[Dynamo] Support for proxying frozen dataclasses

ghstack-source-id: fb6556cd2f9424fe223147471fe95126441954d9
Pull Request resolved: https://github.com/pytorch/pytorch/pull/134846

.ci/docker/aotriton_version.txt

@@ -1,5 +1,5 @@
-0.7b
+0.6b
 manylinux_2_17
 rocm6.2
-9be04068c3c0857a4cfd17d7e39e71d0423ebac2
+7f07e8a1cb1f99627eb6d77f5c0e9295c775f3c7
-3e9e1959d23b93d78a08fcc5f868125dc3854dece32fd9458be9ef4467982291
+e4ab195d2bd19e939c675a13280c29714c6ef9f2cf420690da150fa0cac043b1

.ci/docker/build.sh

@@ -236,7 +236,7 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-focal-py3-clang10-onnx)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     CLANG_VERSION=10
     PROTOBUF=yes
     DB=yes
@@ -245,7 +245,7 @@ case "$image" in
     ONNX=yes
     ;;
   pytorch-linux-focal-py3-clang9-android-ndk-r21e)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     CLANG_VERSION=9
     LLVMDEV=yes
     PROTOBUF=yes
@@ -254,8 +254,8 @@ case "$image" in
     GRADLE_VERSION=6.8.3
     NINJA_VERSION=1.9.0
     ;;
-  pytorch-linux-focal-py3.9-clang10)
+  pytorch-linux-focal-py3.8-clang10)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     CLANG_VERSION=10
     PROTOBUF=yes
     DB=yes
@@ -276,8 +276,8 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-focal-py3.9-gcc9)
+  pytorch-linux-focal-py3.8-gcc9)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
@@ -286,23 +286,23 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-focal-rocm-n-1-py3)
-    ANACONDA_PYTHON_VERSION=3.10
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    ROCM_VERSION=6.1
+    ROCM_VERSION=6.0
     NINJA_VERSION=1.9.0
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
   pytorch-linux-focal-rocm-n-py3)
-    ANACONDA_PYTHON_VERSION=3.10
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    ROCM_VERSION=6.2
+    ROCM_VERSION=6.1
     NINJA_VERSION=1.9.0
     CONDA_CMAKE=yes
     TRITON=yes
@@ -318,8 +318,8 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
-    pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
+    pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
@@ -330,8 +330,8 @@ case "$image" in
     DOCS=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-clang12)
+  pytorch-linux-jammy-cuda11.8-cudnn9-py3.8-clang12)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     CUDA_VERSION=11.8
     CUDNN_VERSION=9
     CLANG_VERSION=12
@@ -355,8 +355,8 @@ case "$image" in
     CONDA_CMAKE=yes
     VISION=yes
     ;;
-  pytorch-linux-jammy-py3.9-gcc11)
+  pytorch-linux-jammy-py3.8-gcc11)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
@@ -379,7 +379,6 @@ case "$image" in
     GCC_VERSION=11
     CONDA_CMAKE=yes
     HALIDE=yes
-    TRITON=yes
     ;;
   pytorch-linux-focal-linter)
     # TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.

.ci/docker/centos-rocm/Dockerfile

@@ -108,10 +108,10 @@ ENV CMAKE_C_COMPILER cc
 ENV CMAKE_CXX_COMPILER c++
 COPY ./common/install_triton.sh install_triton.sh
 COPY ./common/common_utils.sh common_utils.sh
-COPY ci_commit_pins/triton.txt triton.txt
+COPY ci_commit_pins/triton-rocm.txt triton-rocm.txt
 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.txt triton_version.txt
+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

.ci/docker/ci_commit_pins/executorch.txt

@@ -1 +1 @@
-cd1c833b079adb324871dcbbe75b43d42ffc0ade
+69472e5c43481324ad923ceb29392ab72830acee

.ci/docker/ci_commit_pins/halide.txt

@@ -1 +1 @@
-461c12871f336fe6f57b55d6a297f13ef209161b
+340136fec6d3ebc73e7a19eba1663e9b0ba8ab2d

.ci/docker/ci_commit_pins/triton-rocm.txt

@@ -0,0 +1 @@
+21eae954efa5bf584da70324b640288c3ee7aede

.ci/docker/ci_commit_pins/triton-xpu.txt

@@ -1 +1 @@
-91b14bf5593cf58a8541f3e6b9125600a867d4ef
+1b2f15840e0d70eec50d84c7a0575cb835524def

.ci/docker/ci_commit_pins/triton.txt

@@ -1 +1 @@
-5fe38ffd73c2ac6ed6323b554205186696631c6f
+dedb7bdf339a3546896d4820366ca562c586bfa0

.ci/docker/common/install_aotriton.sh

@@ -4,12 +4,12 @@ set -ex
 
 source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
 
-TARBALL='aotriton.tar.gz'
+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}-shared.tar.gz"
+AOTRITON_URL="https://github.com/ROCm/aotriton/releases/download/${VER}/aotriton-${VER}-${MANYLINUX}_${ARCH}-${ROCMBASE}-shared.tar.bz2"
 
 cd "${AOTRITON_INSTALL_PREFIX}"
 # Must use -L to follow redirects

.ci/docker/common/install_cpython.sh

@@ -7,7 +7,7 @@ PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/hea
 GET_PIP_URL=https://bootstrap.pypa.io/get-pip.py
 
 # Python versions to be installed in /opt/$VERSION_NO
-CPYTHON_VERSIONS=${CPYTHON_VERSIONS:-"3.8.1 3.9.0 3.10.1 3.11.0 3.12.0 3.13.0 3.13.0t"}
+CPYTHON_VERSIONS=${CPYTHON_VERSIONS:-"3.8.1 3.9.0 3.10.1 3.11.0 3.12.0 3.13.0"}
 
 function check_var {
     if [ -z "$1" ]; then
@@ -22,13 +22,6 @@ function do_cpython_build {
     check_var $py_ver
     check_var $py_folder
     tar -xzf Python-$py_ver.tgz
-
-    local additional_flags=""
-    if [ "$py_ver" == "3.13.0t" ]; then
-        additional_flags=" --disable-gil"
-        mv cpython-3.13/ cpython-3.13t/
-    fi
-
     pushd $py_folder
 
     local prefix="/opt/_internal/cpython-${py_ver}"
@@ -44,10 +37,8 @@ function do_cpython_build {
         local openssl_flags="--with-openssl=${WITH_OPENSSL} --with-openssl-rpath=auto"
     fi
 
-
-
     # -Wformat added for https://bugs.python.org/issue17547 on Python 2.6
-    CFLAGS="-Wformat" ./configure --prefix=${prefix} ${openssl_flags} ${shared_flags} ${additional_flags} > /dev/null
+    CFLAGS="-Wformat" ./configure --prefix=${prefix} ${openssl_flags} ${shared_flags} > /dev/null
 
     make -j40 > /dev/null
     make install > /dev/null
@@ -78,14 +69,7 @@ function build_cpython {
     check_var $py_ver
     check_var $PYTHON_DOWNLOAD_URL
     local py_ver_folder=$py_ver
-
+    if [ "$py_ver" = "3.13.0" ]; then
-    if [ "$py_ver" = "3.13.0t" ]; then
-        PY_VER_SHORT="3.13"
-        PYT_VER_SHORT="3.13t"
-        check_var $PYTHON_DOWNLOAD_GITHUB_BRANCH
-        wget $PYTHON_DOWNLOAD_GITHUB_BRANCH/$PY_VER_SHORT.tar.gz -O Python-$py_ver.tgz
-        do_cpython_build $py_ver cpython-$PYT_VER_SHORT
-    elif [ "$py_ver" = "3.13.0" ]; then
         PY_VER_SHORT="3.13"
         check_var $PYTHON_DOWNLOAD_GITHUB_BRANCH
         wget $PYTHON_DOWNLOAD_GITHUB_BRANCH/$PY_VER_SHORT.tar.gz -O Python-$py_ver.tgz

.ci/docker/common/install_cusparselt.sh

@@ -5,7 +5,7 @@ set -ex
 # cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
 mkdir tmp_cusparselt && cd tmp_cusparselt
 
-if [[ ${CUDA_VERSION:0:4} =~ ^12\.[2-6]$ ]]; then
+if [[ ${CUDA_VERSION:0:4} =~ ^12\.[2-4]$ ]]; then
     arch_path='sbsa'
     export TARGETARCH=${TARGETARCH:-$(uname -m)}
     if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then

.ci/docker/common/install_miopen.sh

@@ -10,21 +10,6 @@ if [[ -z $ROCM_VERSION ]]; then
     exit 1;
 fi
 
-IS_UBUNTU=0
-ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
-case "$ID" in
-  ubuntu)
-    IS_UBUNTU=1
-    ;;
-  centos)
-    IS_UBUNTU=0
-    ;;
-  *)
-    echo "Unable to determine OS..."
-    exit 1
-    ;;
-esac
-
 # To make version comparison easier, create an integer representation.
 save_IFS="$IFS"
 IFS=. ROCM_VERSION_ARRAY=(${ROCM_VERSION})
@@ -72,11 +57,9 @@ MIOPEN_CMAKE_COMMON_FLAGS="
 -DMIOPEN_BUILD_DRIVER=OFF
 "
 # Pull MIOpen repo and set DMIOPEN_EMBED_DB based on ROCm version
-if [[ $ROCM_INT -ge 60300 ]]; then
+if [[ $ROCM_INT -ge 60200 ]] && [[ $ROCM_INT -lt 60300 ]]; then
-    echo "ROCm 6.3+ MIOpen does not need any patches, do not build from source"
+    echo "ROCm 6.2 MIOpen does not need any patches, do not build from source"
     exit 0
-elif [[ $ROCM_INT -ge 60200 ]] && [[ $ROCM_INT -lt 60300 ]]; then
-    MIOPEN_BRANCH="release/rocm-rel-6.2-staging"
 elif [[ $ROCM_INT -ge 60100 ]] && [[ $ROCM_INT -lt 60200 ]]; then
     echo "ROCm 6.1 MIOpen does not need any patches, do not build from source"
     exit 0
@@ -110,21 +93,12 @@ else
     exit 1
 fi
 
-
+yum remove -y miopen-hip
-if [[ ${IS_UBUNTU} == 1 ]]; then
-  apt-get remove -y miopen-hip
-else
-  yum remove -y miopen-hip
-fi
 
 git clone https://github.com/ROCm/MIOpen -b ${MIOPEN_BRANCH}
 pushd MIOpen
 # remove .git to save disk space since CI runner was running out
 rm -rf .git
-# Don't build CK to save docker build time
-if [[ $ROCM_INT -ge 60200 ]]; then
-    sed -i '/composable_kernel/d' requirements.txt
-fi
 # Don't build MLIR to save docker build time
 # since we are disabling MLIR backend for MIOpen anyway
 if [[ $ROCM_INT -ge 50400 ]] && [[ $ROCM_INT -lt 50500 ]]; then
@@ -137,15 +111,10 @@ cmake -P install_deps.cmake --minimum
 
 # clean up since CI runner was running out of disk space
 rm -rf /tmp/*
-if [[ ${IS_UBUNTU} == 1 ]]; then
+yum clean all
-  apt-get autoclean && apt-get clean
+rm -rf /var/cache/yum
-  rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
+rm -rf /var/lib/yum/yumdb
-else
+rm -rf /var/lib/yum/history
-  yum clean all
-  rm -rf /var/cache/yum
-  rm -rf /var/lib/yum/yumdb
-  rm -rf /var/lib/yum/history
-fi
 
 ## Build MIOpen
 mkdir -p build
@@ -162,11 +131,7 @@ make -j $(nproc) package
 # clean up since CI runner was running out of disk space
 rm -rf /usr/local/cget
 
-if [[ ${IS_UBUNTU} == 1 ]]; then
+yum install -y miopen-*.rpm
-  sudo dpkg -i miopen-hip*.deb
-else
-  yum install -y miopen-*.rpm
-fi
 
 popd
 rm -rf MIOpen

.ci/docker/common/install_onnx.sh

@@ -15,7 +15,7 @@ pip_install \
   flatbuffers==2.0 \
   mock==5.0.1 \
   ninja==1.10.2 \
-  networkx==2.5 \
+  networkx==2.0 \
   numpy==1.24.2
 
 # ONNXRuntime should be installed before installing
@@ -30,9 +30,10 @@ pip_install \
 
 pip_install coloredlogs packaging
 
-pip_install onnxruntime==1.18.1
+pip_install onnxruntime==1.18
-pip_install onnx==1.16.2
+pip_install onnx==1.16.0
-pip_install onnxscript==0.1.0.dev20240831 --no-deps
+# pip_install "onnxscript@git+https://github.com/microsoft/onnxscript@3e869ef8ccf19b5ebd21c10d3e9c267c9a9fa729" --no-deps
+pip_install onnxscript==0.1.0.dev20240613 --no-deps
 # required by onnxscript
 pip_install ml_dtypes
 

.ci/docker/common/install_triton.sh

@@ -12,7 +12,10 @@ conda_reinstall() {
   as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y --force-reinstall $*
 }
 
-if [ -n "${XPU_VERSION}" ]; then
+if [ -n "${ROCM_VERSION}" ]; then
+  TRITON_REPO="https://github.com/openai/triton"
+  TRITON_TEXT_FILE="triton-rocm"
+elif [ -n "${XPU_VERSION}" ]; then
   TRITON_REPO="https://github.com/intel/intel-xpu-backend-for-triton"
   TRITON_TEXT_FILE="triton-xpu"
 else

.ci/docker/conda/build.sh

@@ -37,12 +37,6 @@ esac
 
 (
   set -x
-  # TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
-  # is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
-  sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
-  sudo systemctl daemon-reload
-  sudo systemctl restart docker
-
   docker build \
     --target final \
     --progress plain \

.ci/docker/manywheel/Dockerfile

@@ -10,7 +10,6 @@ ENV LANG en_US.UTF-8
 ENV LANGUAGE en_US.UTF-8
 
 ARG DEVTOOLSET_VERSION=9
-
 # Note: This is required patch since CentOS have reached EOL
 # otherwise any yum install setp will fail
 RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo

.ci/docker/manywheel/build.sh

@@ -124,14 +124,7 @@ if [[ -n ${MANY_LINUX_VERSION} && -z ${DOCKERFILE_SUFFIX} ]]; then
 fi
 (
     set -x
-
+    DOCKER_BUILDKIT=1 docker build \
-    # TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
-    # is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
-    sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
-    sudo systemctl daemon-reload
-    sudo systemctl restart docker
-
-    DOCKER_BUILDKIT=1 docker build  \
         ${DOCKER_GPU_BUILD_ARG} \
         --build-arg "GPU_IMAGE=${GPU_IMAGE}" \
         --target "${TARGET}" \

