius.io/ius-release-el7.rpm \
https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
RUN yum swap -y git git236-core
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
@ -116,8 +116,8 @@ COPY --from=libpng /usr/local/lib/pkgconfig /usr/local/
COPY --from=jni /usr/local/include/jni.h /usr/local/include/jni.h
FROM common as cpu_final
ARG BASE_CUDA_VERSION=12.6
ARG DEVTOOLSET_VERSION=13
ARG BASE_CUDA_VERSION=11.8
ARG DEVTOOLSET_VERSION=11
# Install Anaconda
ADD ./common/install_conda_docker.sh install_conda.sh
RUN bash ./install_conda.sh && rm install_conda.sh
@ -156,11 +156,8 @@ ENV ROCM_PATH /opt/rocm
# and avoid 3.21.0 cmake+ninja issues with ninja inserting "-Wl,--no-as-needed" in LINK_FLAGS for static linker
RUN python3 -m pip install --upgrade pip && \
python3 -mpip install cmake==3.28.4
# replace the libdrm in /opt/amdgpu with custom amdgpu.ids lookup path
ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
# ROCm 6.4 rocm-smi depends on system drm.h header
RUN yum install -y libdrm-devel
ENV MKLROOT /opt/intel
ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh ${ROCM_VERSION} && rm install_rocm_magma.sh
@ -174,6 +171,6 @@ ENV XPU_DRIVER_TYPE ROLLING
RUN python3 -m pip install --upgrade pip && \
python3 -mpip install cmake==3.28.4
ADD ./common/install_xpu.sh install_xpu.sh
ENV XPU_VERSION 2025.1
ENV XPU_VERSION 2025.0
RUN bash ./install_xpu.sh && rm install_xpu.sh
RUN pushd /opt/_internal && tar -xJf static-libs-for-embedding-only.tar.xz && popd

View File

@ -1,6 +1,7 @@
FROM quay.io/pypa/manylinux_2_28_aarch64 as base
ARG GCCTOOLSET_VERSION=13
# Graviton needs GCC 10 or above for the build. GCC12 is the default version in almalinux-8.
ARG GCCTOOLSET_VERSION=11
# Language variabes
ENV LC_ALL=en_US.UTF-8
@ -35,10 +36,7 @@ RUN yum install -y \
yasm \
zstd \
sudo \
gcc-toolset-${GCCTOOLSET_VERSION}-gcc \
gcc-toolset-${GCCTOOLSET_VERSION}-gcc-c++ \
gcc-toolset-${GCCTOOLSET_VERSION}-gcc-gfortran \
gcc-toolset-${GCCTOOLSET_VERSION}-gdb
gcc-toolset-${GCCTOOLSET_VERSION}-toolchain
# (optional) Install non-default Ninja version
ARG NINJA_VERSION
@ -58,7 +56,6 @@ RUN git config --global --add safe.directory "*"
FROM base as openblas
# Install openblas
ARG OPENBLAS_VERSION
ADD ./common/install_openblas.sh install_openblas.sh
RUN bash ./install_openblas.sh && rm install_openblas.sh

View File

@ -0,0 +1,94 @@
FROM quay.io/pypa/manylinux2014_aarch64 as base
# Graviton needs GCC 10 for the build
ARG DEVTOOLSET_VERSION=10
# Language variabes
ENV LC_ALL=en_US.UTF-8
ENV LANG=en_US.UTF-8
ENV LANGUAGE=en_US.UTF-8
# Installed needed OS packages. This is to support all
# the binary builds (torch, vision, audio, text, data)
RUN yum -y install epel-release
RUN yum -y update
RUN yum install -y \
autoconf \
automake \
bison \
bzip2 \
curl \
diffutils \
file \
git \
make \
patch \
perl \
unzip \
util-linux \
wget \
which \
xz \
yasm \
less \
zstd \
libgomp \
sudo \
devtoolset-${DEVTOOLSET_VERSION}-gcc \
devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ \
devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
devtoolset-${DEVTOOLSET_VERSION}-binutils
# Ensure the expected devtoolset is used
ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
# git236+ would refuse to run git commands in repos owned by other users
# Which causes version check to fail, as pytorch repo is bind-mounted into the image
# Override this behaviour by treating every folder as safe
# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
RUN git config --global --add safe.directory "*"
###############################################################################
# libglfortran.a hack
#
# libgfortran.a from quay.io/pypa/manylinux2014_aarch64 is not compiled with -fPIC.
# This causes __stack_chk_guard@@GLIBC_2.17 on pytorch build. To solve, get
# ubuntu's libgfortran.a which is compiled with -fPIC
# NOTE: Need a better way to get this library as Ubuntu's package can be removed by the vender, or changed
###############################################################################
RUN cd ~/ \
&& curl -L -o ~/libgfortran-10-dev.deb http://ports.ubuntu.com/ubuntu-ports/pool/universe/g/gcc-10/libgfortran-10-dev_10.5.0-4ubuntu2_arm64.deb \
&& ar x ~/libgfortran-10-dev.deb \
&& tar --use-compress-program=unzstd -xvf data.tar.zst -C ~/ \
&& cp -f ~/usr/lib/gcc/aarch64-linux-gnu/10/libgfortran.a /opt/rh/devtoolset-10/root/usr/lib/gcc/aarch64-redhat-linux/10/
# install cmake
RUN yum install -y cmake3 && \
ln -s /usr/bin/cmake3 /usr/bin/cmake
FROM base as openssl
# Install openssl (this must precede `build python` step)
# (In order to have a proper SSL module, Python is compiled
# against a recent openssl [see env vars above], which is linked
# statically. We delete openssl afterwards.)
ADD ./common/install_openssl.sh install_openssl.sh
RUN bash ./install_openssl.sh && rm install_openssl.sh
ENV SSL_CERT_FILE=/opt/_internal/certs.pem
FROM base as openblas
# Install openblas
ADD ./common/install_openblas.sh install_openblas.sh
RUN bash ./install_openblas.sh && rm install_openblas.sh
FROM openssl as final
# remove unncessary python versions
RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
COPY --from=openblas /opt/OpenBLAS/ /opt/OpenBLAS/
ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH

View File

@ -1,7 +1,7 @@
FROM quay.io/pypa/manylinux_2_28_aarch64 as base
# Cuda ARM build needs gcc 11
ARG DEVTOOLSET_VERSION=13
ARG DEVTOOLSET_VERSION=11
# Language variables
ENV LC_ALL=en_US.UTF-8
@ -34,10 +34,7 @@ RUN yum install -y \
zstd \
libgomp \
sudo \
gcc-toolset-${DEVTOOLSET_VERSION}-gcc \
gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ \
gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
gcc-toolset-${DEVTOOLSET_VERSION}-gdb
gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
# Ensure the expected devtoolset is used
ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
@ -69,11 +66,10 @@ RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
FROM base as cuda
ARG BASE_CUDA_VERSION
# Install CUDA
ADD ./common/install_cuda.sh install_cuda.sh
ADD ./common/install_cuda_aarch64.sh install_cuda_aarch64.sh
COPY ./common/install_nccl.sh install_nccl.sh
COPY ./common/install_cusparselt.sh install_cusparselt.sh
COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh ci_commit_pins/nccl-cu* install_cusparselt.sh
RUN bash ./install_cuda_aarch64.sh ${BASE_CUDA_VERSION} && rm install_cuda_aarch64.sh install_nccl.sh ci_commit_pins/nccl-cu*
FROM base as magma
ARG BASE_CUDA_VERSION

View File

@ -5,9 +5,7 @@ ENV LC_ALL=C.UTF-8
ENV LANG=C.UTF-8
ENV LANGUAGE=C.UTF-8
# there is a bugfix in gcc >= 14 for precompiled headers and s390x vectorization interaction.
# with earlier gcc versions test/inductor/test_cpu_cpp_wrapper.py will fail.
ARG DEVTOOLSET_VERSION=14
ARG DEVTOOLSET_VERSION=13
# Installed needed OS packages. This is to support all
# the binary builds (torch, vision, audio, text, data)
RUN yum -y install epel-release
@ -60,8 +58,7 @@ RUN yum install -y \
libxslt-devel \
libxml2-devel \
openssl-devel \
valgrind \
ninja-build
valgrind
ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
@ -106,6 +103,9 @@ CMD ["/bin/bash"]
# install test dependencies:
# - grpcio requires system openssl, bundled crypto fails to build
RUN dnf install -y \
protobuf-devel \
protobuf-c-devel \
protobuf-lite-devel \
hdf5-devel \
python3-h5py \
git
@ -129,9 +129,6 @@ RUN pip3 install flatbuffers && \
git clone https://github.com/microsoft/onnxruntime && \
cd onnxruntime && git checkout v1.21.0 && \
git submodule update --init --recursive && \
./build.sh --config Release --parallel 0 --enable_pybind \
--build_wheel --enable_training --enable_training_apis \
--enable_training_ops --skip_tests --allow_running_as_root \
--compile_no_warning_as_error && \
./build.sh --config Release --parallel 0 --enable_pybind --build_wheel --enable_training --enable_training_apis --enable_training_ops --skip_tests --allow_running_as_root && \
pip3 install ./build/Linux/Release/dist/onnxruntime_training-*.whl && \
cd .. && /bin/rm -rf ./onnxruntime

