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Author SHA1 Message Date
bd14a05729 [dynamo] Allow inlining of hooks for the top module
ghstack-source-id: 51408faf9d8b5f054544107f38316f2ccf1f7a3a
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124501
2024-05-10 10:04:37 -07:00
7af546f53f [wip][inductor] Fix batch fusion pass
ghstack-source-id: e6872d4b64bf35d3cfe98cf816b8eaab983fc256
Pull Request resolved: https://github.com/pytorch/pytorch/pull/125935
2024-05-10 10:04:37 -07:00
4636 changed files with 233568 additions and 96708 deletions

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@ -1,5 +0,0 @@
0.6b
manylinux_2_17
rocm6
04b5df8c8123f90cba3ede7e971e6fbc6040d506
3db6ecbc915893ff967abd6e1b43bd5f54949868873be60dc802086c3863e648

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@ -84,30 +84,16 @@ fi
# CMake 3.18 is needed to support CUDA17 language variant
CMAKE_VERSION=3.18.5
_UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
_UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
_UCX_COMMIT=00bcc6bb18fc282eb160623b4c0d300147f579af
_UCC_COMMIT=7cb07a76ccedad7e56ceb136b865eb9319c258ea
# 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 "$image" in
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.0
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
@ -119,24 +105,9 @@ case "$image" in
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.0
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks)
pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
@ -149,39 +120,9 @@ case "$image" in
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
CUDA_VERSION=12.4.0
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.12
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
pytorch-linux-focal-cuda11.8-cudnn8-py3-gcc9)
CUDA_VERSION=11.8.0
CUDNN_VERSION=9
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
@ -193,37 +134,9 @@ case "$image" in
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.0
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9)
CUDA_VERSION=12.1.1
CUDNN_VERSION=9
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
DB=yes
VISION=yes
KATEX=yes
UCX_COMMIT=${_UCX_COMMIT}
UCC_COMMIT=${_UCC_COMMIT}
CONDA_CMAKE=yes
TRITON=yes
;;
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
CUDA_VERSION=12.4.0
CUDNN_VERSION=9
CUDNN_VERSION=8
ANACONDA_PYTHON_VERSION=3.10
GCC_VERSION=9
PROTOBUF=yes
@ -313,7 +226,7 @@ case "$image" in
PROTOBUF=yes
DB=yes
VISION=yes
XPU_VERSION=0.5
BASEKIT_VERSION=2024.0.0-49522
NINJA_VERSION=1.9.0
CONDA_CMAKE=yes
TRITON=yes
@ -330,10 +243,10 @@ case "$image" in
DOCS=yes
INDUCTOR_BENCHMARKS=yes
;;
pytorch-linux-jammy-cuda11.8-cudnn9-py3.8-clang12)
pytorch-linux-jammy-cuda11.8-cudnn8-py3.8-clang12)
ANACONDA_PYTHON_VERSION=3.8
CUDA_VERSION=11.8
CUDNN_VERSION=9
CUDNN_VERSION=8
CLANG_VERSION=12
PROTOBUF=yes
DB=yes
@ -380,7 +293,7 @@ case "$image" in
ANACONDA_PYTHON_VERSION=3.9
CONDA_CMAKE=yes
;;
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
pytorch-linux-jammy-cuda11.8-cudnn8-py3.9-linter)
ANACONDA_PYTHON_VERSION=3.9
CUDA_VERSION=11.8
CONDA_CMAKE=yes
@ -447,7 +360,7 @@ tmp_tag=$(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
if [[ ${CUDNN_VERSION} == 8 ]]; then
IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
fi
fi
@ -490,7 +403,7 @@ docker build \
--build-arg "DOCS=${DOCS}" \
--build-arg "INDUCTOR_BENCHMARKS=${INDUCTOR_BENCHMARKS}" \
--build-arg "EXECUTORCH=${EXECUTORCH}" \
--build-arg "XPU_VERSION=${XPU_VERSION}" \
--build-arg "BASEKIT_VERSION=${BASEKIT_VERSION}" \
--build-arg "ACL=${ACL:-}" \
--build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
--build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
@ -499,7 +412,7 @@ docker build \
"$@" \
.
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn8-devel-ubuntu18.04-rc`,
# for this case we will set UBUNTU_VERSION to `18.04-rc` so that the Dockerfile could
# find the correct image. As a result, here we have to replace the
# "$UBUNTU_VERSION" == "18.04-rc"

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@ -62,7 +62,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@ -77,9 +77,6 @@ RUN rm install_rocm.sh
COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
RUN bash ./install_rocm_magma.sh
RUN rm install_rocm_magma.sh
COPY ./common/install_amdsmi.sh install_amdsmi.sh
RUN bash ./install_amdsmi.sh
RUN rm install_amdsmi.sh
ENV PATH /opt/rocm/bin:$PATH
ENV PATH /opt/rocm/hcc/bin:$PATH
ENV PATH /opt/rocm/hip/bin:$PATH
@ -113,13 +110,6 @@ COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton-rocm.txt triton_version.txt
# Install AOTriton (Early fail)
COPY ./aotriton_version.txt aotriton_version.txt
COPY ./common/common_utils.sh common_utils.sh
COPY ./common/install_aotriton.sh install_aotriton.sh
RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
# 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

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@ -1 +1 @@
01cbe5045a6898c9a925f01435c8277b2fe6afcc
bbe6246e37d8aa791c67daaf9d9d61b26c9ccfdc

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@ -1,6 +1,6 @@
set -euo pipefail
readonly version=v24.04
readonly version=v23.08
readonly src_host=https://review.mlplatform.org/ml
readonly src_repo=ComputeLibrary

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@ -1,5 +0,0 @@
#!/bin/bash
set -ex
cd /opt/rocm/share/amd_smi && pip install .

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@ -1,23 +0,0 @@
#!/bin/bash
set -ex
source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
TARBALL='aotriton.tar.bz2'
# This read command alwasy returns with exit code 1
read -d "\n" VER MANYLINUX ROCMBASE PINNED_COMMIT SHA256 < aotriton_version.txt || true
ARCH=$(uname -m)
AOTRITON_INSTALL_PREFIX="$1"
AOTRITON_URL="https://github.com/ROCm/aotriton/releases/download/${VER}/aotriton-${VER}-${MANYLINUX}_${ARCH}-${ROCMBASE}.tar.bz2"
cd "${AOTRITON_INSTALL_PREFIX}"
# Must use -L to follow redirects
curl -L --retry 3 -o "${TARBALL}" "${AOTRITON_URL}"
ACTUAL_SHA256=$(sha256sum "${TARBALL}" | cut -d " " -f 1)
if [ "${SHA256}" != "${ACTUAL_SHA256}" ]; then
echo -n "Error: The SHA256 of downloaded tarball is ${ACTUAL_SHA256},"
echo " which does not match the expected value ${SHA256}."
exit
fi
tar xf "${TARBALL}" && rm -rf "${TARBALL}"

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@ -3,7 +3,7 @@
set -ex
install_ubuntu() {
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
# NVIDIA dockers for RC releases use tag names like `11.0-cudnn8-devel-ubuntu18.04-rc`,
# for this case we will set UBUNTU_VERSION to `18.04-rc` so that the Dockerfile could
# find the correct image. As a result, here we have to check for
# "$UBUNTU_VERSION" == "18.04"*

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@ -1,18 +1,20 @@
#!/bin/bash
if [[ -n "${CUDNN_VERSION}" ]]; then
if [[ ${CUDNN_VERSION} == 8 ]]; then
# cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
mkdir tmp_cudnn
pushd tmp_cudnn
if [[ ${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"
if [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-8.9.2.26_cuda12-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${CUDNN_NAME}.tar.xz
elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
CUDNN_NAME="cudnn-linux-x86_64-8.7.0.84_cuda11-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/redist/cudnn/v8.7.0/local_installers/11.8/${CUDNN_NAME}.tar.xz
else
print "Unsupported CUDA version ${CUDA_VERSION}"
exit 1
fi
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${CUDNN_NAME}.tar.xz
tar xf ${CUDNN_NAME}.tar.xz
cp -a ${CUDNN_NAME}/include/* /usr/local/cuda/include/
cp -a ${CUDNN_NAME}/lib/* /usr/local/cuda/lib64/

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@ -5,14 +5,9 @@ set -ex
# cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
mkdir tmp_cusparselt && cd tmp_cusparselt
if [[ ${CUDA_VERSION:0:4} =~ ^12\.[1-4]$ ]]; 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-${arch_path}-0.5.2.1-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
if [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.5.2.1-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/${CUSPARSELT_NAME}.tar.xz
elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.4.0.7-archive"
curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/${CUSPARSELT_NAME}.tar.xz

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@ -30,10 +30,10 @@ pip_install \
pip_install coloredlogs packaging
pip_install onnxruntime==1.18
pip_install onnx==1.16.0
pip_install onnxruntime==1.17.0
pip_install onnx==1.15.0
# pip_install "onnxscript@git+https://github.com/microsoft/onnxscript@3e869ef8ccf19b5ebd21c10d3e9c267c9a9fa729" --no-deps
pip_install onnxscript==0.1.0.dev20240523 --no-deps
pip_install onnxscript==0.1.0.dev20240315 --no-deps
# 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/

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@ -6,6 +6,9 @@ ver() {
printf "%3d%03d%03d%03d" $(echo "$1" | tr '.' ' ');
}
# Map ROCm version to AMDGPU version
declare -A AMDGPU_VERSIONS=( ["5.0"]="21.50" ["5.1.1"]="22.10.1" ["5.2"]="22.20" )
install_ubuntu() {
apt-get update
if [[ $UBUNTU_VERSION == 18.04 ]]; then
@ -23,14 +26,31 @@ install_ubuntu() {
apt-get install -y libc++1
apt-get install -y libc++abi1
# 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
if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
# Add amdgpu repository
UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
local amdgpu_baseurl
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu"
else
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/ubuntu"
fi
echo "deb [arch=amd64] ${amdgpu_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
fi
ROCM_REPO="ubuntu"
if [[ $(ver $ROCM_VERSION) -lt $(ver 4.2) ]]; then
ROCM_REPO="xenial"
fi
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
ROCM_REPO="${UBUNTU_VERSION_NAME}"
fi
# Add rocm repository
wget -qO - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add -
local rocm_baseurl="http://repo.radeon.com/rocm/apt/${ROCM_VERSION}"
echo "deb [arch=amd64] ${rocm_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/rocm.list
echo "deb [arch=amd64] ${rocm_baseurl} ${ROCM_REPO} main" > /etc/apt/sources.list.d/rocm.list
apt-get update --allow-insecure-repositories
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \
@ -39,8 +59,7 @@ install_ubuntu() {
rocm-libs \
rccl \
rocprofiler-dev \
roctracer-dev \
amd-smi-lib
roctracer-dev
if [[ $(ver $ROCM_VERSION) -ge $(ver 6.1) ]]; then
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated rocm-llvm-dev
@ -49,18 +68,29 @@ install_ubuntu() {
# precompiled miopen kernels added in ROCm 3.5, renamed in ROCm 5.5
# search for all unversioned packages
# if search fails it will abort this script; use true to avoid case where search fails
MIOPENHIPGFX=$(apt-cache search --names-only miopen-hip-gfx | awk '{print $1}' | grep -F -v . || true)
if [[ "x${MIOPENHIPGFX}" = x ]]; then
echo "miopen-hip-gfx package not available" && exit 1
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.5) ]]; then
MIOPENHIPGFX=$(apt-cache search --names-only miopen-hip-gfx | awk '{print $1}' | grep -F -v . || true)
if [[ "x${MIOPENHIPGFX}" = x ]]; then
echo "miopen-hip-gfx package not available" && exit 1
else
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENHIPGFX}
fi
else
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENHIPGFX}
MIOPENKERNELS=$(apt-cache search --names-only miopenkernels | awk '{print $1}' | grep -F -v . || true)
if [[ "x${MIOPENKERNELS}" = x ]]; then
echo "miopenkernels package not available" && exit 1
else
DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENKERNELS}
fi
fi
# ROCm 6.0 had a regression where journal_mode was enabled on the kdb files resulting in permission errors at runtime
for kdb in /opt/rocm/share/miopen/db/*.kdb
do
sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
done
if [[ $(ver $ROCM_VERSION) -ge $(ver 6.0) ]]; then
for kdb in /opt/rocm/share/miopen/db/*.kdb
do
sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
done
fi
# Cleanup
apt-get autoclean && apt-get clean
@ -77,19 +107,25 @@ install_centos() {
yum install -y epel-release
yum install -y dkms kernel-headers-`uname -r` kernel-devel-`uname -r`
# Add amdgpu repository
local amdgpu_baseurl
if [[ $OS_VERSION == 9 ]]; then
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/9.0/main/x86_64"
else
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/7.9/main/x86_64"
if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
# Add amdgpu repository
local amdgpu_baseurl
if [[ $OS_VERSION == 9 ]]; then
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/9.0/main/x86_64"
else
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/7.9/main/x86_64"
else
amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/7.9/main/x86_64"
fi
fi
echo "[AMDGPU]" > /etc/yum.repos.d/amdgpu.repo
echo "name=AMDGPU" >> /etc/yum.repos.d/amdgpu.repo
echo "baseurl=${amdgpu_baseurl}" >> /etc/yum.repos.d/amdgpu.repo
echo "enabled=1" >> /etc/yum.repos.d/amdgpu.repo
echo "gpgcheck=1" >> /etc/yum.repos.d/amdgpu.repo
echo "gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key" >> /etc/yum.repos.d/amdgpu.repo
fi
echo "[AMDGPU]" > /etc/yum.repos.d/amdgpu.repo
echo "name=AMDGPU" >> /etc/yum.repos.d/amdgpu.repo
echo "baseurl=${amdgpu_baseurl}" >> /etc/yum.repos.d/amdgpu.repo
echo "enabled=1" >> /etc/yum.repos.d/amdgpu.repo
echo "gpgcheck=1" >> /etc/yum.repos.d/amdgpu.repo
echo "gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key" >> /etc/yum.repos.d/amdgpu.repo
local rocm_baseurl="http://repo.radeon.com/rocm/yum/${ROCM_VERSION}"
echo "[ROCm]" > /etc/yum.repos.d/rocm.repo
@ -107,23 +143,33 @@ install_centos() {
rocm-libs \
rccl \
rocprofiler-dev \
roctracer-dev \
amd-smi-lib
roctracer-dev
# precompiled miopen kernels; search for all unversioned packages
# if search fails it will abort this script; use true to avoid case where search fails
MIOPENHIPGFX=$(yum -q search miopen-hip-gfx | grep miopen-hip-gfx | awk '{print $1}'| grep -F kdb. || true)
if [[ "x${MIOPENHIPGFX}" = x ]]; then
echo "miopen-hip-gfx package not available" && exit 1
if [[ $(ver $ROCM_VERSION) -ge $(ver 5.5) ]]; then
MIOPENHIPGFX=$(yum -q search miopen-hip-gfx | grep miopen-hip-gfx | awk '{print $1}'| grep -F kdb. || true)
if [[ "x${MIOPENHIPGFX}" = x ]]; then
echo "miopen-hip-gfx package not available" && exit 1
else
yum install -y ${MIOPENHIPGFX}
fi
else
yum install -y ${MIOPENHIPGFX}
MIOPENKERNELS=$(yum -q search miopenkernels | grep miopenkernels- | awk '{print $1}'| grep -F kdb. || true)
if [[ "x${MIOPENKERNELS}" = x ]]; then
echo "miopenkernels package not available" && exit 1
else
yum install -y ${MIOPENKERNELS}
fi
fi
# ROCm 6.0 had a regression where journal_mode was enabled on the kdb files resulting in permission errors at runtime
for kdb in /opt/rocm/share/miopen/db/*.kdb
do
sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
done
if [[ $(ver $ROCM_VERSION) -ge $(ver 6.0) ]]; then
for kdb in /opt/rocm/share/miopen/db/*.kdb
do
sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
done
fi
# Cleanup
yum clean all

View File

@ -15,7 +15,7 @@ conda_reinstall() {
if [ -n "${ROCM_VERSION}" ]; then
TRITON_REPO="https://github.com/openai/triton"
TRITON_TEXT_FILE="triton-rocm"
elif [ -n "${XPU_VERSION}" ]; then
elif [ -n "${BASEKIT_VERSION}" ]; then
TRITON_REPO="https://github.com/intel/intel-xpu-backend-for-triton"
TRITON_TEXT_FILE="triton-xpu"
else

View File

@ -5,7 +5,8 @@ set -ex
install_ubuntu() {
apt-get update
apt-get install -y --no-install-recommends \
libopencv-dev
libopencv-dev \
libavcodec-dev
# Cleanup
apt-get autoclean && apt-get clean
@ -18,7 +19,8 @@ install_centos() {
yum --enablerepo=extras install -y epel-release
yum install -y \
opencv-devel
opencv-devel \
ffmpeg-devel
# Cleanup
yum clean all

View File

@ -3,7 +3,10 @@ set -xe
# Intel® software for general purpose GPU capabilities.
# Refer to https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html
# Refer to https://dgpu-docs.intel.com/releases/LTS_803.29_20240131.html
# Intel® oneAPI Base Toolkit (version 2024.0.0) has been updated to include functional and security updates.
# Refer to https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html
# Users should update to the latest version as it becomes available
@ -14,16 +17,14 @@ function install_ubuntu() {
# Set up the repository. To do this, download the key to the system keyring
wget -qO - https://repositories.intel.com/gpu/intel-graphics.key \
| gpg --dearmor --output /usr/share/keyrings/intel-graphics.gpg
wget -qO - https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
| gpg --dearmor --output /usr/share/keyrings/intel-for-pytorch-gpu-dev-keyring.gpg
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
| gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
# Add the signed entry to APT sources and configure the APT client to use the Intel repository
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] \
https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" \
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" \
| tee /etc/apt/sources.list.d/intel-gpu-jammy.list
echo "deb [signed-by=/usr/share/keyrings/intel-for-pytorch-gpu-dev-keyring.gpg] \
https://apt.repos.intel.com/intel-for-pytorch-gpu-dev all main" \
| tee /etc/apt/sources.list.d/intel-for-pytorch-gpu-dev.list
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" \
| tee /etc/apt/sources.list.d/oneAPI.list
# Update the packages list and repository index
apt-get update
@ -39,11 +40,11 @@ function install_ubuntu() {
mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo
# Development Packages
apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev level-zero-dev
# Install Intel Support Packages
if [ -n "$XPU_VERSION" ]; then
apt-get install -y intel-for-pytorch-gpu-dev-${XPU_VERSION}
# Install Intel® oneAPI Base Toolkit
if [ -n "$BASEKIT_VERSION" ]; then
apt-get install intel-basekit=$BASEKIT_VERSION -y
else
apt-get install -y intel-for-pytorch-gpu-dev
apt-get install intel-basekit -y
fi
# Cleanup

View File

@ -56,7 +56,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@ -139,7 +139,7 @@ COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
ARG CUDNN_VERSION
ARG CUDA_VERSION
COPY ./common/install_cudnn.sh install_cudnn.sh
RUN if [ -n "${CUDNN_VERSION}" ]; then bash install_cudnn.sh; fi
RUN if [ "${CUDNN_VERSION}" -eq 8 ]; then bash install_cudnn.sh; fi
RUN rm install_cudnn.sh
# Install CUSPARSELT
@ -152,7 +152,6 @@ RUN rm install_cusparselt.sh
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

@ -53,7 +53,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@ -78,11 +78,6 @@ ENV MAGMA_HOME /opt/rocm/magma
ENV LANG C.UTF-8
ENV LC_ALL C.UTF-8
# Install amdsmi
COPY ./common/install_amdsmi.sh install_amdsmi.sh
RUN bash ./install_amdsmi.sh
RUN rm install_amdsmi.sh
# (optional) Install non-default CMake version
ARG CMAKE_VERSION
COPY ./common/install_cmake.sh install_cmake.sh
@ -105,13 +100,6 @@ COPY triton_version.txt triton_version.txt
RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
RUN rm install_triton.sh common_utils.sh triton-rocm.txt triton_version.txt
# Install AOTriton
COPY ./aotriton_version.txt aotriton_version.txt
COPY ./common/common_utils.sh common_utils.sh
COPY ./common/install_aotriton.sh install_aotriton.sh
RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
# Install ccache/sccache (do this last, so we get priority in PATH)
COPY ./common/install_cache.sh install_cache.sh
ENV PATH /opt/cache/bin:$PATH

View File

@ -62,7 +62,7 @@ RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_d
RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
# Install XPU Dependencies
ARG XPU_VERSION
ARG BASEKIT_VERSION
COPY ./common/install_xpu.sh install_xpu.sh
RUN bash ./install_xpu.sh && rm install_xpu.sh
@ -83,7 +83,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi

View File

@ -80,7 +80,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
RUN rm install_db.sh
ENV INSTALLED_DB ${DB}
# (optional) Install vision packages like OpenCV
# (optional) Install vision packages like OpenCV and ffmpeg
ARG VISION
COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi

View File

@ -44,7 +44,15 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda11* ]]; then
fi
fi
if [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
if [[ ${BUILD_ENVIRONMENT} == *"caffe2"* ]]; then
echo "Caffe2 build is ON"
export BUILD_CAFFE2=ON
fi
if [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
export ATEN_THREADING=TBB
export USE_TBB=1
elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
export ATEN_THREADING=NATIVE
fi
@ -286,9 +294,6 @@ else
fi
WERROR=1 python setup.py bdist_wheel
else
if [[ "$BUILD_ENVIRONMENT" == *xla* ]]; then
source .ci/pytorch/install_cache_xla.sh
fi
python setup.py bdist_wheel
fi
pip_install_whl "$(echo dist/*.whl)"
@ -330,7 +335,7 @@ else
SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
mkdir -p "$CUSTOM_OP_BUILD"
pushd "$CUSTOM_OP_BUILD"
cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPython_EXECUTABLE="$(which python)" \
cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd
@ -343,7 +348,7 @@ else
SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
mkdir -p "$JIT_HOOK_BUILD"
pushd "$JIT_HOOK_BUILD"
cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPython_EXECUTABLE="$(which python)" \
cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd
@ -355,7 +360,7 @@ else
python --version
mkdir -p "$CUSTOM_BACKEND_BUILD"
pushd "$CUSTOM_BACKEND_BUILD"
cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPython_EXECUTABLE="$(which python)" \
cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
-DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
make VERBOSE=1
popd

View File

@ -6,4 +6,4 @@ source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
echo "Testing pytorch docs"
cd docs
TERM=vt100 make doctest
make doctest

View File

@ -1,37 +0,0 @@
#!/bin/bash
# Script for installing sccache on the xla build job, which uses xla's docker
# 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
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
# 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"
}
write_sccache_stub cc
write_sccache_stub c++
write_sccache_stub gcc
write_sccache_stub g++
write_sccache_stub clang
write_sccache_stub clang++

View File

@ -18,7 +18,6 @@ time python test/run_test.py --verbose -i distributed/test_c10d_gloo
time python test/run_test.py --verbose -i distributed/test_c10d_nccl
time python test/run_test.py --verbose -i distributed/test_c10d_spawn_gloo
time python test/run_test.py --verbose -i distributed/test_c10d_spawn_nccl
time python test/run_test.py --verbose -i distributed/test_cuda_p2p
time python test/run_test.py --verbose -i distributed/test_store
time python test/run_test.py --verbose -i distributed/test_pg_wrapper
time python test/run_test.py --verbose -i distributed/rpc/cuda/test_tensorpipe_agent
@ -51,9 +50,6 @@ time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_ra
# FSDP2 tests
time python test/run_test.py --verbose -i distributed/_composable/fsdp/test_fully_shard_training -- -k test_2d_mlp_with_nd_mesh
# Pipelining composability tests
time python test/run_test.py --verbose -i distributed/pipelining/test_composability.py
# Other tests
time python test/run_test.py --verbose -i test_cuda_primary_ctx
time python test/run_test.py --verbose -i test_optim -- -k test_forloop_goes_right_direction_multigpu

View File

@ -264,18 +264,6 @@ elif [[ $TEST_CONFIG == 'nogpu_AVX512' ]]; then
export ATEN_CPU_CAPABILITY=avx2
fi
# temp workarounds for https://github.com/pytorch/pytorch/issues/126692, remove when fixed
if [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]]; then
pushd test
CUDA_VERSION=$(python -c "import torch; print(torch.version.cuda)")
if [ "$CUDA_VERSION" == "12.4" ]; then
ISCUDA124="cu124"
else
ISCUDA124=""
fi
popd
fi
test_python_legacy_jit() {
time python test/run_test.py --include test_jit_legacy test_jit_fuser_legacy --verbose
assert_git_not_dirty
@ -338,7 +326,6 @@ test_inductor_distributed() {
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_frozen.py --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_mixed_precision.py -k test_compute_dtype --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_mixed_precision.py -k test_reduce_dtype --verbose
python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_clip_grad_norm_.py -k test_clip_grad_norm_2d --verbose
python test/run_test.py -i distributed/fsdp/test_fsdp_tp_integration.py -k test_fsdp_tp_integration --verbose
# this runs on both single-gpu and multi-gpu instance. It should be smart about skipping tests that aren't supported
@ -363,20 +350,10 @@ test_inductor() {
test_inductor_cpp_wrapper_abi_compatible() {
export TORCHINDUCTOR_ABI_COMPATIBLE=1
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
echo "Testing Inductor cpp wrapper mode with TORCHINDUCTOR_ABI_COMPATIBLE=1"
# cpu stack allocation causes segfault and needs more investigation
PYTORCH_TESTING_DEVICE_ONLY_FOR="" python test/run_test.py --include inductor/test_cpu_cpp_wrapper
TORCHINDUCTOR_STACK_ALLOCATION=0 python test/run_test.py --include inductor/test_cpu_cpp_wrapper
python test/run_test.py --include inductor/test_cuda_cpp_wrapper
TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/timm_models.py --device cuda --accuracy --amp \
--training --inductor --disable-cudagraphs --only vit_base_patch16_224 \
--output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/inductor_timm_training.csv"
}
# "Global" flags for inductor benchmarking controlled by TEST_CONFIG
@ -538,16 +515,16 @@ test_single_dynamo_benchmark() {
--output "$TEST_REPORTS_DIR/${name}_${suite}.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/${name}_$suite.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/${TEST_CONFIG}_${name}.csv"
--expected "benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG}_${name}.csv"
python benchmarks/dynamo/check_graph_breaks.py \
--actual "$TEST_REPORTS_DIR/${name}_$suite.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/${TEST_CONFIG}_${name}.csv"
--expected "benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG}_${name}.csv"
fi
}
test_inductor_micro_benchmark() {
TEST_REPORTS_DIR=$(pwd)/test/test-reports
python benchmarks/gpt_fast/benchmark.py --output "${TEST_REPORTS_DIR}/gpt_fast_benchmark.csv"
TEST_REPORTS_DIR=$(pwd)/test/test-micro-reports
python benchmarks/gpt_fast/benchmark.py
}
test_dynamo_benchmark() {
@ -565,11 +542,7 @@ test_dynamo_benchmark() {
test_single_dynamo_benchmark "dashboard" "$suite" "$shard_id" "$@"
else
if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
if [[ "${TEST_CONFIG}" == *freezing* ]]; then
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --float32 --freezing "$@"
else
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --float32 "$@"
fi
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --float32 "$@"
elif [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
else
@ -583,16 +556,12 @@ test_inductor_torchbench_smoketest_perf() {
TEST_REPORTS_DIR=$(pwd)/test/test-reports
mkdir -p "$TEST_REPORTS_DIR"
# Test some models in the cpp wrapper mode
TORCHINDUCTOR_ABI_COMPATIBLE=1 TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
--bfloat16 --inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
TORCHINDUCTOR_ABI_COMPATIBLE=1 TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
--bfloat16 --inference --inductor --only llama --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
TORCHINDUCTOR_ABI_COMPATIBLE=1 TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
--bfloat16 --inference --inductor --only moco --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
# smoke test the cpp_wrapper mode
TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy --bfloat16 \
--inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_smoketest.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/inductor_torchbench_inference.csv"
--actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_smoketest.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_inference.csv"
python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --float16 --training \
--batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only hf_Bert \
@ -607,13 +576,7 @@ test_inductor_torchbench_smoketest_perf() {
# https://github.com/pytorch/pytorch/actions/runs/7158691360/job/19491437314,
# and thus we lower its threshold to reduce flakiness. If this continues to be a problem,
# we switch to use some other model.
# Use 4.7 for cuda 12.4, change back to 4.9 after fixing https://github.com/pytorch/pytorch/issues/126692
if [ "$CUDA_VERSION" == "12.4" ]; then
THRESHOLD=4.7
else
THRESHOLD=4.9
fi
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t $THRESHOLD
python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t 4.9
# Check memory compression ratio for a few models
for test in hf_Albert timm_vision_transformer; do
@ -625,15 +588,6 @@ test_inductor_torchbench_smoketest_perf() {
"$TEST_REPORTS_DIR/inductor_training_smoketest_$test.csv" \
--expected benchmarks/dynamo/expected_ci_perf_inductor_torchbench.csv
done
# Perform some "warm-start" runs for a few huggingface models.
for test in AlbertForQuestionAnswering AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
python benchmarks/dynamo/huggingface.py --accuracy --training --amp --inductor --device cuda --warm-start-latency \
--only $test --output "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv"
python benchmarks/dynamo/check_accuracy.py \
--actual "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv" \
--expected "benchmarks/dynamo/ci_expected_accuracy/${ISCUDA124}/inductor_huggingface_training.csv"
done
}
test_inductor_torchbench_cpu_smoketest_perf(){
@ -717,6 +671,7 @@ test_aten() {
${SUDO} ln -sf "$TORCH_LIB_DIR"/libmkldnn* "$TEST_BASE_DIR"
${SUDO} ln -sf "$TORCH_LIB_DIR"/libnccl* "$TEST_BASE_DIR"
${SUDO} ln -sf "$TORCH_LIB_DIR"/libtorch* "$TEST_BASE_DIR"
${SUDO} ln -sf "$TORCH_LIB_DIR"/libtbb* "$TEST_BASE_DIR"
ls "$TEST_BASE_DIR"
aten/tools/run_tests.sh "$TEST_BASE_DIR"
@ -741,6 +696,21 @@ test_without_numpy() {
popd
}
# pytorch extensions require including torch/extension.h which includes all.h
# which includes utils.h which includes Parallel.h.
# So you can call for instance parallel_for() from your extension,
# but the compilation will fail because of Parallel.h has only declarations
# and definitions are conditionally included Parallel.h(see last lines of Parallel.h).
# I tried to solve it #39612 and #39881 by including Config.h into Parallel.h
# But if Pytorch is built with TBB it provides Config.h
# that has AT_PARALLEL_NATIVE_TBB=1(see #3961 or #39881) and it means that if you include
# torch/extension.h which transitively includes Parallel.h
# which transitively includes tbb.h which is not available!
if [[ "${BUILD_ENVIRONMENT}" == *tbb* ]]; then
sudo mkdir -p /usr/include/tbb
sudo cp -r "$PWD"/third_party/tbb/include/tbb/* /usr/include/tbb
fi
test_libtorch() {
local SHARD="$1"
@ -754,6 +724,7 @@ test_libtorch() {
ln -sf "$TORCH_LIB_DIR"/libc10* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libshm* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libtorch* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libtbb* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libnvfuser* "$TORCH_BIN_DIR"
export CPP_TESTS_DIR="${TORCH_BIN_DIR}"
@ -890,6 +861,7 @@ test_rpc() {
# test reporting process to function as expected.
ln -sf "$TORCH_LIB_DIR"/libtorch* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libc10* "$TORCH_BIN_DIR"
ln -sf "$TORCH_LIB_DIR"/libtbb* "$TORCH_BIN_DIR"
CPP_TESTS_DIR="${TORCH_BIN_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_cpp_rpc
}
@ -1297,10 +1269,6 @@ elif [[ "${TEST_CONFIG}" == *dynamo* && "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHAR
elif [[ "${TEST_CONFIG}" == *dynamo* && $SHARD_NUMBER -gt 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
install_torchvision
test_dynamo_shard "${SHARD_NUMBER}"
elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
install_torchvision
test_python_shard "$SHARD_NUMBER"
test_aten
elif [[ "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
test_without_numpy
install_torchvision
@ -1330,6 +1298,10 @@ elif [[ "${BUILD_ENVIRONMENT}" == *-mobile-lightweight-dispatch* ]]; then
test_libtorch
elif [[ "${TEST_CONFIG}" = docs_test ]]; then
test_docs_test
elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
install_torchvision
test_python
test_aten
elif [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
install_torchvision
test_python

View File

@ -96,13 +96,8 @@ if [[ "$PACKAGE_TYPE" == conda ]]; then
conda install \${EXTRA_CONDA_FLAGS} -y "\$pkg" --offline
)
elif [[ "$PACKAGE_TYPE" != libtorch ]]; then
if [[ "\$BUILD_ENVIRONMENT" != *s390x* ]]; then
pip install "\$pkg" --index-url "https://download.pytorch.org/whl/\${CHANNEL}/${DESIRED_CUDA}"
retry pip install -q numpy protobuf typing-extensions
else
pip install "\$pkg"
retry pip install -q numpy protobuf typing-extensions
fi
pip install "\$pkg" --index-url "https://download.pytorch.org/whl/\${CHANNEL}/${DESIRED_CUDA}"
retry pip install -q numpy protobuf typing-extensions
fi
if [[ "$PACKAGE_TYPE" == libtorch ]]; then
pkg="\$(ls /final_pkgs/*-latest.zip)"

View File

@ -76,8 +76,8 @@ TRITON_VERSION=$(cat $PYTORCH_ROOT/.ci/docker/triton_version.txt)
# Here PYTORCH_EXTRA_INSTALL_REQUIREMENTS is already set for the all the wheel builds hence append TRITON_CONSTRAINT
if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
# Only linux Python < 3.13 are supported wheels for triton
TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64' and python_version < '3.13'"
# Only linux Python < 3.12 are supported wheels for triton
TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64' and python_version < '3.12'"
TRITON_REQUIREMENT="triton==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
TRITON_SHORTHASH=$(cut -c1-10 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton.txt)

View File

@ -61,7 +61,6 @@ readability-simplify-subscript-expr,
readability-string-compare,
'
HeaderFilterRegex: '^(aten/|c10/|torch/).*$'
AnalyzeTemporaryDtors: false
WarningsAsErrors: '*'
CheckOptions:
misc-header-include-cycle.IgnoredFilesList: 'format.h;ivalue.h;custom_class.h;Dict.h;List.h'
...

View File

@ -1,12 +1,9 @@
self-hosted-runner:
labels:
# GitHub hosted x86 Linux runners
- linux.20_04.4x
- linux.20_04.16x
# Repo-specific LF hosted ARC runners
- linux.large.arc
# Organization-wide AWS Linux Runners
- linux.large
- linux.large.arc
- linux.2xlarge
- linux.4xlarge
- linux.12xlarge
@ -16,34 +13,17 @@ self-hosted-runner:
- linux.8xlarge.nvidia.gpu
- linux.16xlarge.nvidia.gpu
- linux.g5.4xlarge.nvidia.gpu
# Organization-wide AWS Linux Runners on Linux Foundation account
- lf.linux.large
- lf.linux.2xlarge
- lf.linux.4xlarge
- lf.linux.12xlarge
- lf.linux.24xlarge
- lf.linux.arm64.2xlarge
- lf.linux.4xlarge.nvidia.gpu
- lf.linux.8xlarge.nvidia.gpu
- lf.linux.16xlarge.nvidia.gpu
- lf.linux.g5.4xlarge.nvidia.gpu
# Repo-specific IBM hosted S390x runner
- linux.s390x
# Organization wide AWS Windows runners
- windows.4xlarge.nonephemeral
- windows.8xlarge.nvidia.gpu
- windows.8xlarge.nvidia.gpu.nonephemeral
- windows.g5.4xlarge.nvidia.gpu
# Organization-wide AMD hosted MI300 runners
- bm-runner
- linux.rocm.gpu
# Repo-specific Apple hosted runners
- macos-m1-ultra
- macos-m2-14
# Org wise AWS `mac2.metal` runners (2020 Mac mini hardware powered by Apple silicon M1 processors)
- macos-m1-stable
- macos-m1-13
- macos-m1-14
# GitHub-hosted MacOS runners
- macos-12-xl
- macos-12
- macos12.3-m1
- macos-latest-xlarge
- macos-13-xlarge
- macos-14-xlarge

View File

@ -66,8 +66,7 @@ runs:
command: |
set -eux
# PyYAML 6.0 doesn't work with MacOS x86 anymore
# This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2
python3 -m pip install requests==2.27.1 pyyaml==6.0.1
python3 -m pip install requests==2.26.0 pyyaml==6.0.1
- name: Parse ref
id: parse-ref

View File

@ -35,7 +35,7 @@ runs:
"${DOCKER_IMAGE}"
)
if [[ "${GPU_ARCH_TYPE}" != "rocm" && "${BUILD_ENVIRONMENT}" != "linux-aarch64-binary-manywheel" && "${BUILD_ENVIRONMENT}" != "linux-s390x-binary-manywheel" ]]; then
if [[ "${GPU_ARCH_TYPE}" != "rocm" && "${BUILD_ENVIRONMENT}" != "linux-aarch64-binary-manywheel" ]]; then
# Propagate download.pytorch.org IP to container. This is only needed on Linux non aarch64 runner
grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" bash -c "/bin/cat >> /etc/hosts"
fi
@ -44,12 +44,3 @@ runs:
# Generate test script
docker exec -t -w "${PYTORCH_ROOT}" -e OUTPUT_SCRIPT="/run.sh" "${container_name}" bash -c "bash .circleci/scripts/binary_linux_test.sh"
docker exec -t "${container_name}" bash -c "source ${BINARY_ENV_FILE} && bash -x /run.sh"
- name: Cleanup docker
if: always() && env.BUILD_ENVIRONMENT == 'linux-s390x-binary-manywheel'
shell: bash
run: |
# on s390x stop the container for clean worker stop
# ignore expansion of "docker ps -q" since it could be empty
# shellcheck disable=SC2046
docker stop $(docker ps -q) || true

View File

@ -1 +1 @@
b829e936f7cc61b48149f5f957a451a38bf2a178
ea437b31ce316ea3d66fe73768c0dcb94edb79ad

View File

@ -1 +1 @@
6f0b61e5d782913a0fc7743812f2a8e522189111
e3fc03314dab5f44e3ed9ccbba6c15fbca3285cd

View File

@ -1,154 +0,0 @@
# Defines runner types that will be provisioned by by LF Self-hosted
# runners for pytorch/pytorch-canary and their labels.
#
# Runners listed here will be available as self hosted runners.
# Configuration is directly pulled from the main branch.
#
# Default values:
#
# runner_types:
# runner_label: # label to specify in the Github Actions workflow
# instance_type: m4.large
# os: linux
# max_available: 20
# disk_size: 50
# is_ephemeral: true
runner_types:
lf.c.linux.12xlarge:
disk_size: 200
instance_type: c5.12xlarge
is_ephemeral: false
max_available: 1000
os: linux
lf.c.linux.24xl.spr-metal:
disk_size: 200
instance_type: c7i.metal-24xl
is_ephemeral: false
max_available: 30
os: linux
lf.c.linux.16xlarge.spr:
disk_size: 200
instance_type: c7i.16xlarge
is_ephemeral: false
max_available: 30
os: linux
lf.c.linux.12xlarge.ephemeral:
disk_size: 200
instance_type: c5.12xlarge
is_ephemeral: true
max_available: 300
os: linux
lf.c.linux.16xlarge.nvidia.gpu:
disk_size: 150
instance_type: g3.16xlarge
is_ephemeral: false
max_available: 30
os: linux
lf.c.linux.24xlarge:
disk_size: 150
instance_type: c5.24xlarge
is_ephemeral: false
max_available: 250
os: linux
lf.c.linux.2xlarge:
disk_size: 150
instance_type: c5.2xlarge
is_ephemeral: false
max_available: 3120
os: linux
lf.c.linux.4xlarge:
disk_size: 150
instance_type: c5.4xlarge
is_ephemeral: false
max_available: 1000
os: linux
lf.c.linux.4xlarge.nvidia.gpu:
disk_size: 150
instance_type: g3.4xlarge
is_ephemeral: false
max_available: 520
os: linux
lf.c.linux.8xlarge.nvidia.gpu:
disk_size: 150
instance_type: g3.8xlarge
is_ephemeral: false
max_available: 400
os: linux
lf.c.linux.g4dn.12xlarge.nvidia.gpu:
disk_size: 150
instance_type: g4dn.12xlarge
is_ephemeral: false
max_available: 50
os: linux
lf.c.linux.g4dn.metal.nvidia.gpu:
disk_size: 150
instance_type: g4dn.metal
is_ephemeral: false
max_available: 30
os: linux
lf.c.linux.g5.48xlarge.nvidia.gpu:
disk_size: 150
instance_type: g5.48xlarge
is_ephemeral: false
max_available: 20
os: linux
lf.c.linux.g5.12xlarge.nvidia.gpu:
disk_size: 150
instance_type: g5.12xlarge
is_ephemeral: false
max_available: 150
os: linux
lf.c.linux.g5.4xlarge.nvidia.gpu:
disk_size: 150
instance_type: g5.4xlarge
is_ephemeral: false
max_available: 1200
os: linux
lf.c.linux.large:
disk_size: 15
instance_type: c5.large
is_ephemeral: false
os: linux
lf.c.linux.arm64.2xlarge:
disk_size: 256
instance_type: t4g.2xlarge
is_ephemeral: false
max_available: 200
os: linux
lf.c.linux.arm64.m7g.2xlarge:
disk_size: 256
instance_type: m7g.2xlarge
is_ephemeral: false
max_available: 20
os: linux
lf.c.windows.4xlarge:
disk_size: 256
instance_type: c5d.4xlarge
is_ephemeral: true
max_available: 420
os: windows
lf.c.windows.4xlarge.nonephemeral:
disk_size: 256
instance_type: c5d.4xlarge
is_ephemeral: false
max_available: 420
os: windows
lf.c.windows.8xlarge.nvidia.gpu:
disk_size: 256
instance_type: p3.2xlarge
is_ephemeral: true
max_available: 150
os: windows
lf.c.windows.8xlarge.nvidia.gpu.nonephemeral:
disk_size: 256
instance_type: p3.2xlarge
is_ephemeral: false
max_available: 150
os: windows
lf.c.windows.g5.4xlarge.nvidia.gpu:
disk_size: 256
instance_type: g5.4xlarge
is_ephemeral: false
max_available: 250
os: windows