.ci/docker/requirements-ci.txt

@@ -30,14 +30,9 @@ dill==0.3.7
 #Pinned versions: 0.3.7
 #test that import: dynamo/test_replay_record.py test_dataloader.py test_datapipe.py test_serialization.py
 
-expecttest==0.2.1
+expecttest==0.1.6
 #Description: method for writing tests where test framework auto populates
 # the expected output based on previous runs
-#Pinned versions: 0.2.1
-#test that import:
-
-fbscribelogger==0.1.6
-#Description: write to scribe from authenticated jobs on CI
 #Pinned versions: 0.1.6
 #test that import:
 
@@ -90,7 +85,7 @@ librosa>=0.6.2 ; python_version < "3.11"
 #Pinned versions:
 #test that import:
 
-mypy==1.11.2
+mypy==1.10.0
 # Pin MyPy version because new errors are likely to appear with each release
 #Description: linter
 #Pinned versions: 1.10.0
@@ -109,7 +104,7 @@ networkx==2.8.8
 #test that import: run_test.py, test_cpp_extensions_aot.py,test_determination.py
 
 numba==0.49.0 ; python_version < "3.9"
-numba==0.55.2 ; python_version == "3.9"
+numba==0.54.1 ; python_version == "3.9"
 numba==0.55.2 ; python_version == "3.10"
 #Description: Just-In-Time Compiler for Numerical Functions
 #Pinned versions: 0.54.1, 0.49.0, <=0.49.1
@@ -337,8 +332,3 @@ onnxscript==0.1.0.dev20240817
 #Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
-
-parameterized==0.8.1
-#Description: Parameterizes unittests, both the tests themselves and the entire testing class
-#Pinned versions:
-#test that import:

.ci/docker/triton_version.txt

@@ -1 +1 @@
-3.1.0
+3.0.0

.ci/docker/ubuntu-rocm/Dockerfile

@@ -68,8 +68,6 @@ 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
-ADD ./common/install_miopen.sh install_miopen.sh
-RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh
 ENV ROCM_PATH /opt/rocm
 ENV PATH /opt/rocm/bin:$PATH
 ENV PATH /opt/rocm/hcc/bin:$PATH
@@ -102,10 +100,10 @@ ARG TRITON
 # try to reach out to S3, which docker build runners don't have access
 COPY ./common/install_triton.sh install_triton.sh
 COPY ./common/common_utils.sh common_utils.sh
-COPY ci_commit_pins/triton.txt triton.txt
+COPY ci_commit_pins/triton-rocm.txt triton-rocm.txt
 COPY triton_version.txt triton_version.txt
 RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
-RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
+RUN rm install_triton.sh common_utils.sh triton-rocm.txt triton_version.txt
 
 # Install AOTriton
 COPY ./aotriton_version.txt aotriton_version.txt
@@ -123,8 +121,5 @@ RUN bash ./install_cache.sh && rm install_cache.sh
 ARG BUILD_ENVIRONMENT
 ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
 
-# Install LLVM dev version (Defined in the pytorch/builder github repository)
-COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
-
 USER jenkins
 CMD ["bash"]

.ci/pytorch/build.sh

@@ -49,8 +49,13 @@ if [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
 fi
 
 # Enable LLVM dependency for TensorExpr testing
-export USE_LLVM=/opt/llvm
+if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
-export LLVM_DIR=/opt/llvm/lib/cmake/llvm
+  export USE_LLVM=/opt/rocm/llvm
+  export LLVM_DIR=/opt/rocm/llvm/lib/cmake/llvm
+else
+  export USE_LLVM=/opt/llvm
+  export LLVM_DIR=/opt/llvm/lib/cmake/llvm
+fi
 
 if [[ "$BUILD_ENVIRONMENT" == *executorch* ]]; then
   # To build test_edge_op_registration
@@ -232,7 +237,7 @@ fi
 
 # Do not change workspace permissions for ROCm CI jobs
 # as it can leave workspace with bad permissions for cancelled jobs
-if [[ "$BUILD_ENVIRONMENT" != *rocm* && "$BUILD_ENVIRONMENT" != *s390x* ]]; then
+if [[ "$BUILD_ENVIRONMENT" != *rocm* ]]; then
   # Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
   WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
   cleanup_workspace() {
@@ -278,11 +283,11 @@ else
     # set only when building other architectures
     # or building non-XLA tests.
     if [[ "$BUILD_ENVIRONMENT" != *rocm*  &&
-          "$BUILD_ENVIRONMENT" != *s390x*   &&
           "$BUILD_ENVIRONMENT" != *xla* ]]; then
       if [[ "$BUILD_ENVIRONMENT" != *py3.8* ]]; then
-        # Install numpy-2.0.2 for builds which are backward compatible with 1.X
+        # Install numpy-2.0 release candidate for builds
-        python -mpip install --pre numpy==2.0.2
+        # Which should be backward compatible with Numpy-1.X
+        python -mpip install --pre numpy==2.0.0rc1
       fi
 
       WERROR=1 python setup.py clean
@@ -341,11 +346,11 @@ else
     CUSTOM_OP_BUILD="${CUSTOM_TEST_ARTIFACT_BUILD_DIR}/custom-op-build"
     CUSTOM_OP_TEST="$PWD/test/custom_operator"
     python --version
-    SITE_PACKAGES="$(python -c 'import site; print(";".join([x for x in site.getsitepackages()] + [x + "/torch" for x in site.getsitepackages()]))')"
+    SITE_PACKAGES="$(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" -DPython_EXECUTABLE="$(which python)" \
+    cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch;$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
           -DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
     make VERBOSE=1
     popd
@@ -355,10 +360,10 @@ else
     JIT_HOOK_BUILD="${CUSTOM_TEST_ARTIFACT_BUILD_DIR}/jit-hook-build"
     JIT_HOOK_TEST="$PWD/test/jit_hooks"
     python --version
-    SITE_PACKAGES="$(python -c 'import site; print(";".join([x for x in site.getsitepackages()] + [x + "/torch" for x in site.getsitepackages()]))')"
+    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="$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
+    cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch;$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
           -DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
     make VERBOSE=1
     popd
@@ -370,7 +375,7 @@ else
     python --version
     mkdir -p "$CUSTOM_BACKEND_BUILD"
     pushd "$CUSTOM_BACKEND_BUILD"
-    cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
+    cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch;$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
           -DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
     make VERBOSE=1
     popd
@@ -403,6 +408,6 @@ fi
 
 # snadampal: skipping it till sccache support added for aarch64
 # https://github.com/pytorch/pytorch/issues/121559
-if [[ "$BUILD_ENVIRONMENT" != *aarch64* &&  "$BUILD_ENVIRONMENT" != *s390x* ]]; then
+if [[ "$BUILD_ENVIRONMENT" != *aarch64* ]]; then
   print_sccache_stats
 fi

.ci/pytorch/create_test_cert.py

@@ -1,4 +1,4 @@
-from datetime import datetime, timedelta, timezone
+from datetime import datetime, timedelta
 from tempfile import mkdtemp
 
 from cryptography import x509
@@ -42,10 +42,10 @@ def create_cert(path, C, ST, L, O, key):
         .issuer_name(issuer)
         .public_key(key.public_key())
         .serial_number(x509.random_serial_number())
-        .not_valid_before(datetime.now(timezone.utc))
+        .not_valid_before(datetime.utcnow())
         .not_valid_after(
             # Our certificate will be valid for 10 days
-            datetime.now(timezone.utc)
+            datetime.utcnow()
             + timedelta(days=10)
         )
         .add_extension(
@@ -88,10 +88,10 @@ def sign_certificate_request(path, csr_cert, ca_cert, private_ca_key):
         .issuer_name(ca_cert.subject)
         .public_key(csr_cert.public_key())
         .serial_number(x509.random_serial_number())
-        .not_valid_before(datetime.now(timezone.utc))
+        .not_valid_before(datetime.utcnow())
         .not_valid_after(
             # Our certificate will be valid for 10 days
-            datetime.now(timezone.utc)
+            datetime.utcnow()
             + timedelta(days=10)
             # Sign our certificate with our private key
         )

.ci/pytorch/macos-test.sh

@@ -9,13 +9,15 @@ if [[ -n "$CONDA_ENV" ]]; then
   export PATH="$CONDA_ENV/bin":$PATH
 fi
 
-# Test that OpenMP is enabled
+# Test that OpenMP is enabled for non-arm64 build
-pushd test
+if [[ ${BUILD_ENVIRONMENT} != *arm64* ]]; then
-if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available()))") == "1" ]]; then
+  pushd test
-  echo "Build should have OpenMP enabled, but torch.backends.openmp.is_available() is False"
+  if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available()))") == "1" ]]; then
-  exit 1
+    echo "Build should have OpenMP enabled, but torch.backends.openmp.is_available() is False"
+    exit 1
+  fi
+  popd
 fi
-popd
 
 setup_test_python() {
   # The CircleCI worker hostname doesn't resolve to an address.
@@ -25,9 +27,8 @@ setup_test_python() {
   echo "Ninja version: $(ninja --version)"
   echo "Python version: $(which python) ($(python --version))"
 
-  # Set the limit on open file handles to 16384
+  # Increase default limit on open file handles from 256 to 1024
-  # might help with intermittent compiler test failures
+  ulimit -n 1024
-  ulimit -n 16384
 }
 
 test_python_all() {

.ci/pytorch/test.sh

@@ -375,8 +375,9 @@ test_inductor_cpp_wrapper_abi_compatible() {
   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
-  python test/run_test.py --include inductor/test_cuda_cpp_wrapper inductor/test_cpu_repro
+  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 \
@@ -400,9 +401,9 @@ pr_time_benchmarks() {
 
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
-  PYTHONPATH=$(pwd)/benchmarks/dynamo/pr_time_benchmarks source benchmarks/dynamo/pr_time_benchmarks/benchmark_runner.sh "$TEST_REPORTS_DIR/pr_time_benchmarks_results.csv" "benchmarks/dynamo/pr_time_benchmarks/benchmarks"
+  PYTHONPATH=$(pwd)/benchmarks/dynamo/pr_time_benchmarks source benchmarks/dynamo/pr_time_benchmarks/benchmark_runner.sh "$TEST_REPORTS_DIR/pr_time_benchmarks_after.txt" "benchmarks/dynamo/pr_time_benchmarks/benchmarks"
   echo "benchmark results on current PR: "
-  cat  "$TEST_REPORTS_DIR/pr_time_benchmarks_results.csv"
+  cat  "$TEST_REPORTS_DIR/pr_time_benchmarks_after.txt"
 
 }
 
@@ -595,9 +596,6 @@ test_single_dynamo_benchmark() {
 
 test_inductor_micro_benchmark() {
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
-  if [[ "${TEST_CONFIG}" == *cpu* ]]; then
-    test_inductor_set_cpu_affinity
-  fi
   python benchmarks/gpt_fast/benchmark.py --output "${TEST_REPORTS_DIR}/gpt_fast_benchmark.csv"
 }
 
@@ -1382,16 +1380,14 @@ test_executorch() {
   assert_git_not_dirty
 }
 
-test_linux_aarch64() {
+test_linux_aarch64(){
   python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
-        test_transformers test_multiprocessing test_numpy_interop \
+       test_transformers test_multiprocessing test_numpy_interop --verbose
-        --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 
   # Dynamo tests
   python test/run_test.py --include dynamo/test_compile dynamo/test_backends dynamo/test_comptime dynamo/test_config \
        dynamo/test_functions dynamo/test_fx_passes_pre_grad dynamo/test_interop dynamo/test_model_output dynamo/test_modules \
-       dynamo/test_optimizers dynamo/test_recompile_ux dynamo/test_recompiles \
+       dynamo/test_optimizers dynamo/test_recompile_ux dynamo/test_recompiles --verbose
-       --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 
   # Inductor tests
   python test/run_test.py --include inductor/test_torchinductor inductor/test_benchmark_fusion inductor/test_codecache \
@@ -1401,8 +1397,7 @@ test_linux_aarch64() {
        inductor/test_max_autotune inductor/test_memory_planning inductor/test_metrics inductor/test_multi_kernel inductor/test_pad_mm \
        inductor/test_pattern_matcher inductor/test_perf inductor/test_profiler inductor/test_select_algorithm inductor/test_smoke \
        inductor/test_split_cat_fx_passes inductor/test_standalone_compile inductor/test_torchinductor \
-       inductor/test_torchinductor_codegen_dynamic_shapes inductor/test_torchinductor_dynamic_shapes inductor/test_memory \
+       inductor/test_torchinductor_codegen_dynamic_shapes inductor/test_torchinductor_dynamic_shapes --verbose
-       --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 }
 
 if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-bazel-* ]]; then
@@ -1484,7 +1479,7 @@ elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
   install_torchvision
   test_inductor_shard "${SHARD_NUMBER}"
   if [[ "${SHARD_NUMBER}" == 1 ]]; then
-    if [[ "${BUILD_ENVIRONMENT}" != linux-jammy-py3.9-gcc11-build ]]; then
+    if [[ "${BUILD_ENVIRONMENT}" != linux-jammy-py3.8-gcc11-build ]]; then
       test_inductor_distributed
     fi
   fi

.ci/pytorch/win-test-helpers/build_pytorch.bat

@@ -24,12 +24,6 @@ call %INSTALLER_DIR%\install_sccache.bat
 if errorlevel 1 goto fail
 if not errorlevel 0 goto fail
 
-if "%USE_XPU%"=="1" (
-  :: Install xpu support packages
-  call %INSTALLER_DIR%\install_xpu.bat
-  if errorlevel 1 exit /b 1
-)
-
 :: Miniconda has been installed as part of the Windows AMI with all the dependencies.
 :: We just need to activate it here
 call %INSTALLER_DIR%\activate_miniconda3.bat
@@ -49,16 +43,6 @@ if "%VC_VERSION%" == "" (
 )
 if errorlevel 1 goto fail
 if not errorlevel 0 goto fail
-
-if "%USE_XPU%"=="1" (
-  :: Activate xpu environment - VS env is required for xpu
-  call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat"
-  if errorlevel 1 exit /b 1
-  :: Reduce build time. Only have MTL self-hosted runner now
-  SET TORCH_XPU_ARCH_LIST=xe-lpg
-  SET USE_KINETO=0
-)
-
 @echo on
 popd
 