View File

@ -1,7 +1,7 @@
#!/usr/bin/env bash
# Script used only in CD pipeline
set -exou pipefail
set -eou pipefail
TOPDIR=$(git rev-parse --show-toplevel)
@ -9,111 +9,152 @@ image="$1"
shift
if [ -z "${image}" ]; then
echo "Usage: $0 IMAGE:ARCHTAG"
echo "Usage: $0 IMAGE"
exit 1
fi
# Go from imagename:tag to tag
DOCKER_TAG_PREFIX=$(echo "${image}" | awk -F':' '{print $2}')
DOCKER_IMAGE="pytorch/${image}"
GPU_ARCH_VERSION=""
if [[ "${DOCKER_TAG_PREFIX}" == cuda* ]]; then
# extract cuda version from image name. e.g. manylinux2_28-builder:cuda12.8 returns 12.8
GPU_ARCH_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'cuda' '{print $2}')
elif [[ "${DOCKER_TAG_PREFIX}" == rocm* ]]; then
# extract rocm version from image name. e.g. manylinux2_28-builder:rocm6.2.4 returns 6.2.4
GPU_ARCH_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'rocm' '{print $2}')
fi
DOCKER_REGISTRY="${DOCKER_REGISTRY:-docker.io}"
GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
MANY_LINUX_VERSION=${MANY_LINUX_VERSION:-}
DOCKERFILE_SUFFIX=${DOCKERFILE_SUFFIX:-}
OPENBLAS_VERSION=${OPENBLAS_VERSION:-}
WITH_PUSH=${WITH_PUSH:-}
case ${image} in
manylinux2_28-builder:cpu)
case ${GPU_ARCH_TYPE} in
cpu)
TARGET=cpu_final
DOCKER_TAG=cpu
GPU_IMAGE=centos:7
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
;;
cpu-manylinux_2_28)
TARGET=cpu_final
DOCKER_TAG=cpu
GPU_IMAGE=amd64/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13"
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="2_28"
;;
manylinux2_28_aarch64-builder:cpu-aarch64)
cpu-aarch64)
TARGET=final
GPU_IMAGE=arm64v8/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13 --build-arg NINJA_VERSION=1.12.1"
MANY_LINUX_VERSION="2_28_aarch64"
OPENBLAS_VERSION="v0.3.29"
DOCKER_TAG=cpu-aarch64
GPU_IMAGE=arm64v8/centos:7
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=10"
MANY_LINUX_VERSION="aarch64"
;;
manylinuxcxx11-abi-builder:cpu-cxx11-abi)
cpu-aarch64-2_28)
TARGET=final
DOCKER_TAG=cpu-aarch64
GPU_IMAGE=arm64v8/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11 --build-arg NINJA_VERSION=1.12.1"
MANY_LINUX_VERSION="2_28_aarch64"
;;
cpu-cxx11-abi)
TARGET=final
DOCKER_TAG=cpu-cxx11-abi
GPU_IMAGE=""
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
MANY_LINUX_VERSION="cxx11-abi"
;;
manylinuxs390x-builder:cpu-s390x)
cpu-s390x)
TARGET=final
DOCKER_TAG=cpu-s390x
GPU_IMAGE=s390x/almalinux:8
DOCKER_GPU_BUILD_ARG=""
MANY_LINUX_VERSION="s390x"
;;
manylinux2_28-builder:cuda11*)
cuda)
TARGET=cuda_final
DOCKER_TAG=cuda${GPU_ARCH_VERSION}
# Keep this up to date with the minimum version of CUDA we currently support
GPU_IMAGE=centos:7
DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=9"
;;
cuda-manylinux_2_28)
TARGET=cuda_final
DOCKER_TAG=cuda${GPU_ARCH_VERSION}
GPU_IMAGE=amd64/almalinux:8
DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="2_28"
;;
manylinux2_28-builder:cuda12*)
cuda-aarch64)
TARGET=cuda_final
GPU_IMAGE=amd64/almalinux:8
DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=13"
MANY_LINUX_VERSION="2_28"
;;
manylinuxaarch64-builder:cuda*)
TARGET=cuda_final
GPU_IMAGE=amd64/almalinux:8
DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=13"
DOCKER_TAG=cuda${GPU_ARCH_VERSION}
GPU_IMAGE=arm64v8/centos:7
DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="aarch64"
DOCKERFILE_SUFFIX="_cuda_aarch64"
;;
manylinux2_28-builder:rocm*)
rocm|rocm-manylinux_2_28)
TARGET=rocm_final
MANY_LINUX_VERSION="2_28"
DEVTOOLSET_VERSION="11"
GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
DOCKER_TAG=rocm${GPU_ARCH_VERSION}
GPU_IMAGE=rocm/dev-centos-7:${GPU_ARCH_VERSION}-complete
DEVTOOLSET_VERSION="9"
if [ ${GPU_ARCH_TYPE} == "rocm-manylinux_2_28" ]; then
MANY_LINUX_VERSION="2_28"
DEVTOOLSET_VERSION="11"
GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
fi
PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
;;
manylinux2_28-builder:xpu)
xpu)
TARGET=xpu_final
DOCKER_TAG=xpu
GPU_IMAGE=amd64/almalinux:8
DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
MANY_LINUX_VERSION="2_28"
;;
*)
echo "ERROR: Unrecognized image name: ${image}"
echo "ERROR: Unrecognized GPU_ARCH_TYPE: ${GPU_ARCH_TYPE}"
exit 1
;;
esac
IMAGES=''
if [[ -n ${MANY_LINUX_VERSION} && -z ${DOCKERFILE_SUFFIX} ]]; then
DOCKERFILE_SUFFIX=_${MANY_LINUX_VERSION}
fi
# Only activate this if in CI
if [ "$(uname -m)" != "s390x" ] && [ -v CI ]; then
# TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
# is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
sudo systemctl daemon-reload
sudo systemctl restart docker
(
set -x
# Only activate this if in CI
if [ "$(uname -m)" != "s390x" ] && [ -v CI ]; then
# TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
# is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
sudo systemctl daemon-reload
sudo systemctl restart docker
fi
DOCKER_BUILDKIT=1 docker build \
${DOCKER_GPU_BUILD_ARG} \
--build-arg "GPU_IMAGE=${GPU_IMAGE}" \
--target "${TARGET}" \
-t "${DOCKER_IMAGE}" \
$@ \
-f "${TOPDIR}/.ci/docker/manywheel/Dockerfile${DOCKERFILE_SUFFIX}" \
"${TOPDIR}/.ci/docker/"
)
GITHUB_REF=${GITHUB_REF:-"dev")}
GIT_BRANCH_NAME=${GITHUB_REF##*/}
GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE}-${GIT_BRANCH_NAME}
DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE}-${GIT_COMMIT_SHA}
if [[ "${WITH_PUSH}" == true ]]; then
(
set -x
docker push "${DOCKER_IMAGE}"
if [[ -n ${GITHUB_REF} ]]; then
docker tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_BRANCH_TAG}
docker tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_SHA_TAG}
docker push "${DOCKER_IMAGE_BRANCH_TAG}"
docker push "${DOCKER_IMAGE_SHA_TAG}"
fi
)
fi
tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
DOCKER_BUILDKIT=1 docker build \
${DOCKER_GPU_BUILD_ARG} \
--build-arg "GPU_IMAGE=${GPU_IMAGE}" \
--build-arg "OPENBLAS_VERSION=${OPENBLAS_VERSION}" \
--target "${TARGET}" \
-t "${tmp_tag}" \
$@ \
-f "${TOPDIR}/.ci/docker/manywheel/Dockerfile${DOCKERFILE_SUFFIX}" \
"${TOPDIR}/.ci/docker/"

View File

@ -97,7 +97,7 @@ find /opt/_internal -type f -print0 \
| xargs -0 -n1 strip --strip-unneeded 2>/dev/null || true
# We do not need the Python test suites, or indeed the precompiled .pyc and
# .pyo files. Partially cribbed from:
# https://github.com/docker-library/python/blob/master/3.4/slim/Dockerfile # @lint-ignore
# https://github.com/docker-library/python/blob/master/3.4/slim/Dockerfile
find /opt/_internal \
\( -type d -a -name test -o -name tests \) \
-o \( -type f -a -name '*.pyc' -o -name '*.pyo' \) \

View File

@ -2,7 +2,7 @@
# Helper utilities for build
# Script used only in CD pipeline
OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/ # @lint-ignore
OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/
CURL_DOWNLOAD_URL=https://curl.se/download
AUTOCONF_DOWNLOAD_URL=https://ftp.gnu.org/gnu/autoconf

View File

@ -41,11 +41,14 @@ fbscribelogger==0.1.7
#Pinned versions: 0.1.6
#test that import:
flatbuffers==24.12.23
flatbuffers==2.0 ; platform_machine != "s390x"
#Description: cross platform serialization library
#Pinned versions: 24.12.23
#Pinned versions: 2.0
#test that import:
flatbuffers ; platform_machine == "s390x"
#Description: cross platform serialization library; Newer version is required on s390x for new python version
hypothesis==5.35.1
# Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
#Description: advanced library for generating parametrized tests
@ -90,7 +93,7 @@ librosa>=0.6.2 ; python_version < "3.11"
#Pinned versions:
#test that import:
mypy==1.15.0
mypy==1.14.0
# Pin MyPy version because new errors are likely to appear with each release
#Description: linter
#Pinned versions: 1.14.0
@ -163,10 +166,10 @@ pillow==11.0.0
#Pinned versions: 10.3.0
#test that import:
protobuf==5.29.4
#Description: Google's data interchange format
#Pinned versions: 5.29.4
#test that import: test_tensorboard.py, test/onnx/*
protobuf==3.20.2
#Description: Googles data interchange format
#Pinned versions: 3.20.1
#test that import: test_tensorboard.py
psutil
#Description: information on running processes and system utilization
@ -334,12 +337,12 @@ sympy==1.13.3
#Pinned versions:
#test that import:
onnx==1.18.0
#Description: Required by onnx tests, and mypy and test_public_bindings.py when checking torch.onnx._internal
onnx==1.17.0
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
onnxscript==0.2.6
onnxscript==0.2.2
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
@ -376,6 +379,3 @@ dataclasses_json==0.6.7
#Description: required for data pipeline and scripts under tools/stats
#Pinned versions: 0.6.7
#test that import:
cmake==4.0.0
#Description: required for building

View File

@ -1,24 +1,15 @@
sphinx==5.3.0
#Description: This is used to generate PyTorch docs
#Pinned versions: 5.3.0
-e git+https://github.com/pytorch/pytorch_sphinx_theme.git@pytorch_sphinx_theme2#egg=pytorch_sphinx_theme2
-e git+https://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
# TODO: sphinxcontrib.katex 0.9.0 adds a local KaTeX server to speed up pre-rendering
# but it doesn't seem to work and hangs around idly. The initial thought is probably
# something related to Docker setup. We can investigate this later
sphinxcontrib.katex==0.8.6
#Description: This is used to generate PyTorch docs
#Pinned versions: 0.8.6
sphinxext-opengraph==0.9.1
#Description: This is used to generate PyTorch docs
#Pinned versions: 0.9.1
sphinx_sitemap==2.6.0
#Description: This is used to generate sitemap for PyTorch docs
#Pinned versions: 2.6.0
matplotlib==3.5.3
#Description: This is used to generate PyTorch docs
#Pinned versions: 3.5.3
@ -55,6 +46,5 @@ myst-nb==0.17.2
# The following are required to build torch.distributed.elastic.rendezvous.etcd* docs
python-etcd==0.4.5
sphinx-copybutton==0.5.0
sphinx-design==0.4.0
sphinxcontrib-mermaid==1.0.0
sphinx-panels==0.4.1
myst-parser==0.18.1

View File

@ -1 +1 @@
3.3.1
3.3.0

View File

@ -0,0 +1,184 @@
ARG UBUNTU_VERSION
ARG CUDA_VERSION
ARG IMAGE_NAME
FROM ${IMAGE_NAME} as base
ARG UBUNTU_VERSION
ARG CUDA_VERSION
ENV DEBIAN_FRONTEND noninteractive
# Install common dependencies (so that this step can be cached separately)
COPY ./common/install_base.sh install_base.sh
RUN bash ./install_base.sh && rm install_base.sh
# Install user
COPY ./common/install_user.sh install_user.sh
RUN bash ./install_user.sh && rm install_user.sh
# Install katex
ARG KATEX
COPY ./common/install_docs_reqs.sh install_docs_reqs.sh
RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
ARG CONDA_CMAKE
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
COPY ./common/install_conda.sh install_conda.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ./common/install_magma_conda.sh install_magma_conda.sh
RUN bash ./install_conda.sh && rm install_conda.sh install_magma_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
# Install gcc
ARG GCC_VERSION
COPY ./common/install_gcc.sh install_gcc.sh
RUN bash ./install_gcc.sh && rm install_gcc.sh
# Install clang
ARG CLANG_VERSION
COPY ./common/install_clang.sh install_clang.sh
RUN bash ./install_clang.sh && rm install_clang.sh
# (optional) Install protobuf for ONNX
ARG PROTOBUF
COPY ./common/install_protobuf.sh install_protobuf.sh
RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
RUN rm install_protobuf.sh
ENV INSTALLED_PROTOBUF ${PROTOBUF}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# (optional) Install UCC
ARG UCX_COMMIT
ARG UCC_COMMIT
ENV UCX_COMMIT $UCX_COMMIT
ENV UCC_COMMIT $UCC_COMMIT
ENV UCX_HOME /usr
ENV UCC_HOME /usr
ADD ./common/install_ucc.sh install_ucc.sh
RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
RUN rm install_ucc.sh
COPY ./common/install_openssl.sh install_openssl.sh
ENV OPENSSL_ROOT_DIR /opt/openssl
RUN bash ./install_openssl.sh
ENV OPENSSL_DIR /opt/openssl
ARG INDUCTOR_BENCHMARKS
ARG ANACONDA_PYTHON_VERSION
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/huggingface.txt huggingface.txt
COPY ci_commit_pins/timm.txt timm.txt
RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
RUN rm install_cmake.sh
ARG TRITON
FROM base as triton-builder
# Install triton, this needs to be done before sccache because the latter will
# try to reach out to S3, which docker build runners don't have access
COPY ./common/install_triton.sh install_triton.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/triton.txt triton.txt
COPY triton_version.txt triton_version.txt
RUN bash ./install_triton.sh
FROM base as final
COPY --from=triton-builder /opt/triton /opt/triton
RUN if [ -n "${TRITON}" ]; then pip install /opt/triton/*.whl; chown -R jenkins:jenkins /opt/conda; fi
RUN rm -rf /opt/triton
ARG HALIDE
# Build and install halide
COPY ./common/install_halide.sh install_halide.sh
COPY ./common/common_utils.sh common_utils.sh
COPY ci_commit_pins/halide.txt halide.txt
RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
RUN rm install_halide.sh common_utils.sh halide.txt
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH
# See https://github.com/pytorch/pytorch/issues/82174
# TODO(sdym@fb.com):
# check if this is needed after full off Xenial migration
ENV CARGO_NET_GIT_FETCH_WITH_CLI true
RUN bash ./install_cache.sh && rm install_cache.sh
ENV CMAKE_CUDA_COMPILER_LAUNCHER=/opt/cache/bin/sccache
# Add jni.h for java host build
COPY ./common/install_jni.sh install_jni.sh
COPY ./java/jni.h jni.h
RUN bash ./install_jni.sh && rm install_jni.sh
# Install Open MPI for CUDA
COPY ./common/install_openmpi.sh install_openmpi.sh
RUN if [ -n "${CUDA_VERSION}" ]; then bash install_openmpi.sh; fi
RUN rm install_openmpi.sh
# Include BUILD_ENVIRONMENT environment variable in image
ARG BUILD_ENVIRONMENT
ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
# AWS specific CUDA build guidance
ENV TORCH_CUDA_ARCH_LIST Maxwell
ENV TORCH_NVCC_FLAGS "-Xfatbin -compress-all"
ENV CUDA_PATH /usr/local/cuda
# Install LLVM dev version (Defined in the pytorch/builder github repository)
COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
# Install CUDNN
ARG CUDNN_VERSION
ARG CUDA_VERSION
COPY ./common/install_cudnn.sh install_cudnn.sh
RUN if [ -n "${CUDNN_VERSION}" ]; then bash install_cudnn.sh; fi
RUN rm install_cudnn.sh
# Install CUSPARSELT
ARG CUDA_VERSION
COPY ./common/install_cusparselt.sh install_cusparselt.sh
RUN bash install_cusparselt.sh
RUN rm install_cusparselt.sh
# Install NCCL
ARG CUDA_VERSION
COPY ./common/install_nccl.sh install_nccl.sh
COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
RUN bash install_nccl.sh
RUN rm install_nccl.sh /ci_commit_pins/nccl-cu*
ENV USE_SYSTEM_NCCL=1
ENV NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
ENV NCCL_LIB_DIR="/usr/local/cuda/lib64/"
# Install CUDSS
ARG CUDA_VERSION
COPY ./common/install_cudss.sh install_cudss.sh
RUN bash install_cudss.sh
RUN rm install_cudss.sh
# Delete /usr/local/cuda-11.X/cuda-11.X symlinks
RUN if [ -h /usr/local/cuda-11.6/cuda-11.6 ]; then rm /usr/local/cuda-11.6/cuda-11.6; fi
RUN if [ -h /usr/local/cuda-11.7/cuda-11.7 ]; then rm /usr/local/cuda-11.7/cuda-11.7; fi
RUN if [ -h /usr/local/cuda-12.1/cuda-12.1 ]; then rm /usr/local/cuda-12.1/cuda-12.1; fi
RUN if [ -h /usr/local/cuda-12.4/cuda-12.4 ]; then rm /usr/local/cuda-12.4/cuda-12.4; fi
USER jenkins
CMD ["bash"]