View File

@ -1,154 +0,0 @@
# Defines runner types that will be provisioned by by LF Self-hosted
# runners for pytorch/pytorch and their labels.
#
# Runners listed here will be available as self hosted runners.
# Configuration is directly pulled from the main branch.
#
# Default values:
#
# runner_types:
# runner_label: # label to specify in the Github Actions workflow
# instance_type: m4.large
# os: linux
# max_available: 20
# disk_size: 50
# is_ephemeral: true
runner_types:
lf.linux.12xlarge:
disk_size: 200
instance_type: c5.12xlarge
is_ephemeral: false
max_available: 1000
os: linux
lf.linux.24xl.spr-metal:
disk_size: 200
instance_type: c7i.metal-24xl
is_ephemeral: false
max_available: 30
os: linux
lf.linux.16xlarge.spr:
disk_size: 200
instance_type: c7i.16xlarge
is_ephemeral: false
max_available: 30
os: linux
lf.linux.12xlarge.ephemeral:
disk_size: 200
instance_type: c5.12xlarge
is_ephemeral: true
max_available: 300
os: linux
lf.linux.16xlarge.nvidia.gpu:
disk_size: 150
instance_type: g3.16xlarge
is_ephemeral: false
max_available: 30
os: linux
lf.linux.24xlarge:
disk_size: 150
instance_type: c5.24xlarge
is_ephemeral: false
max_available: 250
os: linux
lf.linux.2xlarge:
disk_size: 150
instance_type: c5.2xlarge
is_ephemeral: false
max_available: 3120
os: linux
lf.linux.4xlarge:
disk_size: 150
instance_type: c5.4xlarge
is_ephemeral: false
max_available: 1000
os: linux
lf.linux.4xlarge.nvidia.gpu:
disk_size: 150
instance_type: g3.4xlarge
is_ephemeral: false
max_available: 520
os: linux
lf.linux.8xlarge.nvidia.gpu:
disk_size: 150
instance_type: g3.8xlarge
is_ephemeral: false
max_available: 400
os: linux
lf.linux.g4dn.12xlarge.nvidia.gpu:
disk_size: 150
instance_type: g4dn.12xlarge
is_ephemeral: false
max_available: 50
os: linux
lf.linux.g4dn.metal.nvidia.gpu:
disk_size: 150
instance_type: g4dn.metal
is_ephemeral: false
max_available: 30
os: linux
lf.linux.g5.48xlarge.nvidia.gpu:
disk_size: 150
instance_type: g5.48xlarge
is_ephemeral: false
max_available: 20
os: linux
lf.linux.g5.12xlarge.nvidia.gpu:
disk_size: 150
instance_type: g5.12xlarge
is_ephemeral: false
max_available: 150
os: linux
lf.linux.g5.4xlarge.nvidia.gpu:
disk_size: 150
instance_type: g5.4xlarge
is_ephemeral: false
max_available: 1200
os: linux
lf.linux.large:
disk_size: 15
instance_type: c5.large
is_ephemeral: false
os: linux
lf.linux.arm64.2xlarge:
disk_size: 256
instance_type: t4g.2xlarge
is_ephemeral: false
max_available: 200
os: linux
lf.linux.arm64.m7g.2xlarge:
disk_size: 256
instance_type: m7g.2xlarge
is_ephemeral: false
max_available: 20
os: linux
lf.windows.4xlarge:
disk_size: 256
instance_type: c5d.4xlarge
is_ephemeral: true
max_available: 420
os: windows
lf.windows.4xlarge.nonephemeral:
disk_size: 256
instance_type: c5d.4xlarge
is_ephemeral: false
max_available: 420
os: windows
lf.windows.8xlarge.nvidia.gpu:
disk_size: 256
instance_type: p3.2xlarge
is_ephemeral: true
max_available: 150
os: windows
lf.windows.8xlarge.nvidia.gpu.nonephemeral:
disk_size: 256
instance_type: p3.2xlarge
is_ephemeral: false
max_available: 150
os: windows
lf.windows.g5.4xlarge.nvidia.gpu:
disk_size: 256
instance_type: g5.4xlarge
is_ephemeral: false
max_available: 250
os: windows

View File

@ -245,7 +245,6 @@
- torch/xpu/**
- test/xpu/**
- third_party/xpu.txt
- .ci/docker/ci_commit_pins/triton-xpu.txt
approved_by:
- EikanWang
- jgong5

View File

@ -1,5 +1,6 @@
tracking_issue: 24422
ciflow_tracking_issue: 64124
TD_rollout_issue: 123120
ciflow_push_tags:
- ciflow/binaries
- ciflow/binaries_conda
@ -8,7 +9,6 @@ ciflow_push_tags:
- ciflow/inductor
- ciflow/inductor-perf-compare
- ciflow/inductor-micro-benchmark
- ciflow/inductor-cu124
- ciflow/linux-aarch64
- ciflow/mps
- ciflow/nightly
@ -20,6 +20,7 @@ ciflow_push_tags:
- ciflow/xpu
- ciflow/torchbench
retryable_workflows:
- lint
- pull
- trunk
- linux-binary

View File

@ -10,6 +10,6 @@ lintrunner==0.10.7
ninja==1.10.0.post1
nvidia-ml-py==11.525.84
pyyaml==6.0
requests==2.32.2
requests==2.31.0
rich==10.9.0
rockset==1.0.3

View File

@ -4,5 +4,6 @@ mkl-include=2022.1.0
ninja=1.10.2
numpy=1.23.3
pyyaml=6.0
requests=2.31.0
setuptools=68.2.2
typing-extensions=4.9.0
typing-extensions=4.3.0

View File

@ -3,5 +3,6 @@ cmake=3.22.1
ninja=1.10.2
numpy=1.23.3
pyyaml=6.0
requests=2.31.0
setuptools=68.2.2
typing-extensions=4.9.0
typing-extensions=4.3.0

View File

@ -2,7 +2,7 @@ numpy=1.22.3
pyyaml=6.0
setuptools=61.2.0
cmake=3.22.*
typing-extensions=4.9.0
typing-extensions=4.3.0
dataclasses=0.8
pip=22.2.2
pillow=10.0.1

View File

@ -4,7 +4,7 @@ numpy=1.21.2
pyyaml=5.3
setuptools=46.0.0
cmake=3.22.*
typing-extensions=4.9.0
typing-extensions=4.3.0
dataclasses=0.8
pip=22.2.2
pillow=10.0.1

View File

@ -2,7 +2,6 @@
import os
import re
from datetime import datetime
from functools import lru_cache
from pathlib import Path
from typing import Any, Callable, Dict, List, Set
@ -188,17 +187,6 @@ def get_recent_prs() -> Dict[str, Any]:
return prs_by_branch_base
@lru_cache(maxsize=1)
def get_open_prs() -> List[Dict[str, Any]]:
return paginate_graphql(
GRAPHQL_OPEN_PRS,
{"owner": "pytorch", "repo": "pytorch"},
lambda data: False,
lambda res: res["data"]["repository"]["pullRequests"]["nodes"],
lambda res: res["data"]["repository"]["pullRequests"]["pageInfo"],
)
def get_branches_with_magic_label_or_open_pr() -> Set[str]:
pr_infos: List[Dict[str, Any]] = paginate_graphql(
GRAPHQL_NO_DELETE_BRANCH_LABEL,
@ -208,7 +196,15 @@ def get_branches_with_magic_label_or_open_pr() -> Set[str]:
lambda res: res["data"]["repository"]["label"]["pullRequests"]["pageInfo"],
)
pr_infos.extend(get_open_prs())
pr_infos.extend(
paginate_graphql(
GRAPHQL_OPEN_PRS,
{"owner": "pytorch", "repo": "pytorch"},
lambda data: False,
lambda res: res["data"]["repository"]["pullRequests"]["nodes"],
lambda res: res["data"]["repository"]["pullRequests"]["pageInfo"],
)
)
# Get the most recent PR for each branch base (group gh together)
branch_bases = set()
@ -274,41 +270,5 @@ def delete_branches() -> None:
delete_branch(git_repo, branch)
def delete_old_ciflow_tags() -> None:
# Deletes ciflow tags if they are associated with a closed PR or a specific
# commit. Lightweight tags don't have information about the date they were
# created, so we can't check how old they are. The script just assumes that
# ciflow tags should be deleted regardless of creation date.
git_repo = GitRepo(str(REPO_ROOT), "origin", debug=True)
def delete_tag(tag: str) -> None:
print(f"Deleting tag {tag}")
ESTIMATED_TOKENS[0] += 1
delete_branch(git_repo, f"refs/tags/{tag}")
tags = git_repo._run_git("tag").splitlines()
open_pr_numbers = [x["number"] for x in get_open_prs()]
for tag in tags:
try:
if ESTIMATED_TOKENS[0] > 400:
print("Estimated tokens exceeded, exiting")
break
if not tag.startswith("ciflow/"):
continue
re_match_pr = re.match(r"^ciflow\/.*\/(\d{5,6})$", tag)
re_match_sha = re.match(r"^ciflow\/.*\/([0-9a-f]{40})$", tag)
if re_match_pr:
pr_number = int(re_match_pr.group(1))
if pr_number in open_pr_numbers:
continue
delete_tag(tag)
elif re_match_sha:
delete_tag(tag)
except Exception as e:
print(f"Failed to check tag {tag}: {e}")
if __name__ == "__main__":
delete_branches()
delete_old_ciflow_tags()

View File

@ -1,52 +0,0 @@
import os
import re
import sys
from github import Github
def main() -> None:
token = os.environ.get("GITHUB_TOKEN")
repo_owner = "pytorch"
repo_name = "pytorch"
pull_request_number = int(sys.argv[1])
g = Github(token)
repo = g.get_repo(f"{repo_owner}/{repo_name}")
pull_request = repo.get_pull(pull_request_number)
pull_request_body = pull_request.body
# PR without description
if pull_request_body is None:
return
# get issue number from the PR body
if not re.search(r"#\d{1,6}", pull_request_body):
print("The pull request does not mention an issue.")
return
issue_number = int(re.findall(r"#(\d{1,6})", pull_request_body)[0])
issue = repo.get_issue(issue_number)
issue_labels = issue.labels
docathon_label_present = any(
label.name == "docathon-h1-2024" for label in issue_labels
)
# if the issue has a docathon label, add all labels from the issue to the PR.
if not docathon_label_present:
print("The 'docathon-h1-2024' label is not present in the issue.")
return
pull_request_labels = pull_request.get_labels()
pull_request_label_names = [label.name for label in pull_request_labels]
issue_label_names = [label.name for label in issue_labels]
labels_to_add = [
label for label in issue_label_names if label not in pull_request_label_names
]
if not labels_to_add:
print("The pull request already has the same labels.")
return
pull_request.add_to_labels(*labels_to_add)
print("Labels added to the pull request!")
if __name__ == "__main__":
main()

View File

@ -19,7 +19,7 @@ CUDA_ARCHES = ["11.8", "12.1", "12.4"]
CUDA_ARCHES_FULL_VERSION = {"11.8": "11.8.0", "12.1": "12.1.1", "12.4": "12.4.0"}
CUDA_ARCHES_CUDNN_VERSION = {"11.8": "9", "12.1": "9", "12.4": "9"}
CUDA_ARCHES_CUDNN_VERSION = {"11.8": "8", "12.1": "8", "12.4": "8"}
ROCM_ARCHES = ["6.0", "6.1"]
@ -31,18 +31,12 @@ CPU_CXX11_ABI_ARCH = ["cpu-cxx11-abi"]
CPU_AARCH64_ARCH = ["cpu-aarch64"]
CPU_S390X_ARCH = ["cpu-s390x"]
CUDA_AARCH64_ARCH = ["cuda-aarch64"]
PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"11.8": (
"nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | " # noqa: B950
"nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu11==8.7.0.84; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | "
@ -55,7 +49,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | " # noqa: B950
"nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | "
@ -68,7 +62,7 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
"nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cudnn-cu12==8.9.7.29; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | "
"nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | "
@ -136,10 +130,6 @@ def arch_type(arch_version: str) -> str:
return "cpu-cxx11-abi"
elif arch_version in CPU_AARCH64_ARCH:
return "cpu-aarch64"
elif arch_version in CPU_S390X_ARCH:
return "cpu-s390x"
elif arch_version in CUDA_AARCH64_ARCH:
return "cuda-aarch64"
else: # arch_version should always be "cpu" in this case
return "cpu"
@ -159,8 +149,6 @@ WHEEL_CONTAINER_IMAGES = {
"cpu": f"pytorch/manylinux-builder:cpu-{DEFAULT_TAG}",
"cpu-cxx11-abi": f"pytorch/manylinuxcxx11-abi-builder:cpu-cxx11-abi-{DEFAULT_TAG}",
"cpu-aarch64": f"pytorch/manylinuxaarch64-builder:cpu-aarch64-{DEFAULT_TAG}",
"cpu-s390x": f"pytorch/manylinuxs390x-builder:cpu-s390x-{DEFAULT_TAG}",
"cuda-aarch64": f"pytorch/manylinuxaarch64-builder:cuda12.4-{DEFAULT_TAG}",
}
CONDA_CONTAINER_IMAGES = {
@ -217,9 +205,7 @@ def translate_desired_cuda(gpu_arch_type: str, gpu_arch_version: str) -> str:
"cpu": "cpu",
"cpu-aarch64": "cpu",
"cpu-cxx11-abi": "cpu-cxx11-abi",
"cpu-s390x": "cpu",
"cuda": f"cu{gpu_arch_version.replace('.', '')}",
"cuda-aarch64": "cu124",
"rocm": f"rocm{gpu_arch_version}",
}.get(gpu_arch_type, gpu_arch_version)
@ -300,11 +286,11 @@ def generate_libtorch_matrix(
"libtorch_variant": libtorch_variant,
"libtorch_config": abi_version if os == "windows" else "",
"devtoolset": abi_version if os != "windows" else "",
"container_image": (
LIBTORCH_CONTAINER_IMAGES[(arch_version, abi_version)]
if os != "windows"
else ""
),
"container_image": LIBTORCH_CONTAINER_IMAGES[
(arch_version, abi_version)
]
if os != "windows"
else "",
"package_type": "libtorch",
"build_name": f"libtorch-{gpu_arch_type}{gpu_arch_version}-{libtorch_variant}-{abi_version}".replace(
".", "_"
@ -320,8 +306,8 @@ def generate_wheels_matrix(
python_versions: Optional[List[str]] = None,
) -> List[Dict[str, str]]:
package_type = "wheel"
if os == "linux" or os == "linux-aarch64" or os == "linux-s390x":
# NOTE: We only build manywheel packages for x86_64 and aarch64 and s390x linux
if os == "linux" or os == "linux-aarch64":
# NOTE: We only build manywheel packages for x86_64 and aarch64 linux
package_type = "manywheel"
if python_versions is None:
@ -337,36 +323,22 @@ def generate_wheels_matrix(
elif os == "linux-aarch64":
# Only want the one arch as the CPU type is different and
# uses different build/test scripts
arches = ["cpu-aarch64", "cuda-aarch64"]
elif os == "linux-s390x":
# Only want the one arch as the CPU type is different and
# uses different build/test scripts
arches = ["cpu-s390x"]
arches = ["cpu-aarch64"]
ret: List[Dict[str, str]] = []
for python_version in python_versions:
for arch_version in arches:
gpu_arch_type = arch_type(arch_version)
# Disable py3.12 builds for ROCm because of triton dependency
# on llnl-hatchet, which doesn't have py3.12 wheels available
if gpu_arch_type == "rocm" and python_version == "3.12":
continue
gpu_arch_version = (
""
if arch_version == "cpu"
or arch_version == "cpu-cxx11-abi"
or arch_version == "cpu-aarch64"
or arch_version == "cpu-s390x"
or arch_version == "cuda-aarch64"
else arch_version
)
# 12.1 linux wheels require PYTORCH_EXTRA_INSTALL_REQUIREMENTS to install
if (
arch_version in ["12.4", "12.1", "11.8"]
and os == "linux"
or arch_version == "cuda-aarch64"
):
if arch_version in ["12.4", "12.1", "11.8"] and os == "linux":
ret.append(
{
"python_version": python_version,
@ -375,16 +347,10 @@ def generate_wheels_matrix(
"desired_cuda": translate_desired_cuda(
gpu_arch_type, gpu_arch_version
),
"devtoolset": (
"cxx11-abi" if arch_version == "cuda-aarch64" else ""
),
"devtoolset": "",
"container_image": WHEEL_CONTAINER_IMAGES[arch_version],
"package_type": package_type,
"pytorch_extra_install_requirements": (
PYTORCH_EXTRA_INSTALL_REQUIREMENTS[arch_version] # fmt: skip
if os != "linux-aarch64"
else ""
),
"pytorch_extra_install_requirements": PYTORCH_EXTRA_INSTALL_REQUIREMENTS[arch_version], # fmt: skip
"build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}".replace( # noqa: B950
".", "_"
),
@ -399,19 +365,17 @@ def generate_wheels_matrix(
"desired_cuda": translate_desired_cuda(
gpu_arch_type, gpu_arch_version
),
"devtoolset": (
"cxx11-abi" if arch_version == "cpu-cxx11-abi" else ""
),
"devtoolset": "cxx11-abi"
if arch_version == "cpu-cxx11-abi"
else "",
"container_image": WHEEL_CONTAINER_IMAGES[arch_version],
"package_type": package_type,
"build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}".replace(
".", "_"
),
"pytorch_extra_install_requirements": (
PYTORCH_EXTRA_INSTALL_REQUIREMENTS["12.1"] # fmt: skip
if os != "linux"
else ""
),
"pytorch_extra_install_requirements":
PYTORCH_EXTRA_INSTALL_REQUIREMENTS["12.1"] # fmt: skip
if os != "linux" else "",
}
)
return ret