.ci/pytorch/win-test-helpers/installation-helpers/install_xpu.bat

@@ -1,91 +0,0 @@
-@echo on
-REM Description: Install Intel Support Packages on Windows
-REM BKM reference: https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-5.html
-
-set XPU_INSTALL_MODE=%~1
-if "%XPU_INSTALL_MODE%"=="" goto xpu_bundle_install_start
-if "%XPU_INSTALL_MODE%"=="bundle" goto xpu_bundle_install_start
-if "%XPU_INSTALL_MODE%"=="driver" goto xpu_driver_install_start
-if "%XPU_INSTALL_MODE%"=="all" goto xpu_driver_install_start
-
-:arg_error
-
-echo Illegal XPU installation mode. The value can be "bundle"/"driver"/"all"
-echo If keep the value as space, will use default "bundle" mode
-exit /b 1
-
-:xpu_driver_install_start
-:: TODO Need more testing for driver installation
-set XPU_DRIVER_LINK=https://downloadmirror.intel.com/830975/gfx_win_101.5972.exe
-curl -o xpu_driver.exe --retry 3 --retry-all-errors -k %XPU_DRIVER_LINK%
-echo "XPU Driver installing..."
-start /wait "Intel XPU Driver Installer" "xpu_driver.exe"
-if errorlevel 1 exit /b 1
-del xpu_driver.exe
-if "%XPU_INSTALL_MODE%"=="driver" goto xpu_install_end
-
-:xpu_bundle_install_start
-
-set XPU_BUNDLE_PARENT_DIR=C:\Program Files (x86)\Intel\oneAPI
-set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/9d1a91e2-e8b8-40a5-8c7f-5db768a6a60c/w_intel-for-pytorch-gpu-dev_p_0.5.3.37_offline.exe
-set XPU_PTI_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/9d1a91e2-e8b8-40a5-8c7f-5db768a6a60c/w_intel-pti-dev_p_0.9.0.37_offline.exe
-set XPU_BUNDLE_VERSION=0.5.3+31
-set XPU_PTI_VERSION=0.9.0+36
-set XPU_BUNDLE_PRODUCT_NAME=intel.oneapi.win.intel-for-pytorch-gpu-dev.product
-set XPU_PTI_PRODUCT_NAME=intel.oneapi.win.intel-pti-dev.product
-set XPU_BUNDLE_INSTALLED=0
-set XPU_PTI_INSTALLED=0
-set XPU_BUNDLE_UNINSTALL=0
-set XPU_PTI_UNINSTALL=0
-
-:: Check if XPU bundle is target version or already installed
-if exist "%XPU_BUNDLE_PARENT_DIR%\Installer\installer.exe" goto xpu_bundle_ver_check
-goto xpu_bundle_install
-
-:xpu_bundle_ver_check
-
-"%XPU_BUNDLE_PARENT_DIR%\Installer\installer.exe" --list-products > xpu_bundle_installed_ver.log
-
-for /f "tokens=1,2" %%a in (xpu_bundle_installed_ver.log) do (
-    if "%%a"=="%XPU_BUNDLE_PRODUCT_NAME%" (
-        echo %%a Installed Version: %%b
-        set XPU_BUNDLE_INSTALLED=1
-        if not "%XPU_BUNDLE_VERSION%"=="%%b" (
-            start /wait "Installer Title" "%XPU_BUNDLE_PARENT_DIR%\Installer\installer.exe" --action=remove --eula=accept --silent --product-id %XPU_BUNDLE_PRODUCT_NAME% --product-ver %%b --log-dir uninstall_bundle
-            set XPU_BUNDLE_UNINSTALL=1
-        )
-    )
-    if "%%a"=="%XPU_PTI_PRODUCT_NAME%" (
-        echo %%a Installed Version: %%b
-        set XPU_PTI_INSTALLED=1
-        if not "%XPU_PTI_VERSION%"=="%%b" (
-            start /wait "Installer Title" "%XPU_BUNDLE_PARENT_DIR%\Installer\installer.exe" --action=remove --eula=accept --silent --product-id %XPU_PTI_PRODUCT_NAME% --product-ver %%b --log-dir uninstall_bundle
-            set XPU_PTI_UNINSTALL=1
-        )
-    )
-)
-if errorlevel 1 exit /b 1
-if exist xpu_bundle_installed_ver.log del xpu_bundle_installed_ver.log
-if "%XPU_BUNDLE_INSTALLED%"=="0" goto xpu_bundle_install
-if "%XPU_BUNDLE_UNINSTALL%"=="1" goto xpu_bundle_install
-if "%XPU_PTI_INSTALLED%"=="0" goto xpu_pti_install
-if "%XPU_PTI_UNINSTALL%"=="1" goto xpu_pti_install
-goto xpu_install_end
-
-:xpu_bundle_install
-
-curl -o xpu_bundle.exe --retry 3 --retry-all-errors -k %XPU_BUNDLE_URL%
-echo "XPU Bundle installing..."
-start /wait "Intel Pytorch Bundle Installer" "xpu_bundle.exe" --action=install --eula=accept --silent --log-dir install_bundle
-if errorlevel 1 exit /b 1
-del xpu_bundle.exe
-
-:xpu_pti_install
-
-curl -o xpu_pti.exe --retry 3 --retry-all-errors -k %XPU_PTI_URL%
-echo "XPU PTI installing..."
-start /wait "Intel PTI Installer" "xpu_pti.exe" --action=install --eula=accept --silent --log-dir install_bundle
-if errorlevel 1 exit /b 1
-del xpu_pti.exe
-
-:xpu_install_end

.ci/pytorch/win-test.sh

@@ -40,12 +40,6 @@ python -m pip install pytest-rerunfailures==10.3 pytest-cpp==2.3.0 tensorboard==
 # Install Z3 optional dependency for Windows builds.
 python -m pip install z3-solver==4.12.2.0
 
-# Install tlparse for test\dynamo\test_structured_trace.py UTs.
-python -m pip install tlparse==0.3.25
-
-# Install parameterized
-python -m pip install parameterized==0.8.1
-
 run_tests() {
     # Run nvidia-smi if available
     for path in '/c/Program Files/NVIDIA Corporation/NVSMI/nvidia-smi.exe' /c/Windows/System32/nvidia-smi.exe; do

.circleci/scripts/binary_linux_test.sh

@@ -119,11 +119,6 @@ fi
 # Test the package
 /builder/check_binary.sh
 
-if [[ "\$GPU_ARCH_TYPE" != *s390x* && "\$GPU_ARCH_TYPE" != *xpu* && "\$GPU_ARCH_TYPE" != *rocm*  && "$PACKAGE_TYPE" != libtorch ]]; then
-  # Exclude s390, xpu, rocm and libtorch builds from smoke testing
-  python /builder/test/smoke_test/smoke_test.py --package=torchonly --torch-compile-check disabled
-fi
-
 # Clean temp files
 cd /builder && git clean -ffdx
 

.circleci/scripts/binary_populate_env.sh

@@ -90,7 +90,7 @@ fi
 if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*rocm.* && $(uname) == "Linux" ]]; then
     TRITON_REQUIREMENT="pytorch-triton-rocm==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
     if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
-        TRITON_SHORTHASH=$(cut -c1-10 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton.txt)
+        TRITON_SHORTHASH=$(cut -c1-10 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton-rocm.txt)
         TRITON_REQUIREMENT="pytorch-triton-rocm==${TRITON_VERSION}+${TRITON_SHORTHASH}; ${TRITON_CONSTRAINT}"
     fi
     if [[ -z "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then

.circleci/scripts/binary_windows_build.sh

@@ -10,11 +10,6 @@ export SCCACHE_BUCKET=ossci-compiler-cache
 export SCCACHE_IGNORE_SERVER_IO_ERROR=1
 export VC_YEAR=2019
 
-if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
-    export VC_YEAR=2022
-    export USE_SCCACHE=0
-fi
-
 echo "Free space on filesystem before build:"
 df -h
 

.circleci/scripts/binary_windows_test.sh

@@ -6,10 +6,6 @@ source "${BINARY_ENV_FILE:-/c/w/env}"
 export CUDA_VERSION="${DESIRED_CUDA/cu/}"
 export VC_YEAR=2019
 
-if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
-    export VC_YEAR=2022
-fi
-
 pushd "$BUILDER_ROOT"
 
 ./windows/internal/smoke_test.bat

.github/actionlint.yaml

@@ -3,6 +3,8 @@ self-hosted-runner:
     # 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.2xlarge
@@ -32,6 +34,30 @@ self-hosted-runner:
     - lf.linux.8xlarge.nvidia.gpu
     - lf.linux.16xlarge.nvidia.gpu
     - lf.linux.g5.4xlarge.nvidia.gpu
+    # Organization-wide AWS Linux Runners with new Amazon 2023 AMI
+    - amz2023.linux.large
+    - amz2023.linux.2xlarge
+    - amz2023.linux.4xlarge
+    - amz2023.linux.12xlarge
+    - amz2023.linux.24xlarge
+    - amz2023.linux.arm64.2xlarge
+    - amz2023.linux.arm64.m7g.4xlarge
+    - amz2023.linux.arm64.m7g.4xlarge.ephemeral
+    - amz2023.linux.4xlarge.nvidia.gpu
+    - amz2023.linux.8xlarge.nvidia.gpu
+    - amz2023.linux.16xlarge.nvidia.gpu
+    - amz2023.linux.g5.4xlarge.nvidia.gpu
+    # Pytorch/pytorch AWS Linux Runners with the new Amazon 2023 AMI on Linux Foundation account
+    - amz2023.lf.linux.large
+    - amz2023.lf.linux.2xlarge
+    - amz2023.lf.linux.4xlarge
+    - amz2023.lf.linux.12xlarge
+    - amz2023.lf.linux.24xlarge
+    - amz2023.lf.linux.arm64.2xlarge
+    - amz2023.lf.linux.4xlarge.nvidia.gpu
+    - amz2023.lf.linux.8xlarge.nvidia.gpu
+    - amz2023.lf.linux.16xlarge.nvidia.gpu
+    - amz2023.lf.linux.g5.4xlarge.nvidia.gpu
     # Repo-specific IBM hosted S390x runner
     - linux.s390x
     # Organization wide AWS Windows runners

.github/ci_commit_pins/audio.txt

@@ -1 +1 @@
-ba696ea3dfec4cbe693bf06a84c75dc196077f5b
+97ed7b36b7a741253d4e41e4da3c901d83294503

.github/label_to_label.yml

@@ -31,10 +31,6 @@
   - "module: flex attention"
   then:
   - "module: higher order operators"
-- any:
-  - "module: aotinductor"
-  then:
-  - "oncall: export"
 - any:
   - "module: dynamo"
   - "module: pt2-dispatcher"

.github/lf-canary-scale-config.yml

@@ -7,14 +7,10 @@
 #   runners. Runners listed here will be available as self hosted
 #   runners, configuration is directly pulled from the main branch.
 #
+# NOTE (Apr, 5, 2021): Linux runners are currently all an amazonlinux2
 #
-# NOTES:
+# NOTE (Jan 5, 2021): Linux runners are all non-ephemeral to reduce the amount of CreateInstaces calls
-#  - Linux runners are by default non-ephemeral to reduce the amount of CreateInstaces calls
+#                     to avoid RequestLimitExceeded issues
-#    to avoid RequestLimitExceeded issues
-#  - When updating this file, run the following command to validate the YAML and to generate
-#    corresponding versions of scale-config for the pytorch/pytorch repo and merge the
-#    pytorch/pytorch changes before merging these changes.
-#    `python .github/scripts/validate_scale_config.py --test-infra-repo-root [path_to_test-infra_root] --pytorch-repo-root [path_to_pytorch_root]``
 #
 # TODO: Add some documentation on how the auto-scaling works
 #
@@ -35,36 +31,58 @@ runner_types:
     is_ephemeral: false
     max_available: 1000
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.10xlarge.avx2:
     disk_size: 200
     instance_type: m4.10xlarge
     is_ephemeral: false
     max_available: 450
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.24xl.spr-metal:
     disk_size: 200
     instance_type: c7i.metal-24xl
     is_ephemeral: false
     max_available: 150
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.16xlarge.spr:
     disk_size: 200
     instance_type: c7i.16xlarge
     is_ephemeral: false
     max_available: 150
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.9xlarge.ephemeral:
     disk_size: 200
     instance_type: c5.9xlarge
     is_ephemeral: true
     max_available: 50
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
     variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
       am2:
         ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.12xlarge.ephemeral:
@@ -73,140 +91,240 @@ runner_types:
     is_ephemeral: true
     max_available: 300
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.16xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g3.16xlarge
     is_ephemeral: false
     max_available: 150
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.24xlarge:
     disk_size: 150
     instance_type: c5.24xlarge
     is_ephemeral: false
     max_available: 500
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.24xlarge.ephemeral:
     disk_size: 150
     instance_type: c5.24xlarge
     is_ephemeral: true
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.2xlarge:
     disk_size: 150
     instance_type: c5.2xlarge
     is_ephemeral: false
     max_available: 3120
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.4xlarge:
     disk_size: 150
     instance_type: c5.4xlarge
     is_ephemeral: false
     max_available: 1000
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.4xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g3.4xlarge
     is_ephemeral: false
     max_available: 1000
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.8xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g3.8xlarge
     is_ephemeral: false
     max_available: 400
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.g4dn.12xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g4dn.12xlarge
     is_ephemeral: false
     max_available: 250
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.g4dn.metal.nvidia.gpu:
     disk_size: 150
     instance_type: g4dn.metal
     is_ephemeral: false
     max_available: 300
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.g5.48xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g5.48xlarge
     is_ephemeral: false
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.g5.12xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g5.12xlarge
     is_ephemeral: false
     max_available: 150
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.g5.4xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g5.4xlarge
     is_ephemeral: false
     max_available: 2400
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.g6.4xlarge.experimental.nvidia.gpu:
     disk_size: 150
     instance_type: g6.4xlarge
     is_ephemeral: false
     max_available: 50
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.large:
     max_available: 1200
     disk_size: 15
     instance_type: c5.large
     is_ephemeral: false
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.c.linux.arm64.2xlarge:
     disk_size: 256
     instance_type: t4g.2xlarge
     is_ephemeral: false
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.c.linux.arm64.m7g.4xlarge:
     disk_size: 256
     instance_type: m7g.4xlarge
     is_ephemeral: false
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.c.linux.arm64.2xlarge.ephemeral:
     disk_size: 256
     instance_type: t4g.2xlarge
     is_ephemeral: true
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.c.linux.arm64.m7g.4xlarge.ephemeral:
     disk_size: 256
     instance_type: m7g.4xlarge
     is_ephemeral: true
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.c.linux.arm64.m7g.metal:
     disk_size: 256
     instance_type: m7g.metal
     is_ephemeral: false
     max_available: 100
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.c.windows.g4dn.xlarge:
     disk_size: 256
     instance_type: g4dn.xlarge