View File

@ -27,6 +27,7 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
ARG ANACONDA_PYTHON_VERSION
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
ARG CONDA_CMAKE
COPY requirements-ci.txt /opt/conda/requirements-ci.txt
COPY ./common/install_conda.sh install_conda.sh
COPY ./common/common_utils.sh common_utils.sh
@ -42,6 +43,13 @@ ARG CLANG_VERSION
COPY ./common/install_clang.sh install_clang.sh
RUN bash ./install_clang.sh && rm install_clang.sh
# (optional) Install protobuf for ONNX
ARG PROTOBUF
COPY ./common/install_protobuf.sh install_protobuf.sh
RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
RUN rm install_protobuf.sh
ENV INSTALLED_PROTOBUF ${PROTOBUF}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@ -100,6 +108,12 @@ COPY ci_commit_pins/timm.txt timm.txt
RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
RUN rm install_cmake.sh
# (optional) Install non-default Ninja version
ARG NINJA_VERSION
COPY ./common/install_ninja.sh install_ninja.sh

View File

@ -28,6 +28,7 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ARG DOCS
ARG BUILD_ENVIRONMENT
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
@ -83,6 +84,12 @@ RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
RUN rm install_cmake.sh
# (optional) Install non-default Ninja version
ARG NINJA_VERSION
COPY ./common/install_ninja.sh install_ninja.sh

View File

@ -28,6 +28,7 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
# Install conda and other packages (e.g., numpy, pytest)
ARG ANACONDA_PYTHON_VERSION
ARG CONDA_CMAKE
ARG DOCS
ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
@ -53,8 +54,7 @@ ARG CUDA_VERSION
COPY ./common/install_cuda.sh install_cuda.sh
COPY ./common/install_nccl.sh install_nccl.sh
COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
COPY ./common/install_cusparselt.sh install_cusparselt.sh
RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu* install_cusparselt.sh
RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu*
ENV DESIRED_CUDA ${CUDA_VERSION}
ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH
# No effect if cuda not installed
@ -74,6 +74,13 @@ ADD ./common/install_ucc.sh install_ucc.sh
RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
RUN rm install_ucc.sh
# (optional) Install protobuf for ONNX
ARG PROTOBUF
COPY ./common/install_protobuf.sh install_protobuf.sh
RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
RUN rm install_protobuf.sh
ENV INSTALLED_PROTOBUF ${PROTOBUF}
# (optional) Install vision packages like OpenCV
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@ -81,6 +88,12 @@ RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
ENV INSTALLED_VISION ${VISION}
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
RUN rm install_cmake.sh
# (optional) Install non-default Ninja version
ARG NINJA_VERSION
COPY ./common/install_ninja.sh install_ninja.sh

View File

@ -1,7 +1,7 @@
SHELL=/usr/bin/env bash
DOCKER_CMD ?= docker
DESIRED_ROCM ?= 6.4
DESIRED_ROCM ?= 6.3
DESIRED_ROCM_SHORT = $(subst .,,$(DESIRED_ROCM))
PACKAGE_NAME = magma-rocm
# inherit this from underlying docker image, do not pass this env var to docker
@ -12,24 +12,24 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
-w /builder \
-e PACKAGE_NAME=${PACKAGE_NAME}${DESIRED_ROCM_SHORT} \
-e DESIRED_ROCM=${DESIRED_ROCM} \
"pytorch/almalinux-builder:rocm${DESIRED_ROCM}" \
"pytorch/manylinux2_28-builder:rocm${DESIRED_ROCM}-main" \
magma-rocm/build_magma.sh
.PHONY: all
all: magma-rocm64
all: magma-rocm63
all: magma-rocm624
.PHONY:
clean:
$(RM) -r magma-*
$(RM) -r output
.PHONY: magma-rocm64
magma-rocm64: DESIRED_ROCM := 6.4
magma-rocm64:
$(DOCKER_RUN)
.PHONY: magma-rocm63
magma-rocm63: DESIRED_ROCM := 6.3
magma-rocm63:
$(DOCKER_RUN)
.PHONY: magma-rocm624
magma-rocm624: DESIRED_ROCM := 6.2.4
magma-rocm624:
$(DOCKER_RUN)

View File

@ -12,12 +12,13 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
-e PACKAGE_NAME=${PACKAGE_NAME}${DESIRED_CUDA_SHORT} \
-e DESIRED_CUDA=${DESIRED_CUDA} \
-e CUDA_ARCH_LIST="${CUDA_ARCH_LIST}" \
"pytorch/almalinux-builder:cuda${DESIRED_CUDA}-main" \
"pytorch/manylinux2_28-builder:cuda${DESIRED_CUDA}-main" \
magma/build_magma.sh
.PHONY: all
all: magma-cuda128
all: magma-cuda126
all: magma-cuda124
all: magma-cuda118
.PHONY:
@ -36,6 +37,11 @@ magma-cuda126: DESIRED_CUDA := 12.6
magma-cuda126:
$(DOCKER_RUN)
.PHONY: magma-cuda124
magma-cuda124: DESIRED_CUDA := 12.4
magma-cuda124:
$(DOCKER_RUN)
.PHONY: magma-cuda118
magma-cuda118: DESIRED_CUDA := 11.8
magma-cuda118: CUDA_ARCH_LIST += -gencode arch=compute_37,code=sm_37

View File

@ -18,10 +18,12 @@ retry () {
$* || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
}
PLATFORM=""
PLATFORM="manylinux2014_x86_64"
# TODO move this into the Docker images
OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
retry yum install -q -y zip openssl
elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
retry yum install -q -y zip openssl
PLATFORM="manylinux_2_28_x86_64"
elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
@ -34,9 +36,6 @@ elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
retry apt-get update
retry apt-get -y install zip openssl
else
echo "Unknown OS: '$OS_NAME'"
exit 1
fi
# We use the package name to test the package by passing this to 'pip install'
@ -80,6 +79,8 @@ if [[ -e /opt/openssl ]]; then
export CMAKE_INCLUDE_PATH="/opt/openssl/include":$CMAKE_INCLUDE_PATH
fi
mkdir -p /tmp/$WHEELHOUSE_DIR
export PATCHELF_BIN=/usr/local/bin/patchelf
@ -320,8 +321,8 @@ for pkg in /$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/torch*linux*.w
# ROCm workaround for roctracer dlopens
if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
patchedpath=$(fname_without_so_number $destpath)
# Keep the so number for XPU dependencies and libgomp.so.1 to avoid twice load
elif [[ "$DESIRED_CUDA" == *"xpu"* || "$filename" == "libgomp.so.1" ]]; then
# Keep the so number for XPU dependencies
elif [[ "$DESIRED_CUDA" == *"xpu"* ]]; then
patchedpath=$destpath
else
patchedpath=$(fname_with_sha256 $destpath)