View File

@ -5,11 +5,11 @@ import sys
from dataclasses import asdict, dataclass, field
from pathlib import Path
from typing import Dict, Iterable, List, Literal, Set
from typing_extensions import TypedDict # Python 3.11+
import generate_binary_build_matrix # type: ignore[import]
import jinja2
from typing_extensions import TypedDict # Python 3.11+
Arch = Literal["windows", "linux", "macos"]
@ -60,7 +60,7 @@ class BinaryBuildWorkflow:
branches: str = "nightly"
# Mainly for macos
cross_compile_arm64: bool = False
macos_runner: str = "macos-14-xlarge"
macos_runner: str = "macos-12-xl"
def __post_init__(self) -> None:
if self.abi_version:
@ -95,7 +95,6 @@ class OperatingSystem:
MACOS = "macos"
MACOS_ARM64 = "macos-arm64"
LINUX_AARCH64 = "linux-aarch64"
LINUX_S390X = "linux-s390x"
LINUX_BINARY_BUILD_WORFKLOWS = [
@ -157,7 +156,7 @@ LINUX_BINARY_SMOKE_WORKFLOWS = [
package_type="manywheel",
build_configs=generate_binary_build_matrix.generate_wheels_matrix(
OperatingSystem.LINUX,
arches=["11.8", "12.1", "12.4"],
arches=["11.8", "12.1"],
python_versions=["3.8"],
),
branches="main",
@ -285,7 +284,7 @@ MACOS_BINARY_BUILD_WORKFLOWS = [
libtorch_variants=["shared-with-deps"],
),
cross_compile_arm64=False,
macos_runner="macos-14-xlarge",
macos_runner="macos-13-xlarge",
ciflow_config=CIFlowConfig(
labels={LABEL_CIFLOW_BINARIES, LABEL_CIFLOW_BINARIES_LIBTORCH},
isolated_workflow=True,
@ -298,7 +297,7 @@ MACOS_BINARY_BUILD_WORKFLOWS = [
OperatingSystem.MACOS_ARM64
),
cross_compile_arm64=False,
macos_runner="macos-14-xlarge",
macos_runner="macos-13-xlarge",
ciflow_config=CIFlowConfig(
labels={LABEL_CIFLOW_BINARIES, LABEL_CIFLOW_BINARIES_WHEEL},
isolated_workflow=True,
@ -308,7 +307,7 @@ MACOS_BINARY_BUILD_WORKFLOWS = [
os=OperatingSystem.MACOS_ARM64,
package_type="conda",
cross_compile_arm64=False,
macos_runner="macos-14-xlarge",
macos_runner="macos-13-xlarge",
build_configs=generate_binary_build_matrix.generate_conda_matrix(
OperatingSystem.MACOS_ARM64
),
@ -333,20 +332,6 @@ AARCH64_BINARY_BUILD_WORKFLOWS = [
),
]
S390X_BINARY_BUILD_WORKFLOWS = [
BinaryBuildWorkflow(
os=OperatingSystem.LINUX_S390X,
package_type="manywheel",
build_configs=generate_binary_build_matrix.generate_wheels_matrix(
OperatingSystem.LINUX_S390X
),
ciflow_config=CIFlowConfig(
labels={LABEL_CIFLOW_BINARIES, LABEL_CIFLOW_BINARIES_WHEEL},
isolated_workflow=True,
),
),
]
def main() -> None:
jinja_env = jinja2.Environment(
@ -365,10 +350,6 @@ def main() -> None:
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
AARCH64_BINARY_BUILD_WORKFLOWS,
),
(
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
S390X_BINARY_BUILD_WORKFLOWS,
),
(
jinja_env.get_template("linux_binary_build_workflow.yml.j2"),
LINUX_BINARY_SMOKE_WORKFLOWS,

View File

@ -7,7 +7,7 @@ eval "$(command conda 'shell.bash' 'hook' 2> /dev/null)"
conda activate "${CONDA_ENV}"
# Use uv to speed up lintrunner init
python3 -m pip install uv==0.1.45
python3 -m pip install uv
CACHE_DIRECTORY="/tmp/.lintbin"
# Try to recover the cached binaries

View File

@ -18,7 +18,6 @@ PYTEST_CACHE_KEY_PREFIX = "pytest_cache"
PYTEST_CACHE_DIR_NAME = ".pytest_cache"
BUCKET = "gha-artifacts"
LASTFAILED_FILE_PATH = Path("v/cache/lastfailed")
TD_HEURISTIC_PREVIOUSLY_FAILED_ADDITIONAL = "previous_failures_additional.json"
# Temp folders
ZIP_UPLOAD = "zip-upload"
@ -192,10 +191,6 @@ def _merge_pytest_caches(
pytest_cache_dir_to_merge_from, pytest_cache_dir_to_merge_into
)
_merge_additional_failures_files(
pytest_cache_dir_to_merge_from, pytest_cache_dir_to_merge_into
)
def _merge_lastfailed_files(source_pytest_cache: Path, dest_pytest_cache: Path) -> None:
# Simple cases where one of the files doesn't exist
@ -237,27 +232,3 @@ def _merged_lastfailed_content(
del to_lastfailed[""]
return to_lastfailed
def _merge_additional_failures_files(
source_pytest_cache: Path, dest_pytest_cache: Path
) -> None:
# Simple cases where one of the files doesn't exist
source_lastfailed_file = (
source_pytest_cache / TD_HEURISTIC_PREVIOUSLY_FAILED_ADDITIONAL
)
dest_lastfailed_file = dest_pytest_cache / TD_HEURISTIC_PREVIOUSLY_FAILED_ADDITIONAL
if not source_lastfailed_file.exists():
return
if not dest_lastfailed_file.exists():
copy_file(source_lastfailed_file, dest_lastfailed_file)
return
# Both files exist, so we need to merge them
from_lastfailed = load_json_file(source_lastfailed_file)
to_lastfailed = load_json_file(dest_lastfailed_file)
merged_content = list(set(from_lastfailed + to_lastfailed))
# Save the results
write_json_file(dest_lastfailed_file, merged_content)

View File

@ -1,28 +0,0 @@
#!/bin/bash
set -eoux pipefail
SYNC_BRANCH=fbcode/pytorch-stable-prototype
git config user.email "fake@example.com"
git config user.name "PyTorch Stable Bot"
git fetch origin main
git fetch origin "$SYNC_BRANCH"
git checkout "$SYNC_BRANCH"
for SHA in $(git log 4333e122d4b74cdf84351ed2907045c6a767b4cd..origin/main --pretty="%h" --reverse -- torch/distributed torch/csrc/distributed test/distributed test/cpp/c10d benchmarks/distributed)
do
# `git merge-base --is-ancestor` exits with code 0 if the given SHA is an ancestor, and non-0 otherwise
if git merge-base --is-ancestor $SHA HEAD || [[ $(git log --grep="(cherry picked from commit $SHA") ]]
then
echo "Skipping $SHA"
continue
fi
echo "Copying $SHA"
git cherry-pick -x "$SHA"
done
if [[ "${WITH_PUSH}" == true ]]; then
git push
fi

View File

@ -773,13 +773,13 @@ class TestBypassFailures(TestCase):
# than the one on the base commit. This should still count as broken trunk
"pr_num": 104214,
"related_failure_count": 0,
"flaky_or_broken_trunk": 1,
"unrelated_failure_count": 1,
},
{
# This PR had one broken trunk failure and it used ghstack
"pr_num": 105145,
"related_failure_count": 0,
"flaky_or_broken_trunk": 1,
"unrelated_failure_count": 1,
},
{
# The failure on the merge base was retried successfully and
@ -788,20 +788,20 @@ class TestBypassFailures(TestCase):
# be used to detect broken trunk
"pr_num": 107160,
"related_failure_count": 0,
"flaky_or_broken_trunk": 1,
"unrelated_failure_count": 4,
},
{
# This PR used Dr.CI broken trunk classification
"pr_num": 111253,
"related_failure_count": 1,
"flaky_or_broken_trunk": 1,
"unrelated_failure_count": 2,
},
]
for case in test_cases:
pr_num = case["pr_num"]
related_failure_count = case["related_failure_count"]
flaky_or_broken_trunk = case["flaky_or_broken_trunk"]
unrelated_failure_count = case["unrelated_failure_count"]
pr = GitHubPR("pytorch", "pytorch", pr_num)
checks = pr.get_checkrun_conclusions()
@ -823,7 +823,7 @@ class TestBypassFailures(TestCase):
)
self.assertTrue(len(pending) == 0)
self.assertTrue(
len(failed) == flaky_or_broken_trunk + related_failure_count
len(failed) == unrelated_failure_count + related_failure_count
)
def test_ignore_current(self, *args: Any) -> None:

View File

@ -2027,8 +2027,10 @@ def categorize_checks(
pending_checks: List[Tuple[str, Optional[str], Optional[int]]] = []
failed_checks: List[Tuple[str, Optional[str], Optional[int]]] = []
# failed_checks_categorization is used to keep track of all ignorable failures when saving the merge record on Rockset
failed_checks_categorization: Dict[str, List[Any]] = defaultdict(list)
# ok_failed_checks is used with ok_failed_checks_threshold while ignorable_failed_checks
# is used to keep track of all ignorable failures when saving the merge record on Rockset
ok_failed_checks: List[Tuple[str, Optional[str], Optional[int]]] = []
ignorable_failed_checks: Dict[str, List[Any]] = defaultdict(list)
# If required_checks is not set or empty, consider all names are relevant
relevant_checknames = [
@ -2056,38 +2058,36 @@ def categorize_checks(
continue
elif not is_passing_status(check_runs[checkname].status):
target = (
failed_checks_categorization[classification]
ignorable_failed_checks[classification]
if classification
in ("IGNORE_CURRENT_CHECK", "BROKEN_TRUNK", "FLAKY", "UNSTABLE")
else failed_checks
)
target.append((checkname, url, job_id))
flaky_or_broken_trunk = (
failed_checks_categorization["BROKEN_TRUNK"]
+ failed_checks_categorization["FLAKY"]
)
if classification in ("BROKEN_TRUNK", "FLAKY", "UNSTABLE"):
ok_failed_checks.append((checkname, url, job_id))
if flaky_or_broken_trunk:
if ok_failed_checks:
warn(
f"The following {len(flaky_or_broken_trunk)} checks failed but were likely due flakiness or broken trunk: "
+ ", ".join([x[0] for x in flaky_or_broken_trunk])
f"The following {len(ok_failed_checks)} checks failed but were likely due flakiness or broken trunk: "
+ ", ".join([x[0] for x in ok_failed_checks])
+ (
f" but this is greater than the threshold of {ok_failed_checks_threshold} so merge will fail"
if ok_failed_checks_threshold is not None
and len(flaky_or_broken_trunk) > ok_failed_checks_threshold
and len(ok_failed_checks) > ok_failed_checks_threshold
else ""
)
)
if (
ok_failed_checks_threshold is not None
and len(flaky_or_broken_trunk) > ok_failed_checks_threshold
and len(ok_failed_checks) > ok_failed_checks_threshold
):
failed_checks = failed_checks + flaky_or_broken_trunk
failed_checks = failed_checks + ok_failed_checks
# The list of failed_checks_categorization is returned so that it can be saved into the Rockset merge record
return (pending_checks, failed_checks, failed_checks_categorization)
# The list of ignorable_failed_checks is returned so that it can be saved into the Rockset merge record
return (pending_checks, failed_checks, ignorable_failed_checks)
def merge(

View File

@ -33,8 +33,6 @@ env:
# Needed for conda builds
{%- if "aarch64" in build_environment %}
ALPINE_IMAGE: "arm64v8/alpine"
{%- elif "s390x" in build_environment %}
ALPINE_IMAGE: "docker.io/s390x/alpine"
{%- else %}
ALPINE_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/tool/alpine"
{%- endif %}
@ -58,11 +56,8 @@ jobs:
uses: ./.github/workflows/_binary-build-linux.yml
with:!{{ upload.binary_env_as_input(config) }}
{%- if "aarch64" in build_environment %}
runs_on: linux.arm64.m7g.4xlarge
runs_on: linux.arm64.2xlarge
ALPINE_IMAGE: "arm64v8/alpine"
{%- elif "s390x" in build_environment %}
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
{%- elif "conda" in build_environment and config["gpu_arch_type"] == "cuda" %}
runs_on: linux.24xlarge
{%- endif %}
@ -71,17 +66,12 @@ jobs:
{%- if config.pytorch_extra_install_requirements is defined and config.pytorch_extra_install_requirements|d('')|length > 0 %}
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: !{{ config.pytorch_extra_install_requirements }}
{%- endif %}
{%- if config["gpu_arch_type"] == "cuda-aarch64" %}
timeout-minutes: 420
{%- endif %}
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
{%- if config["gpu_arch_type"] != "cuda-aarch64" %}
!{{ config["build_name"] }}-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: !{{ config["build_name"] }}-build
{%- if config["gpu_arch_type"] != "rocm" %}
{%- if config["gpu_arch_type"] != "rocm" %}
uses: ./.github/workflows/_binary-test-linux.yml
with:!{{ upload.binary_env_as_input(config) }}
build_name: !{{ config["build_name"] }}
@ -89,9 +79,6 @@ jobs:
{%- if "aarch64" in build_environment %}
runs_on: linux.arm64.2xlarge
ALPINE_IMAGE: "arm64v8/alpine"
{%- elif "s390x" in build_environment %}
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
{%- elif config["gpu_arch_type"] == "rocm" %}
runs_on: linux.rocm.gpu
{%- elif config["gpu_arch_type"] == "cuda" %}
@ -101,7 +88,7 @@ jobs:
{%- endif %}
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
{%- else %}
{%- else %}
runs-on: linux.rocm.gpu
timeout-minutes: !{{ common.timeout_minutes }}
!{{ upload.binary_env(config) }}
@ -126,8 +113,7 @@ jobs:
uses: ./pytorch/.github/actions/test-pytorch-binary
- name: Teardown ROCm
uses: ./.github/actions/teardown-rocm
{%- endif %}
{%- endif %}
{%- endif %}
{%- if branches == "nightly" %}
!{{ upload.upload_binaries(config) }}

View File

@ -57,11 +57,7 @@
id-token: write
contents: read
{%- if has_test %}
{%- if config["gpu_arch_type"] == "cuda-aarch64" %}
needs: !{{ config["build_name"] }}-build
{%- else %}
needs: !{{ config["build_name"] }}-test
{%- endif %}
{%- else %}
needs: !{{ config["build_name"] }}-build
{%- endif %}

View File

@ -12,15 +12,10 @@ on:
type: string
description: The build environment
runs_on:
required: false
default: linux.12xlarge
type: string
description: Hardware to run this "build"job on, linux.12xlarge or linux.arm64.2xlarge.
timeout-minutes:
required: false
default: 210
type: number
description: timeout for the job
required: false
default: linux.12xlarge
type: string
description: Hardware to run this "build"job on, linux.12xlarge or linux.arm64.2xlarge.
ALPINE_IMAGE:
required: false
type: string
@ -83,7 +78,7 @@ on:
jobs:
build:
runs-on: ${{ inputs.runs_on }}
timeout-minutes: ${{ inputs.timeout-minutes }}
timeout-minutes: 210
env:
PYTORCH_ROOT: ${{ inputs.PYTORCH_ROOT }}
BUILDER_ROOT: ${{ inputs.BUILDER_ROOT }}
@ -144,7 +139,6 @@ jobs:
run: env
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
if: inputs.build_environment != 'linux-s390x-binary-manywheel'
uses: pytorch/test-infra/.github/actions/setup-ssh@main
continue-on-error: true
with:
@ -153,14 +147,12 @@ jobs:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
with:
no-sudo: ${{ inputs.build_environment == 'linux-aarch64-binary-manywheel' || inputs.build_environment == 'linux-s390x-binary-manywheel' }}
no-sudo: ${{ inputs.build_environment == 'linux-aarch64-binary-manywheel' }}
- name: Setup Linux
if: inputs.build_environment != 'linux-s390x-binary-manywheel'
uses: ./.github/actions/setup-linux
- name: Chown workspace
if: inputs.build_environment != 'linux-s390x-binary-manywheel'
uses: ./.github/actions/chown-workspace
with:
ALPINE_IMAGE: ${{ inputs.ALPINE_IMAGE }}
@ -173,7 +165,7 @@ jobs:
rm -rf "${GITHUB_WORKSPACE}"
mkdir "${GITHUB_WORKSPACE}"
if [[ ${{ inputs.build_environment }} == 'linux-aarch64-binary-manywheel' ]] || [[ ${{ inputs.build_environment }} == 'linux-s390x-binary-manywheel' ]] ; then
if [[ ${{ inputs.build_environment }} == 'linux-aarch64-binary-manywheel' ]]; then
rm -rf "${RUNNER_TEMP}/artifacts"
mkdir "${RUNNER_TEMP}/artifacts"
fi
@ -220,7 +212,7 @@ jobs:
]}
- name: Pull Docker image
if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' && inputs.build_environment != 'linux-s390x-binary-manywheel' }}
if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' }}
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: ${{ inputs.DOCKER_IMAGE }}
@ -262,7 +254,7 @@ jobs:
fi
- name: Chown artifacts
if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' && inputs.build_environment != 'linux-s390x-binary-manywheel' }}
if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' }}
shell: bash
run: |
# Ensure the working directory gets chowned back to the current user
@ -277,20 +269,11 @@ jobs:
${{ runner.temp }}/artifacts/*
- name: Teardown Linux
if: always() && inputs.build_environment != 'linux-s390x-binary-manywheel'
if: always()
uses: pytorch/test-infra/.github/actions/teardown-linux@main
- name: Chown workspace
if: always() && inputs.build_environment != 'linux-s390x-binary-manywheel'
if: always()
uses: ./pytorch/.github/actions/chown-workspace
with:
ALPINE_IMAGE: ${{ inputs.ALPINE_IMAGE }}
- name: Cleanup docker
if: always() && inputs.build_environment == 'linux-s390x-binary-manywheel'
shell: bash
run: |
# on s390x stop the container for clean worker stop
# ignore expansion of "docker ps -q" since it could be empty
# shellcheck disable=SC2046
docker stop $(docker ps -q) || true

View File

@ -127,7 +127,6 @@ jobs:
} >> "${GITHUB_ENV} }}"
- name: "[FB EMPLOYEES] Enable SSH (Click me for login details)"
if: inputs.build_environment != 'linux-s390x-binary-manywheel'
uses: pytorch/test-infra/.github/actions/setup-ssh@main
continue-on-error: true
with:
@ -137,14 +136,12 @@ jobs:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
with:
no-sudo: ${{ inputs.build_environment == 'linux-aarch64-binary-manywheel' || inputs.build_environment == 'linux-s390x-binary-manywheel' }}
no-sudo: ${{ inputs.build_environment == 'linux-aarch64-binary-manywheel' }}
- name: Setup Linux
if: inputs.build_environment != 'linux-s390x-binary-manywheel'
uses: ./.github/actions/setup-linux
- name: Chown workspace
if: inputs.build_environment != 'linux-s390x-binary-manywheel'
uses: ./.github/actions/chown-workspace
with:
ALPINE_IMAGE: ${{ inputs.ALPINE_IMAGE }}
@ -206,7 +203,7 @@ jobs:
if: ${{ inputs.GPU_ARCH_TYPE == 'cuda' && steps.filter.outputs.is-test-matrix-empty == 'False' }}
- name: Pull Docker image
if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' && inputs.build_environment != 'linux-s390x-binary-manywheel' }}
if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' }}
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: ${{ inputs.DOCKER_IMAGE }}
@ -216,11 +213,11 @@ jobs:
uses: ./pytorch/.github/actions/test-pytorch-binary
- name: Teardown Linux
if: always() && inputs.build_environment != 'linux-s390x-binary-manywheel'
if: always()
uses: pytorch/test-infra/.github/actions/teardown-linux@main
- name: Chown workspace
if: always() && inputs.build_environment != 'linux-s390x-binary-manywheel'
if: always()
uses: ./pytorch/.github/actions/chown-workspace
with:
ALPINE_IMAGE: ${{ inputs.ALPINE_IMAGE }}

View File

@ -8,8 +8,6 @@ on:
jobs:
assign:
runs-on: ubuntu-latest
permissions:
issues: write
steps:
- name: Check for "/assigntome" in comment
uses: actions/github-script@v6
@ -28,14 +26,14 @@ jobs:
repo: context.repo.repo,
issue_number: issueNumber
});
const hasLabel = issue.labels.some(label => label.name === 'docathon-h1-2024');
const hasLabel = issue.labels.some(label => label.name === 'docathon-h2-2023');
if (hasLabel) {
if (issue.assignee !== null) {
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: issueNumber,
body: "The issue is already assigned. Please pick an opened and unnasigned issue with the [docathon-h1-2024 label](https://github.com/pytorch/pytorch/issues?q=is%3Aopen+is%3Aissue+label%3Adocathon-h1-2024)."
body: "The issue is already assigned. Please pick an opened and unnasigned issue with the [docathon-h2-2023 label](https://github.com/pytorch/pytorch/issues?q=is%3Aopen+is%3Aissue+label%3Adocathon-h2-2023)."
});
} else {
await github.rest.issues.addAssignees({
@ -46,7 +44,7 @@ jobs:
});
}
} else {
const commmentMessage = "This issue does not have the correct label. Please pick an opened and unnasigned issue with the [docathon-h1-2024 label](https://github.com/pytorch/pytorch/issues?q=is%3Aopen+is%3Aissue+label%3Adocathon-h1-2024)."
const commmentMessage = "This issue does not have the correct label. Please pick an opened and unnasigned issue with the [docathon-h2-2023 label](https://github.com/pytorch/pytorch/issues?q=is%3Aopen+is%3Aissue+label%3Adocathon-h2-2023)."
await github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,

View File

@ -49,7 +49,7 @@ jobs:
{ config: "default",
shard: 1,
num_shards: 1,
runner: "macos-14-xlarge",
runner: "macos-13-xlarge",
ios_platform: "SIMULATOR",
ios_arch: "arm64",
use_lite_interpreter: ${{ inputs.use_lite_interpreter || 1 }},
@ -60,7 +60,7 @@ jobs:
{ config: "default",
shard: 1,
num_shards: 1,
runner: "macos-14-xlarge",
runner: "macos-13-xlarge",
ios_platform: "OS",
ios_arch: "arm64",
use_lite_interpreter: ${{ inputs.use_lite_interpreter || 1 }},