.github/lf-scale-config.yml

@@ -7,14 +7,10 @@
 #   runners. Runners listed here will be available as self hosted
 #   runners, configuration is directly pulled from the main branch.
 #
+# NOTE (Apr, 5, 2021): Linux runners are currently all an amazonlinux2
 #
-# NOTES:
+# NOTE (Jan 5, 2021): Linux runners are all non-ephemeral to reduce the amount of CreateInstaces calls
-#  - Linux runners are by default non-ephemeral to reduce the amount of CreateInstaces calls
+#                     to avoid RequestLimitExceeded issues
-#    to avoid RequestLimitExceeded issues
-#  - When updating this file, run the following command to validate the YAML and to generate
-#    corresponding versions of scale-config for the pytorch/pytorch repo and merge the
-#    pytorch/pytorch changes before merging these changes.
-#    `python .github/scripts/validate_scale_config.py --test-infra-repo-root [path_to_test-infra_root] --pytorch-repo-root [path_to_pytorch_root]``
 #
 # TODO: Add some documentation on how the auto-scaling works
 #
@@ -35,36 +31,58 @@ runner_types:
     is_ephemeral: false
     max_available: 1000
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.10xlarge.avx2:
     disk_size: 200
     instance_type: m4.10xlarge
     is_ephemeral: false
     max_available: 450
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.24xl.spr-metal:
     disk_size: 200
     instance_type: c7i.metal-24xl
     is_ephemeral: false
     max_available: 150
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.16xlarge.spr:
     disk_size: 200
     instance_type: c7i.16xlarge
     is_ephemeral: false
     max_available: 150
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.9xlarge.ephemeral:
     disk_size: 200
     instance_type: c5.9xlarge
     is_ephemeral: true
     max_available: 50
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
     variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
       am2:
         ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.12xlarge.ephemeral:
@@ -73,140 +91,240 @@ runner_types:
     is_ephemeral: true
     max_available: 300
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.16xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g3.16xlarge
     is_ephemeral: false
     max_available: 150
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.24xlarge:
     disk_size: 150
     instance_type: c5.24xlarge
     is_ephemeral: false
     max_available: 500
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.24xlarge.ephemeral:
     disk_size: 150
     instance_type: c5.24xlarge
     is_ephemeral: true
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.2xlarge:
     disk_size: 150
     instance_type: c5.2xlarge
     is_ephemeral: false
     max_available: 3120
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.4xlarge:
     disk_size: 150
     instance_type: c5.4xlarge
     is_ephemeral: false
     max_available: 1000
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.4xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g3.4xlarge
     is_ephemeral: false
     max_available: 1000
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.8xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g3.8xlarge
     is_ephemeral: false
     max_available: 400
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.g4dn.12xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g4dn.12xlarge
     is_ephemeral: false
     max_available: 250
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.g4dn.metal.nvidia.gpu:
     disk_size: 150
     instance_type: g4dn.metal
     is_ephemeral: false
     max_available: 300
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.g5.48xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g5.48xlarge
     is_ephemeral: false
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.g5.12xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g5.12xlarge
     is_ephemeral: false
     max_available: 150
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.g5.4xlarge.nvidia.gpu:
     disk_size: 150
     instance_type: g5.4xlarge
     is_ephemeral: false
     max_available: 2400
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.g6.4xlarge.experimental.nvidia.gpu:
     disk_size: 150
     instance_type: g6.4xlarge
     is_ephemeral: false
     max_available: 50
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.large:
     max_available: 1200
     disk_size: 15
     instance_type: c5.large
     is_ephemeral: false
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-x86_64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-x86_64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-x86_64-ebs
   lf.linux.arm64.2xlarge:
     disk_size: 256
     instance_type: t4g.2xlarge
     is_ephemeral: false
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.linux.arm64.m7g.4xlarge:
     disk_size: 256
     instance_type: m7g.4xlarge
     is_ephemeral: false
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.linux.arm64.2xlarge.ephemeral:
     disk_size: 256
     instance_type: t4g.2xlarge
     is_ephemeral: true
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.linux.arm64.m7g.4xlarge.ephemeral:
     disk_size: 256
     instance_type: m7g.4xlarge
     is_ephemeral: true
     max_available: 200
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.linux.arm64.m7g.metal:
     disk_size: 256
     instance_type: m7g.metal
     is_ephemeral: false
     max_available: 100
     os: linux
-    ami: al2023-ami-2023.5.202*-kernel-6.1-arm64
+    ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+    variants:
+      amz2023:
+        ami: al2023-ami-2023.5.20240701.0-kernel-6.1-arm64
+      am2:
+        ami: amzn2-ami-hvm-2.0.20240306.2-arm64-gp2
   lf.windows.g4dn.xlarge:
     disk_size: 256
     instance_type: g4dn.xlarge

.github/merge_rules.yaml

@@ -86,18 +86,6 @@
   - pull
   - inductor
 
-- name: OSS CI / pytorchbot / slow tests
-  patterns:
-  - test/slow_tests.json
-  approved_by:
-  - pytorchbot
-  ignore_flaky_failures: false
-  mandatory_checks_name:
-  - EasyCLA
-  - Lint
-  - pull
-  - slow
-
 - name: OSS CI /pytorchbot / Executorch
   patterns:
   - .ci/docker/ci_commit_pins/executorch.txt
@@ -119,8 +107,8 @@
   mandatory_checks_name:
   - EasyCLA
   - Lint
-  - pull / linux-focal-py3_9-clang9-xla / build
+  - pull / linux-focal-py3_8-clang9-xla / build
-  - pull / linux-focal-py3_9-clang9-xla / test (xla, 1, 1, linux.12xlarge)
+  - pull / linux-focal-py3_8-clang9-xla / test (xla, 1, 1, linux.12xlarge)
 
 - name: Documentation
   patterns:
@@ -544,7 +532,6 @@
   - anijain2305
   - bdhirsh
   - zou3519
-  - isuruf
   mandatory_checks_name:
   - EasyCLA
   - Lint

.github/pytorch-probot.yml

@@ -9,7 +9,6 @@ ciflow_push_tags:
 - ciflow/inductor-rocm
 - ciflow/inductor-perf-compare
 - ciflow/inductor-micro-benchmark
-- ciflow/inductor-micro-benchmark-cpu-x86
 - ciflow/inductor-cu124
 - ciflow/linux-aarch64
 - ciflow/mps

.github/requirements/pip-requirements-macOS.txt

@@ -1,7 +1,6 @@
 boto3==1.19.12
 hypothesis==6.56.4
-expecttest==0.2.1
+expecttest==0.1.6
-fbscribelogger==0.1.6
 librosa>=0.6.2
 mpmath==1.3.0
 networkx==2.8.7
@@ -31,4 +30,3 @@ optree==0.12.1
 # NB: test_hparams_* from test_tensorboard is failing with protobuf 5.26.0 in
 # which the stringify metadata is wrong when escaping double quote
 protobuf==3.20.2
-parameterized==0.8.1

.github/scripts/build_triton_wheel.py

@@ -15,7 +15,9 @@ REPO_DIR = SCRIPT_DIR.parent.parent
 
 def read_triton_pin(device: str = "cuda") -> str:
     triton_file = "triton.txt"
-    if device == "xpu":
+    if device == "rocm":
+        triton_file = "triton-rocm.txt"
+    elif device == "xpu":
         triton_file = "triton-xpu.txt"
     with open(REPO_DIR / ".ci" / "docker" / "ci_commit_pins" / triton_file) as f:
         return f.read().strip()

.github/scripts/generate_binary_build_matrix.py

@@ -325,7 +325,6 @@ def generate_wheels_matrix(
     os: str,
     arches: Optional[List[str]] = None,
     python_versions: Optional[List[str]] = None,
-    use_split_build: bool = False,
 ) -> List[Dict[str, str]]:
     package_type = "wheel"
     if os == "linux" or os == "linux-aarch64" or os == "linux-s390x":
@@ -341,7 +340,7 @@ def generate_wheels_matrix(
         if os == "linux":
             arches += CPU_CXX11_ABI_ARCH + CUDA_ARCHES + ROCM_ARCHES + XPU_ARCHES
         elif os == "windows":
-            arches += CUDA_ARCHES + XPU_ARCHES
+            arches += CUDA_ARCHES
         elif os == "linux-aarch64":
             # Only want the one arch as the CPU type is different and
             # uses different build/test scripts
@@ -372,17 +371,7 @@ def generate_wheels_matrix(
             ) and python_version == "3.13":
                 continue
 
-            if use_split_build and (
-                arch_version not in ["12.4", "12.1", "11.8", "cpu"] or os != "linux"
-            ):
-                raise RuntimeError(
-                    "Split build is only supported on linux with cuda 12.4, 12.1, 11.8, and cpu.\n"
-                    f"Currently attempting to build on arch version {arch_version} and os {os}.\n"
-                    "Please modify the matrix generation to exclude this combination."
-                )
-
             # 12.1 linux wheels require PYTORCH_EXTRA_INSTALL_REQUIREMENTS to install
-
             if (
                 arch_version in ["12.4", "12.1", "11.8"]
                 and os == "linux"
@@ -396,7 +385,6 @@ def generate_wheels_matrix(
                         "desired_cuda": translate_desired_cuda(
                             gpu_arch_type, gpu_arch_version
                         ),
-                        "use_split_build": "True" if use_split_build else "False",
                         "devtoolset": (
                             "cxx11-abi" if arch_version == "cuda-aarch64" else ""
                         ),
@@ -412,8 +400,7 @@ def generate_wheels_matrix(
                         ),
                     }
                 )
-                # Special build building to use on Colab. Python 3.11 for 12.1 CUDA
+                if arch_version != "cuda-aarch64":
-                if python_version == "3.11" and arch_version == "12.1":
                     ret.append(
                         {
                             "python_version": python_version,
@@ -422,16 +409,40 @@ def generate_wheels_matrix(
                             "desired_cuda": translate_desired_cuda(
                                 gpu_arch_type, gpu_arch_version
                             ),
-                            "use_split_build": "True" if use_split_build else "False",
+                            "use_split_build": "True",
                             "devtoolset": "",
                             "container_image": WHEEL_CONTAINER_IMAGES[arch_version],
                             "package_type": package_type,
-                            "pytorch_extra_install_requirements": "",
+                            "pytorch_extra_install_requirements": (
-                            "build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}-full".replace(  # noqa: B950
+                                PYTORCH_EXTRA_INSTALL_REQUIREMENTS[arch_version]  # fmt: skip
+                                if os != "linux-aarch64"
+                                else ""
+                            ),
+                            "build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}-split".replace(  # noqa: B950
                                 ".", "_"
                             ),
                         }
                     )
+                    # Special build building to use on Colab. PyThon 3.10 for 12.1 CUDA
+                    if python_version == "3.10" and arch_version == "12.1":
+                        ret.append(
+                            {
+                                "python_version": python_version,
+                                "gpu_arch_type": gpu_arch_type,
+                                "gpu_arch_version": gpu_arch_version,
+                                "desired_cuda": translate_desired_cuda(
+                                    gpu_arch_type, gpu_arch_version
+                                ),
+                                "use_split_build": "False",
+                                "devtoolset": "",
+                                "container_image": WHEEL_CONTAINER_IMAGES[arch_version],
+                                "package_type": package_type,
+                                "pytorch_extra_install_requirements": "",
+                                "build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}-full".replace(  # noqa: B950
+                                    ".", "_"
+                                ),
+                            }
+                        )
             else:
                 ret.append(
                     {
@@ -441,7 +452,6 @@ def generate_wheels_matrix(
                         "desired_cuda": translate_desired_cuda(
                             gpu_arch_type, gpu_arch_version
                         ),
-                        "use_split_build": "True" if use_split_build else "False",
                         "devtoolset": (
                             "cxx11-abi" if arch_version == "cpu-cxx11-abi" else ""
                         ),
@@ -452,12 +462,11 @@ def generate_wheels_matrix(
                         ),
                         "pytorch_extra_install_requirements": (
                             PYTORCH_EXTRA_INSTALL_REQUIREMENTS["12.1"]  # fmt: skip
-                            if os != "linux" and gpu_arch_type != "xpu"
+                            if os != "linux"
                             else ""
                         ),
                     }
                 )
-
     return ret
 
 

.github/scripts/generate_ci_workflows.py

@@ -61,7 +61,6 @@ class BinaryBuildWorkflow:
     # Mainly for macos
     cross_compile_arm64: bool = False
     macos_runner: str = "macos-14-xlarge"
-    use_split_build: bool = False
 
     def __post_init__(self) -> None:
         if self.abi_version:
@@ -70,9 +69,6 @@ class BinaryBuildWorkflow:
             )
         else:
             self.build_environment = f"{self.os}-binary-{self.package_type}"
-        if self.use_split_build:
-            # added to distinguish concurrency groups
-            self.build_environment += "-split"
 
     def generate_workflow_file(self, workflow_template: jinja2.Template) -> None:
         output_file_path = (
@@ -114,20 +110,6 @@ LINUX_BINARY_BUILD_WORFKLOWS = [
             isolated_workflow=True,
         ),
     ),
-    BinaryBuildWorkflow(
-        os=OperatingSystem.LINUX,
-        package_type="manywheel",
-        build_configs=generate_binary_build_matrix.generate_wheels_matrix(
-            OperatingSystem.LINUX,
-            use_split_build=True,
-            arches=["11.8", "12.1", "12.4", "cpu"],
-        ),
-        ciflow_config=CIFlowConfig(
-            labels={LABEL_CIFLOW_BINARIES, LABEL_CIFLOW_BINARIES_WHEEL},
-            isolated_workflow=True,
-        ),
-        use_split_build=True,
-    ),
     BinaryBuildWorkflow(
         os=OperatingSystem.LINUX,
         package_type="conda",
@@ -180,21 +162,6 @@ LINUX_BINARY_SMOKE_WORKFLOWS = [
         ),
         branches="main",
     ),
-    BinaryBuildWorkflow(
-        os=OperatingSystem.LINUX,
-        package_type="manywheel",
-        build_configs=generate_binary_build_matrix.generate_wheels_matrix(
-            OperatingSystem.LINUX,
-            arches=["11.8", "12.1", "12.4"],
-            python_versions=["3.9"],
-            use_split_build=True,
-        ),
-        ciflow_config=CIFlowConfig(
-            labels={LABEL_CIFLOW_PERIODIC},
-        ),
-        branches="main",
-        use_split_build=True,
-    ),
     BinaryBuildWorkflow(
         os=OperatingSystem.LINUX,
         package_type="libtorch",

.github/scripts/github_utils.py

@@ -46,24 +46,16 @@ def gh_fetch_url_and_headers(
         with urlopen(Request(url, headers=headers, data=data_, method=method)) as conn:
             return conn.headers, reader(conn)
     except HTTPError as err:
-        if (
+        if err.code == 403 and all(
-            err.code == 403
+            key in err.headers for key in ["X-RateLimit-Limit", "X-RateLimit-Used"]
-            and all(
-                key in err.headers
-                for key in ["X-RateLimit-Limit", "X-RateLimit-Remaining"]
-            )
-            and int(err.headers["X-RateLimit-Remaining"]) == 0
         ):
             print(
-                f"""{url}
+                f"""Rate limit exceeded:
-                Rate limit exceeded:
                 Used: {err.headers['X-RateLimit-Used']}
                 Limit: {err.headers['X-RateLimit-Limit']}
                 Remaining: {err.headers['X-RateLimit-Remaining']}
                 Resets at: {err.headers['x-RateLimit-Reset']}"""
             )
-        else:
-            print(f"Error fetching {url} {err}")
         raise
 