View File

@ -15,9 +15,6 @@ export INSTALL_TEST=0 # dont install test binaries into site-packages
export USE_CUPTI_SO=0
export USE_CUSPARSELT=${USE_CUSPARSELT:-1} # Enable if not disabled by libtorch build
export USE_CUFILE=${USE_CUFILE:-1}
export USE_SYSTEM_NCCL=1
export NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
export NCCL_LIB_DIR="/usr/local/cuda/lib64/"
# Keep an array of cmake variables to add to
if [[ -z "$CMAKE_ARGS" ]]; then
@ -39,8 +36,10 @@ if [[ -n "$DESIRED_CUDA" ]]; then
if [[ ${DESIRED_CUDA} =~ ^[0-9]+\.[0-9]+$ ]]; then
CUDA_VERSION=${DESIRED_CUDA}
else
# cu126, cu128 etc...
if [[ ${#DESIRED_CUDA} -eq 5 ]]; then
# cu90, cu92, cu100, cu101
if [[ ${#DESIRED_CUDA} -eq 4 ]]; then
CUDA_VERSION="${DESIRED_CUDA:2:1}.${DESIRED_CUDA:3:1}"
elif [[ ${#DESIRED_CUDA} -eq 5 ]]; then
CUDA_VERSION="${DESIRED_CUDA:2:2}.${DESIRED_CUDA:4:1}"
fi
fi
@ -62,6 +61,10 @@ case ${CUDA_VERSION} in
TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
;;
12.4)
TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
;;
11.8)
TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};3.7;9.0"
EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
@ -88,15 +91,14 @@ fi
mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
else
echo "Unknown OS: '$OS_NAME'"
exit 1
fi
DEPS_LIST=(
@ -106,8 +108,26 @@ DEPS_SONAME=(
"libgomp.so.1"
)
# CUDA 11.8 have to ship the libcusparseLt.so.0 with the binary
# since nvidia-cusparselt-cu11 is not available in PYPI
if [[ $USE_CUSPARSELT == "1" && $CUDA_VERSION == "11.8" ]]; then
DEPS_SONAME+=(
"libcusparseLt.so.0"
)
DEPS_LIST+=(
"/usr/local/cuda/lib64/libcusparseLt.so.0"
)
fi
# CUDA_VERSION 12.6, 12.8
# Turn USE_CUFILE off for CUDA 11.8, 12.4 since nvidia-cufile-cu11 and 1.9.0.20 are
# not available in PYPI
if [[ $CUDA_VERSION == "11.8" || $CUDA_VERSION == "12.4" ]]; then
export USE_CUFILE=0
fi
# CUDA_VERSION 12.4, 12.6, 12.8
if [[ $CUDA_VERSION == 12* ]]; then
export USE_STATIC_CUDNN=0
# Try parallelizing nvcc as well
@ -131,8 +151,6 @@ if [[ $CUDA_VERSION == 12* ]]; then
"/usr/local/cuda/lib64/libnvToolsExt.so.1"
"/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"
)
DEPS_SONAME+=(
"libcudnn_adv.so.9"
@ -150,9 +168,17 @@ if [[ $CUDA_VERSION == 12* ]]; then
"libnvToolsExt.so.1"
"libnvrtc.so.12"
"libnvrtc-builtins.so"
"libcufile.so.0"
"libcufile_rdma.so.1"
)
if [[ $USE_CUFILE == 1 ]]; then
DEPS_LIST+=(
"/usr/local/cuda/lib64/libcufile.so.0"
"/usr/local/cuda/lib64/libcufile_rdma.so.1"
)
DEPS_SONAME+=(
"libcufile.so.0"
"libcufile_rdma.so.1"
)
fi
else
echo "Using nvidia libs from pypi."
CUDA_RPATHS=(
@ -165,43 +191,34 @@ if [[ $CUDA_VERSION == 12* ]]; then
'$ORIGIN/../../nvidia/curand/lib'
'$ORIGIN/../../nvidia/cusolver/lib'
'$ORIGIN/../../nvidia/cusparse/lib'
'$ORIGIN/../../nvidia/cusparselt/lib'
'$ORIGIN/../../cusparselt/lib'
'$ORIGIN/../../nvidia/nccl/lib'
'$ORIGIN/../../nvidia/nvshmem/lib'
'$ORIGIN/../../nvidia/nvtx/lib'
'$ORIGIN/../../nvidia/cufile/lib'
)
if [[ $USE_CUFILE == 1 ]]; then
CUDA_RPATHS+=(
'$ORIGIN/../../nvidia/cufile/lib'
)
fi
CUDA_RPATHS=$(IFS=: ; echo "${CUDA_RPATHS[*]}")
export C_SO_RPATH=$CUDA_RPATHS':$ORIGIN:$ORIGIN/lib'
export LIB_SO_RPATH=$CUDA_RPATHS':$ORIGIN'
export FORCE_RPATH="--force-rpath"
export USE_STATIC_NCCL=0
export USE_SYSTEM_NCCL=1
export ATEN_STATIC_CUDA=0
export USE_CUDA_STATIC_LINK=0
export USE_CUPTI_SO=1
export NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
export NCCL_LIB_DIR="/usr/local/cuda/lib64/"
fi
elif [[ $CUDA_VERSION == "11.8" ]]; then
export USE_STATIC_CUDNN=0
# Turn USE_CUFILE off for CUDA 11.8 since nvidia-cufile-cu11 and 1.9.0.20 are
# not available in PYPI
export USE_CUFILE=0
# Try parallelizing nvcc as well
export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"
# Bundle ptxas into the wheel, see https://github.com/pytorch/pytorch/pull/119750
export BUILD_BUNDLE_PTXAS=1
# CUDA 11.8 have to ship the libcusparseLt.so.0 with the binary
# since nvidia-cusparselt-cu11 is not available in PYPI
if [[ $USE_CUSPARSELT == "1" ]]; then
DEPS_SONAME+=(
"libcusparseLt.so.0"
)
DEPS_LIST+=(
"/usr/local/cuda/lib64/libcusparseLt.so.0"
)
fi
if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
echo "Bundling with cudnn and cublas."
DEPS_LIST+=(
@ -256,9 +273,12 @@ elif [[ $CUDA_VERSION == "11.8" ]]; then
export LIB_SO_RPATH=$CUDA_RPATHS':$ORIGIN'
export FORCE_RPATH="--force-rpath"
export USE_STATIC_NCCL=0
export USE_SYSTEM_NCCL=1
export ATEN_STATIC_CUDA=0
export USE_CUDA_STATIC_LINK=0
export USE_CUPTI_SO=1
export NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
export NCCL_LIB_DIR="/usr/local/cuda/lib64/"
fi
else
echo "Unknown cuda version $CUDA_VERSION"

View File

@ -22,7 +22,9 @@ retry () {
# TODO move this into the Docker images
OS_NAME=`awk -F= '/^NAME/{print $2}' /etc/os-release`
if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
retry yum install -q -y zip openssl
elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
retry yum install -q -y zip openssl
elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
retry dnf install -q -y zip openssl
@ -33,9 +35,6 @@ elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
sed -i 's/.*nvidia.*/# &/' $(find /etc/apt/ -type f -name "*.list")
retry apt-get update
retry apt-get -y install zip openssl
else
echo "Unknown OS: '$OS_NAME'"
exit 1
fi
# Version: setup.py uses $PYTORCH_BUILD_VERSION.post$PYTORCH_BUILD_NUMBER if

View File

@ -95,7 +95,6 @@ ROCM_SO_FILES=(
"libroctracer64.so"
"libroctx64.so"
"libhipblaslt.so"
"libhipsparselt.so"
"libhiprtc.so"
)
@ -187,28 +186,20 @@ do
OS_SO_FILES[${#OS_SO_FILES[@]}]=$file_name # Append lib to array
done
ARCH=$(echo $PYTORCH_ROCM_ARCH | sed 's/;/|/g') # Replace ; seperated arch list to bar for grep
# rocBLAS library files
ROCBLAS_LIB_SRC=$ROCM_HOME/lib/rocblas/library
ROCBLAS_LIB_DST=lib/rocblas/library
ROCBLAS_ARCH_SPECIFIC_FILES=$(ls $ROCBLAS_LIB_SRC | grep -E $ARCH)
ROCBLAS_OTHER_FILES=$(ls $ROCBLAS_LIB_SRC | grep -v gfx)
ROCBLAS_LIB_FILES=($ROCBLAS_ARCH_SPECIFIC_FILES $OTHER_FILES)
ARCH=$(echo $PYTORCH_ROCM_ARCH | sed 's/;/|/g') # Replace ; seperated arch list to bar for grep
ARCH_SPECIFIC_FILES=$(ls $ROCBLAS_LIB_SRC | grep -E $ARCH)
OTHER_FILES=$(ls $ROCBLAS_LIB_SRC | grep -v gfx)
ROCBLAS_LIB_FILES=($ARCH_SPECIFIC_FILES $OTHER_FILES)
# hipblaslt library files
HIPBLASLT_LIB_SRC=$ROCM_HOME/lib/hipblaslt/library
HIPBLASLT_LIB_DST=lib/hipblaslt/library
HIPBLASLT_ARCH_SPECIFIC_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -E $ARCH)
HIPBLASLT_OTHER_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -v gfx)
HIPBLASLT_LIB_FILES=($HIPBLASLT_ARCH_SPECIFIC_FILES $HIPBLASLT_OTHER_FILES)
# hipsparselt library files
HIPSPARSELT_LIB_SRC=$ROCM_HOME/lib/hipsparselt/library
HIPSPARSELT_LIB_DST=lib/hipsparselt/library
HIPSPARSELT_ARCH_SPECIFIC_FILES=$(ls $HIPSPARSELT_LIB_SRC | grep -E $ARCH)
#HIPSPARSELT_OTHER_FILES=$(ls $HIPSPARSELT_LIB_SRC | grep -v gfx)
HIPSPARSELT_LIB_FILES=($HIPSPARSELT_ARCH_SPECIFIC_FILES $HIPSPARSELT_OTHER_FILES)
ARCH_SPECIFIC_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -E $ARCH)
OTHER_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -v gfx)
HIPBLASLT_LIB_FILES=($ARCH_SPECIFIC_FILES $OTHER_FILES)
# ROCm library files
ROCM_SO_PATHS=()
@ -243,14 +234,12 @@ DEPS_SONAME=(
DEPS_AUX_SRCLIST=(
"${ROCBLAS_LIB_FILES[@]/#/$ROCBLAS_LIB_SRC/}"
"${HIPBLASLT_LIB_FILES[@]/#/$HIPBLASLT_LIB_SRC/}"
"${HIPSPARSELT_LIB_FILES[@]/#/$HIPSPARSELT_LIB_SRC/}"
"/opt/amdgpu/share/libdrm/amdgpu.ids"
)
DEPS_AUX_DSTLIST=(
"${ROCBLAS_LIB_FILES[@]/#/$ROCBLAS_LIB_DST/}"
"${HIPBLASLT_LIB_FILES[@]/#/$HIPBLASLT_LIB_DST/}"
"${HIPSPARSELT_LIB_FILES[@]/#/$HIPSPARSELT_LIB_DST/}"
"share/libdrm/amdgpu.ids"
)

View File

@ -20,11 +20,7 @@ fi
source /opt/intel/oneapi/compiler/latest/env/vars.sh
source /opt/intel/oneapi/pti/latest/env/vars.sh
source /opt/intel/oneapi/umf/latest/env/vars.sh
source /opt/intel/oneapi/ccl/latest/env/vars.sh
source /opt/intel/oneapi/mpi/latest/env/vars.sh
export USE_STATIC_MKL=1
export USE_ONEMKL=1
export USE_XCCL=1
WHEELHOUSE_DIR="wheelhousexpu"
LIBTORCH_HOUSE_DIR="libtorch_housexpu"

View File

@ -10,3 +10,5 @@ example: `py2-cuda9.0-cudnn7-ubuntu16.04`. The Docker images that are
built on Jenkins and are used in triggered builds already have this
environment variable set in their manifest. Also see
`./docker/jenkins/*/Dockerfile` and search for `BUILD_ENVIRONMENT`.
Our Jenkins installation is located at https://ci.pytorch.org/jenkins/.

View File

@ -52,6 +52,12 @@ fi
export USE_LLVM=/opt/llvm
export LLVM_DIR=/opt/llvm/lib/cmake/llvm
if [[ "$BUILD_ENVIRONMENT" == *executorch* ]]; then
# To build test_edge_op_registration
export BUILD_EXECUTORCH=ON
export USE_CUDA=0
fi
if ! which conda; then
# In ROCm CIs, we are doing cross compilation on build machines with
# intel cpu and later run tests on machines with amd cpu.
@ -165,12 +171,6 @@ fi
if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
# shellcheck disable=SC1091
source /opt/intel/oneapi/compiler/latest/env/vars.sh
# shellcheck disable=SC1091
source /opt/intel/oneapi/ccl/latest/env/vars.sh
# shellcheck disable=SC1091
source /opt/intel/oneapi/mpi/latest/env/vars.sh
# Enable XCCL build
export USE_XCCL=1
# XPU kineto feature dependencies are not fully ready, disable kineto build as temp WA
export USE_KINETO=0
export TORCH_XPU_ARCH_LIST=pvc
@ -301,18 +301,6 @@ else
fi
pip_install_whl "$(echo dist/*.whl)"
if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
echo "Checking that xpu is compiled"
pushd dist/
if python -c 'import torch; exit(0 if torch.xpu._is_compiled() else 1)'; then
echo "XPU support is compiled in."
else
echo "XPU support is NOT compiled in."
exit 1
fi
popd
fi
# TODO: I'm not sure why, but somehow we lose verbose commands
set -x

View File

@ -216,14 +216,6 @@ else
fi
fi
###############################################################################
# Check XPU configured correctly
###############################################################################
if [[ "$DESIRED_CUDA" == 'xpu' && "$PACKAGE_TYPE" != 'libtorch' ]]; then
echo "Checking that xpu is compiled"
python -c 'import torch; exit(0 if torch.xpu._is_compiled() else 1)'
fi
###############################################################################
# Check CUDA configured correctly
###############################################################################
@ -302,22 +294,19 @@ except RuntimeError as e:
fi
###############################################################################
# Check for C++ ABI compatibility to GCC-11 - GCC 13
# Check for C++ ABI compatibility to GCC-11
###############################################################################
if [[ "$(uname)" == 'Linux' && "$PACKAGE_TYPE" == 'manywheel' ]]; then
pushd /tmp
# Per https://gcc.gnu.org/onlinedocs/gcc/C_002b_002b-Dialect-Options.html
# gcc-11 is ABI16, gcc-13 is ABI18, gcc-14 is ABI19
# gcc 11 - CUDA 11.8, xpu, rocm
# gcc 13 - CUDA 12.6, 12.8 and cpu
# Please see issue for reference: https://github.com/pytorch/pytorch/issues/152426
if [[ "$(uname -m)" == "s390x" ]]; then
cxx_abi="19"
elif [[ "$DESIRED_CUDA" != 'cu118' && "$DESIRED_CUDA" != 'xpu' && "$DESIRED_CUDA" != 'rocm'* ]]; then
cxx_abi="18"
else
cxx_abi="16"
# Per https://gcc.gnu.org/onlinedocs/gcc/C_002b_002b-Dialect-Options.html gcc-11 is ABI16
# Though manylinux_2.28 should have been build with gcc-14, per
# https://github.com/pypa/manylinux?tab=readme-ov-file#manylinux_2_28-almalinux-8-based
# On s390x gcc 14 is used because it contains fix for interaction
# between precompiled headers and vectorization builtins.
# This fix is not available in earlier gcc versions.
# gcc-14 uses ABI19.
if [[ "$(uname -m)" != "s390x" ]]; then
python -c "import torch; exit(0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi1016' else 1)"
fi
python -c "import torch; exit(0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi10${cxx_abi}' else 1)"
popd
fi