View File

@ -18,6 +18,6 @@ jobs:
ROCKSET_API_KEY: ${{ secrets.ROCKSET_API_KEY }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
pip3 install requests==2.32.2
pip3 install requests==2.26
pip3 install rockset==1.0.3
python3 .github/scripts/close_nonexistent_disable_issues.py

View File

@ -29,7 +29,7 @@ jobs:
- name: Setup Python
uses: actions/setup-python@v4
with:
python-version: '3.11'
python-version: '3.8'
architecture: x64
check-latest: false

View File

@ -1,30 +0,0 @@
name: Docathon Labels Sync
on:
pull_request_target:
types: [opened, synchronize, edited]
branches: [main]
jobs:
check-labels:
runs-on: ubuntu-latest
permissions:
issues: write
pull-requests: write
steps:
- name: Check out the repo
uses: actions/checkout@v2
with:
fetch-depth: 1
- name: Set up Python
uses: actions/setup-python@v2
with:
python-version: 3.x
- name: Install dependencies
run: |
pip install requests==2.32.3
pip install PyGithub==2.3.0
- name: Run Python script
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: python ./.github/scripts/docathon-label-sync.py ${{ github.event.pull_request.number }}

View File

@ -38,19 +38,15 @@ jobs:
matrix:
runner: [linux.12xlarge]
docker-image-name: [
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9,
pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks,
pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks,
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9,
pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks,
pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks,
pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9,
pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9,
pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks,
pytorch-linux-focal-cuda11.8-cudnn8-py3-gcc9,
pytorch-linux-focal-py3.8-clang10,
pytorch-linux-focal-py3.11-clang10,
pytorch-linux-focal-py3.12-clang10,
pytorch-linux-focal-rocm-n-1-py3,
pytorch-linux-focal-rocm-n-py3,
pytorch-linux-jammy-cuda11.8-cudnn9-py3.8-clang12,
pytorch-linux-jammy-cuda11.8-cudnn8-py3.8-clang12,
pytorch-linux-focal-py3-clang9-android-ndk-r21e,
pytorch-linux-jammy-py3.8-gcc11,
pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks,
@ -58,7 +54,7 @@ jobs:
pytorch-linux-jammy-py3-clang15-asan,
pytorch-linux-focal-py3-clang10-onnx,
pytorch-linux-focal-linter,
pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter,
pytorch-linux-jammy-cuda11.8-cudnn8-py3.9-linter,
pytorch-linux-jammy-py3-clang12-executorch
]
include:

View File

@ -149,10 +149,3 @@ jobs:
- name: Teardown Linux
uses: pytorch/test-infra/.github/actions/teardown-linux@main
if: always()
validate:
needs: build
uses: pytorch/builder/.github/workflows/validate-docker-images.yml@main
with:
channel: nightly
ref: main

View File

@ -50,11 +50,11 @@ jobs:
GPU_ARCH_TYPE: cpu-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
DESIRED_PYTHON: "3.8"
runs_on: linux.arm64.m7g.4xlarge
runs_on: linux.arm64.2xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_8-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cpu-aarch64-test: # Testing
@ -100,51 +100,6 @@ jobs:
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_8-cuda-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.8"
runs_on: linux.arm64.m7g.4xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_8-cuda-aarch64
build_environment: linux-aarch64-binary-manywheel
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda-aarch64-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_8-cuda-aarch64-build
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda-aarch64
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_9-cpu-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -158,11 +113,11 @@ jobs:
GPU_ARCH_TYPE: cpu-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
DESIRED_PYTHON: "3.9"
runs_on: linux.arm64.m7g.4xlarge
runs_on: linux.arm64.2xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_9-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cpu-aarch64-test: # Testing
@ -208,51 +163,6 @@ jobs:
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_9-cuda-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.9"
runs_on: linux.arm64.m7g.4xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_9-cuda-aarch64
build_environment: linux-aarch64-binary-manywheel
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda-aarch64-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_9-cuda-aarch64-build
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.9"
build_name: manywheel-py3_9-cuda-aarch64
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cpu-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -266,11 +176,11 @@ jobs:
GPU_ARCH_TYPE: cpu-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
DESIRED_PYTHON: "3.10"
runs_on: linux.arm64.m7g.4xlarge
runs_on: linux.arm64.2xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cpu-aarch64-test: # Testing
@ -316,51 +226,6 @@ jobs:
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cuda-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.10"
runs_on: linux.arm64.m7g.4xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_10-cuda-aarch64
build_environment: linux-aarch64-binary-manywheel
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda-aarch64-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_10-cuda-aarch64-build
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda-aarch64
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cpu-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -374,11 +239,11 @@ jobs:
GPU_ARCH_TYPE: cpu-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
DESIRED_PYTHON: "3.11"
runs_on: linux.arm64.m7g.4xlarge
runs_on: linux.arm64.2xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cpu-aarch64-test: # Testing
@ -424,51 +289,6 @@ jobs:
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cuda-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.11"
runs_on: linux.arm64.m7g.4xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_11-cuda-aarch64
build_environment: linux-aarch64-binary-manywheel
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda-aarch64-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_11-cuda-aarch64-build
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda-aarch64
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cpu-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
@ -482,11 +302,11 @@ jobs:
GPU_ARCH_TYPE: cpu-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
DESIRED_PYTHON: "3.12"
runs_on: linux.arm64.m7g.4xlarge
runs_on: linux.arm64.2xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cpu-aarch64
build_environment: linux-aarch64-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cpu-aarch64-test: # Testing
@ -531,48 +351,3 @@ jobs:
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cuda-aarch64-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.12"
runs_on: linux.arm64.m7g.4xlarge
ALPINE_IMAGE: "arm64v8/alpine"
build_name: manywheel-py3_12-cuda-aarch64
build_environment: linux-aarch64-binary-manywheel
timeout-minutes: 420
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda-aarch64-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-cuda-aarch64-build
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_TYPE: cuda-aarch64
DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
DESIRED_DEVTOOLSET: cxx11-abi
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda-aarch64
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml

View File

@ -48,7 +48,7 @@ jobs:
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda11_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==8.7.0.84; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda11_8-test: # Testing
@ -88,7 +88,7 @@ jobs:
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_1
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_1-test: # Testing
@ -111,43 +111,3 @@ jobs:
runs_on: linux.4xlarge.nvidia.gpu
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_4-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_VERSION: 12.4
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_4
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_4-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_8-cuda12_4-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cu124
GPU_ARCH_VERSION: 12.4
GPU_ARCH_TYPE: cuda
DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_4
build_environment: linux-binary-manywheel
runs_on: linux.4xlarge.nvidia.gpu
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}

View File

@ -174,7 +174,7 @@ jobs:
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda11_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==8.7.0.84; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda11_8-test: # Testing
@ -237,7 +237,7 @@ jobs:
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_1
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_1-test: # Testing
@ -300,7 +300,7 @@ jobs:
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cuda12_4
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.7.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cuda12_4-test: # Testing
@ -690,7 +690,7 @@ jobs:
DESIRED_PYTHON: "3.9"
build_name: manywheel-py3_9-cuda11_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==8.7.0.84; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda11_8-test: # Testing
@ -753,7 +753,7 @@ jobs:
DESIRED_PYTHON: "3.9"
build_name: manywheel-py3_9-cuda12_1
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda12_1-test: # Testing
@ -816,7 +816,7 @@ jobs:
DESIRED_PYTHON: "3.9"
build_name: manywheel-py3_9-cuda12_4
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.7.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cuda12_4-test: # Testing
@ -1206,7 +1206,7 @@ jobs:
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda11_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==8.7.0.84; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda11_8-test: # Testing
@ -1269,7 +1269,7 @@ jobs:
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda12_1
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_1-test: # Testing
@ -1332,7 +1332,7 @@ jobs:
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cuda12_4
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.7.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cuda12_4-test: # Testing
@ -1722,7 +1722,7 @@ jobs:
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda11_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==8.7.0.84; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda11_8-test: # Testing
@ -1785,7 +1785,7 @@ jobs:
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda12_1
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_1-test: # Testing
@ -1848,7 +1848,7 @@ jobs:
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cuda12_4
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.7.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cuda12_4-test: # Testing
@ -2238,7 +2238,7 @@ jobs:
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda11_8
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu11==11.8.89; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu11==11.8.87; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu11==8.7.0.84; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu11==11.11.3.6; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu11==10.9.0.58; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu11==10.3.0.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu11==11.4.1.48; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu11==11.7.5.86; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu11==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu11==11.8.86; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda11_8-test: # Testing
@ -2301,7 +2301,7 @@ jobs:
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda12_1
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_1-test: # Testing
@ -2364,7 +2364,7 @@ jobs:
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cuda12_4
build_environment: linux-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.7.29; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cuda12_4-test: # Testing
@ -2410,3 +2410,209 @@ jobs:
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-rocm6_0-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.0
GPU_ARCH_VERSION: 6.0
GPU_ARCH_TYPE: rocm
DOCKER_IMAGE: pytorch/manylinux-builder:rocm6.0-main
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-rocm6_0
build_environment: linux-binary-manywheel
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-rocm6_0-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_12-rocm6_0-build
runs-on: linux.rocm.gpu
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.0
GPU_ARCH_VERSION: 6.0
GPU_ARCH_TYPE: rocm
SKIP_ALL_TESTS: 1
DOCKER_IMAGE: pytorch/manylinux-builder:rocm6.0-main
DESIRED_PYTHON: "3.12"
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
- uses: actions/download-artifact@v3
name: Download Build Artifacts
with:
name: manywheel-py3_12-rocm6_0
path: "${{ runner.temp }}/artifacts/"
- name: Checkout PyTorch
uses: malfet/checkout@silent-checkout
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
quiet-checkout: true
- name: Clean PyTorch checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: pytorch
- name: Checkout pytorch/builder
uses: malfet/checkout@silent-checkout
with:
ref: main
submodules: recursive
repository: pytorch/builder
path: builder
quiet-checkout: true
- name: Clean pytorch/builder checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: builder
- name: ROCm set GPU_FLAG
run: |
echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd --device=/dev/dri --group-add video --group-add daemon" >> "${GITHUB_ENV}"
- name: Pull Docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: pytorch/manylinux-builder:rocm6.0-main
- name: Test Pytorch binary
uses: ./pytorch/.github/actions/test-pytorch-binary
- name: Teardown ROCm
uses: ./.github/actions/teardown-rocm
manywheel-py3_12-rocm6_0-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-rocm6_0-test
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.0
GPU_ARCH_VERSION: 6.0
GPU_ARCH_TYPE: rocm
DOCKER_IMAGE: pytorch/manylinux-builder:rocm6.0-main
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-rocm6_0
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-rocm6_1-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.1
GPU_ARCH_VERSION: 6.1
GPU_ARCH_TYPE: rocm
DOCKER_IMAGE: pytorch/manylinux-builder:rocm6.1-main
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-rocm6_1
build_environment: linux-binary-manywheel
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-rocm6_1-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_12-rocm6_1-build
runs-on: linux.rocm.gpu
timeout-minutes: 240
env:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.1
GPU_ARCH_VERSION: 6.1
GPU_ARCH_TYPE: rocm
SKIP_ALL_TESTS: 1
DOCKER_IMAGE: pytorch/manylinux-builder:rocm6.1-main
DESIRED_PYTHON: "3.12"
steps:
- name: Setup ROCm
uses: ./.github/actions/setup-rocm
- uses: actions/download-artifact@v3
name: Download Build Artifacts
with:
name: manywheel-py3_12-rocm6_1
path: "${{ runner.temp }}/artifacts/"
- name: Checkout PyTorch
uses: malfet/checkout@silent-checkout
with:
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
submodules: recursive
path: pytorch
quiet-checkout: true
- name: Clean PyTorch checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: pytorch
- name: Checkout pytorch/builder
uses: malfet/checkout@silent-checkout
with:
ref: main
submodules: recursive
repository: pytorch/builder
path: builder
quiet-checkout: true
- name: Clean pytorch/builder checkout
run: |
# Remove any artifacts from the previous checkouts
git clean -fxd
working-directory: builder
- name: ROCm set GPU_FLAG
run: |
echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd --device=/dev/dri --group-add video --group-add daemon" >> "${GITHUB_ENV}"
- name: Pull Docker image
uses: pytorch/test-infra/.github/actions/pull-docker-image@main
with:
docker-image: pytorch/manylinux-builder:rocm6.1-main
- name: Test Pytorch binary
uses: ./pytorch/.github/actions/test-pytorch-binary
- name: Teardown ROCm
uses: ./.github/actions/teardown-rocm
manywheel-py3_12-rocm6_1-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-rocm6_1-test
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: rocm6.1
GPU_ARCH_VERSION: 6.1
GPU_ARCH_TYPE: rocm
DOCKER_IMAGE: pytorch/manylinux-builder:rocm6.1-main
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-rocm6_1
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml

View File

@ -1,353 +0,0 @@
# @generated DO NOT EDIT MANUALLY
# Template is at: .github/templates/linux_binary_build_workflow.yml.j2
# Generation script: .github/scripts/generate_ci_workflows.py
name: linux-s390x-binary-manywheel
on:
push:
# NOTE: Meta Employees can trigger new nightlies using: https://fburl.com/trigger_pytorch_nightly_build
branches:
- nightly
tags:
# NOTE: Binary build pipelines should only get triggered on release candidate builds
# Release candidate tags look like: v1.11.0-rc1
- v[0-9]+.[0-9]+.[0-9]+-rc[0-9]+
- 'ciflow/binaries/*'
- 'ciflow/binaries_wheel/*'
workflow_dispatch:
env:
# Needed for conda builds
ALPINE_IMAGE: "docker.io/s390x/alpine"
ANACONDA_USER: pytorch
AWS_DEFAULT_REGION: us-east-1
BINARY_ENV_FILE: /tmp/env
BUILD_ENVIRONMENT: linux-s390x-binary-manywheel
BUILDER_ROOT: /builder
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
PR_NUMBER: ${{ github.event.pull_request.number }}
PYTORCH_FINAL_PACKAGE_DIR: /artifacts
PYTORCH_ROOT: /pytorch
SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
SKIP_ALL_TESTS: 0
concurrency:
group: linux-s390x-binary-manywheel-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
cancel-in-progress: true
jobs:
manywheel-py3_8-cpu-s390x-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.8"
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_8-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cpu-s390x-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_8-cpu-s390x-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cpu-s390x
build_environment: linux-s390x-binary-manywheel
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_8-cpu-s390x-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_8-cpu-s390x-test
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.8"
build_name: manywheel-py3_8-cpu-s390x
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_9-cpu-s390x-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.9"
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_9-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cpu-s390x-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_9-cpu-s390x-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.9"
build_name: manywheel-py3_9-cpu-s390x
build_environment: linux-s390x-binary-manywheel
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_9-cpu-s390x-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_9-cpu-s390x-test
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.9"
build_name: manywheel-py3_9-cpu-s390x
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_10-cpu-s390x-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.10"
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_10-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cpu-s390x-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_10-cpu-s390x-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cpu-s390x
build_environment: linux-s390x-binary-manywheel
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_10-cpu-s390x-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_10-cpu-s390x-test
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.10"
build_name: manywheel-py3_10-cpu-s390x
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_11-cpu-s390x-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.11"
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_11-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cpu-s390x-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_11-cpu-s390x-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cpu-s390x
build_environment: linux-s390x-binary-manywheel
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_11-cpu-s390x-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_11-cpu-s390x-test
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.11"
build_name: manywheel-py3_11-cpu-s390x
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml
manywheel-py3_12-cpu-s390x-build:
if: ${{ github.repository_owner == 'pytorch' }}
uses: ./.github/workflows/_binary-build-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.12"
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
build_name: manywheel-py3_12-cpu-s390x
build_environment: linux-s390x-binary-manywheel
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cpu-s390x-test: # Testing
if: ${{ github.repository_owner == 'pytorch' }}
needs: manywheel-py3_12-cpu-s390x-build
uses: ./.github/workflows/_binary-test-linux.yml
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cpu-s390x
build_environment: linux-s390x-binary-manywheel
runs_on: linux.s390x
ALPINE_IMAGE: "docker.io/s390x/alpine"
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
manywheel-py3_12-cpu-s390x-upload: # Uploading
if: ${{ github.repository_owner == 'pytorch' }}
permissions:
id-token: write
contents: read
needs: manywheel-py3_12-cpu-s390x-test
with:
PYTORCH_ROOT: /pytorch
BUILDER_ROOT: /builder
PACKAGE_TYPE: manywheel
# TODO: This is a legacy variable that we eventually want to get rid of in
# favor of GPU_ARCH_VERSION
DESIRED_CUDA: cpu
GPU_ARCH_TYPE: cpu-s390x
DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
DESIRED_PYTHON: "3.12"
build_name: manywheel-py3_12-cpu-s390x
secrets:
github-token: ${{ secrets.GITHUB_TOKEN }}
conda-pytorchbot-token: ${{ secrets.CONDA_PYTORCHBOT_TOKEN }}
conda-pytorchbot-token-test: ${{ secrets.CONDA_PYTORCHBOT_TOKEN_TEST }}
uses: ./.github/workflows/_binary-upload.yml

View File

@ -34,7 +34,7 @@ concurrency:
jobs:
conda-py3_8-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -152,7 +152,7 @@ jobs:
uses: ./.github/workflows/_binary-upload.yml
conda-py3_9-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -270,7 +270,7 @@ jobs:
uses: ./.github/workflows/_binary-upload.yml
conda-py3_10-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -388,7 +388,7 @@ jobs:
uses: ./.github/workflows/_binary-upload.yml
conda-py3_11-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -506,7 +506,7 @@ jobs:
uses: ./.github/workflows/_binary-upload.yml
conda-py3_12-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch

View File

@ -34,7 +34,7 @@ concurrency:
jobs:
libtorch-cpu-shared-with-deps-cxx11-abi-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch

View File

@ -34,7 +34,7 @@ concurrency:
jobs:
wheel-py3_8-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -46,7 +46,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
@ -153,7 +153,7 @@ jobs:
uses: ./.github/workflows/_binary-upload.yml
wheel-py3_9-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -165,7 +165,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
@ -272,7 +272,7 @@ jobs:
uses: ./.github/workflows/_binary-upload.yml
wheel-py3_10-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -284,7 +284,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
@ -391,7 +391,7 @@ jobs:
uses: ./.github/workflows/_binary-upload.yml
wheel-py3_11-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -403,7 +403,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}
@ -510,7 +510,7 @@ jobs:
uses: ./.github/workflows/_binary-upload.yml
wheel-py3_12-cpu-build:
if: ${{ github.repository_owner == 'pytorch' }}
runs-on: macos-14-xlarge
runs-on: macos-13-xlarge
timeout-minutes: 240
env:
PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@ -522,7 +522,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
# For sccache access (only on non-forked PRs)
AWS_ACCESS_KEY_ID: ${{ secrets.MACOS_SCCACHE_S3_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.MACOS_SCCACHE_S3_SECRET_ACCESS_KEY }}

View File

@ -46,7 +46,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -290,7 +290,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -536,7 +536,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -782,7 +782,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.8"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -1027,7 +1027,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -1271,7 +1271,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -1517,7 +1517,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -1763,7 +1763,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.9"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2008,7 +2008,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2252,7 +2252,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2498,7 +2498,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2744,7 +2744,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.10"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -2989,7 +2989,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -3233,7 +3233,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -3479,7 +3479,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -3725,7 +3725,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.11"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -3970,7 +3970,7 @@ jobs:
GPU_ARCH_TYPE: cpu
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -4214,7 +4214,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -4460,7 +4460,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash
@ -4706,7 +4706,7 @@ jobs:
GPU_ARCH_TYPE: cuda
SKIP_ALL_TESTS: 1
DESIRED_PYTHON: "3.12"
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cudnn-cu12==8.9.2.26; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cublas-cu12==12.1.3.1; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.0.2.54; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.2.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.4.5.107; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.1.0.106; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.20.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'
steps:
- name: Display EC2 information
shell: bash