 
@@ -168,14 +160,6 @@ def gh_post_commit_comment(
     )
 
 
-def gh_close_pr(org: str, repo: str, pr_num: int, dry_run: bool = False) -> None:
-    url = f"{GITHUB_API_URL}/repos/{org}/{repo}/pulls/{pr_num}"
-    if dry_run:
-        print(f"Dry run closing PR {pr_num}")
-    else:
-        gh_fetch_url(url, method="PATCH", data={"state": "closed"})
-
-
 def gh_delete_comment(org: str, repo: str, comment_id: int) -> None:
     url = f"{GITHUB_API_URL}/repos/{org}/{repo}/issues/comments/{comment_id}"
     gh_fetch_url(url, method="DELETE")

.github/scripts/lintrunner.sh

@@ -17,11 +17,6 @@ if [[ -d "${CACHE_DIRECTORY}" ]]; then
     cp -r "${CACHE_DIRECTORY}" . || true
 fi
 
-# if lintrunner is not installed, install it
-if ! command -v lintrunner &> /dev/null; then
-    python3 -m pip install lintrunner==0.12.5
-fi
-
 # This has already been cached in the docker image
 lintrunner init 2> /dev/null
 
@@ -38,7 +33,7 @@ python3 torch/utils/data/datapipes/gen_pyi.py
 
 RC=0
 # Run lintrunner on all files
-if ! lintrunner --force-color --tee-json=lint.json ${ADDITIONAL_LINTRUNNER_ARGS} 2> /dev/null; then
+if ! lintrunner --force-color --all-files --tee-json=lint.json ${ADDITIONAL_LINTRUNNER_ARGS} 2> /dev/null; then
     echo ""
     echo -e "\e[1m\e[36mYou can reproduce these results locally by using \`lintrunner -m origin/main\`. (If you don't get the same results, run \'lintrunner init\' to update your local linter)\e[0m"
     echo -e "\e[1m\e[36mSee https://github.com/pytorch/pytorch/wiki/lintrunner for setup instructions.\e[0m"

.github/scripts/runner_determinator.py

@@ -3,94 +3,49 @@
 """
 This runner determinator is used to determine which set of runners to run a
 GitHub job on. It uses the first comment of a GitHub issue (by default
-https://github.com/pytorch/test-infra/issues/5132) to define the configuration
+https://github.com/pytorch/test-infra/issues/5132) as a user list to determine
-of which runners should be used to run which job.
+which users will get their jobs to run on experimental runners. This user list
-
+is also a comma separated list of additional features or experiments which the
-The configuration has two parts, the settings and a list of opted-in users,
+user could be opted in to.
-separated by a line containing "---".  If the line is not present, the
-settings are considered to be empty with only the second part, the user
-list, defined.
-
-The first part is a YAML block that defines the rollout settings. This can be
-used to define any settings that are needed to determine which runners to use.
-It's fields are defined by the RolloutSettings class below.
-
-The second part is a list of users who are explicitly opted in to the LF fleet.
-The user list is also a comma separated list of additional features or
-experiments which the user could be opted in to.
 
 The user list has the following rules:
 
-- Users are GitHub usernames, which must start with the @ prefix
+- Users are GitHub usernames with the @ prefix
+- If the first line is a "*" then all users will use the new runners
+- If the first line is a "!" then all users will use the old runners
 - Each user is also a comma-separated list of features/experiments to enable
-- A "#" prefix opts the user out of all experiments
+- A "#" prefix indicates the user is opted out of the new runners but is opting
+  into features/experiments.
 
-Example config:
+Example user list:
-    # A list of experiments that can be opted into.
-    # This defines the behavior they'll induce when opted into.
-    # Expected syntax is:
-    #   [experiment_name]: # Name of the experiment. Also used for the label prefix.
-    #      rollout_perc: [int] # % of workflows to run with this experiment when users are not opted in.
 
-    experiments:
+    @User1
-      lf:
+    @User2,amz2023
-        rollout_percent: 25
+    #@UserOptOutOfNewRunner,amz2023
-
-    ---
-
-    # Opt-ins:
-    # Users can opt into the LF fleet by adding their GitHub username to this list
-    # and specifying experiments to enable in a comma-separated list.
-    # Experiments should be from the above list.
-
-    @User1,lf,split_build
-    @User2,lf
-    @User3,split_build
 """
 
 import logging
 import os
-import random
 from argparse import ArgumentParser
 from logging import LogRecord
-from typing import Any, Dict, Iterable, List, NamedTuple, Tuple
+from typing import Any, Iterable
 
-import yaml
 from github import Auth, Github
 from github.Issue import Issue
 
 
-DEFAULT_LABEL_PREFIX = ""  # use meta runners
+WORKFLOW_LABEL_META = ""  # use meta runners
 WORKFLOW_LABEL_LF = "lf."  # use runners from the linux foundation
 WORKFLOW_LABEL_LF_CANARY = "lf.c."  # use canary runners from the linux foundation
 
+RUNNER_AMI_LEGACY = ""
+RUNNER_AMI_AMZ2023 = "amz2023"
+
 GITHUB_OUTPUT = os.getenv("GITHUB_OUTPUT", "")
 GH_OUTPUT_KEY_AMI = "runner-ami"
 GH_OUTPUT_KEY_LABEL_TYPE = "label-type"
 
 
-SETTING_EXPERIMENTS = "experiments"
-
-LF_FLEET_EXPERIMENT = "lf"
-CANARY_FLEET_SUFFIX = ".c"
-
-
-class Experiment(NamedTuple):
-    rollout_perc: float = (
-        0  # Percentage of workflows to experiment on when user is not opted-in.
-    )
-
-    # Add more fields as needed
-
-
-class Settings(NamedTuple):
-    """
-    Settings for the experiments that can be opted into.
-    """
-
-    experiments: Dict[str, Experiment] = {}
-
-
 class ColorFormatter(logging.Formatter):
     """Color codes the log messages based on the log level"""
 
@@ -182,14 +137,11 @@ def get_issue(gh: Github, repo: str, issue_num: int) -> Issue:
 
 
 def get_potential_pr_author(
-    github_token: str, repo: str, username: str, ref_type: str, ref_name: str
+    gh: Github, repo: str, username: str, ref_type: str, ref_name: str
 ) -> str:
     # If the trigger was a new tag added by a bot, this is a ciflow case
     # Fetch the actual username from the original PR. The PR number is
     # embedded in the tag name: ciflow/<name>/<pr-number>
-
-    gh = get_gh_client(github_token)
-
     if username == "pytorch-bot[bot]" and ref_type == "tag":
         split_tag = ref_name.split("/")
         if (
@@ -211,233 +163,126 @@ def get_potential_pr_author(
 
 
 def is_exception_branch(branch: str) -> bool:
-    """
-    Branches that get opted out of all experiments and should always use Meta runners
-    """
     return branch.split("/")[0] in {"main", "nightly", "release", "landchecks"}
 
 
-def load_yaml(yaml_text: str) -> Any:
+def get_workflow_type(issue: Issue, workflow_requestors: Iterable[str]) -> str:
     try:
-        data = yaml.safe_load(yaml_text)
+        first_comment = issue.get_comments()[0].body.strip("\n\t ")
-        return data
-    except yaml.YAMLError as exc:
-        log.exception("Error loading YAML")
-        raise
 
-
+        if first_comment[0] == "!":
-def extract_settings_user_opt_in_from_text(rollout_state: str) -> Tuple[str, str]:
+            log.info("LF Workflows are disabled for everyone. Using meta runners.")
-    """
+            return WORKFLOW_LABEL_META
-    Extracts the text with settings, if any, and the opted in users from the rollout state.
+        elif first_comment[0] == "*":
-
+            log.info("LF Workflows are enabled for everyone. Using LF runners.")
-    If the issue body contains "---" then the text above that is the settings
+            return WORKFLOW_LABEL_LF
-    and the text below is the list of opted in users.
+        else:
-
+            all_opted_in_users = {
-    If it doesn't contain "---" then the settings are empty and the rest is the users.
+                usr_raw.strip("\n\t@ ").split(",")[0]
-    """
+                for usr_raw in first_comment.split()
-    rollout_state_parts = rollout_state.split("---")
+            }
-    if len(rollout_state_parts) >= 2:
+            opted_in_requestors = {
-        return rollout_state_parts[0], rollout_state_parts[1]
+                usr for usr in workflow_requestors if usr in all_opted_in_users
-    else:
+            }
-        return "", rollout_state
+            if opted_in_requestors:
-
-
-class UserOptins(Dict[str, List[str]]):
-    """
-    Dictionary of users with a list of features they have opted into
-    """
-
-
-def parse_user_opt_in_from_text(user_optin_text: str) -> UserOptins:
-    """
-    Parse the user opt-in text into a key value pair of username and the list of features they have opted into
-
-    Users are GitHub usernames with the @ prefix. Each user is also a comma-separated list of features/experiments to enable.
-        - Example line: "@User1,lf,split_build"
-        - A "#" prefix indicates the user is opted out of all experiments
-
-
-    """
-    optins = UserOptins()
-    for user in user_optin_text.split("\n"):
-        user = user.strip("\r\n\t -")
-        if not user or not user.startswith("@"):
-            # Not a valid user. Skip
-            continue
-
-        if user:
-            usr_name = user.split(",")[0].strip("@")
-            optins[usr_name] = [exp.strip(" ") for exp in user.split(",")[1:]]
-
-    return optins
-
-
-def parse_settings_from_text(settings_text: str) -> Settings:
-    """
-    Parse the experiments from the issue body into a list of ExperimentSettings
-    """
-    try:
-        if settings_text:
-            # Escape the backtick as well so that we can have the settings in a code block on the GH issue
-            # for easy reading
-            # Note: Using ascii for the backtick so that the cat step in _runner-determinator.yml doesn't choke on
-            #       the backtick character in shell commands.
-            backtick = chr(96)  # backtick character
-            settings_text = settings_text.strip(f"\r\n\t{backtick} ")
-            settings = load_yaml(settings_text)
-
-            # For now we just load experiments. We can expand this if/when we add more settings
-            experiments = {}
-
-            for exp_name, exp_settings in settings.get(SETTING_EXPERIMENTS).items():
-                valid_settings = {}
-                for setting in exp_settings:
-                    if setting not in Experiment._fields:
-                        log.warning(
-                            f"Unexpected setting in experiment: {setting} = {exp_settings[setting]}"
-                        )
-                    else:
-                        valid_settings[setting] = exp_settings[setting]
-
-                experiments[exp_name] = Experiment(**valid_settings)
-            return Settings(experiments)
-
-    except Exception:
-        log.exception("Failed to parse settings")
-
-    return Settings()
-
-
-def parse_settings(rollout_state: str) -> Settings:
-    """
-    Parse settings, if any, from the rollout state.
-
-    If the issue body contains "---" then the text above that is the settings
-    and the text below is the list of opted in users.
-
-    If it doesn't contain "---" then the settings are empty and the default values are used.
-    """
-    settings_text, _ = extract_settings_user_opt_in_from_text(rollout_state)
-    return parse_settings_from_text(settings_text)
-
-
-def parse_users(rollout_state: str) -> UserOptins:
-    """
-    Parse users from the rollout state.
-
-    """
-    _, users_text = extract_settings_user_opt_in_from_text(rollout_state)
-    return parse_user_opt_in_from_text(users_text)
-
-
-def is_user_opted_in(user: str, user_optins: UserOptins, experiment_name: str) -> bool:
-    """
-    Check if a user is opted into an experiment
-    """
-    return experiment_name in user_optins.get(user, [])
-
-
-def get_runner_prefix(
-    rollout_state: str, workflow_requestors: Iterable[str], is_canary: bool = False
-) -> str:
-    settings = parse_settings(rollout_state)
-    user_optins = parse_users(rollout_state)
-
-    fleet_prefix = ""
-    prefixes = []
-    for experiment_name, experiment_settings in settings.experiments.items():
-        enabled = False
-
-        # Is any workflow_requestor opted in to this experiment?
-        opted_in_users = [
-            requestor
-            for requestor in workflow_requestors
-            if is_user_opted_in(requestor, user_optins, experiment_name)
-        ]
-
-        if opted_in_users:
-            log.info(
-                f"{', '.join(opted_in_users)} have opted into experiment {experiment_name}."
-            )
-            enabled = True
-        elif experiment_settings.rollout_perc:
-            # If no user is opted in, then we randomly enable the experiment based on the rollout percentage
-            if random.uniform(0, 100) <= experiment_settings.rollout_perc:
                 log.info(
-                    f"Based on rollout percentage of {experiment_settings.rollout_perc}%, enabling experiment {experiment_name}."
+                    f"LF Workflows are enabled for {', '.join(opted_in_requestors)}. Using LF runners."
                 )
-                enabled = True
+                return WORKFLOW_LABEL_LF
-
-        if enabled:
-            label = experiment_name
-            if experiment_name == LF_FLEET_EXPERIMENT:
-                # We give some special treatment to the "lf" experiment since determines the fleet we use
-                #  - If it's enabled, then we always list it's prefix first
-                #  - If we're in the canary branch, then we append ".c" to the lf prefix
-                if is_canary:
-                    label += CANARY_FLEET_SUFFIX
-                fleet_prefix = label
             else:
-                prefixes.append(label)
+                log.info(
+                    f"LF Workflows are disabled for {', '.join(workflow_requestors)}. Using meta runners."
+                )
+                return WORKFLOW_LABEL_META
 
-    if len(prefixes) > 1:
+    except Exception as e:
         log.error(
-            f"Only a fleet and one other experiment can be enabled for a job at any time. Enabling {prefixes[0]} and ignoring the rest, which are {', '.join(prefixes[1:])}"
+            f"Failed to get determine workflow type. Falling back to meta runners. Exception: {e}"
         )
-        prefixes = prefixes[:1]
+        return WORKFLOW_LABEL_META
-
-    # Fleet always comes first
-    if fleet_prefix:
-        prefixes.insert(0, fleet_prefix)
-
-    return ".".join(prefixes) + "." if prefixes else ""
 
 
-def get_rollout_state_from_issue(github_token: str, repo: str, issue_num: int) -> str:
+def get_optin_feature(
-    """
+    issue: Issue, workflow_requestors: Iterable[str], feature: str, fallback: str
-    Gets the first comment of the issue, which contains the desired rollout state.
+) -> str:
+    try:
+        first_comment = issue.get_comments()[0].body.strip("\n\t ")
+        userlist = {u.lstrip("#").strip("\n\t@ ") for u in first_comment.split()}
+        all_opted_in_users = set()
+        for user in userlist:
+            for i in user.split(","):
+                if i == feature:
+                    all_opted_in_users.add(user.split(",")[0])
+        opted_in_requestors = {
+            usr for usr in workflow_requestors if usr in all_opted_in_users
+        }
 