View File

@ -13,6 +13,10 @@ if [[ "${BUILD_ENVIRONMENT}" == *rocm* ]]; then
# HIP_PLATFORM is auto-detected by hipcc; unset to avoid build errors
unset HIP_PLATFORM
export PYTORCH_TEST_WITH_ROCM=1
# temporary to locate some kernel issues on the CI nodes
export HSAKMT_DEBUG_LEVEL=4
# improve rccl performance for distributed tests
export HSA_FORCE_FINE_GRAIN_PCIE=1
fi
# TODO: Renable libtorch testing for MacOS, see https://github.com/pytorch/pytorch/issues/62598

View File

@ -1,50 +1,31 @@
#!/bin/bash
# Script for installing sccache on the xla build job, which uses xla's docker
# image, which has sccache installed but doesn't write the stubs. This is
# mostly copied from .ci/docker/install_cache.sh. Changes are: removing checks
# that will always return the same thing, ex checks for for rocm, CUDA, changing
# the path where sccache is installed, not changing /etc/environment, and not
# installing/downloading sccache as it is already in the docker image.
# image and doesn't have sccache installed on it. This is mostly copied from
# .ci/docker/install_cache.sh. Changes are: removing checks that will always
# return the same thing, ex checks for for rocm, CUDA, and changing the path
# where sccache is installed, and not changing /etc/environment.
set -ex -o pipefail
install_binary() {
echo "Downloading sccache binary from S3 repo"
curl --retry 3 https://s3.amazonaws.com/ossci-linux/sccache -o /tmp/cache/bin/sccache
}
mkdir -p /tmp/cache/bin
mkdir -p /tmp/cache/lib
export PATH="/tmp/cache/bin:$PATH"
install_binary
chmod a+x /tmp/cache/bin/sccache
function write_sccache_stub() {
# Unset LD_PRELOAD for ps because of asan + ps issues
# https://gcc.gnu.org/bugzilla/show_bug.cgi?id=90589
if [ "$1" == "gcc" ]; then
# Do not call sccache recursively when dumping preprocessor argument
# For some reason it's very important for the first cached nvcc invocation
cat >"/tmp/cache/bin/$1" <<EOF
#!/bin/sh
# sccache does not support -E flag, so we need to call the original compiler directly in order to avoid calling this wrapper recursively
for arg in "\$@"; do
if [ "\$arg" = "-E" ]; then
exec $(which "$1") "\$@"
fi
done
if [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
exec sccache $(which "$1") "\$@"
else
exec $(which "$1") "\$@"
fi
EOF
else
cat >"/tmp/cache/bin/$1" <<EOF
#!/bin/sh
if [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
exec sccache $(which "$1") "\$@"
else
exec $(which "$1") "\$@"
fi
EOF
fi
# shellcheck disable=SC2086
# shellcheck disable=SC2059
printf "#!/bin/sh\nif [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then\n exec sccache $(which $1) \"\$@\"\nelse\n exec $(which $1) \"\$@\"\nfi" > "/tmp/cache/bin/$1"
chmod a+x "/tmp/cache/bin/$1"
}

View File

@ -34,14 +34,11 @@ if which sccache > /dev/null; then
fi
print_cmake_info
if [[ ${BUILD_ENVIRONMENT} == *"distributed"* ]]; then
# Needed for inductor benchmarks, as lots of HF networks make `torch.distribtued` calls
USE_DISTRIBUTED=1 USE_OPENMP=1 WERROR=1 python setup.py bdist_wheel
else
# Explicitly set USE_DISTRIBUTED=0 to align with the default build config on mac. This also serves as the sole CI config that tests
# that building with USE_DISTRIBUTED=0 works at all. See https://github.com/pytorch/pytorch/issues/86448
USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel --plat-name macosx_11_0_arm64
fi
# Explicitly set USE_DISTRIBUTED=0 to align with the default build config on mac. This also serves as the sole CI config that tests
# that building with USE_DISTRIBUTED=0 works at all. See https://github.com/pytorch/pytorch/issues/86448
USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel
if which sccache > /dev/null; then
print_sccache_stats
fi

View File

@ -20,4 +20,14 @@ print_cmake_info() {
CONDA_INSTALLATION_DIR=$(dirname "$CMAKE_EXEC")
# Print all libraries under cmake rpath for debugging
ls -la "$CONDA_INSTALLATION_DIR/../lib"
export CMAKE_EXEC
# Explicitly add conda env lib folder to cmake rpath to address the flaky issue
# where cmake dependencies couldn't be found. This seems to point to how conda
# links $CMAKE_EXEC to its package cache when cloning a new environment
install_name_tool -add_rpath @executable_path/../lib "${CMAKE_EXEC}" || true
# Adding the rpath will invalidate cmake signature, so signing it again here
# to trust the executable. EXC_BAD_ACCESS (SIGKILL (Code Signature Invalid))
# with an exit code 137 otherwise
codesign -f -s - "${CMAKE_EXEC}" || true
}

View File

@ -42,16 +42,6 @@ test_python_all() {
assert_git_not_dirty
}
test_python_mps() {
setup_test_python
time python test/run_test.py --verbose --mps
MTL_CAPTURE_ENABLED=1 ${CONDA_RUN} python3 test/test_mps.py --verbose -k test_metal_capture
assert_git_not_dirty
}
test_python_shard() {
if [[ -z "$NUM_TEST_SHARDS" ]]; then
echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
@ -165,7 +155,6 @@ test_jit_hooks() {
torchbench_setup_macos() {
git clone --recursive https://github.com/pytorch/vision torchvision
git clone --recursive https://github.com/pytorch/audio torchaudio
brew install jpeg-turbo libpng
pushd torchvision
git fetch
@ -180,8 +169,7 @@ torchbench_setup_macos() {
git checkout "$(cat ../.github/ci_commit_pins/audio.txt)"
git submodule update --init --recursive
python setup.py clean
#TODO: Remove me, when figure out how to make TorchAudio find brew installed openmp
USE_OPENMP=0 python setup.py develop
python setup.py develop
popd
# Shellcheck doesn't like it when you pass no arguments to a function that can take args. See https://www.shellcheck.net/wiki/SC2120
@ -189,8 +177,9 @@ torchbench_setup_macos() {
checkout_install_torchbench
}
pip_benchmark_deps() {
python -mpip install --no-input astunparse requests cython scikit-learn
conda_benchmark_deps() {
conda install -y astunparse numpy scipy ninja pyyaml setuptools cmake typing-extensions requests protobuf numba cython scikit-learn
conda install -y -c conda-forge librosa
}
@ -198,7 +187,7 @@ test_torchbench_perf() {
print_cmake_info
echo "Launching torchbench setup"
pip_benchmark_deps
conda_benchmark_deps
torchbench_setup_macos
TEST_REPORTS_DIR=$(pwd)/test/test-reports
@ -225,62 +214,32 @@ test_torchbench_smoketest() {
print_cmake_info
echo "Launching torchbench setup"
pip_benchmark_deps
conda_benchmark_deps
# shellcheck disable=SC2119,SC2120
torchbench_setup_macos
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
local backend=eager
local dtype=notset
local device=mps
local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor)
local hf_models=(GoogleFnet YituTechConvBert Speech2Text2ForCausalLM)
for backend in eager inductor; do
touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
for dtype in notset float16 bfloat16; do
echo "Launching torchbench inference performance run for backend ${backend} and dtype ${dtype}"
local dtype_arg="--${dtype}"
if [ "$dtype" == notset ]; then
dtype_arg="--float32"
fi
touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
for model in "${models[@]}"; do
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
--performance --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv" || true
if [ "$backend" == "inductor" ]; then
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
--accuracy --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_accuracy.csv" || true
fi
done
for model in "${hf_models[@]}"; do
if [ "$backend" == "inductor" ]; then
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/huggingface.py \
--performance --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/inductor_${backend}_huggingface_${dtype}_inference_${device}_performance.csv" || true
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/huggingface.py \
--accuracy --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/inductor_${backend}_huggingface_${dtype}_inference_${device}_accuracy.csv" || true
fi
done
done
for dtype in notset amp; do
echo "Launching torchbench training performance run for backend ${backend} and dtype ${dtype}"
touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
local dtype_arg="--${dtype}"
if [ "$dtype" == notset ]; then
dtype_arg="--float32"
fi
for model in "${models[@]}"; do
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
--performance --only "$model" --backend "$backend" --training --devices "$device" "$dtype_arg" \
--output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv" || true
done
done
echo "Setup complete, launching torchbench training performance run"
for model in hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152; do
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
--performance --only "$model" --backend "$backend" --training --devices "$device" \
--output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
done
echo "Launching torchbench inference performance run"
for model in hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152; do
PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
--performance --only "$model" --backend "$backend" --inference --devices "$device" \
--output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
done
echo "Pytorch benchmark on mps device completed"
@ -290,7 +249,7 @@ test_hf_perf() {
print_cmake_info
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
pip_benchmark_deps
conda_benchmark_deps
torchbench_setup_macos
echo "Launching HuggingFace training perf run"
@ -306,7 +265,7 @@ test_timm_perf() {
print_cmake_info
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
pip_benchmark_deps
conda_benchmark_deps
torchbench_setup_macos
echo "Launching timm training perf run"
@ -332,8 +291,6 @@ elif [[ $TEST_CONFIG == *"perf_timm"* ]]; then
test_timm_perf
elif [[ $TEST_CONFIG == *"perf_smoketest"* ]]; then
test_torchbench_smoketest
elif [[ $TEST_CONFIG == *"mps"* ]]; then
test_python_mps
elif [[ $NUM_TEST_SHARDS -gt 1 ]]; then
test_python_shard "${SHARD_NUMBER}"
if [[ "${SHARD_NUMBER}" == 1 ]]; then

View File

@ -0,0 +1,22 @@
#!/bin/bash
set -e
run_test () {
rm -rf test_tmp/ && mkdir test_tmp/ && cd test_tmp/
"$@"
cd .. && rm -rf test_tmp/
}
get_runtime_of_command () {
TIMEFORMAT=%R
# runtime=$( { time ($@ &> /dev/null); } 2>&1 1>/dev/null)
runtime=$( { time "$@"; } 2>&1 1>/dev/null)
if [[ $runtime == *"Error"* ]]; then
exit 1
fi
runtime=${runtime#+++ $@}
runtime=$(python -c "print($runtime)")
echo "$runtime"
}

View File

@ -0,0 +1,91 @@
import argparse
import json
import math
import sys
parser = argparse.ArgumentParser()
parser.add_argument(
"--test-name", dest="test_name", action="store", required=True, help="test name"
)
parser.add_argument(
"--sample-stats",
dest="sample_stats",
action="store",
required=True,
help="stats from sample",
)
parser.add_argument(
"--update",
action="store_true",
help="whether to update baseline using stats from sample",
)
args = parser.parse_args()
test_name = args.test_name
if "cpu" in test_name:
backend = "cpu"
elif "gpu" in test_name:
backend = "gpu"
data_file_path = f"../{backend}_runtime.json"
with open(data_file_path) as data_file:
data = json.load(data_file)
if test_name in data:
mean = float(data[test_name]["mean"])
sigma = float(data[test_name]["sigma"])
else:
# Let the test pass if baseline number doesn't exist
mean = sys.maxsize
sigma = 0.001
print("population mean: ", mean)
print("population sigma: ", sigma)
# Let the test pass if baseline number is NaN (which happened in
# the past when we didn't have logic for catching NaN numbers)
if math.isnan(mean) or math.isnan(sigma):
mean = sys.maxsize
sigma = 0.001
sample_stats_data = json.loads(args.sample_stats)
sample_mean = float(sample_stats_data["mean"])
sample_sigma = float(sample_stats_data["sigma"])
print("sample mean: ", sample_mean)
print("sample sigma: ", sample_sigma)
if math.isnan(sample_mean):
raise Exception("""Error: sample mean is NaN""") # noqa: TRY002
elif math.isnan(sample_sigma):
raise Exception("""Error: sample sigma is NaN""") # noqa: TRY002
z_value = (sample_mean - mean) / sigma
print("z-value: ", z_value)
if z_value >= 3:
raise Exception( # noqa: TRY002
f"""\n
z-value >= 3, there is high chance of perf regression.\n
To reproduce this regression, run
`cd .ci/pytorch/perf_test/ && bash {test_name}.sh` on your local machine
and compare the runtime before/after your code change.
"""
)
else:
print("z-value < 3, no perf regression detected.")
if args.update:
print("We will use these numbers as new baseline.")
new_data_file_path = f"../new_{backend}_runtime.json"
with open(new_data_file_path) as new_data_file:
new_data = json.load(new_data_file)
new_data[test_name] = {}
new_data[test_name]["mean"] = sample_mean
new_data[test_name]["sigma"] = max(sample_sigma, sample_mean * 0.1)
with open(new_data_file_path, "w") as new_data_file:
json.dump(new_data, new_data_file, indent=4)