View File

@ -1,108 +0,0 @@
name: inductor-cu124
on:
push:
tags:
- ciflow/inductor-cu124/*
workflow_dispatch:
schedule:
# Run every 4 hours during the week and every 12 hours on the weekend
- cron: 45 0,4,8,12,16,20 * * 1-5
- cron: 45 4,12 * * 0,6
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
cancel-in-progress: true
permissions: read-all
jobs:
linux-focal-cuda12_4-py3_10-gcc9-inductor-build:
# Should be synced with the one in inductor.yml, but this doesn't run inductor_timm
name: cuda12.4-py3.10-gcc9-sm86
uses: ./.github/workflows/_linux-build.yml
with:
sync-tag: linux-focal-cuda12_4-py3_10-gcc9-inductor-build
build-environment: linux-focal-cuda12.4-py3.10-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "inductor", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_distributed", shard: 1, num_shards: 1, runner: "linux.g5.12xlarge.nvidia.gpu" },
{ config: "inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "dynamic_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "dynamic_inductor_timm", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "dynamic_inductor_timm", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "dynamic_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "dynamic_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_timm", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_timm", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "aot_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_cpp_wrapper_abi_compatible", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_4-py3_10-gcc9-inductor-test:
name: cuda12.4-py3.10-gcc9-sm86
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_4-py3_10-gcc9-inductor-build
with:
sync-tag: linux-focal-cuda12_4-py3_10-gcc9-inductor-test
build-environment: linux-focal-cuda12.4-py3.10-gcc9-sm86
docker-image: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-inductor-build.outputs.test-matrix }}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_4-py3_10-gcc9-inductor-build-gcp:
name: cuda12.4-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.4-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [
{ config: "inductor_torchbench_smoketest_perf", shard: 1, num_shards: 1, runner: "linux.gcp.a100" },
]}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_4-py3_10-gcc9-inductor-test-gcp:
name: cuda12.4-py3.10-gcc9-sm80
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_4-py3_10-gcc9-inductor-build-gcp
with:
build-environment: linux-focal-cuda12.4-py3.10-gcc9-sm80
docker-image: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-inductor-build-gcp.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-inductor-build-gcp.outputs.test-matrix }}
use-gha: anything-non-empty-to-use-gha
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_4-py3_12-gcc9-inductor-build:
name: cuda12.4-py3.12-gcc9-sm86
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.4-py3.12-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "inductor", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_4-py3_12-gcc9-inductor-test:
name: cuda12.4-py3.12-gcc9-sm86
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_4-py3_12-gcc9-inductor-build
with:
build-environment: linux-focal-cuda12.4-py3.12-gcc9-sm86
docker-image: ${{ needs.linux-focal-cuda12_4-py3_12-gcc9-inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_4-py3_12-gcc9-inductor-build.outputs.test-matrix }}

View File

@ -21,7 +21,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [

View File

@ -18,7 +18,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [

View File

@ -71,7 +71,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [

View File

@ -23,7 +23,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.6'
test-matrix: |
{ include: [

View File

@ -44,7 +44,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
@ -86,7 +86,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [
@ -107,56 +107,6 @@ jobs:
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_1-py3_12-gcc9-inductor-build:
name: cuda12.1-py3.12-gcc9-sm86
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.12-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "inductor", shard: 1, num_shards: 1, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_1-py3_12-gcc9-inductor-test:
name: cuda12.1-py3.12-gcc9-sm86
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_1-py3_12-gcc9-inductor-build
with:
build-environment: linux-focal-cuda12.1-py3.12-gcc9-sm86
docker-image: ${{ needs.linux-focal-cuda12_1-py3_12-gcc9-inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_12-gcc9-inductor-build.outputs.test-matrix }}
linux-focal-cuda12_4-py3_10-gcc9-inductor-build:
# Should be synced with the one in inductor-periodic.yml but this only runs inductor_timm
name: cuda12.4-py3.10-gcc9-sm86
uses: ./.github/workflows/_linux-build.yml
with:
sync-tag: linux-focal-cuda12_4-py3_10-gcc9-inductor-build
build-environment: linux-focal-cuda12.4-py3.10-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.6'
test-matrix: |
{ include: [
{ config: "inductor_timm", shard: 1, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "inductor_timm", shard: 2, num_shards: 2, runner: "linux.g5.4xlarge.nvidia.gpu" },
]}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-focal-cuda12_4-py3_10-gcc9-inductor-test:
name: cuda12.4-py3.10-gcc9-sm86
uses: ./.github/workflows/_linux-test.yml
needs: linux-focal-cuda12_4-py3_10-gcc9-inductor-build
with:
sync-tag: linux-focal-cuda12_4-py3_10-gcc9-inductor-test
build-environment: linux-focal-cuda12.4-py3.10-gcc9-sm86
docker-image: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-inductor-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-inductor-build.outputs.test-matrix }}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
linux-jammy-cpu-py3_8-gcc11-inductor-build:
name: linux-jammy-cpu-py3.8-gcc11-inductor
uses: ./.github/workflows/_linux-build.yml
@ -170,17 +120,12 @@ jobs:
{ config: "cpu_inductor_timm", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_huggingface_freezing", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
{ config: "cpu_inductor_timm_freezing", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_timm_freezing", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_torchbench_freezing", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "cpu_inductor_torchbench_freezing", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_huggingface", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_timm", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_timm", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_torchbench", shard: 1, num_shards: 2, runner: "linux.12xlarge" },
{ config: "dynamic_cpu_inductor_torchbench", shard: 2, num_shards: 2, runner: "linux.12xlarge" },
{ config: "inductor_torchbench_cpu_smoketest_perf", shard: 1, num_shards: 1, runner: "linux.24xl.spr-metal" },
{ config: "inductor_torchbench_cpu_smoketest_perf", shard: 1, num_shards: 1, runner: "linux.12xlarge" },
]}
secrets:
HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}

View File

@ -20,7 +20,7 @@ jobs:
with:
timeout: 120
runner: linux.2xlarge
docker-image: pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter
docker-image: pytorch-linux-jammy-cuda11.8-cudnn8-py3.9-linter
# NB: A shallow checkout won't work here because calculate-docker-image requires a full checkout
# to run git rev-parse HEAD~:.ci/docker when a new image is needed
fetch-depth: 0
@ -36,7 +36,7 @@ jobs:
with:
timeout: 120
runner: linux.2xlarge
docker-image: pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter
docker-image: pytorch-linux-jammy-cuda11.8-cudnn8-py3.9-linter
# NB: A shallow checkout won't work here because calculate-docker-image requires a full checkout
# to run git rev-parse HEAD~:.ci/docker when a new image is needed
fetch-depth: 0

View File

@ -13,31 +13,29 @@ concurrency:
permissions: read-all
jobs:
macos-py3-arm64-build:
name: macos-py3-arm64
macos-13-py3-arm64-build:
name: macos-13-py3-arm64
uses: ./.github/workflows/_mac-build.yml
with:
sync-tag: macos-py3-arm64-build
build-environment: macos-py3-arm64
build-environment: macos-13-py3-arm64
runner-type: macos-m1-stable
build-generates-artifacts: true
# To match the one pre-installed in the m1 runners
python-version: 3.9.12
# The runner macos-m2-14 is not a typo, it's a custom runner that is different
# than our AWS macos-m1-14 runners
test-matrix: |
{ include: [
{ config: "mps", shard: 1, num_shards: 1, runner: "macos-m1-13" },
{ config: "mps", shard: 1, num_shards: 1, runner: "macos-m1-stable" },
{ config: "mps", shard: 1, num_shards: 1, runner: "macos-m2-14" },
]}
macos-py3-arm64-mps-test:
name: macos-py3-arm64-mps
uses: ./.github/workflows/_mac-test-mps.yml
needs: macos-py3-arm64-build
needs: macos-13-py3-arm64-build
with:
sync-tag: macos-py3-arm64-mps-test
build-environment: macos-py3-arm64
build-environment: macos-13-py3-arm64
# Same as the build job
python-version: 3.9.12
test-matrix: ${{ needs.macos-py3-arm64-build.outputs.test-matrix }}
test-matrix: ${{ needs.macos-13-py3-arm64-build.outputs.test-matrix }}

View File

@ -32,7 +32,7 @@ jobs:
cache: pip
- run: |
pip3 install requests==2.32.2 rockset==1.0.3 boto3==1.19.12
pip3 install requests==2.26 rockset==1.0.3 boto3==1.19.12
- name: Upload external contribution stats
uses: nick-fields/retry@v2.8.2

View File

@ -37,59 +37,6 @@ jobs:
permissions:
id-token: write
contents: read
linux-focal-cuda12_1-py3_10-gcc9-build:
name: linux-focal-cuda12.1-py3.10-gcc9
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "nogpu_AVX512", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "nogpu_NO_AVX2", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_1-py3_10-gcc9-test:
name: linux-focal-cuda12.1-py3.10-gcc9
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-focal-cuda12_1-py3_10-gcc9-build
- target-determination
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9
docker-image: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-build.outputs.test-matrix }}
linux-focal-cuda12_4-py3_10-gcc9-build:
name: linux-focal-cuda12.4-py3.10-gcc9
uses: ./.github/workflows/_linux-build-label.yml
with:
build-environment: linux-focal-cuda12.4-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "deploy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
{ config: "nogpu_AVX512", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "nogpu_NO_AVX2", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_4-py3_10-gcc9-test:
name: linux-focal-cuda12.4-py3.10-gcc9
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-focal-cuda12_4-py3_10-gcc9-build
- target-determination
with:
timeout-minutes: 360
build-environment: linux-focal-cuda12.4-py3.10-gcc9
docker-image: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-build.outputs.test-matrix }}
parallelnative-linux-jammy-py3_8-gcc11-build:
name: parallelnative-linux-jammy-py3.8-gcc11
@ -120,7 +67,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda11.8-py3.9-gcc9
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn8-py3-gcc9
cuda-arch-list: 8.6
test-matrix: |
{ include: [
@ -142,7 +89,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda11.8-py3.10-gcc9-debug
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn8-py3-gcc9
build-with-debug: true
test-matrix: |
{ include: [
@ -204,7 +151,7 @@ jobs:
{ config: "default",
shard: 1,
num_shards: 1,
runner: "macos-14-xlarge",
runner: "macos-13-xlarge",
ios_platform: "SIMULATOR",
ios_arch: "arm64",
use_lite_interpreter: 1,
@ -215,7 +162,7 @@ jobs:
{ config: "default",
shard: 1,
num_shards: 1,
runner: "macos-14-xlarge",
runner: "macos-13-xlarge",
ios_platform: "OS",
ios_arch: "arm64",
use_lite_interpreter: 1,

View File

@ -237,7 +237,7 @@ jobs:
uses: ./.github/workflows/_linux-build-label.yml
with:
build-environment: linux-focal-cuda11.8-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda11.8-cudnn8-py3-gcc9
test-matrix: |
{ include: [
{ config: "distributed", shard: 1, num_shards: 3, runner: "linux.8xlarge.nvidia.gpu" },
@ -262,7 +262,7 @@ jobs:
uses: ./.github/workflows/_linux-build-label.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 5, runner: "linux.4xlarge.nvidia.gpu" },
@ -297,12 +297,12 @@ jobs:
{ config: "default", shard: 1, num_shards: 1 },
]}
linux-jammy-cuda-11_8-cudnn9-py3_8-clang12-build:
name: linux-jammy-cuda11.8-cudnn9-py3.8-clang12
linux-jammy-cuda-11_8-cudnn8-py3_8-clang12-build:
name: linux-jammy-cuda11.8-cudnn8-py3.8-clang12
uses: ./.github/workflows/_linux-build-label.yml
with:
build-environment: linux-jammy-cuda11.8-cudnn9-py3.8-clang12
docker-image-name: pytorch-linux-jammy-cuda11.8-cudnn9-py3.8-clang12
build-environment: linux-jammy-cuda11.8-cudnn8-py3.8-clang12
docker-image-name: pytorch-linux-jammy-cuda11.8-cudnn8-py3.8-clang12
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1 },
@ -361,7 +361,7 @@ jobs:
uses: ./.github/workflows/_bazel-build-test.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-bazel-test
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
cuda-version: cpu
test-matrix: |
{ include: [
@ -373,25 +373,13 @@ jobs:
uses: ./.github/workflows/_bazel-build-test.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-bazel-test
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
cuda-version: "12.1"
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_4-py3_10-gcc9-bazel-test:
name: linux-focal-cuda12.4-py3.10-gcc9-bazel-test
uses: ./.github/workflows/_bazel-build-test.yml
with:
build-environment: linux-focal-cuda12.4-py3.10-gcc9-bazel-test
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9
cuda-version: "12.4"
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-py3-clang9-android-ndk-r21e-gradle-custom-build-single:
name: linux-focal-py3-clang9-android-ndk-r21e-gradle-custom-build-single
uses: ./.github/workflows/_android-build-test.yml
@ -447,7 +435,7 @@ jobs:
uses: ./.github/workflows/_linux-build-label.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
cuda-arch-list: 8.6
test-matrix: |
{ include: [

View File

@ -41,7 +41,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3-gcc9-slow-gradcheck
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
cuda-arch-list: 8.6
test-matrix: |
{ include: [
@ -70,7 +70,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
cuda-arch-list: 8.6
test-matrix: |
{ include: [

View File

@ -1,30 +0,0 @@
name: Sync Distributed Folder
on:
#push:
# branches:
# - 'main'
# paths:
# - 'torch/distributed/**'
workflow_dispatch:
pull_request:
paths:
- '.github/scripts/sync_distributed_folder_prototype.sh'
- '.github/workflows/sync_distributed_folder_prototype.yml'
env:
WITH_PUSH: ${{ github.event_name == 'push' && github.ref == 'refs/heads/main' }}
permissions:
contents: write
concurrency:
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
cancel-in-progress: true
jobs:
sync:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- run: .github/scripts/sync_distributed_folder_prototype.sh

View File

@ -26,7 +26,7 @@ jobs:
id: calculate-docker-image
uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
with:
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
working-directory: pytorch
- name: Use following to pull public copy of the image

View File

@ -16,7 +16,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks
cuda-arch-list: '8.0'
test-matrix: |
{ include: [

View File

@ -34,39 +34,36 @@ jobs:
id-token: write
contents: read
linux-focal-cuda12_4-py3_10-gcc9-sm86-build:
name: linux-focal-cuda12.4-py3.10-gcc9-sm86
uses: ./.github/workflows/_linux-build-label.yml
linux-focal-cuda12_1-py3_10-gcc9-build:
name: linux-focal-cuda12.1-py3.10-gcc9
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.4-py3.10-gcc9-sm86
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9
cuda-arch-list: 8.6
build-environment: linux-focal-cuda12.1-py3.10-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 2, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 3, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 4, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "default", shard: 5, num_shards: 5, runner: "linux.g5.4xlarge.nvidia.gpu" },
{ config: "nogpu_AVX512", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "nogpu_NO_AVX2", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "linux.4xlarge.nvidia.gpu" },
]}
linux-focal-cuda12_4-py3_10-gcc9-sm86-test:
name: linux-focal-cuda12.4-py3.10-gcc9-sm86
linux-focal-cuda12_1-py3_10-gcc9-test:
name: linux-focal-cuda12.1-py3.10-gcc9
uses: ./.github/workflows/_linux-test.yml
needs:
- linux-focal-cuda12_4-py3_10-gcc9-sm86-build
- linux-focal-cuda12_1-py3_10-gcc9-build
- target-determination
with:
build-environment: linux-focal-cuda12.4-py3.10-gcc9-sm86
docker-image: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-sm86-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_4-py3_10-gcc9-sm86-build.outputs.test-matrix }}
build-environment: linux-focal-cuda12.1-py3.10-gcc9
docker-image: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-cuda12_1-py3_10-gcc9-build.outputs.test-matrix }}
libtorch-linux-focal-cuda12_1-py3_7-gcc9-debug-build:
name: libtorch-linux-focal-cuda12.1-py3.7-gcc9-debug
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: libtorch-linux-focal-cuda12.1-py3.7-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
build-generates-artifacts: false
runner: linux.4xlarge
test-matrix: |
@ -80,32 +77,7 @@ jobs:
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.1-py3.10-gcc9-no-ops
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1 },
]}
libtorch-linux-focal-cuda12_4-py3_7-gcc9-debug-build:
name: libtorch-linux-focal-cuda12.4-py3.7-gcc9-debug
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: libtorch-linux-focal-cuda12.4-py3.7-gcc9
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9
build-generates-artifacts: false
runner: linux.4xlarge
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1 },
]}
# no-ops builds test USE_PER_OPERATOR_HEADERS=0 where ATen/ops is not generated
linux-focal-cuda12_4-py3_10-gcc9-no-ops-build:
name: linux-focal-cuda12.4-py3.10-gcc9-no-ops
uses: ./.github/workflows/_linux-build.yml
with:
build-environment: linux-focal-cuda12.4-py3.10-gcc9-no-ops
docker-image-name: pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9
docker-image-name: pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1 },
@ -122,12 +94,12 @@ jobs:
{ config: "default", shard: 1, num_shards: 1, runner: "linux.2xlarge" },
]}
macos-py3-arm64-build:
name: macos-py3-arm64
macos-13-py3-arm64-build:
name: macos-13-py3-arm64
uses: ./.github/workflows/_mac-build.yml
with:
sync-tag: macos-py3-arm64-build
build-environment: macos-py3-arm64
build-environment: macos-13-py3-arm64
runner-type: macos-m1-stable
build-generates-artifacts: true
# To match the one pre-installed in the m1 runners
@ -142,30 +114,31 @@ jobs:
macos-py3-arm64-mps-test:
name: macos-py3-arm64-mps
uses: ./.github/workflows/_mac-test-mps.yml
needs: macos-py3-arm64-build
if: needs.macos-py3-arm64-build.outputs.build-outcome == 'success'
needs: macos-13-py3-arm64-build
if: needs.macos-13-py3-arm64-build.outputs.build-outcome == 'success'
with:
sync-tag: macos-py3-arm64-mps-test
build-environment: macos-py3-arm64
build-environment: macos-13-py3-arm64
# Same as the build job
python-version: 3.9.12
test-matrix: |
{ include: [
{ config: "mps", shard: 1, num_shards: 1, runner: "macos-m1-13" },
{ config: "mps", shard: 1, num_shards: 1, runner: "macos-m1-stable" },
{ config: "mps", shard: 1, num_shards: 1, runner: "macos-m1-14" },
]}
macos-py3-arm64-test:
name: macos-py3-arm64
macos-13-py3-arm64-test:
name: macos-13-py3-arm64
uses: ./.github/workflows/_mac-test.yml
needs:
- macos-py3-arm64-build
- macos-13-py3-arm64-build
- target-determination
with:
build-environment: macos-py3-arm64
build-environment: macos-13-py3-arm64
# Same as the build job
python-version: 3.9.12
test-matrix: ${{ needs.macos-py3-arm64-build.outputs.test-matrix }}
test-matrix: ${{ needs.macos-13-py3-arm64-build.outputs.test-matrix }}
win-vs2019-cpu-py3-build:
name: win-vs2019-cpu-py3
@ -219,9 +192,7 @@ jobs:
sync-tag: rocm-build
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 2, runner: "linux.rocm.gpu" },
{ config: "default", shard: 2, num_shards: 2, runner: "linux.rocm.gpu" },
{ config: "distributed", shard: 1, num_shards: 1, runner: "linux.rocm.gpu" },
{ config: "default", shard: 1, num_shards: 1, runner: "linux.rocm.gpu" },
]}
linux-focal-rocm6_1-py3_8-test:
@ -237,4 +208,4 @@ jobs:
build-environment: linux-focal-rocm6.1-py3.8
docker-image: ${{ needs.linux-focal-rocm6_1-py3_8-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-rocm6_1-py3_8-build.outputs.test-matrix }}
tests-to-include: "test_nn test_torch test_cuda test_ops test_unary_ufuncs test_binary_ufuncs test_autograd inductor/test_torchinductor distributed/test_c10d_common distributed/test_c10d_nccl"
tests-to-include: "test_nn test_torch test_cuda test_ops test_unary_ufuncs test_binary_ufuncs test_autograd inductor/test_torchinductor"