-    The default issue we use - https://github.com/pytorch/test-infra/issues/5132
+        if opted_in_requestors:
-    """
+            log.info(
-    gh = get_gh_client(github_token)
+                f"Feature {feature} is enabled for {', '.join(opted_in_requestors)}. Using feature {feature}."
-    issue = get_issue(gh, repo, issue_num)
+            )
-    return str(issue.get_comments()[0].body.strip("\n\t "))
+            return feature
+        else:
+            log.info(
+                f"Feature {feature} is disabled for {', '.join(workflow_requestors)}. Using fallback \"{fallback}\"."
+            )
+            return fallback
+
+    except Exception as e:
+        log.error(
+            f'Failed to determine if user has opted-in to feature {feature}. Using fallback "{fallback}". Exception: {e}'
+        )
+        return fallback
 
 
 def main() -> None:
     args = parse_args()
 
     if args.github_ref_type == "branch" and is_exception_branch(args.github_branch):
-        log.info(
+        log.info(f"Exception branch: '{args.github_branch}', using meta runners")
-            f"Exception branch: '{args.github_branch}', using Meta runners and no experiments."
+        label_type = WORKFLOW_LABEL_META
-        )
+        runner_ami = RUNNER_AMI_LEGACY
-        runner_label_prefix = DEFAULT_LABEL_PREFIX
     else:
         try:
-            rollout_state = get_rollout_state_from_issue(
+            gh = get_gh_client(args.github_token)
-                args.github_token, args.github_issue_repo, args.github_issue
+            # The default issue we use - https://github.com/pytorch/test-infra/issues/5132
-            )
+            issue = get_issue(gh, args.github_issue_repo, args.github_issue)
-
             username = get_potential_pr_author(
-                args.github_token,
+                gh,
                 args.github_repo,
                 args.github_actor,
                 args.github_ref_type,
                 args.github_branch,
             )
-
+            label_type = get_workflow_type(
-            is_canary = args.github_repo == "pytorch/pytorch-canary"
+                issue,
-
+                (
-            runner_label_prefix = get_runner_prefix(
+                    args.github_issue_owner,
-                rollout_state, (args.github_issue_owner, username), is_canary
+                    username,
+                ),
+            )
+            runner_ami = get_optin_feature(
+                issue=issue,
+                workflow_requestors=(
+                    args.github_issue_owner,
+                    username,
+                ),
+                feature=RUNNER_AMI_AMZ2023,
+                fallback=RUNNER_AMI_LEGACY,
             )
-
         except Exception as e:
             log.error(
-                f"Failed to get issue. Defaulting to Meta runners and no experiments. Exception: {e}"
+                f"Failed to get issue. Falling back to meta runners. Exception: {e}"
             )
+            label_type = WORKFLOW_LABEL_META
+            runner_ami = RUNNER_AMI_LEGACY
 
-    set_github_output(GH_OUTPUT_KEY_LABEL_TYPE, runner_label_prefix)
+    # For Canary builds use canary runners
+    if args.github_repo == "pytorch/pytorch-canary" and label_type == WORKFLOW_LABEL_LF:
+        label_type = WORKFLOW_LABEL_LF_CANARY
+
+    set_github_output(GH_OUTPUT_KEY_LABEL_TYPE, label_type)
+    set_github_output(GH_OUTPUT_KEY_AMI, runner_ami)
 
 
 if __name__ == "__main__":

.github/scripts/s390x-ci/README.md

@@ -3,7 +3,7 @@
 ## Install prerequisites.
 
 ```
-$ sudo dnf install podman podman-docker jq
+$ sudo dnf install docker
 ```
 
 ## Add services.
@@ -27,48 +27,23 @@ $ sudo systemctl enable --now qemu-user-static
 
 ## Rebuild the image
 
-First build s390x builder image `docker.io/pytorch/manylinuxs390x-builder`,
+In order to build or update the `iiilinuxibmcom/actions-runner` image, e.g. to get the
-using following commands:
+latest OS security fixes, use the following commands:
-
-```
-$ cd ~
-$ git clone https://github.com/pytorch/pytorch
-$ cd pytorch
-$ git submodule update --init --recursive
-$ GPU_ARCH_TYPE=cpu-s390x "$(pwd)/.ci/docker/manywheel/build.sh" manylinuxs390x-builder
-$ docker image tag localhost/pytorch/manylinuxs390x-builder docker.io/pytorch/manylinuxs390x-builder:cpu-s390x
-$ docker image save -o ~/manywheel-s390x.tar docker.io/pytorch/manylinuxs390x-builder:cpu-s390x
-```
-
-Next step is to build `actions-runner` image using:
 
 ```
 $ cd self-hosted-builder
 $ sudo docker build \
+      --build-arg repo=<owner>/<name> \
+      --build-arg token=<***> \
       --pull \
       -f actions-runner.Dockerfile \
-      -t iiilinuxibmcom/actions-runner.<name> \
+      -t iiilinuxibmcom/actions-runner \
       .
 ```
 
-If there are failures, ensure that selinux doesn't prevent it from working.
+If it fails, ensure that selinux doesn't prevent it from working.
 In worst case, selinux can be disabled with `setenforce 0`.
 