View File

@ -0,0 +1,18 @@
import json
import sys
import numpy
sample_data_list = sys.argv[1:]
sample_data_list = [float(v.strip()) for v in sample_data_list]
sample_mean = numpy.mean(sample_data_list)
sample_sigma = numpy.std(sample_data_list)
data = {
"mean": sample_mean,
"sigma": sample_sigma,
}
print(json.dumps(data))

View File

@ -0,0 +1,43 @@
#!/bin/bash
set -e
. ./common.sh
test_cpu_speed_mini_sequence_labeler () {
echo "Testing: mini sequence labeler, CPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/pytorch/benchmark.git
cd benchmark/
git checkout 726567a455edbfda6199445922a8cfee82535664
cd scripts/mini_sequence_labeler
SAMPLE_ARRAY=()
NUM_RUNS=$1
for (( i=1; i<=NUM_RUNS; i++ )) do
runtime=$(get_runtime_of_command python main.py)
SAMPLE_ARRAY+=("${runtime}")
done
cd ../../..
stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
echo "Runtime stats in seconds:"
echo "$stats"
if [ "$2" == "compare_with_baseline" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
elif [ "$2" == "compare_and_update" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_cpu_speed_mini_sequence_labeler "$@"
fi

View File

@ -0,0 +1,45 @@
#!/bin/bash
set -e
. ./common.sh
test_cpu_speed_mnist () {
echo "Testing: MNIST, CPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/pytorch/examples.git -b perftests
cd examples/mnist
conda install -c pytorch torchvision-cpu
# Download data
python main.py --epochs 0
SAMPLE_ARRAY=()
NUM_RUNS=$1
for (( i=1; i<=NUM_RUNS; i++ )) do
runtime=$(get_runtime_of_command python main.py --epochs 1 --no-log)
echo "$runtime"
SAMPLE_ARRAY+=("${runtime}")
done
cd ../..
stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
echo "Runtime stats in seconds:"
echo "$stats"
if [ "$2" == "compare_with_baseline" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
elif [ "$2" == "compare_and_update" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_cpu_speed_mnist "$@"
fi

View File

@ -0,0 +1,29 @@
#!/bin/bash
. ./common.sh
test_cpu_speed_torch () {
echo "Testing: torch.*, CPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/yf225/perf-tests.git
if [ "$1" == "compare_with_baseline" ]; then
export ARGS=(--compare ../cpu_runtime.json)
elif [ "$1" == "compare_and_update" ]; then
export ARGS=(--compare ../cpu_runtime.json --update ../new_cpu_runtime.json)
elif [ "$1" == "update_only" ]; then
export ARGS=(--update ../new_cpu_runtime.json)
fi
if ! python perf-tests/modules/test_cpu_torch.py "${ARGS[@]}"; then
echo "To reproduce this regression, run \`cd .ci/pytorch/perf_test/ && bash ${FUNCNAME[0]}.sh\` on your local machine and compare the runtime before/after your code change."
exit 1
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_cpu_speed_torch "$@"
fi

View File

@ -0,0 +1,29 @@
#!/bin/bash
. ./common.sh
test_cpu_speed_torch_tensor () {
echo "Testing: torch.Tensor.*, CPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/yf225/perf-tests.git
if [ "$1" == "compare_with_baseline" ]; then
export ARGS=(--compare ../cpu_runtime.json)
elif [ "$1" == "compare_and_update" ]; then
export ARGS=(--compare ../cpu_runtime.json --update ../new_cpu_runtime.json)
elif [ "$1" == "update_only" ]; then
export ARGS=(--update ../new_cpu_runtime.json)
fi
if ! python perf-tests/modules/test_cpu_torch_tensor.py "${ARGS[@]}"; then
echo "To reproduce this regression, run \`cd .ci/pytorch/perf_test/ && bash ${FUNCNAME[0]}.sh\` on your local machine and compare the runtime before/after your code change."
exit 1
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_cpu_speed_torch_tensor "$@"
fi

View File

@ -0,0 +1,44 @@
#!/bin/bash
set -e
. ./common.sh
test_gpu_speed_cudnn_lstm () {
echo "Testing: CuDNN LSTM, GPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/pytorch/benchmark.git
cd benchmark/
git checkout 43dfb2c0370e70ef37f249dc09aff9f0ccd2ddb0
cd scripts/
SAMPLE_ARRAY=()
NUM_RUNS=$1
for (( i=1; i<=NUM_RUNS; i++ )) do
runtime=$(get_runtime_of_command python cudnn_lstm.py --skip-cpu-governor-check)
echo "$runtime"
SAMPLE_ARRAY+=("${runtime}")
done
cd ../..
stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
echo "Runtime stats in seconds:"
echo "$stats"
if [ "$2" == "compare_with_baseline" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
elif [ "$2" == "compare_and_update" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_gpu_speed_cudnn_lstm "$@"
fi

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@ -0,0 +1,44 @@
#!/bin/bash
set -e
. ./common.sh
test_gpu_speed_lstm () {
echo "Testing: LSTM, GPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/pytorch/benchmark.git
cd benchmark/
git checkout 43dfb2c0370e70ef37f249dc09aff9f0ccd2ddb0
cd scripts/
SAMPLE_ARRAY=()
NUM_RUNS=$1
for (( i=1; i<=NUM_RUNS; i++ )) do
runtime=$(get_runtime_of_command python lstm.py --skip-cpu-governor-check)
echo "$runtime"
SAMPLE_ARRAY+=("${runtime}")
done
cd ../..
stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
echo "Runtime stats in seconds:"
echo "$stats"
if [ "$2" == "compare_with_baseline" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
elif [ "$2" == "compare_and_update" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_gpu_speed_lstm "$@"
fi

View File

@ -0,0 +1,44 @@
#!/bin/bash
set -e
. ./common.sh
test_gpu_speed_mlstm () {
echo "Testing: MLSTM, GPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/pytorch/benchmark.git
cd benchmark/
git checkout 43dfb2c0370e70ef37f249dc09aff9f0ccd2ddb0
cd scripts/
SAMPLE_ARRAY=()
NUM_RUNS=$1
for (( i=1; i<=NUM_RUNS; i++ )) do
runtime=$(get_runtime_of_command python mlstm.py --skip-cpu-governor-check)
echo "$runtime"
SAMPLE_ARRAY+=("${runtime}")
done
cd ../..
stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
echo "Runtime stats in seconds:"
echo "$stats"
if [ "$2" == "compare_with_baseline" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
elif [ "$2" == "compare_and_update" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_gpu_speed_mlstm "$@"
fi

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@ -0,0 +1,48 @@
#!/bin/bash
set -e
. ./common.sh
test_gpu_speed_mnist () {
echo "Testing: MNIST, GPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/pytorch/examples.git -b perftests
cd examples/mnist
conda install -c pytorch torchvision
# Download data
python main.py --epochs 0
SAMPLE_ARRAY=()
NUM_RUNS=$1
# Needs warm up to get accurate number
python main.py --epochs 1 --no-log
for (( i=1; i<=NUM_RUNS; i++ )) do
runtime=$(get_runtime_of_command python main.py --epochs 1 --no-log)
echo "$runtime"
SAMPLE_ARRAY+=("${runtime}")
done
cd ../..
stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
echo "Runtime stats in seconds:"
echo "$stats"
if [ "$2" == "compare_with_baseline" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
elif [ "$2" == "compare_and_update" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_gpu_speed_mnist "$@"
fi

View File

@ -0,0 +1,53 @@
#!/bin/bash
set -e
. ./common.sh
test_gpu_speed_word_language_model () {
echo "Testing: word language model on Wikitext-2, GPU"
export OMP_NUM_THREADS=4
export MKL_NUM_THREADS=4
git clone https://github.com/pytorch/examples.git -b perftests
cd examples/word_language_model
cd data/wikitext-2
# Reduce dataset size, so that we can have more runs per test
sed -n '1,200p' test.txt > test_tmp.txt
sed -n '1,1000p' train.txt > train_tmp.txt
sed -n '1,200p' valid.txt > valid_tmp.txt
mv test_tmp.txt test.txt
mv train_tmp.txt train.txt
mv valid_tmp.txt valid.txt
cd ../..
SAMPLE_ARRAY=()
NUM_RUNS=$1
for (( i=1; i<=NUM_RUNS; i++ )) do
runtime=$(get_runtime_of_command python main.py --cuda --epochs 1)
echo "$runtime"
SAMPLE_ARRAY+=("${runtime}")
done
cd ../..
stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
echo "Runtime stats in seconds:"
echo "$stats"
if [ "$2" == "compare_with_baseline" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
elif [ "$2" == "compare_and_update" ]; then
python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
fi
}
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
run_test test_gpu_speed_word_language_model "$@"
fi

View File

@ -0,0 +1,14 @@
import json
import sys
data_file_path = sys.argv[1]
commit_hash = sys.argv[2]
with open(data_file_path) as data_file:
data = json.load(data_file)
data["commit"] = commit_hash
with open(data_file_path, "w") as data_file:
json.dump(data, data_file)

View File

@ -119,6 +119,12 @@ popd
git rm -rf "$install_path" || true
mv "$pt_checkout/docs/build/html" "$install_path"
# Prevent Google from indexing $install_path/_modules. This folder contains
# generated source files.
# NB: the following only works on gnu sed. The sed shipped with mac os is different.
# One can `brew install gnu-sed` on a mac and then use "gsed" instead of "sed".
find "$install_path/_modules" -name "*.html" -print0 | xargs -0 sed -i '/<head>/a \ \ <meta name="robots" content="noindex">'
git add "$install_path" || true
git status
git config user.email "soumith+bot@pytorch.org"

View File

@ -76,7 +76,7 @@ fi
# Environment initialization
if [[ "$(uname)" == Darwin ]]; then
# Install the testing dependencies
retry pip install -q future hypothesis ${NUMPY_PACKAGE} ${PROTOBUF_PACKAGE} pytest setuptools six typing_extensions pyyaml
retry conda install -yq future hypothesis ${NUMPY_PACKAGE} ${PROTOBUF_PACKAGE} pytest setuptools six typing_extensions pyyaml
else
retry pip install -qr requirements.txt || true
retry pip install -q hypothesis protobuf pytest setuptools || true
@ -91,6 +91,7 @@ fi
echo "Testing with:"
pip freeze
conda list || true
##############################################################################
# Smoke tests