View File

@ -32,3 +32,174 @@ jobs:
echo
echo "Once the jobs are deemed stable enough (% red signal < 5% and TTS < 3h),"
echo " they can graduate and move back to pull or trunk."
#
# Experimental ARC jobs
#
llm-td:
name: before-test
uses: ./.github/workflows/llm_td_retrieval.yml
permissions:
id-token: write
contents: read
target-determination:
name: before-test
uses: ./.github/workflows/target_determination.yml
needs: llm-td
permissions:
id-token: write
contents: read
linux-jammy-py3_8-gcc11-build:
name: linux-jammy-py3.8-gcc11
uses: ./.github/workflows/_linux-build-rg.yml
with:
build-environment: linux-jammy-py3.8-gcc11
docker-image-name: pytorch-linux-jammy-py3.8-gcc11
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "default", shard: 2, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "default", shard: 3, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "docs_test", shard: 1, num_shards: 1, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "jit_legacy", shard: 1, num_shards: 1, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "backwards_compat", shard: 1, num_shards: 1, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "distributed", shard: 1, num_shards: 2, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "distributed", shard: 2, num_shards: 2, runner: "arc-lf-linux.2xlarge.avx512" },
]}
linux-jammy-py3_8-gcc11-test:
name: linux-jammy-py3.8-gcc11
uses: ./.github/workflows/_linux-test-rg.yml
needs:
- linux-jammy-py3_8-gcc11-build
- target-determination
with:
build-environment: linux-jammy-py3.8-gcc11
docker-image: ${{ needs.linux-jammy-py3_8-gcc11-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-jammy-py3_8-gcc11-build.outputs.test-matrix }}
linux-jammy-py3_8-gcc11-no-ops:
name: linux-jammy-py3.8-gcc11-no-ops
uses: ./.github/workflows/_linux-build-rg.yml
with:
build-environment: linux-jammy-py3.8-gcc11-no-ops
docker-image-name: pytorch-linux-jammy-py3.8-gcc11
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1 },
]}
linux-jammy-py3_8-gcc11-pch:
name: linux-jammy-py3.8-gcc11-pch
uses: ./.github/workflows/_linux-build-rg.yml
with:
build-environment: linux-jammy-py3.8-gcc11-pch
docker-image-name: pytorch-linux-jammy-py3.8-gcc11
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 1 },
]}
linux-focal-py3_8-clang10-onnx-build:
name: linux-focal-py3.8-clang10-onnx
uses: ./.github/workflows/_linux-build-rg.yml
with:
build-environment: linux-focal-py3.8-clang10-onnx
docker-image-name: pytorch-linux-focal-py3-clang10-onnx
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 2, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "default", shard: 2, num_shards: 2, runner: "arc-lf-linux.2xlarge.avx512" },
]}
linux-focal-py3_8-clang10-onnx-test:
name: linux-focal-py3.8-clang10-onnx
uses: ./.github/workflows/_linux-test-rg.yml
needs:
- linux-focal-py3_8-clang10-onnx-build
- target-determination
with:
build-environment: linux-focal-py3.8-clang10-onnx
docker-image: ${{ needs.linux-focal-py3_8-clang10-onnx-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-py3_8-clang10-onnx-build.outputs.test-matrix }}
linux-jammy-py3_10-clang15-asan-build:
name: linux-jammy-py3.10-clang15-asan
uses: ./.github/workflows/_linux-build-rg.yml
with:
build-environment: linux-jammy-py3.10-clang15-asan
docker-image-name: pytorch-linux-jammy-py3-clang15-asan
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 2, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 3, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 4, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 5, num_shards: 6, runner: "linux.4xlarge" },
{ config: "default", shard: 6, num_shards: 6, runner: "linux.4xlarge" },
]}
sync-tag: asan-build-arc
linux-focal-py3_8-clang10-build:
name: linux-focal-py3.8-clang10
uses: ./.github/workflows/_linux-build-rg.yml
with:
build-environment: linux-focal-py3.8-clang10
docker-image-name: pytorch-linux-focal-py3.8-clang10
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "default", shard: 2, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "default", shard: 3, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "crossref", shard: 1, num_shards: 2, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "crossref", shard: 2, num_shards: 2, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
]}
linux-focal-py3_8-clang10-test:
name: linux-focal-py3.8-clang10
uses: ./.github/workflows/_linux-test-rg.yml
needs:
- linux-focal-py3_8-clang10-build
- target-determination
with:
build-environment: linux-focal-py3.8-clang10
docker-image: ${{ needs.linux-focal-py3_8-clang10-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-py3_8-clang10-build.outputs.test-matrix }}
linux-focal-py3_11-clang10-build:
name: linux-focal-py3.11-clang10
uses: ./.github/workflows/_linux-build-rg.yml
with:
build-environment: linux-focal-py3.11-clang10
docker-image-name: pytorch-linux-focal-py3.11-clang10
test-matrix: |
{ include: [
{ config: "default", shard: 1, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "default", shard: 2, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "default", shard: 3, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "crossref", shard: 1, num_shards: 2, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "crossref", shard: 2, num_shards: 2, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "dynamo", shard: 1, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "dynamo", shard: 2, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
{ config: "dynamo", shard: 3, num_shards: 3, runner: "arc-lf-linux.2xlarge.avx512" },
]}
linux-focal-py3_11-clang10-test:
name: linux-focal-py3.11-clang10
uses: ./.github/workflows/_linux-test-rg.yml
needs:
- linux-focal-py3_11-clang10-build
- target-determination
with:
build-environment: linux-focal-py3.11-clang10
docker-image: ${{ needs.linux-focal-py3_11-clang10-build.outputs.docker-image }}
test-matrix: ${{ needs.linux-focal-py3_11-clang10-build.outputs.test-matrix }}
#
# End of Experimental ARC jobs
#

View File

@ -28,7 +28,7 @@ jobs:
- name: Install Python Packages
run: |
pip3 install rockset==1.0.3 boto3==1.19.12 requests==2.32.2
pip3 install rockset==1.0.3 boto3==1.19.12 requests==2.27.1
- name: Create alerts
run: |

View File

@ -2,7 +2,7 @@ name: Upload test stats
on:
workflow_run:
workflows: [pull, trunk, periodic, inductor, unstable, slow, unstable-periodic, inductor-periodic, rocm, inductor-micro-benchmark]
workflows: [pull, trunk, periodic, inductor, unstable, slow, unstable-periodic, inductor-periodic, rocm]
types:
- completed
@ -47,10 +47,9 @@ jobs:
cache: pip
- run: |
pip3 install requests==2.32.2 rockset==1.0.3 boto3==1.19.12
pip3 install requests==2.26 rockset==1.0.3 boto3==1.19.12
- name: Upload test artifacts
id: upload-s3
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
@ -95,19 +94,6 @@ jobs:
# Analyze the results from disable tests rerun and upload them to S3
python3 -m tools.stats.check_disabled_tests --workflow-run-id "${WORKFLOW_RUN_ID}" --workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" --repo "${REPO_FULLNAME}"
- name: Upload gpt-fast benchmark results to Rockset
if: steps.upload-s3.outcome && steps.upload-s3.outcome == 'success' && github.event.workflow_run.name == 'inductor-micro-benchmark'
env:
ROCKSET_API_KEY: ${{ secrets.ROCKSET_API_KEY }}
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
WORKFLOW_RUN_ID: ${{ github.event.workflow_run.id }}
WORKFLOW_RUN_ATTEMPT: ${{ github.event.workflow_run.run_attempt }}
REPO_FULLNAME: ${{ github.event.workflow_run.repository.full_name }}
HEAD_BRANCH: ${{ github.event.workflow_run.head_branch }}
run: |
python3 -m tools.stats.upload_dynamo_perf_stats --workflow-run-id "${WORKFLOW_RUN_ID}" --workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" --repo "${REPO_FULLNAME}" --head-branch "${HEAD_BRANCH}" --rockset-collection oss_ci_benchmark --rockset-workspace benchmarks --match-filename "^gpt_fast_benchmark"
check-api-rate:
if: ${{ always() && github.repository_owner == 'pytorch' }}
runs-on: ubuntu-latest

View File

@ -40,7 +40,7 @@ jobs:
cache: pip
- run: |
pip3 install requests==2.32.2 rockset==1.0.3 boto3==1.19.12
pip3 install requests==2.26 rockset==1.0.3 boto3==1.19.12
- name: Upload torch dynamo performance stats to S3
id: upload-s3
@ -68,4 +68,4 @@ jobs:
REPO_FULLNAME: ${{ github.event.workflow_run.repository.full_name }}
HEAD_BRANCH: ${{ github.event.workflow_run.head_branch }}
run: |
python3 -m tools.stats.upload_dynamo_perf_stats --workflow-run-id "${WORKFLOW_RUN_ID}" --workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" --repo "${REPO_FULLNAME}" --head-branch "${HEAD_BRANCH}" --rockset-collection torch_dynamo_perf_stats --rockset-workspace inductor --match-filename "^inductor_"
python3 -m tools.stats.upload_dynamo_perf_stats --workflow-run-id "${WORKFLOW_RUN_ID}" --workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" --repo "${REPO_FULLNAME}" --head-branch "${HEAD_BRANCH}"

View File

@ -1,43 +0,0 @@
name: Upload test stats intermediate
on:
workflow_dispatch:
inputs:
workflow_id:
description: workflow_id of the run
required: true
workflow_run_attempt:
description: workflow_run_attempt of the run
required: true
jobs:
intermediate_upload_test_stats:
name: Intermediate upload test stats for ${{ inputs.workflow_id }}
runs-on: ubuntu-22.04
environment: upload-stats
steps:
- name: Checkout PyTorch
uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
with:
fetch-depth: 1
submodules: false
- uses: actions/setup-python@v4
with:
python-version: '3.11'
cache: pip
- run: |
pip3 install requests==2.32.2 rockset==1.0.3 boto3==1.19.12
- name: Upload test stats
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
WORKFLOW_RUN_ID: ${{ inputs.workflow_id }}
WORKFLOW_RUN_ATTEMPT: ${{ inputs.workflow_run_attempt }}
run: |
python3 -m tools.stats.upload_test_stats_intermediate \
--workflow-run-id "${WORKFLOW_RUN_ID}" \
--workflow-run-attempt "${WORKFLOW_RUN_ATTEMPT}" \

32
.gitmodules vendored
View File

@ -2,6 +2,10 @@
ignore = dirty
path = third_party/pybind11
url = https://github.com/pybind/pybind11.git
[submodule "third_party/cub"]
ignore = dirty
path = third_party/cub
url = https://github.com/NVlabs/cub.git
[submodule "third_party/eigen"]
ignore = dirty
path = third_party/eigen
@ -18,6 +22,10 @@
ignore = dirty
path = third_party/protobuf
url = https://github.com/protocolbuffers/protobuf.git
[submodule "third_party/ios-cmake"]
ignore = dirty
path = third_party/ios-cmake
url = https://github.com/Yangqing/ios-cmake.git
[submodule "third_party/NNPACK"]
ignore = dirty
path = third_party/NNPACK
@ -42,6 +50,10 @@
ignore = dirty
path = third_party/psimd
url = https://github.com/Maratyszcza/psimd.git
[submodule "third_party/zstd"]
ignore = dirty
path = third_party/zstd
url = https://github.com/facebook/zstd.git
[submodule "third_party/cpuinfo"]
ignore = dirty
path = third_party/cpuinfo
@ -54,6 +66,10 @@
ignore = dirty
path = third_party/onnx
url = https://github.com/onnx/onnx.git
[submodule "third_party/onnx-tensorrt"]
ignore = dirty
path = third_party/onnx-tensorrt
url = https://github.com/onnx/onnx-tensorrt
[submodule "third_party/sleef"]
ignore = dirty
path = third_party/sleef
@ -70,6 +86,14 @@
ignore = dirty
path = third_party/gemmlowp/gemmlowp
url = https://github.com/google/gemmlowp.git
[submodule "third_party/QNNPACK"]
ignore = dirty
path = third_party/QNNPACK
url = https://github.com/pytorch/QNNPACK
[submodule "third_party/neon2sse"]
ignore = dirty
path = third_party/neon2sse
url = https://github.com/intel/ARM_NEON_2_x86_SSE.git
[submodule "third_party/fbgemm"]
ignore = dirty
path = third_party/fbgemm
@ -78,6 +102,10 @@
ignore = dirty
path = third_party/foxi
url = https://github.com/houseroad/foxi.git
[submodule "third_party/tbb"]
path = third_party/tbb
url = https://github.com/01org/tbb
branch = tbb_2018
[submodule "android/libs/fbjni"]
ignore = dirty
path = android/libs/fbjni
@ -124,7 +152,3 @@
[submodule "third_party/opentelemetry-cpp"]
path = third_party/opentelemetry-cpp
url = https://github.com/open-telemetry/opentelemetry-cpp.git
[submodule "third_party/cpp-httplib"]
path = third_party/cpp-httplib
url = https://github.com/yhirose/cpp-httplib.git
branch = v0.15.3

View File

@ -193,7 +193,6 @@ include_patterns = [
'aten/src/ATen/*.cpp',
'aten/src/ATen/core/*.h',
'aten/src/ATen/core/*.cpp',
'aten/src/ATen/detail/*',
'aten/src/ATen/functorch/*.h',
'aten/src/ATen/functorch/*.cpp',
'c10/**/*.cpp',
@ -235,6 +234,7 @@ exclude_patterns = [
'torch/csrc/jit/serialization/import_legacy.cpp',
'torch/csrc/jit/serialization/export.cpp',
'torch/csrc/lazy/**/*',
'torch/csrc/onnx/init.cpp',
'torch/csrc/mps/**/*',
]
init_command = [
@ -1052,18 +1052,19 @@ exclude_patterns = [
'test/quantization/fx/test_numeric_suite_fx.py',
'test/quantization/fx/test_quantize_fx.py',
'test/quantization/fx/test_subgraph_rewriter.py',
'test/test_datapipe.py',
'test/test_fake_tensor.py',
'test/test_flop_counter.py',
'test/test_function_schema.py',
'test/test_functional_autograd_benchmark.py',
'test/test_functional_optim.py',
'test/test_functionalization_of_rng_ops.py',
'test/test_datapipe.py',
'test/test_futures.py',
'test/test_fx.py',
'test/test_fx_experimental.py',
'test/test_fx_passes.py',
'test/test_fx_reinplace_pass.py',
'test/test_hub.py',
'test/test_import_stats.py',
'test/test_itt.py',
'test/test_jit.py',
@ -1072,6 +1073,7 @@ exclude_patterns = [
'test/test_jit_disabled.py',
'test/test_jit_fuser.py',
'test/test_jit_fuser_legacy.py',
'test/test_jit_fuser_te.py',
'test/test_jit_legacy.py',
'test/test_jit_llga_fuser.py',
'test/test_jit_profiling.py',
@ -1079,7 +1081,9 @@ exclude_patterns = [
'test/test_jit_string.py',
'test/test_jiterator.py',
'test/test_kernel_launch_checks.py',
'test/test_license.py',
'test/test_linalg.py',
'test/test_logging.py',
'test/test_masked.py',
'test/test_maskedtensor.py',
'test/test_matmul_cuda.py',
@ -1101,6 +1105,13 @@ exclude_patterns = [
'test/test_native_mha.py',
'test/test_nestedtensor.py',
'test/test_nn.py',
'test/test_nnapi.py',
'test/test_numba_integration.py',
'test/test_numpy_interop.py',
'test/test_nvfuser_dynamo.py',
'test/test_nvfuser_frontend.py',
'test/test_openmp.py',
'test/test_optim.py',
'test/test_out_dtype_op.py',
'test/test_overrides.py',
'test/test_prims.py',
@ -1114,6 +1125,9 @@ exclude_patterns = [
'test/test_segment_reductions.py',
'test/test_serialization.py',
'test/test_set_default_mobile_cpu_allocator.py',
'test/test_shape_ops.py',
'test/test_show_pickle.py',
'test/test_sort_and_select.py',
'test/test_sparse.py',
'test/test_sparse_csr.py',
'test/test_sparse_semi_structured.py',
@ -1127,13 +1141,30 @@ exclude_patterns = [
'test/test_tensorexpr.py',
'test/test_tensorexpr_pybind.py',
'test/test_testing.py',
'test/test_throughput_benchmark.py',
'test/test_torch.py',
'test/test_transformers.py',
'test/test_type_hints.py',
'test/test_type_info.py',
'test/test_type_promotion.py',
'test/test_unary_ufuncs.py',
'test/test_utils.py',
'test/test_vulkan.py',
'test/test_xnnpack_integration.py',
'test/torch_np/numpy_test/**/*.py',
'test/typing/fail/bitwise_ops.py',
'test/typing/fail/creation_ops.py',
'test/typing/fail/random.py',
'test/typing/pass/creation_ops.py',
'test/typing/pass/math_ops.py',
'test/typing/reveal/module_list.py',
'test/typing/reveal/namedtuple.py',
'test/typing/reveal/opt_size.py',
'test/typing/reveal/size.py',
'test/typing/reveal/tensor_constructors.py',
'test/typing/reveal/tensor_copy.py',
'test/typing/reveal/tensor_sampling.py',
'test/typing/reveal/torch_optim.py',
'torch/_awaits/__init__.py',
'torch/_custom_op/__init__.py',
'torch/_custom_op/autograd.py',
@ -1532,6 +1563,28 @@ exclude_patterns = [
'torch/distributed/optim/post_localSGD_optimizer.py',
'torch/distributed/optim/utils.py',
'torch/distributed/optim/zero_redundancy_optimizer.py',
'torch/distributed/pipeline/__init__.py',
'torch/distributed/pipeline/sync/__init__.py',
'torch/distributed/pipeline/sync/_balance/__init__.py',
'torch/distributed/pipeline/sync/_balance/blockpartition.py',
'torch/distributed/pipeline/sync/_balance/profile.py',
'torch/distributed/pipeline/sync/batchnorm.py',
'torch/distributed/pipeline/sync/checkpoint.py',
'torch/distributed/pipeline/sync/copy.py',
'torch/distributed/pipeline/sync/dependency.py',
'torch/distributed/pipeline/sync/microbatch.py',
'torch/distributed/pipeline/sync/phony.py',
'torch/distributed/pipeline/sync/pipe.py',
'torch/distributed/pipeline/sync/pipeline.py',
'torch/distributed/pipeline/sync/skip/__init__.py',
'torch/distributed/pipeline/sync/skip/layout.py',
'torch/distributed/pipeline/sync/skip/namespace.py',
'torch/distributed/pipeline/sync/skip/portal.py',
'torch/distributed/pipeline/sync/skip/skippable.py',
'torch/distributed/pipeline/sync/skip/tracker.py',
'torch/distributed/pipeline/sync/stream.py',
'torch/distributed/pipeline/sync/utils.py',
'torch/distributed/pipeline/sync/worker.py',
'torch/distributed/remote_device.py',
'torch/distributed/rendezvous.py',
'torch/distributed/rpc/__init__.py',
@ -1556,6 +1609,7 @@ exclude_patterns = [
'torch/distributed/tensor/parallel/input_reshard.py',
'torch/distributed/tensor/parallel/multihead_attention_tp.py',
'torch/distributed/tensor/parallel/style.py',
'torch/distributed/utils.py',
'torch/fft/__init__.py',
'torch/func/__init__.py',
'torch/functional.py',
@ -1647,6 +1701,18 @@ exclude_patterns = [
'torch/hub.py',
'torch/library.py',
'torch/linalg/__init__.py',
# UFMT causes import cycle on masked
'torch/masked/__init__.py',
'torch/masked/_docs.py',
'torch/masked/_ops.py',
'torch/masked/maskedtensor/__init__.py',
'torch/masked/maskedtensor/_ops_refs.py',
'torch/masked/maskedtensor/binary.py',
'torch/masked/maskedtensor/core.py',
'torch/masked/maskedtensor/creation.py',
'torch/masked/maskedtensor/passthrough.py',
'torch/masked/maskedtensor/reductions.py',
'torch/masked/maskedtensor/unary.py',
'torch/monitor/__init__.py',
'torch/nested/__init__.py',
'torch/nn/__init__.py',
@ -1825,6 +1891,8 @@ exclude_patterns = [
'torch/testing/_internal/distributed/nn/__init__.py',
'torch/testing/_internal/distributed/nn/api/__init__.py',
'torch/testing/_internal/distributed/nn/api/remote_module_test.py',
'torch/testing/_internal/distributed/pipe_with_ddp_test.py',
'torch/testing/_internal/distributed/pipeline/__init__.py',
'torch/testing/_internal/distributed/rpc/__init__.py',
'torch/testing/_internal/distributed/rpc/dist_autograd_test.py',
'torch/testing/_internal/distributed/rpc/dist_optimizer_test.py',
@ -1867,6 +1935,8 @@ exclude_patterns = [
'torch/utils/_mode_utils.py',
'torch/utils/_python_dispatch.py',
'torch/utils/_stats.py',
'torch/utils/_sympy/__init__.py',
'torch/utils/_sympy/functions.py',
'torch/utils/_traceback.py',
'torch/utils/_zip.py',
'torch/utils/backcompat/__init__.py',
@ -2079,7 +2149,7 @@ init_command = [
'python3',
'tools/linter/adapters/pip_init.py',
'--dry-run={{DRYRUN}}',
'ruff==0.4.8',
'ruff==0.4.1',
]
is_formatter = true