-Now prepare all necessary files for runner registration:
-
-```
-$ sudo mkdir -p /etc/actions-runner/<name>
-$ sudo chmod 700 /etc/actions-runner/<name>
-$ sudo /bin/cp <github_app_private_key_file> /etc/actions-runner/<name>/key_private.pem
-$ sudo echo <github_app_id> | sudo tee /etc/actions-runner/<name>/appid.env
-$ sudo echo <github_app_install_id> | sudo tee /etc/actions-runner/<name>/installid.env
-$ sudo echo NAME=<worker_name> | sudo tee    /etc/actions-runner/<name>/env
-$ sudo echo ORG=<github_org>   | sudo tee -a /etc/actions-runner/<name>/env
-$ cd self-hosted-builder
-$ sudo /bin/cp helpers/*.sh /usr/local/bin/
-$ sudo chmod 755 /usr/local/bin/app_token.sh /usr/local/bin/gh_token_generator.sh
-```
-
 ## Autostart the runner.
 
 ```

.github/scripts/s390x-ci/self-hosted-builder/actions-runner.Dockerfile

@@ -1,12 +1,12 @@
 # Self-Hosted IBM Z Github Actions Runner.
 
 # Temporary image: amd64 dependencies.
-FROM docker.io/amd64/ubuntu:23.10 as ld-prefix
+FROM docker.io/amd64/ubuntu:22.04 as ld-prefix
 ENV DEBIAN_FRONTEND=noninteractive
-RUN apt-get update && apt-get -y install ca-certificates libicu72 libssl3
+RUN apt-get update && apt-get -y install ca-certificates libicu70 libssl3
 
 # Main image.
-FROM docker.io/s390x/ubuntu:23.10
+FROM docker.io/s390x/ubuntu:22.04
 
 # Packages for pytorch building and testing.
 ENV DEBIAN_FRONTEND=noninteractive
@@ -16,7 +16,6 @@ RUN apt-get update && apt-get -y install \
         gcc \
         git \
         jq \
-        zip \
         libxml2-dev \
         libxslt-dev \
         ninja-build \
@@ -44,28 +43,24 @@ COPY fs/ /
 
 RUN chmod +x /usr/bin/actions-runner /usr/bin/entrypoint
 
-# install podman
-RUN apt -y install podman podman-docker
-
 # amd64 Github Actions Runner.
 RUN useradd -m actions-runner
 USER actions-runner
 WORKDIR /home/actions-runner
+RUN curl -L https://github.com/actions/runner/releases/download/v2.309.0/actions-runner-linux-x64-2.309.0.tar.gz | tar -xz
 
-# set up python virtual environment which is later used by runner.
+# repository
-# build workflows use "python -m pip install ...",
+ARG repo
-# and it doesn't work for non-root user
-RUN virtualenv --system-site-packages venv
 
-# copy prebuilt manywheel docker image for builds and tests
+# repository token
-# build command is:
+ARG token
-# GPU_ARCH_TYPE=cpu-s390x "$(pwd)/manywheel/build_docker.sh"
-# and save command is:
-# docker image save -o manywheel-s390x.tar pytorch/manylinuxs390x-builder:cpu-s390x
-#
-COPY --chown=actions-runner:actions-runner manywheel-s390x.tar /home/actions-runner/manywheel-s390x.tar
 
-RUN curl -L https://github.com/actions/runner/releases/download/v2.317.0/actions-runner-linux-x64-2.317.0.tar.gz | tar -xz
+RUN ./config.sh \
+        --unattended \
+        --url "https://github.com/${repo}" \
+        --token "${token}" \
+        --no-default-labels \
+        --labels self-hosted,linux.s390x
 
 ENTRYPOINT ["/usr/bin/entrypoint"]
 CMD ["/usr/bin/actions-runner"]

.github/scripts/s390x-ci/self-hosted-builder/actions-runner@.service

@@ -8,16 +8,12 @@ StartLimitIntervalSec=0
 Type=simple
 Restart=always
 ExecStartPre=-/usr/bin/docker rm --force actions-runner.%i
-ExecStartPre=-/usr/local/bin/gh_token_generator.sh /etc/actions-runner/%i/appid.env /etc/actions-runner/%i/installid.env /etc/actions-runner/%i/key_private.pem /etc/actions-runner/%i/ghtoken.env
 ExecStart=/usr/bin/docker run \
-              --env-file=/etc/actions-runner/%i/env \
-              --env-file=/etc/actions-runner/%i/ghtoken.env \
               --init \
               --interactive \
               --name=actions-runner.%i \
               --rm \
-              --privileged \
+              iiilinuxibmcom/actions-runner
-              iiilinuxibmcom/actions-runner.%i
 ExecStop=/bin/sh -c "docker exec actions-runner.%i kill -INT -- -1"
 ExecStop=/bin/sh -c "docker wait actions-runner.%i"
 ExecStop=/bin/sh -c "docker rm actions-runner.%i"

.github/scripts/s390x-ci/self-hosted-builder/fs/usr/bin/actions-runner

@@ -2,45 +2,5 @@
 
 set -e -u
 
-# first import docker image
-if [ -f ./manywheel-s390x.tar ] ; then
-        docker image load --input manywheel-s390x.tar
-        docker image tag docker.io/pytorch/manylinuxs390x-builder:cpu-s390x docker.io/pytorch/manylinuxs390x-builder:cpu-s390x-main
-        rm -f manywheel-s390x.tar
-fi
-
-token_file=registration-token.json
-
-# Generate registration token
-curl \
-        -X POST \
-        -H "Accept: application/vnd.github.v3+json" \
-        -H "Authorization: Bearer ${ACCESS_TOKEN}" \
-        "https://api.github.com/orgs/${ORG}/actions/runners/registration-token" \
-        -o "$token_file"
-
-unset ACCESS_TOKEN
-
-# register runner as ephemeral runner
-# it does one job, stops and unregisters
-registration_token=$(jq --raw-output .token "$token_file")
-
-./config.sh \
-        --unattended \
-        --ephemeral \
-        --url "https://github.com/${ORG}" \
-        --token "${registration_token}" \
-        --name "${NAME}" \
-        --no-default-labels \
-        --labels self-hosted,linux.s390x
-
-unset registration_token
-rm -f "$token_file"
-
-# enter into python virtual environment.
-# build workflows use "python -m pip install ...",
-# and it doesn't work for non-root user
-source venv/bin/activate
-
 # Run one job.
-./run.sh
+./run.sh --once

.github/scripts/s390x-ci/self-hosted-builder/helpers/app_token.sh

@@ -1,84 +0,0 @@
-#!/usr/bin/env bash
-#
-# Request an ACCESS_TOKEN to be used by a GitHub APP
-# Environment variable that need to be set up:
-# * APP_ID, the GitHub's app ID
-# * INSTALL_ID, the Github's app's installation ID
-# * APP_PRIVATE_KEY, the content of GitHub app's private key in PEM format.
-#
-# https://github.com/orgs/community/discussions/24743#discussioncomment-3245300
-#
-
-set -o pipefail
-
-_GITHUB_HOST=${GITHUB_HOST:="github.com"}
-
-# If URL is not github.com then use the enterprise api endpoint
-if [[ ${GITHUB_HOST} = "github.com" ]]; then
-  URI="https://api.${_GITHUB_HOST}"
-else
-  URI="https://${_GITHUB_HOST}/api/v3"
-fi
-
-API_VERSION=v3
-API_HEADER="Accept: application/vnd.github.${API_VERSION}+json"
-CONTENT_LENGTH_HEADER="Content-Length: 0"
-APP_INSTALLATIONS_URI="${URI}/app/installations"
-
-
-# JWT parameters based off
-# https://docs.github.com/en/developers/apps/building-github-apps/authenticating-with-github-apps#authenticating-as-a-github-app
-#
-# JWT token issuance and expiration parameters
-JWT_IAT_DRIFT=60
-JWT_EXP_DELTA=600
-
-JWT_JOSE_HEADER='{
-    "alg": "RS256",
-    "typ": "JWT"
-}'
-
-
-build_jwt_payload() {
-    now=$(date +%s)
-    iat=$((now - JWT_IAT_DRIFT))
-    jq -c \
-        --arg iat_str "${iat}" \
-        --arg exp_delta_str "${JWT_EXP_DELTA}" \
-        --arg app_id_str "${APP_ID}" \
-    '
-        ($iat_str | tonumber) as $iat
-        | ($exp_delta_str | tonumber) as $exp_delta
-        | ($app_id_str | tonumber) as $app_id
-        | .iat = $iat
-        | .exp = ($iat + $exp_delta)
-        | .iss = $app_id
-    ' <<< "{}" | tr -d '\n'
-}
-
-base64url() {
-    base64 | tr '+/' '-_' | tr -d '=\n'
-}
-
-rs256_sign() {
-    openssl dgst -binary -sha256 -sign <(echo "$1")
-}
-
-request_access_token() {
-    jwt_payload=$(build_jwt_payload)
-    encoded_jwt_parts=$(base64url <<<"${JWT_JOSE_HEADER}").$(base64url <<<"${jwt_payload}")
-    encoded_mac=$(echo -n "$encoded_jwt_parts" | rs256_sign "${APP_PRIVATE_KEY}" | base64url)
-    generated_jwt="${encoded_jwt_parts}.${encoded_mac}"
-
-    auth_header="Authorization: Bearer ${generated_jwt}"
-
-    app_installations_response=$(curl -sX POST \
-        -H "${auth_header}" \
-        -H "${API_HEADER}" \
-        --header "X-GitHub-Api-Version: 2022-11-28" \
-        --url "https://api.github.com/app/installations/${INSTALL_ID}/access_tokens" \
-    )
-    echo "$app_installations_response" | jq --raw-output '.token'
-}
-
-request_access_token

.github/scripts/s390x-ci/self-hosted-builder/helpers/gh_token_generator.sh

@@ -1,10 +0,0 @@
-#!/usr/bin/env bash
-
-SCRIPT_DIR=$(dirname "$0")
-APP_ID=$1
-INSTALL_ID=$2
-APP_PRIVATE_KEY=$3
-DST_FILE="$4"
-
-ACCESS_TOKEN="$(APP_ID="$(<"${APP_ID}")" INSTALL_ID="$(<"${INSTALL_ID}")" APP_PRIVATE_KEY="$(<"${APP_PRIVATE_KEY}")" "${SCRIPT_DIR}/app_token.sh")"
-echo "ACCESS_TOKEN=${ACCESS_TOKEN}" > "${DST_FILE}"

.github/scripts/sync_distributed_folder_prototype.sh

@@ -0,0 +1,35 @@
+#!/bin/bash
+
+set -eoux pipefail
+
+SYNC_BRANCH=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"
+
+# Using a hardcoded SHA here is a massive speedup as we can skip the entire history of the pytorch GitHub repo.
+# This specific SHA was chosen as it was before the "branch point" of the stable branch
+for SHA in $(git log ba3b05fdf37ddbc3c301294d6a560a816335e717..origin/main --pretty="%h" -- 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" -X theirs
+    git reset --soft HEAD~1
+    git add torch/distributed torch/csrc/distributed test/distributed test/cpp/c10d benchmarks/distributed
+    git checkout .
+    git commit --reuse-message=HEAD@{1}
+    git clean -f
+done
+
+if [[ "${WITH_PUSH}" == true ]]; then
+  git push
+fi

.github/scripts/tag_docker_images_for_release.py

@@ -51,8 +51,6 @@ def main() -> None:
 
     for platform_image in platform_images:  # type: ignore[attr-defined]
         for arch in platform_image.keys():  # type: ignore[attr-defined]
-            if arch == "cpu-s390x":
-                continue
             tag_image(
                 platform_image[arch],  # type: ignore[index]
                 default_tag,

.github/scripts/test_runner_determinator.py

@@ -1,237 +0,0 @@
-from unittest import main, TestCase
-from unittest.mock import Mock, patch
-
-import runner_determinator as rd
-
-
-class TestRunnerDeterminatorIssueParser(TestCase):
-    def test_parse_settings(self) -> None:
-        settings_text = """
-        experiments:
-            lf:
-                rollout_perc: 25
-            otherExp:
-                rollout_perc: 0
-        ---
-
-        Users:
-        @User1,lf
-        @User2,lf,otherExp
-
-        """
-
-        settings = rd.parse_settings(settings_text)
-
-        self.assertTupleEqual(
-            rd.Experiment(rollout_perc=25),
-            settings.experiments["lf"],
-            "lf settings not parsed correctly",
-        )
-        self.assertTupleEqual(
-            rd.Experiment(rollout_perc=0),
-            settings.experiments["otherExp"],
-            "otherExp settings not parsed correctly",
-        )
-
-    def test_parse_settings_in_code_block(self) -> None:
-        settings_text = """
-
-        ```
-        experiments:
-            lf:
-                rollout_perc: 25
-            otherExp:
-                rollout_perc: 0
-
-        ```
-
-        ---
-
-        Users:
-        @User1,lf
-        @User2,lf,otherExp
-
-        """
-
-        settings = rd.parse_settings(settings_text)
-
-        self.assertTupleEqual(
-            rd.Experiment(rollout_perc=25),
-            settings.experiments["lf"],
-            "lf settings not parsed correctly",
-        )
-        self.assertTupleEqual(
-            rd.Experiment(rollout_perc=0),
-            settings.experiments["otherExp"],
-            "otherExp settings not parsed correctly",
-        )
-
-    def test_parse_users(self) -> None:
-        settings_text = """
-        experiments:
-            lf:
-                rollout_perc: 0
-            otherExp:
-                rollout_perc: 0
-        ---
-
-        Users:
-        @User1,lf
-        @User2,lf,otherExp
-
-        """
-
-        users = rd.parse_users(settings_text)
-        self.assertDictEqual(
-            {"User1": ["lf"], "User2": ["lf", "otherExp"]},
-            users,
-            "Users not parsed correctly",
-        )
-
-    def test_parse_users_without_settings(self) -> None:
-        settings_text = """
-
-        @User1,lf
-        @User2,lf,otherExp
-
-        """
-
-        users = rd.parse_users(settings_text)
-        self.assertDictEqual(
-            {"User1": ["lf"], "User2": ["lf", "otherExp"]},
-            users,
-            "Users not parsed correctly",
-        )
-
-
-class TestRunnerDeterminatorGetRunnerPrefix(TestCase):
-    def test_opted_in_user(self) -> None:
-        settings_text = """
-        experiments:
-            lf:
-                rollout_perc: 0
-            otherExp:
-                rollout_perc: 0
-        ---
-
-        Users:
-        @User1,lf
-        @User2,lf,otherExp
-
-        """
-        prefix = rd.get_runner_prefix(settings_text, ["User1"])
-        self.assertEqual("lf.", prefix, "Runner prefix not correct for User1")
-
-    def test_opted_in_user_two_experiments(self) -> None:
-        settings_text = """
-        experiments:
-            lf:
-                rollout_perc: 0
-            otherExp:
-                rollout_perc: 0
-        ---
-
-        Users:
-        @User1,lf
-        @User2,lf,otherExp
-
-        """
-        prefix = rd.get_runner_prefix(settings_text, ["User2"])
-        self.assertEqual("lf.otherExp.", prefix, "Runner prefix not correct for User2")
-
-    @patch("random.uniform", return_value=50)
-    def test_opted_out_user(self, mock_uniform: Mock) -> None:
-        settings_text = """
-        experiments:
-            lf:
-                rollout_perc: 25
-            otherExp:
-                rollout_perc: 25
-        ---
-
-        Users:
-        @User1,lf
-        @User2,lf,otherExp
-
-        """
-        prefix = rd.get_runner_prefix(settings_text, ["User3"])
-        self.assertEqual("", prefix, "Runner prefix not correct for user")
-
-    @patch("random.uniform", return_value=10)
-    def test_opted_out_user_was_pulled_in_by_rollout(self, mock_uniform: Mock) -> None:
-        settings_text = """
-        experiments:
-            lf:
-                rollout_perc: 25
-            otherExp:
-                rollout_perc: 25
-        ---
-
-        Users:
-        @User1,lf
-        @User2,lf,otherExp
-
-        """
-
-        # User3 is opted out, but is pulled into both experiments by the 10% rollout
-        prefix = rd.get_runner_prefix(settings_text, ["User3"])
-        self.assertEqual("lf.otherExp.", prefix, "Runner prefix not correct for user")
-
-    def test_lf_prefix_always_comes_first(self) -> None:
-        settings_text = """
-        experiments:
-            otherExp:
-                rollout_perc: 0
-            lf:
-                rollout_perc: 0
-        ---
-
-        Users:
-        @User1,lf
-        @User2,otherExp,lf
-
-        """
-
-        prefix = rd.get_runner_prefix(settings_text, ["User2"])
-        self.assertEqual("lf.otherExp.", prefix, "Runner prefix not correct for user")
-
-    def test_ignores_commented_users(self) -> None:
-        settings_text = """
-        experiments:
-            lf:
-                rollout_perc: 0
-            otherExp:
-                rollout_perc: 0
-        ---
-
-        Users:
-        #@User1,lf
-        @User2,lf,otherExp
-
-        """
-
-        prefix = rd.get_runner_prefix(settings_text, ["User1"])
-        self.assertEqual("", prefix, "Runner prefix not correct for user")
-
-    def test_ignores_extra_experiments(self) -> None:
-        settings_text = """
-        experiments:
-            lf:
-                rollout_perc: 0
-            otherExp:
-                rollout_perc: 0
-            foo:
-                rollout_perc: 0
-        ---
-
-        Users:
-        @User1,lf,otherExp,foo
-
-        """
-
-        prefix = rd.get_runner_prefix(settings_text, ["User1"])
-        self.assertEqual("lf.otherExp.", prefix, "Runner prefix not correct for user")
-
-
-if __name__ == "__main__":
-    main()

.github/scripts/trymerge.py

@@ -36,7 +36,6 @@ from warnings import warn
 
 import yaml
 from github_utils import (
-    gh_close_pr,
     gh_fetch_json_list,
     gh_fetch_merge_base,
     gh_fetch_url,
@@ -1175,11 +1174,11 @@ class GitHubPR:
             for pr in additional_merged_prs:
                 pr.add_numbered_label(MERGE_COMPLETE_LABEL, dry_run)
 
-        # When the merge process reaches this part, we can assume that the commit
-        # has been successfully pushed to trunk
-        merge_commit_sha = repo.rev_parse(name=self.default_branch())
-
         if comment_id and self.pr_num:
+            # When the merge process reaches this part, we can assume that the commit
+            # has been successfully pushed to trunk
+            merge_commit_sha = repo.rev_parse(name=REMOTE_MAIN_BRANCH)
+
             # Finally, upload the record to Rockset. The list of pending and failed
             # checks are at the time of the merge
             save_merge_record(
@@ -1204,17 +1203,6 @@ class GitHubPR:
         else:
             print("Missing comment ID or PR number, couldn't upload to Rockset")
 
-        # Usually Github will see that the commit has "resolves <pr_num>" in the
-        # commit message and close the PR, but sometimes it doesn't, leading to
-        # confusion.  When it doesn't, we close it manually.
-        time.sleep(60)  # Give Github some time to close the PR
-        manually_close_merged_pr(
-            pr=self,
-            additional_merged_prs=additional_merged_prs,
-            merge_commit_sha=merge_commit_sha,
-            dry_run=dry_run,
-        )
-
     def merge_changes(
         self,
         repo: GitRepo,
@@ -1515,34 +1503,6 @@ def checks_to_markdown_bullets(
     ]
 
 
-def manually_close_merged_pr(
-    pr: GitHubPR,
-    additional_merged_prs: List[GitHubPR],
-    merge_commit_sha: str,
-    dry_run: bool,
-) -> None:
-    def _comment_and_close(pr: GitHubPR, comment: str) -> None:
-        pr = GitHubPR(pr.org, pr.project, pr.pr_num)  # Refresh the PR
-        if not pr.is_closed():
-            gh_post_pr_comment(pr.org, pr.project, pr.pr_num, comment, dry_run)
-            gh_close_pr(pr.org, pr.project, pr.pr_num, dry_run)
-
-    message = (
-        f"This PR (#{pr.pr_num}) was merged in {merge_commit_sha} but it is still open, likely due to a Github bug, "
-        "so mergebot is closing it manually.  If you think this is a mistake, please feel free to reopen and contact Dev Infra."
-    )
-    _comment_and_close(pr, message)
-    for additional_pr in additional_merged_prs:
-        message = (
-            f"This PR (#{additional_pr.pr_num}) was merged as part of PR #{pr.pr_num} in the stack under {merge_commit_sha} "
-            "but it is still open, likely due to a Github bug, so mergebot is closing it manually. "
-            "If you think this is a mistake, please feel free to reopen and contact Dev Infra."
-        )
-        _comment_and_close(additional_pr, message)
-
-    print(f"PR {pr.pr_num} and all additional PRs in the stack have been closed.")
-
-
 @retries_decorator()
 def save_merge_record(
     comment_id: int,

.github/templates/common.yml.j2

@@ -1,7 +1,7 @@
 {%- set upload_artifact_s3_action = "seemethere/upload-artifact-s3@v5" -%}
 {%- set download_artifact_s3_action = "seemethere/download-artifact-s3@v4" -%}
-{%- set upload_artifact_action = "actions/upload-artifact@v4.4.0" -%}
+{%- set upload_artifact_action = "actions/upload-artifact@v3" -%}
-{%- set download_artifact_action = "actions/download-artifact@v4.1.7" -%}
+{%- set download_artifact_action = "actions/download-artifact@v3" -%}
 