View File

@ -0,0 +1,71 @@
#!/bin/bash
SCRIPT_PARENT_DIR=$(dirname "${BASH_SOURCE[0]}")
# shellcheck source=.ci/pytorch/common.sh
source "$SCRIPT_PARENT_DIR/common.sh"
cd .ci/pytorch/perf_test
echo "Running CPU perf test for PyTorch..."
pip install -q awscli
# Set multipart_threshold to be sufficiently high, so that `aws s3 cp` is not a multipart read
# More info at https://github.com/aws/aws-cli/issues/2321
aws configure set default.s3.multipart_threshold 5GB
UPSTREAM_DEFAULT_BRANCH="$(git remote show https://github.com/pytorch/pytorch.git | awk '/HEAD branch/ {print $NF}')"
if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
# Get current default branch commit hash
DEFAULT_BRANCH_COMMIT_ID=$(git log --format="%H" -n 1)
export DEFAULT_BRANCH_COMMIT_ID
fi
# Find the default branch commit to test against
git remote add upstream https://github.com/pytorch/pytorch.git
git fetch upstream
IFS=$'\n'
while IFS='' read -r commit_id; do
if aws s3 ls s3://ossci-perf-test/pytorch/cpu_runtime/"${commit_id}".json; then
LATEST_TESTED_COMMIT=${commit_id}
break
fi
done < <(git rev-list upstream/"$UPSTREAM_DEFAULT_BRANCH")
aws s3 cp s3://ossci-perf-test/pytorch/cpu_runtime/"${LATEST_TESTED_COMMIT}".json cpu_runtime.json
if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
# Prepare new baseline file
cp cpu_runtime.json new_cpu_runtime.json
python update_commit_hash.py new_cpu_runtime.json "${DEFAULT_BRANCH_COMMIT_ID}"
fi
# Include tests
# shellcheck source=./perf_test/test_cpu_speed_mini_sequence_labeler.sh
. ./test_cpu_speed_mini_sequence_labeler.sh
# shellcheck source=./perf_test/test_cpu_speed_mnist.sh
. ./test_cpu_speed_mnist.sh
# shellcheck source=./perf_test/test_cpu_speed_torch.sh
. ./test_cpu_speed_torch.sh
# shellcheck source=./perf_test/test_cpu_speed_torch_tensor.sh
. ./test_cpu_speed_torch_tensor.sh
# Run tests
export TEST_MODE="compare_with_baseline"
if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
export TEST_MODE="compare_and_update"
fi
# Operator tests
run_test test_cpu_speed_torch ${TEST_MODE}
run_test test_cpu_speed_torch_tensor ${TEST_MODE}
# Sample model tests
run_test test_cpu_speed_mini_sequence_labeler 20 ${TEST_MODE}
run_test test_cpu_speed_mnist 20 ${TEST_MODE}
if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
# This could cause race condition if we are testing the same default branch commit twice,
# but the chance of them executing this line at the same time is low.
aws s3 cp new_cpu_runtime.json s3://ossci-perf-test/pytorch/cpu_runtime/"${DEFAULT_BRANCH_COMMIT_ID}".json --acl public-read
fi

View File

@ -0,0 +1,76 @@
#!/bin/bash
# shellcheck source=./common.sh
source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
pushd .ci/pytorch/perf_test
echo "Running GPU perf test for PyTorch..."
# Trying to uninstall PyYAML can cause problem. Workaround according to:
# https://github.com/pypa/pip/issues/5247#issuecomment-415571153
pip install -q awscli --ignore-installed PyYAML
# Set multipart_threshold to be sufficiently high, so that `aws s3 cp` is not a multipart read
# More info at https://github.com/aws/aws-cli/issues/2321
aws configure set default.s3.multipart_threshold 5GB
UPSTREAM_DEFAULT_BRANCH="$(git remote show https://github.com/pytorch/pytorch.git | awk '/HEAD branch/ {print $NF}')"
if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
# Get current default branch commit hash
DEFAULT_BRANCH_COMMIT_ID=$(git log --format="%H" -n 1)
export DEFAULT_BRANCH_COMMIT_ID
fi
# Find the default branch commit to test against
git remote add upstream https://github.com/pytorch/pytorch.git
git fetch upstream
IFS=$'\n'
while IFS='' read -r commit_id; do
if aws s3 ls s3://ossci-perf-test/pytorch/gpu_runtime/"${commit_id}".json; then
LATEST_TESTED_COMMIT=${commit_id}
break
fi
done < <(git rev-list upstream/"$UPSTREAM_DEFAULT_BRANCH")
aws s3 cp s3://ossci-perf-test/pytorch/gpu_runtime/"${LATEST_TESTED_COMMIT}".json gpu_runtime.json
if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
# Prepare new baseline file
cp gpu_runtime.json new_gpu_runtime.json
python update_commit_hash.py new_gpu_runtime.json "${DEFAULT_BRANCH_COMMIT_ID}"
fi
# Include tests
# shellcheck source=./perf_test/test_gpu_speed_mnist.sh
. ./test_gpu_speed_mnist.sh
# shellcheck source=./perf_test/test_gpu_speed_word_language_model.sh
. ./test_gpu_speed_word_language_model.sh
# shellcheck source=./perf_test/test_gpu_speed_cudnn_lstm.sh
. ./test_gpu_speed_cudnn_lstm.sh
# shellcheck source=./perf_test/test_gpu_speed_lstm.sh
. ./test_gpu_speed_lstm.sh
# shellcheck source=./perf_test/test_gpu_speed_mlstm.sh
. ./test_gpu_speed_mlstm.sh
# Run tests
if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
run_test test_gpu_speed_mnist 20 compare_and_update
run_test test_gpu_speed_word_language_model 20 compare_and_update
run_test test_gpu_speed_cudnn_lstm 20 compare_and_update
run_test test_gpu_speed_lstm 20 compare_and_update
run_test test_gpu_speed_mlstm 20 compare_and_update
else
run_test test_gpu_speed_mnist 20 compare_with_baseline
run_test test_gpu_speed_word_language_model 20 compare_with_baseline
run_test test_gpu_speed_cudnn_lstm 20 compare_with_baseline
run_test test_gpu_speed_lstm 20 compare_with_baseline
run_test test_gpu_speed_mlstm 20 compare_with_baseline
fi
if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
# This could cause race condition if we are testing the same default branch commit twice,
# but the chance of them executing this line at the same time is low.
aws s3 cp new_gpu_runtime.json s3://ossci-perf-test/pytorch/gpu_runtime/"${DEFAULT_BRANCH_COMMIT_ID}".json --acl public-read
fi
popd

View File

@ -1,77 +0,0 @@
import ctypes
import os
import sys
from pathlib import Path
def get_gomp_thread():
"""
Retrieves the maximum number of OpenMP threads after loading the `libgomp.so.1` library
and the `libtorch_cpu.so` library. It then queries the
maximum number of threads available for OpenMP parallel regions using the
`omp_get_max_threads` function.
Returns:
int: The maximum number of OpenMP threads available.
Notes:
- The function assumes the default path for `libgomp.so.1` on AlmaLinux OS.
- The path to `libtorch_cpu.so` is constructed based on the Python executable's
installation directory.
- This function is specific to environments where PyTorch and OpenMP are used
together and may require adjustments for other setups.
"""
python_path = Path(sys.executable).resolve()
python_prefix = (
python_path.parent.parent
) # Typically goes to the Python installation root
# Get the additional ABI flags (if any); it may be an empty string.
abiflags = getattr(sys, "abiflags", "")
# Construct the Python directory name correctly (e.g., "python3.13t").
python_version = (
f"python{sys.version_info.major}.{sys.version_info.minor}{abiflags}"
)
libtorch_cpu_path = (
python_prefix
/ "lib"
/ python_version
/ "site-packages"
/ "torch"
/ "lib"
/ "libtorch_cpu.so"
)
# use the default gomp path of AlmaLinux OS
libgomp_path = "/usr/lib64/libgomp.so.1"
# if it does not exist, try Ubuntu path
if not os.path.exists(libgomp_path):
libgomp_path = f"/usr/lib/{os.uname().machine}-linux-gnu/libgomp.so.1"
os.environ["GOMP_CPU_AFFINITY"] = "0-3"
libgomp = ctypes.CDLL(libgomp_path)
libgomp = ctypes.CDLL(libtorch_cpu_path)
libgomp.omp_get_max_threads.restype = ctypes.c_int
libgomp.omp_get_max_threads.argtypes = []
omp_max_threads = libgomp.omp_get_max_threads()
return omp_max_threads
def main():
omp_max_threads = get_gomp_thread()
print(
f"omp_max_threads after loading libgomp.so and libtorch_cpu.so: {omp_max_threads}"
)
if omp_max_threads == 1:
raise RuntimeError(
"omp_max_threads is 1. Check whether libgomp.so is loaded twice."
)
if __name__ == "__main__":
main()

View File

@ -191,10 +191,6 @@ if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
# shellcheck disable=SC1091
source /opt/intel/oneapi/umf/latest/env/vars.sh
fi
# shellcheck disable=SC1091
source /opt/intel/oneapi/ccl/latest/env/vars.sh
# shellcheck disable=SC1091
source /opt/intel/oneapi/mpi/latest/env/vars.sh
# Check XPU status before testing
xpu-smi discovery
fi
@ -318,18 +314,6 @@ test_python() {
assert_git_not_dirty
}
test_python_smoke() {
# Smoke tests for H100
time python test/run_test.py --include test_matmul_cuda inductor/test_fp8 inductor/test_max_autotune $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
assert_git_not_dirty
}
test_h100_distributed() {
# Distributed tests at H100
time python test/run_test.py --include distributed/_composable/test_composability/test_pp_composability.py $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
assert_git_not_dirty
}
test_lazy_tensor_meta_reference_disabled() {
export TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1
echo "Testing lazy tensor operations without meta reference"
@ -414,15 +398,8 @@ test_inductor_aoti() {
# We need to hipify before building again
python3 tools/amd_build/build_amd.py
fi
if [[ "$BUILD_ENVIRONMENT" == *sm86* ]]; then
BUILD_AOT_INDUCTOR_TEST=1 TORCH_CUDA_ARCH_LIST=8.6 USE_FLASH_ATTENTION=OFF python setup.py develop
# TODO: Replace me completely, as one should not use conda libstdc++, nor need special path to TORCH_LIB
LD_LIBRARY_PATH=/opt/conda/envs/py_3.10/lib/:${TORCH_LIB_DIR}:$LD_LIBRARY_PATH
CPP_TESTS_DIR="${BUILD_BIN_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference -dist=loadfile
else
BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference -dist=loadfile
fi
BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference
}
test_inductor_cpp_wrapper_shard() {
@ -437,11 +414,10 @@ test_inductor_cpp_wrapper_shard() {
if [[ "$1" -eq "2" ]]; then
# For now, manually put the opinfo tests in shard 2, and all other tests in
# shard 1. Run all CPU tests, as well as specific GPU tests triggering past
# bugs, for now.
# shard 1. Test specific things triggering past bugs, for now.
python test/run_test.py \
--include inductor/test_torchinductor_opinfo \
-k 'linalg or to_sparse or TestInductorOpInfoCPU' \
-k 'linalg or to_sparse' \
--verbose
exit
fi
@ -826,7 +802,16 @@ test_inductor_torchbench_smoketest_perf() {
done
}
test_inductor_get_core_number() {
if [[ "${TEST_CONFIG}" == *aarch64* ]]; then
echo "$(($(lscpu | grep 'Cluster(s):' | awk '{print $2}') * $(lscpu | grep 'Core(s) per cluster:' | awk '{print $4}')))"
else
echo "$(($(lscpu | grep 'Socket(s):' | awk '{print $2}') * $(lscpu | grep 'Core(s) per socket:' | awk '{print $4}')))"
fi
}
test_inductor_set_cpu_affinity(){
#set jemalloc
JEMALLOC_LIB="$(find /usr/lib -name libjemalloc.so.2)"
export LD_PRELOAD="$JEMALLOC_LIB":"$LD_PRELOAD"
export MALLOC_CONF="oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:-1,muzzy_decay_ms:-1"
@ -838,23 +823,14 @@ test_inductor_set_cpu_affinity(){
export KMP_AFFINITY=granularity=fine,compact,1,0
export KMP_BLOCKTIME=1
fi
# Use nproc here instead of lscpu because it takes into account cgroups slice
cpus=$(nproc)
thread_per_core=$(lscpu | grep 'Thread(s) per core:' | awk '{print $4}')
cores=$((cpus / thread_per_core))
# Set number of cores to 16 on aarch64 for performance runs
cores=$(test_inductor_get_core_number)
# Set number of cores to 16 on Aarch64 for performance runs.
if [[ "${TEST_CONFIG}" == *aarch64* && $cores -gt 16 ]]; then
cores=16
fi
export OMP_NUM_THREADS=$cores
# Handle cgroups slice start and end CPU
start_cpu=$(python -c 'import os; print(min(os.sched_getaffinity(0)))')
# Leaving one physical CPU for other tasks
end_cpu=$(($(python -c 'import os; print(max(os.sched_getaffinity(0)))') - thread_per_core))
export TASKSET="taskset -c $start_cpu-$end_cpu"
end_core=$((cores-1))
export TASKSET="taskset -c 0-$end_core"
}
test_inductor_torchbench_cpu_smoketest_perf(){
@ -1199,6 +1175,7 @@ build_xla() {
# These functions are defined in .circleci/common.sh in pytorch/xla repo
retry install_pre_deps_pytorch_xla $XLA_DIR $USE_CACHE
CMAKE_PREFIX_PATH="${SITE_PACKAGES}/torch:${CMAKE_PREFIX_PATH}" XLA_SANDBOX_BUILD=1 build_torch_xla $XLA_DIR
retry install_post_deps_pytorch_xla
assert_git_not_dirty
}
@ -1500,6 +1477,8 @@ test_executorch() {
export PYTHON_EXECUTABLE=python
export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
# For llama3
bash examples/models/llama3_2_vision/install_requirements.sh
# NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
# from the PR
bash .ci/scripts/setup-linux.sh --build-tool cmake
@ -1526,7 +1505,7 @@ test_executorch() {
test_linux_aarch64() {
python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
test_transformers test_multiprocessing test_numpy_interop test_autograd test_binary_ufuncs test_complex test_spectral_ops \
test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops test_cpp_extensions_open_device_registration \
test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
--shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
# Dynamo tests
@ -1542,7 +1521,7 @@ test_linux_aarch64() {
inductor/test_inplacing_pass inductor/test_kernel_benchmark inductor/test_layout_optim \
inductor/test_max_autotune inductor/test_memory_planning inductor/test_metrics inductor/test_multi_kernel inductor/test_pad_mm \
inductor/test_pattern_matcher inductor/test_perf inductor/test_profiler inductor/test_select_algorithm inductor/test_smoke \
inductor/test_split_cat_fx_passes inductor/test_compile inductor/test_torchinductor \
inductor/test_split_cat_fx_passes inductor/test_standalone_compile inductor/test_torchinductor \
inductor/test_torchinductor_codegen_dynamic_shapes inductor/test_torchinductor_dynamic_shapes inductor/test_memory \
inductor/test_triton_cpu_backend inductor/test_triton_extension_backend inductor/test_mkldnn_pattern_matcher inductor/test_cpu_cpp_wrapper \
--shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
@ -1560,8 +1539,7 @@ test_operator_benchmark() {
cd "${TEST_DIR}"/benchmarks/operator_benchmark
$TASKSET python -m benchmark_all_test --device "$1" --tag-filter "$2" \
--output-csv "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.csv" \
--output-json-for-dashboard "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.json" \
--output-dir "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.csv"
pip_install pandas
python check_perf_csv.py \
@ -1646,7 +1624,7 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
install_torchaudio cuda
fi
install_torchvision
TORCH_CUDA_ARCH_LIST="8.0;8.6" install_torchao
TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install git+https://github.com/pytorch/ao.git
id=$((SHARD_NUMBER-1))
# https://github.com/opencv/opencv-python/issues/885
pip_install opencv-python==4.8.0.74
@ -1729,10 +1707,6 @@ elif [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
test_python
test_aten
test_xpu_bin
elif [[ "${TEST_CONFIG}" == smoke ]]; then
test_python_smoke
elif [[ "${TEST_CONFIG}" == h100_distributed ]]; then
test_h100_distributed
else
install_torchvision
install_monkeytype