View File

@ -125,6 +125,10 @@ filegroup(
data = [":generate-code"],
)
exports_files(
srcs = ["aten/src/ATen/cpu/tbb/extra/version_string.ver.in"],
)
# ATen
filegroup(
name = "aten_base_cpp",
@ -271,6 +275,7 @@ header_template_rule(
"@AT_BUILD_WITH_LAPACK@": "1",
"@AT_PARALLEL_OPENMP@": "0",
"@AT_PARALLEL_NATIVE@": "1",
"@AT_PARALLEL_NATIVE_TBB@": "0",
"@AT_BLAS_F2C@": "0",
"@AT_BLAS_USE_CBLAS_DOT@": "1",
},
@ -354,9 +359,6 @@ cc_library(
":aten_src_ATen_config",
] + generated_cpu_cpp + aten_ufunc_generated_cpu_sources("aten/src/ATen/{}"),
copts = ATEN_COPTS,
linkopts = [
"-ldl",
],
data = if_cuda(
[":libcaffe2_nvrtc.so"],
[],
@ -454,15 +456,65 @@ CAFFE2_COPTS = COMMON_COPTS + [
filegroup(
name = "caffe2_core_srcs",
srcs = [
"caffe2/core/allocator.cc",
"caffe2/core/blob_serialization.cc",
"caffe2/core/blob_stats.cc",
"caffe2/core/common.cc",
"caffe2/core/context.cc",
"caffe2/core/context_base.cc",
"caffe2/core/db.cc",
"caffe2/core/event.cc",
"caffe2/core/export_c10_op_to_caffe2.cc",
"caffe2/core/graph.cc",
"caffe2/core/init.cc",
"caffe2/core/init_denormals.cc",
"caffe2/core/init_intrinsics_check.cc",
"caffe2/core/init_omp.cc",
"caffe2/core/int8_serialization.cc",
"caffe2/core/memonger.cc",
"caffe2/core/module.cc",
"caffe2/core/net.cc",
"caffe2/core/net_async_base.cc",
"caffe2/core/net_async_scheduling.cc",
"caffe2/core/net_async_task.cc",
"caffe2/core/net_async_task_future.cc",
"caffe2/core/net_async_task_graph.cc",
"caffe2/core/net_async_tracing.cc",
"caffe2/core/net_dag_utils.cc",
"caffe2/core/net_parallel.cc",
"caffe2/core/net_simple.cc",
"caffe2/core/net_simple_refcount.cc",
"caffe2/core/nomnigraph/Representations/NeuralNet.cc",
"caffe2/core/nomnigraph/tests/test_util.cc",
"caffe2/core/numa.cc",
"caffe2/core/operator.cc",
"caffe2/core/operator_schema.cc",
"caffe2/core/plan_executor.cc",
"caffe2/core/prof_dag_counters.cc",
"caffe2/core/qtensor.cc",
"caffe2/core/qtensor_serialization.cc",
"caffe2/core/stats.cc",
"caffe2/core/tensor.cc",
"caffe2/core/tensor_int8.cc",
"caffe2/core/test_utils.cc",
"caffe2/core/transform.cc",
"caffe2/core/types.cc",
"caffe2/core/workspace.cc",
],
)
filegroup(
name = "caffe2_perfkernels_srcs",
srcs = [
"caffe2/perfkernels/adagrad.cc",
"caffe2/perfkernels/embedding_lookup.cc",
"caffe2/perfkernels/embedding_lookup_idx.cc",
"caffe2/perfkernels/fused_8bit_rowwise_embedding_lookup.cc",
"caffe2/perfkernels/fused_8bit_rowwise_embedding_lookup_idx.cc",
"caffe2/perfkernels/fused_nbit_rowwise_conversion.cc",
"caffe2/perfkernels/lstm_unit_cpu_common.cc",
"caffe2/perfkernels/math_cpu_base.cc",
"caffe2/perfkernels/typed_axpy.cc",
],
)
@ -480,7 +532,19 @@ filegroup(
filegroup(
name = "caffe2_utils_srcs",
srcs = [
"caffe2/utils/bench_utils.cc",
"caffe2/utils/cpuid.cc",
"caffe2/utils/math/broadcast.cc",
"caffe2/utils/math/elementwise.cc",
"caffe2/utils/math/reduce.cc",
"caffe2/utils/math/transpose.cc",
"caffe2/utils/math/utils.cc",
"caffe2/utils/math_cpu.cc",
"caffe2/utils/murmur_hash3.cc",
"caffe2/utils/proto_utils.cc",
"caffe2/utils/proto_wrap.cc",
"caffe2/utils/signal_handler.cc",
"caffe2/utils/smart_tensor_printer.cc",
"caffe2/utils/string_utils.cc",
"caffe2/utils/threadpool/ThreadPool.cc",
"caffe2/utils/threadpool/pthreadpool.cc",
@ -498,9 +562,12 @@ cc_library(
name = "caffe2_for_aten_headers",
hdrs = [
"caffe2/core/common.h",
"caffe2/core/logging.h",
"caffe2/core/types.h",
"caffe2/perfkernels/common.h",
"caffe2/perfkernels/embedding_lookup.h",
"caffe2/perfkernels/embedding_lookup_idx.h",
"caffe2/utils/cpuid.h",
"caffe2/utils/fixed_divisor.h",
] + glob([
"caffe2/utils/threadpool/*.h",
@ -510,6 +577,7 @@ cc_library(
deps = [
":caffe2_core_macros",
"//c10",
"//caffe2/proto:caffe2_pb",
],
)
@ -517,9 +585,18 @@ cc_library(
name = "caffe2_headers",
hdrs = glob(
[
"caffe2/core/*.h",
"caffe2/core/nomnigraph/include/nomnigraph/Converters/*.h",
"caffe2/core/nomnigraph/include/nomnigraph/Generated/*.h",
"caffe2/core/nomnigraph/include/nomnigraph/Graph/*.h",
"caffe2/core/nomnigraph/include/nomnigraph/Representations/*.h",
"caffe2/core/nomnigraph/include/nomnigraph/Support/*.h",
"caffe2/core/nomnigraph/include/nomnigraph/Transformations/*.h",
"caffe2/core/nomnigraph/tests/*.h",
"caffe2/perfkernels/*.h",
"caffe2/serialize/*.h",
"caffe2/utils/*.h",
"caffe2/utils/math/*.h",
"caffe2/utils/threadpool/*.h",
"modules/**/*.h",
],
@ -528,12 +605,18 @@ cc_library(
],
) + if_cuda(glob([
"caffe2/**/*.cuh",
"caffe2/image/*.h",
])),
copts = CAFFE2_COPTS,
includes = [
"caffe2/core/nomnigraph/include",
],
visibility = ["//visibility:public"],
deps = [
":caffe2_core_macros",
":caffe2_for_aten_headers",
"//caffe2/proto:caffe2_pb",
"//caffe2/proto:cc_proto",
],
)
@ -554,6 +637,8 @@ cc_library(
":caffe2_perfkernels_avx",
":caffe2_perfkernels_avx2",
":caffe2_perfkernels_avx512",
"//caffe2/proto:caffe2_pb",
"//caffe2/proto:cc_proto",
"//third_party/miniz-2.1.0:miniz",
"@com_google_protobuf//:protobuf",
"@eigen",
@ -578,7 +663,6 @@ cu_library(
name = "torch_cuda",
srcs = [
"torch/csrc/distributed/c10d/intra_node_comm.cu",
"torch/csrc/distributed/c10d/Utils.cu",
"torch/csrc/distributed/c10d/quantization/quantization_gpu.cu",
],
copts = torch_cuda_half_options,
@ -687,7 +771,7 @@ cc_library(
[
"torch/*.h",
"torch/csrc/**/*.h",
"torch/csrc/distributed/c10d/**/*.hpp",
"torch/csrc/distributed/c10d/*.hpp",
"torch/lib/libshm/*.h",
],
exclude = [
@ -746,14 +830,10 @@ cc_library(
"torch/csrc/cuda/python_nccl.cpp",
"torch/csrc/cuda/nccl.cpp",
"torch/csrc/distributed/c10d/intra_node_comm.cu",
"torch/csrc/distributed/c10d/Utils.cu",
"torch/csrc/distributed/c10d/quantization/quantization_gpu.cu",
],
)) + torch_sources,
copts = TORCH_COPTS,
linkopts = [
"-lrt",
],
defines = [
"CAFFE2_NIGHTLY_VERSION=20200115",
],
@ -761,8 +841,8 @@ cc_library(
deps = [
":caffe2",
":torch_headers",
"//caffe2/proto:torch_cc_proto",
"@kineto",
"@cpp-httplib",
] + if_cuda([
"@cuda//:nvToolsExt",
"@cutlass",
@ -774,9 +854,6 @@ cc_library(
cc_library(
name = "shm",
srcs = glob(["torch/lib/libshm/*.cpp"]),
linkopts = [
"-lrt",
],
deps = [
":torch",
],

File diff suppressed because it is too large Load Diff

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@ -667,6 +667,7 @@ only interested in a specific component.
- Working on a test binary? Run `(cd build && ninja bin/test_binary_name)` to
rebuild only that test binary (without rerunning cmake). (Replace `ninja` with
`make` if you don't have ninja installed).
- Don't need Caffe2? Pass `BUILD_CAFFE2=0` to disable Caffe2 build.
On the initial build, you can also speed things up with the environment
variables `DEBUG`, `USE_DISTRIBUTED`, `USE_MKLDNN`, `USE_CUDA`, `USE_FLASH_ATTENTION`, `USE_MEM_EFF_ATTENTION`, `BUILD_TEST`, `USE_FBGEMM`, `USE_NNPACK` and `USE_QNNPACK`.
@ -789,7 +790,7 @@ USE_PRECOMPILED_HEADERS=1 python setup.py develop
```
This adds a build step where the compiler takes `<ATen/ATen.h>` and essentially
dumps its internal AST to a file so the compiler can avoid repeating itself for
dumps it's internal AST to a file so the compiler can avoid repeating itself for
every `.cpp` file.
One caveat is that when enabled, this header gets included in every file by default.
@ -1195,7 +1196,7 @@ build_with_asan()
LDFLAGS="-stdlib=libstdc++" \
CFLAGS="-fsanitize=address -fno-sanitize-recover=all -shared-libasan -pthread" \
CXX_FLAGS="-pthread" \
USE_CUDA=0 USE_OPENMP=0 USE_DISTRIBUTED=0 DEBUG=1 \
USE_CUDA=0 USE_OPENMP=0 BUILD_CAFFE2_OPS=0 USE_DISTRIBUTED=0 DEBUG=1 \
python setup.py develop
}
@ -1320,7 +1321,7 @@ There are two possible choices for which commit to use:
1. Checkout commit `B`, the head of the PR (manually committed by the PR
author).
2. Checkout commit `C`, the hypothetical result of what would happen if the PR
were merged into its destination (usually `main`).
were merged into it's destination (usually `main`).
For all practical purposes, most people can think of the commit being used as
commit `B` (choice **1**).

View File

@ -1,4 +1,4 @@
![PyTorch Logo](https://github.com/pytorch/pytorch/raw/main/docs/source/_static/img/pytorch-logo-dark.png)
![PyTorch Logo](https://github.com/pytorch/pytorch/blob/main/docs/source/_static/img/pytorch-logo-dark.png)
--------------------------------------------------------------------------------
@ -24,9 +24,6 @@ Our trunk health (Continuous Integration signals) can be found at [hud.pytorch.o
- [NVIDIA Jetson Platforms](#nvidia-jetson-platforms)
- [From Source](#from-source)
- [Prerequisites](#prerequisites)
- [NVIDIA CUDA Support](#nvidia-cuda-support)
- [AMD ROCm Support](#amd-rocm-support)
- [Intel GPU Support](#intel-gpu-support)
- [Install Dependencies](#install-dependencies)
- [Get the PyTorch Source](#get-the-pytorch-source)
- [Install PyTorch](#install-pytorch)
@ -98,7 +95,7 @@ from several research papers on this topic, as well as current and past work suc
While this technique is not unique to PyTorch, it's one of the fastest implementations of it to date.
You get the best of speed and flexibility for your crazy research.
![Dynamic graph](https://github.com/pytorch/pytorch/raw/main/docs/source/_static/img/dynamic_graph.gif)
![Dynamic graph](https://github.com/pytorch/pytorch/blob/main/docs/source/_static/img/dynamic_graph.gif)
### Python First
@ -165,7 +162,6 @@ If you are installing from source, you will need:
We highly recommend installing an [Anaconda](https://www.anaconda.com/download) environment. You will get a high-quality BLAS library (MKL) and you get controlled dependency versions regardless of your Linux distro.
##### NVIDIA CUDA Support
If you want to compile with CUDA support, [select a supported version of CUDA from our support matrix](https://pytorch.org/get-started/locally/), then install the following:
- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads)
- [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v8.5 or above
@ -178,7 +174,6 @@ Other potentially useful environment variables may be found in `setup.py`.
If you are building for NVIDIA's Jetson platforms (Jetson Nano, TX1, TX2, AGX Xavier), Instructions to install PyTorch for Jetson Nano are [available here](https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/)
##### AMD ROCm Support
If you want to compile with ROCm support, install
- [AMD ROCm](https://rocm.docs.amd.com/en/latest/deploy/linux/quick_start.html) 4.0 and above installation
- ROCm is currently supported only for Linux systems.
@ -186,14 +181,6 @@ If you want to compile with ROCm support, install
If you want to disable ROCm support, export the environment variable `USE_ROCM=0`.
Other potentially useful environment variables may be found in `setup.py`.
##### Intel GPU Support
If you want to compile with Intel GPU support, follow these
- [PyTorch Prerequisites for Intel GPUs](https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html) instructions.
- Intel GPU is supported for Linux and Windows.
If you want to disable Intel GPU support, export the environment variable `USE_XPU=0`.
Other potentially useful environment variables may be found in `setup.py`.
#### Install Dependencies
**Common**
@ -209,11 +196,10 @@ pip install -r requirements.txt
```bash
conda install intel::mkl-static intel::mkl-include
# CUDA only: Add LAPACK support for the GPU if needed
conda install -c pytorch magma-cuda121 # or the magma-cuda* that matches your CUDA version from https://anaconda.org/pytorch/repo
conda install -c pytorch magma-cuda110 # or the magma-cuda* that matches your CUDA version from https://anaconda.org/pytorch/repo
# (optional) If using torch.compile with inductor/triton, install the matching version of triton
# Run from the pytorch directory after cloning
# For Intel GPU support, please explicitly `export USE_XPU=1` before running command.
make triton
```
@ -393,7 +379,7 @@ You can also pass the `CMAKE_VARS="..."` environment variable to specify additio
See [setup.py](./setup.py) for the list of available variables.
```bash
make -f docker.Makefile
CMAKE_VARS="BUILD_CAFFE2=ON BUILD_CAFFE2_OPS=ON" make -f docker.Makefile
```
### Building the Documentation

View File

@ -37,7 +37,6 @@
- [TL;DR](#tldr)
- [Accelerator Software](#accelerator-software)
- [Special support cases](#special-support-cases)
- [Operating Systems](#operating-systems)
- [Submitting Tutorials](#submitting-tutorials)
- [Special Topics](#special-topics)
- [Updating submodules for a release](#updating-submodules-for-a-release)
@ -49,14 +48,14 @@
Following is the Release Compatibility Matrix for PyTorch releases:
| PyTorch version | Python | Stable CUDA | Experimental CUDA | Stable ROCm |
| --- | --- | --- | --- | --- |
| 2.3 | >=3.8, <=3.11, (3.12 experimental) | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 | ROCm 6.0 |
| 2.2 | >=3.8, <=3.11, (3.12 experimental) | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 | ROCm 5.7 |
| 2.1 | >=3.8, <=3.11 | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 | ROCm 5.6 |
| 2.0 | >=3.8, <=3.11 | CUDA 11.7, CUDNN 8.5.0.96 | CUDA 11.8, CUDNN 8.7.0.84 | ROCm 5.4 |
| 1.13 | >=3.7, <=3.10 | CUDA 11.6, CUDNN 8.3.2.44 | CUDA 11.7, CUDNN 8.5.0.96 | ROCm 5.2 |
| 1.12 | >=3.7, <=3.10 | CUDA 11.3, CUDNN 8.3.2.44 | CUDA 11.6, CUDNN 8.3.2.44 | ROCm 5.0 |
| PyTorch version | Python | Stable CUDA | Experimental CUDA |
| --- | --- | --- | --- |
| 2.3 | >=3.8, <=3.11, (3.12 experimental) | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 |
| 2.2 | >=3.8, <=3.11, (3.12 experimental) | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 |
| 2.1 | >=3.8, <=3.11 | CUDA 11.8, CUDNN 8.7.0.84 | CUDA 12.1, CUDNN 8.9.2.26 |
| 2.0 | >=3.8, <=3.11 | CUDA 11.7, CUDNN 8.5.0.96 | CUDA 11.8, CUDNN 8.7.0.84 |
| 1.13 | >=3.7, <=3.10 | CUDA 11.6, CUDNN 8.3.2.44 | CUDA 11.7, CUDNN 8.5.0.96 |
| 1.12 | >=3.7, <=3.10 | CUDA 11.3, CUDNN 8.3.2.44 | CUDA 11.6, CUDNN 8.3.2.44 |
## Release Cadence
@ -263,7 +262,7 @@ requires `pytorchbot`, so it's only available in PyTorch atm.
### Cherry Picking Reverts
If PR that has been cherry-picked into release branch has been reverted, its cherry-pick must be reverted as well.
If PR that has been cherry-picked into release branch has been reverted, it's cherry-pick must be reverted as well.
Reverts for changes that was committed into the main branch prior to the branch cut, must be propagated into release branch as well.
@ -427,15 +426,6 @@ the size restrictions for publishing on PyPI so the default version that is publ
These special support cases will be handled on a case by case basis and support may be continued if current PyTorch maintainers feel as though there may still be a
need to support these particular versions of software.
## Operating Systems
Supported OS flavors are summarized in the table below:
| Operating System family | Architectrue | Notes |
| --- | --- | --- |
| Linux | aarch64, x86_64 | Wheels are manylinux2014 compatible, i.e. they should be runnable on any Linux system with glibc-2.17 or above. |
| MacOS | arm64 | Builds should be compatible with MacOS 11 (Big Sur) or newer, but are actively tested against MacOS 14 (Sonoma). |
| MacOS | x86_64 | Requires MacOS Catalina or above, not supported after 2.2, see https://github.com/pytorch/pytorch/issues/114602 |
| Windows | x86_64 | Buils are compatible with Windows-10 or newer. |
# Submitting Tutorials
Tutorials in support of a release feature must be submitted to the [pytorch/tutorials](https://github.com/pytorch/tutorials) repo at least two weeks before the release date to allow for editorial and technical review. There is no cherry-pick process for tutorials. All tutorials will be merged around the release day and published at [pytorch.org/tutorials](https://pytorch.org/tutorials/).

View File

@ -5,7 +5,6 @@
- [Untrusted models](#untrusted-models)
- [Untrusted inputs](#untrusted-inputs)
- [Data privacy](#data-privacy)
- [Using distributed features](#using-distributed-features)
## Reporting Security Issues
@ -40,7 +39,7 @@ Important Note: The trustworthiness of a model is not binary. You must always de
### Untrusted inputs during training and prediction
If you plan to open your model to untrusted inputs, be aware that inputs can also be used as vectors by malicious agents. To minimize risks, make sure to give your model only the permissions strictly required, and keep your libraries updated with the latest security patches.
If you plan to open your model to untrusted inputs, be aware that inputs can also be used as vectors by malicious agents. To minimize risks, make sure to give your model only the permisisons strictly required, and keep your libraries updated with the lates security patches.
If applicable, prepare your model against bad inputs and prompt injections. Some recommendations:
- Pre-analysis: check how the model performs by default when exposed to prompt injection (e.g. using fuzzing for prompt injection).
@ -55,9 +54,3 @@ If applicable, prepare your model against bad inputs and prompt injections. Some
**Take special security measures if your model if you train models with sensitive data**. Prioritize [sandboxing](https://developers.google.com/code-sandboxing) your models and:
- Do not feed sensitive data to untrusted model (even if runs in a sandboxed environment)
- If you consider publishing a model that was partially trained with sensitive data, be aware that data can potentially be recovered from the trained weights (especially if model overfits).
### Using distributed features
PyTorch can be used for distributed computing, and as such there is a `torch.distributed` package. PyTorch Distributed features are intended for internal communication only. They are not built for use in untrusted environments or networks.
For performance reasons, none of the PyTorch Distributed primitives (including c10d, RPC, and TCPStore) include any authorization protocol and will send messages unencrypted. They accept connections from anywhere, and execute the workload sent without performing any checks. Therefore, if you run a PyTorch Distributed program on your network, anybody with access to the network can execute arbitrary code with the privileges of the user running PyTorch.

View File

@ -168,10 +168,14 @@ new_local_repository(
path = "third_party/opentelemetry-cpp",
)
new_local_repository(
name = "cpp-httplib",
build_file = "//third_party:cpp-httplib.BUILD",
path = "third_party/cpp-httplib",
new_patched_local_repository(
name = "tbb",
build_file = "//third_party:tbb.BUILD",
patch_strip = 1,
patches = [
"@//third_party:tbb.patch",
],
path = "third_party/tbb",
)
new_local_repository(
@ -351,4 +355,9 @@ local_repository(
path = "third_party/onnx/third_party/benchmark",
)
local_repository(
name = "unused_onnx_tensorrt_benchmark",
path = "third_party/onnx-tensorrt/third_party/onnx/third_party/benchmark",
)
### Unused repos end

View File

@ -1,6 +1,5 @@
from torchvision import models
import torch
from torchvision import models
print(torch.version.__version__)

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