View File

@ -37,11 +37,6 @@ call %INSTALLER_DIR%\activate_miniconda3.bat
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
:: Update CMake
call choco upgrade -y cmake --no-progress --installargs 'ADD_CMAKE_TO_PATH=System' --apply-install-arguments-to-dependencies --version=3.27.9
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
call pip install mkl-include==2021.4.0 mkl-devel==2021.4.0
if errorlevel 1 goto fail
if not errorlevel 0 goto fail
@ -93,7 +88,7 @@ set PATH=%CUDA_PATH%\bin;%CUDA_PATH%\libnvvp;%PATH%
:cuda_build_end
set DISTUTILS_USE_SDK=1
set PATH=%TMP_DIR_WIN%\bin;C:\Program Files\CMake\bin;%PATH%
set PATH=%TMP_DIR_WIN%\bin;%PATH%
:: The latest Windows CUDA test is running on AWS G5 runner with A10G GPU
if "%TORCH_CUDA_ARCH_LIST%" == "" set TORCH_CUDA_ARCH_LIST=8.6

View File

@ -24,7 +24,7 @@ if "%CUDA_SUFFIX%" == "" (
if "%REBUILD%"=="" (
if "%BUILD_ENVIRONMENT%"=="" (
curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --output %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z & REM @lint-ignore
curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --output %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z
) else (
aws s3 cp s3://ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --quiet
)

View File

@ -38,7 +38,7 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
fi
# TODO: Move both of them to Windows AMI
python -m pip install pytest-rerunfailures==10.3 pytest-cpp==2.3.0 tensorboard==2.13.0 protobuf==5.29.4 pytest-subtests==0.13.1
python -m pip install pytest-rerunfailures==10.3 pytest-cpp==2.3.0 tensorboard==2.13.0 pytest-subtests==0.13.1
# Install Z3 optional dependency for Windows builds.
python -m pip install z3-solver==4.12.2.0

View File

@ -7,7 +7,7 @@ if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
:: activate visual studio
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" arm64
call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
where cl.exe
cd %DEPENDENCIES_DIR%

View File

@ -7,7 +7,7 @@ if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
:: activate visual studio
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" arm64
call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
where cl.exe
:: Clone OpenBLAS

View File

@ -2,7 +2,7 @@
cd %PYTORCH_ROOT%
:: activate visual studio
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" arm64
call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
where cl.exe
:: create virtual environment

View File

@ -21,7 +21,7 @@ if %ENABLE_APL% == 1 (
)
:: activate visual studio
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" arm64
call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
where cl.exe
:: change to source directory

View File

@ -21,7 +21,7 @@ if %ENABLE_APL% == 1 (
)
:: activate visual studio
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" arm64
call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
where cl.exe
:: change to source directory

View File

@ -33,7 +33,7 @@ pushd tmp
set VC_VERSION_LOWER=14
set VC_VERSION_UPPER=36
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" arm64
call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
set install_root=%CD%
set INCLUDE=%INCLUDE%;%install_root%\include;%install_root%\include\torch\csrc\api\include

View File

@ -1,7 +1,7 @@
@echo off
:: This script parses args, installs required libraries (MKL, Magma, libuv)
:: and then delegates to cpu.bat, cuda80.bat, etc.
:: This script parses args, installs required libraries (miniconda, MKL,
:: Magma), and then delegates to cpu.bat, cuda80.bat, etc.
if not "%CUDA_VERSION%" == "" if not "%PYTORCH_BUILD_VERSION%" == "" if not "%PYTORCH_BUILD_NUMBER%" == "" goto env_end
if "%~1"=="" goto arg_error
@ -36,18 +36,28 @@ set DESIRED_PYTHON_PREFIX=py%DESIRED_PYTHON_PREFIX:;=;py%
set SRC_DIR=%~dp0
pushd %SRC_DIR%
:: Install Miniconda3
set "CONDA_HOME=%CD%\conda"
set "tmp_conda=%CONDA_HOME%"
set "miniconda_exe=%CD%\miniconda.exe"
rmdir /s /q conda
del miniconda.exe
curl --retry 3 -k https://repo.anaconda.com/miniconda/Miniconda3-py311_23.9.0-0-Windows-x86_64.exe -o "%miniconda_exe%"
start /wait "" "%miniconda_exe%" /S /InstallationType=JustMe /RegisterPython=0 /AddToPath=0 /D=%tmp_conda%
if ERRORLEVEL 1 exit /b 1
set "ORIG_PATH=%PATH%"
set "PATH=%CONDA_HOME%;%CONDA_HOME%\scripts;%CONDA_HOME%\Library\bin;%PATH%"
:: setup build environment
:: create a new conda environment and install packages
:try
SET /A tries=3
:loop
IF %tries% LEQ 0 GOTO :exception
call setup_build.bat
call condaenv.bat
IF %ERRORLEVEL% EQU 0 GOTO :done
SET /A "tries=%tries%-1"
:exception
echo "Failed to setup build environment"
echo "Failed to create conda env"
exit /B 1
:done
@ -63,7 +73,7 @@ if "%DEBUG%" == "1" (
if not "%CUDA_VERSION%" == "cpu" if not "%CUDA_VERSION%" == "xpu" (
rmdir /s /q magma_%CUDA_PREFIX%_%BUILD_TYPE%
del magma_%CUDA_PREFIX%_%BUILD_TYPE%.7z
curl -k https://s3.amazonaws.com/ossci-windows/magma_%MAGMA_VERSION%_%CUDA_PREFIX%_%BUILD_TYPE%.7z -o magma_%CUDA_PREFIX%_%BUILD_TYPE%.7z %= @lint-ignore =%
curl -k https://s3.amazonaws.com/ossci-windows/magma_%MAGMA_VERSION%_%CUDA_PREFIX%_%BUILD_TYPE%.7z -o magma_%CUDA_PREFIX%_%BUILD_TYPE%.7z
7z x -aoa magma_%CUDA_PREFIX%_%BUILD_TYPE%.7z -omagma_%CUDA_PREFIX%_%BUILD_TYPE%
)
@ -97,20 +107,19 @@ set TH_BINARY_BUILD=1
set INSTALL_TEST=0
for %%v in (%DESIRED_PYTHON_PREFIX%) do (
:: Set Environment vars for the build
set "CMAKE_PREFIX_PATH=%CD%\Python\Library\;%PATH%"
set "PYTHON_LIB_PATH=%CD%\Python\Library\bin"
:: Activate Python Environment
set PYTHON_PREFIX=%%v
set "CONDA_LIB_PATH=%CONDA_HOME%\envs\%%v\Library\bin"
if not "%ADDITIONAL_PATH%" == "" (
set "PATH=%ADDITIONAL_PATH%;%PATH%"
set "PATH=%ADDITIONAL_PATH%;%CONDA_HOME%\envs\%%v;%CONDA_HOME%\envs\%%v\scripts;%CONDA_HOME%\envs\%%v\Library\bin;%ORIG_PATH%"
) else (
set "PATH=%CONDA_HOME%\envs\%%v;%CONDA_HOME%\envs\%%v\scripts;%CONDA_HOME%\envs\%%v\Library\bin;%ORIG_PATH%"
)
pip install ninja
@setlocal
:: Set Flags
if not "%CUDA_VERSION%"=="cpu" if not "%CUDA_VERSION%" == "xpu" (
set "MAGMA_HOME=%cd%\magma_%CUDA_PREFIX%_%BUILD_TYPE%"
set MAGMA_HOME=%cd%\magma_%CUDA_PREFIX%_%BUILD_TYPE%
)
echo "Calling arch build script"
call %CUDA_PREFIX%.bat

View File

@ -0,0 +1,27 @@
IF "%DESIRED_PYTHON%"=="" (
echo DESIRED_PYTHON is NOT defined.
exit /b 1
)
:: Create a new conda environment
setlocal EnableDelayedExpansion
FOR %%v IN (%DESIRED_PYTHON%) DO (
set PYTHON_VERSION_STR=%%v
set PYTHON_VERSION_STR=!PYTHON_VERSION_STR:.=!
conda remove -n py!PYTHON_VERSION_STR! --all -y || rmdir %CONDA_HOME%\envs\py!PYTHON_VERSION_STR! /s
if "%%v" == "3.9" call conda create -n py!PYTHON_VERSION_STR! -y numpy=2.0.1 boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
if "%%v" == "3.10" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.0.1 boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
if "%%v" == "3.11" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.0.1 boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
if "%%v" == "3.12" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.0.1 boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
if "%%v" == "3.13" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.1.2 boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
if "%%v" == "3.13t" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.1.2 boto3 cmake ninja typing_extensions setuptools=72.1.0 python-freethreading python=3.13
call conda run -n py!PYTHON_VERSION_STR! pip install pyyaml
call conda run -n py!PYTHON_VERSION_STR! pip install mkl-include
call conda run -n py!PYTHON_VERSION_STR! pip install mkl-static
)
endlocal
:: Install libuv
conda install -y -q -c conda-forge libuv=1.39
set libuv_ROOT=%CONDA_HOME%\Library
echo libuv_ROOT=%libuv_ROOT%

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