 {%- set timeout_minutes = 240 -%}
 

.github/templates/macos_binary_build_workflow.yml.j2

@@ -101,7 +101,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: !{{ config["build_name"] }}

.github/templates/upload.yml.j2

@@ -45,7 +45,7 @@
   {%- if is_windows %}
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
   {%- endif %}
 
 {%- else %}

.github/templates/windows_binary_build_workflow.yml.j2

@@ -104,9 +104,9 @@ jobs:
       - get-label-type
 {%- if config["gpu_arch_type"] == "cuda" %}
 {%- if branches == "nightly" %}
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
 {%- else %}
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge.nonephemeral"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu.nonephemeral"
 {%- endif %}
 {%- else %}
     runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.4xlarge.nonephemeral"

.github/workflows/_binary-build-linux.yml

@@ -283,7 +283,7 @@ jobs:
           # Ensure the working directory gets chowned back to the current user
           docker run --rm -v "${RUNNER_TEMP}/artifacts:/v" -w /v "${ALPINE_IMAGE}" chown -R "$(id -u):$(id -g)" .
 
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' }}
         with:
           name: ${{ inputs.build_name }}

.github/workflows/_binary-test-linux.yml

@@ -210,7 +210,7 @@ jobs:
 
       - name: Download Build Artifacts
         if: ${{ steps.filter.outputs.is-test-matrix-empty == 'False' }}
-        uses: actions/download-artifact@v4.1.7
+        uses: actions/download-artifact@v3
         with:
           name: ${{ inputs.build_name }}
           path: "${{ runner.temp }}/artifacts/"

.github/workflows/_binary-upload.yml

@@ -126,7 +126,7 @@ jobs:
         # NB: When the previous build job is skipped, there won't be any artifacts and
         # this step will fail. Binary build jobs can only be skipped on CI, not nightly
         continue-on-error: true
-        uses: actions/download-artifact@v4.1.7
+        uses: actions/download-artifact@v3
         with:
           name: ${{ inputs.build_name }}
           path: "${{ runner.temp }}/artifacts/"

.github/workflows/_ios-build-test.yml

@@ -292,7 +292,7 @@ jobs:
           bundler-cache: true
 
       - name: Download arm64 artifacts
-        uses: actions/download-artifact@v4.1.7
+        uses: actions/download-artifact@v3
         with:
           name: pytorch-ios-build-artifacts-arm64
 

.github/workflows/_linux-build.yml

@@ -109,7 +109,6 @@ jobs:
     steps:
       - name: Setup SSH (Click me for login details)
         uses: pytorch/test-infra/.github/actions/setup-ssh@main
-        if: inputs.build-environment != 'linux-s390x-binary-manywheel'
         with:
           github-secret: ${{ secrets.GITHUB_TOKEN }}
 
@@ -119,16 +118,13 @@ jobs:
       # checkout. In other cases you should prefer a local checkout.
       - name: Checkout PyTorch
         uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
-        with:
-          no-sudo: ${{ inputs.build-environment == 'linux-s390x-binary-manywheel' }}
 
       - name: Setup Linux
         uses: ./.github/actions/setup-linux
-        if: inputs.build-environment != 'linux-s390x-binary-manywheel'
 
       - name: configure aws credentials
         uses: aws-actions/configure-aws-credentials@v3
-        if: ${{ inputs.aws-role-to-assume != '' && inputs.build-environment != 'linux-s390x-binary-manywheel' }}
+        if: ${{ inputs.aws-role-to-assume != '' }}
         with:
           role-to-assume: ${{ inputs.aws-role-to-assume }}
           role-session-name: gha-linux-build
@@ -137,13 +133,11 @@ jobs:
       - name: Calculate docker image
         id: calculate-docker-image
         uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
-        if: inputs.build-environment != 'linux-s390x-binary-manywheel'
         with:
           docker-image-name: ${{ inputs.docker-image-name }}
 
       - name: Use following to pull public copy of the image
         id: print-ghcr-mirror
-        if: inputs.build-environment != 'linux-s390x-binary-manywheel'
         env:
           ECR_DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
         shell: bash
@@ -153,7 +147,6 @@ jobs:
 
       - name: Pull docker image
         uses: pytorch/test-infra/.github/actions/pull-docker-image@main
-        if: inputs.build-environment != 'linux-s390x-binary-manywheel'
         with:
           docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
 
@@ -181,7 +174,6 @@ jobs:
       - name: Download pytest cache
         uses: ./.github/actions/pytest-cache-download
         continue-on-error: true
-        if: inputs.build-environment != 'linux-s390x-binary-manywheel'
         with:
           cache_dir: .pytest_cache
           job_identifier: ${{ github.workflow }}_${{ inputs.build-environment }}
@@ -203,7 +195,6 @@ jobs:
           PR_LABELS: ${{ toJson(github.event.pull_request.labels.*.name) }}
           TORCH_CUDA_ARCH_LIST: ${{ inputs.cuda-arch-list }}
           DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
-          DOCKER_IMAGE_S390X: ${{ inputs.docker-image-name }}
           XLA_CUDA: ${{ contains(inputs.build-environment, 'xla') && '0' || '' }}
           DEBUG: ${{ inputs.build-with-debug && '1' || '0' }}
           OUR_GITHUB_JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
@@ -211,21 +202,7 @@ jobs:
           SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.SCRIBE_GRAPHQL_ACCESS_TOKEN }}
           USE_SPLIT_BUILD: ${{ inputs.use_split_build }}
         run: |
-          if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then
-            JENKINS_USER=
-            USED_IMAGE="${DOCKER_IMAGE_S390X}"
-
-            # since some steps are skipped on s390x, if they are necessary, run them here
-            env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}"
-            env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}"
-          else
-            JENKINS_USER="--user jenkins"
-            USED_IMAGE="${DOCKER_IMAGE}"
-          fi
-
           # detached container should get cleaned up by teardown_ec2_linux
-          # Used for JENKINS_USER, which can be empty
-          # shellcheck disable=SC2086
           container_name=$(docker run \
             -e BUILD_ENVIRONMENT \
             -e MAX_JOBS="$(nproc --ignore=2)" \
@@ -248,10 +225,10 @@ jobs:
             --cap-add=SYS_PTRACE \
             --tty \
             --detach \
-            ${JENKINS_USER} \
+            --user jenkins \
             -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \
             -w /var/lib/jenkins/workspace \
-            "${USED_IMAGE}"
+            "${DOCKER_IMAGE}"
           )
           docker exec -t "${container_name}" sh -c '.ci/pytorch/build.sh'
 
@@ -262,7 +239,7 @@ jobs:
 
       - name: Store PyTorch Build Artifacts on S3
         uses: seemethere/upload-artifact-s3@v5
-        if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped' && !inputs.use_split_build && inputs.build-environment != 'linux-s390x-binary-manywheel'
+        if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped' && !inputs.use_split_build
         with:
           name: ${{ inputs.build-environment }}
           retention-days: 14
@@ -272,7 +249,7 @@ jobs:
 
       - name: Store PyTorch Build Artifacts on S3 for split build
         uses: seemethere/upload-artifact-s3@v5
-        if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped' && inputs.use_split_build && inputs.build-environment != 'linux-s390x-binary-manywheel'
+        if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped' && inputs.use_split_build
         with:
           name: ${{ inputs.build-environment }}-experimental-split-build
           retention-days: 14
@@ -280,26 +257,8 @@ jobs:
           path: artifacts.zip
           s3-bucket: ${{ inputs.s3-bucket }}
 
-      - name: Store PyTorch Build Artifacts for s390x
-        uses: actions/upload-artifact@v3
-        if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped' && !inputs.use_split_build && inputs.build-environment == 'linux-s390x-binary-manywheel'
-        with:
-          name: ${{ inputs.build-environment }}
-          retention-days: 14
-          if-no-files-found: error
-          path: artifacts.zip
-
-      - name: Store PyTorch Build Artifacts for s390x for split build
-        uses: actions/upload-artifact@v3
-        if: inputs.build-generates-artifacts && steps.build.outcome != 'skipped' && inputs.use_split_build && inputs.build-environment == 'linux-s390x-binary-manywheel'
-        with:
-          name: ${{ inputs.build-environment }}-experimental-split-build
-          retention-days: 14
-          if-no-files-found: error
-          path: artifacts.zip
-
       - name: Upload sccache stats
-        if: steps.build.outcome != 'skipped' && inputs.build-environment != 'linux-s390x-binary-manywheel'
+        if: steps.build.outcome != 'skipped'
         uses: seemethere/upload-artifact-s3@v5
         with:
           s3-prefix: |
@@ -311,13 +270,4 @@ jobs:
 
       - name: Teardown Linux
         uses: pytorch/test-infra/.github/actions/teardown-linux@main
-        if: always() && inputs.build-environment != 'linux-s390x-binary-manywheel'
+        if: always()
-
-      - 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

.github/workflows/_mac-test-mps.yml

@@ -88,13 +88,6 @@ jobs:
           environment-file: .github/requirements/conda-env-${{ runner.os }}-${{ runner.arch }}
           pip-requirements-file: .github/requirements/pip-requirements-${{ runner.os }}.txt
 
-      - name: Get workflow job id
-        id: get-job-id
-        uses: ./.github/actions/get-workflow-job-id
-        if: always()
-        with:
-          github-token: ${{ secrets.GITHUB_TOKEN }}
-
       - name: Install PyTorch and run MPS tests
         id: test
         env:
@@ -110,14 +103,6 @@ jobs:
           NO_TEST_TIMEOUT: ${{ needs.filter.outputs.ci-no-test-timeout }}
           NO_TD: ${{ needs.filter.outputs.ci-no-td }}
           PIP_REQUIREMENTS_FILE: .github/requirements/pip-requirements-${{ runner.os }}.txt
-          GITHUB_REPOSITORY: ${{ github.repository }}
-          GITHUB_WORKFLOW: ${{ github.workflow }}
-          GITHUB_JOB: ${{ github.job }}
-          GITHUB_RUN_ID: ${{ github.run_id }}
-          GITHUB_RUN_NUMBER: ${{ github.run_number }}
-          GITHUB_RUN_ATTEMPT: ${{ github.run_attempt }}
-          JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
-          JOB_NAME: ${{ steps.get-job-id.outputs.job-name }}
           REENABLED_ISSUES: ${{ needs.filter.outputs.reenabled-issues }}
         run: |
           # shellcheck disable=SC1090
@@ -159,6 +144,13 @@ jobs:
         run: |
           cat test/**/*_toprint.log || true
 
+      - name: Get workflow job id
+        id: get-job-id
+        uses: ./.github/actions/get-workflow-job-id
+        if: always()
+        with:
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+
       - name: Upload test artifacts
         uses: ./.github/actions/upload-test-artifacts
         if: always() && steps.test.conclusion && steps.test.conclusion != 'skipped'

.github/workflows/_runner-determinator.yml

@@ -62,94 +62,49 @@ jobs:
           """
           This runner determinator is used to determine which set of runners to run a
           GitHub job on. It uses the first comment of a GitHub issue (by default
-          https://github.com/pytorch/test-infra/issues/5132) to define the configuration
+          https://github.com/pytorch/test-infra/issues/5132) as a user list to determine
-          of which runners should be used to run which job.
+          which users will get their jobs to run on experimental runners. This user list
-
+          is also a comma separated list of additional features or experiments which the
-          The configuration has two parts, the settings and a list of opted-in users,
+          user could be opted in to.
-          separated by a line containing "---".  If the line is not present, the
-          settings are considered to be empty with only the second part, the user
-          list, defined.
-
-          The first part is a YAML block that defines the rollout settings. This can be
-          used to define any settings that are needed to determine which runners to use.
-          It's fields are defined by the RolloutSettings class below.
-
-          The second part is a list of users who are explicitly opted in to the LF fleet.
-          The user list is also a comma separated list of additional features or
-          experiments which the user could be opted in to.
 
           The user list has the following rules:
 
-          - Users are GitHub usernames, which must start with the @ prefix
+          - Users are GitHub usernames with the @ prefix
+          - If the first line is a "*" then all users will use the new runners
+          - If the first line is a "!" then all users will use the old runners
           - Each user is also a comma-separated list of features/experiments to enable
-          - A "#" prefix opts the user out of all experiments
+          - A "#" prefix indicates the user is opted out of the new runners but is opting
+            into features/experiments.
 
-          Example config:
+          Example user list:
-              # A list of experiments that can be opted into.
-              # This defines the behavior they'll induce when opted into.
-              # Expected syntax is:
-              #   [experiment_name]: # Name of the experiment. Also used for the label prefix.
-              #      rollout_perc: [int] # % of workflows to run with this experiment when users are not opted in.
 
-              experiments:
+              @User1
-                lf:
+              @User2,amz2023
-                  rollout_percent: 25
+              #@UserOptOutOfNewRunner,amz2023
-
-              ---
-
-              # Opt-ins:
-              # Users can opt into the LF fleet by adding their GitHub username to this list
-              # and specifying experiments to enable in a comma-separated list.
-              # Experiments should be from the above list.
-
-              @User1,lf,split_build
-              @User2,lf
-              @User3,split_build
           """
 
           import logging
           import os
-          import random
           from argparse import ArgumentParser
           from logging import LogRecord
-          from typing import Any, Dict, Iterable, List, NamedTuple, Tuple
+          from typing import Any, Iterable
 
-          import yaml
           from github import Auth, Github
           from github.Issue import Issue
 
 
-          DEFAULT_LABEL_PREFIX = ""  # use meta runners
+          WORKFLOW_LABEL_META = ""  # use meta runners
           WORKFLOW_LABEL_LF = "lf."  # use runners from the linux foundation
           WORKFLOW_LABEL_LF_CANARY = "lf.c."  # use canary runners from the linux foundation
 
+          RUNNER_AMI_LEGACY = ""
+          RUNNER_AMI_AMZ2023 = "amz2023"
+
           GITHUB_OUTPUT = os.getenv("GITHUB_OUTPUT", "")
           GH_OUTPUT_KEY_AMI = "runner-ami"
           GH_OUTPUT_KEY_LABEL_TYPE = "label-type"
 
 
-          SETTING_EXPERIMENTS = "experiments"
-
-          LF_FLEET_EXPERIMENT = "lf"
-          CANARY_FLEET_SUFFIX = ".c"
-
-
-          class Experiment(NamedTuple):
-              rollout_perc: float = (
-                  0  # Percentage of workflows to experiment on when user is not opted-in.
-              )
-
-              # Add more fields as needed
-
-
-          class Settings(NamedTuple):
-              """
-              Settings for the experiments that can be opted into.
-              """
-
-              experiments: Dict[str, Experiment] = {}
-
-
           class ColorFormatter(logging.Formatter):
               """Color codes the log messages based on the log level"""
 
@@ -241,14 +196,11 @@ jobs:
 
 
           def get_potential_pr_author(
-              github_token: str, repo: str, username: str, ref_type: str, ref_name: str
+              gh: Github, repo: str, username: str, ref_type: str, ref_name: str
           ) -> str:
               # If the trigger was a new tag added by a bot, this is a ciflow case
               # Fetch the actual username from the original PR. The PR number is
               # embedded in the tag name: ciflow/<name>/<pr-number>
-
-              gh = get_gh_client(github_token)
-
               if username == "pytorch-bot[bot]" and ref_type == "tag":
                   split_tag = ref_name.split("/")
                   if (
@@ -270,238 +222,130 @@ jobs:
 
 
           def is_exception_branch(branch: str) -> bool:
-              """
-              Branches that get opted out of all experiments and should always use Meta runners
-              """
               return branch.split("/")[0] in {"main", "nightly", "release", "landchecks"}
 
 
-          def load_yaml(yaml_text: str) -> Any:
+          def get_workflow_type(issue: Issue, workflow_requestors: Iterable[str]) -> str:
               try:
-                  data = yaml.safe_load(yaml_text)
+                  first_comment = issue.get_comments()[0].body.strip("\n\t ")
-                  return data
-              except yaml.YAMLError as exc:
-                  log.exception("Error loading YAML")
-                  raise
 
-
+                  if first_comment[0] == "!":
-          def extract_settings_user_opt_in_from_text(rollout_state: str) -> Tuple[str, str]:
+                      log.info("LF Workflows are disabled for everyone. Using meta runners.")
-              """
+                      return WORKFLOW_LABEL_META
-              Extracts the text with settings, if any, and the opted in users from the rollout state.
+                  elif first_comment[0] == "*":
-
+                      log.info("LF Workflows are enabled for everyone. Using LF runners.")
-              If the issue body contains "---" then the text above that is the settings
+                      return WORKFLOW_LABEL_LF
-              and the text below is the list of opted in users.
+                  else:
-
+                      all_opted_in_users = {
-              If it doesn't contain "---" then the settings are empty and the rest is the users.
+                          usr_raw.strip("\n\t@ ").split(",")[0]
-              """
+                          for usr_raw in first_comment.split()
-              rollout_state_parts = rollout_state.split("---")
+                      }
-              if len(rollout_state_parts) >= 2:
+                      opted_in_requestors = {
-                  return rollout_state_parts[0], rollout_state_parts[1]
+                          usr for usr in workflow_requestors if usr in all_opted_in_users
-              else:
+                      }
-                  return "", rollout_state
+                      if opted_in_requestors:
-
-
-          class UserOptins(Dict[str, List[str]]):
-              """
-              Dictionary of users with a list of features they have opted into
-              """
-
-
-          def parse_user_opt_in_from_text(user_optin_text: str) -> UserOptins:
-              """
-              Parse the user opt-in text into a key value pair of username and the list of features they have opted into
-
-              Users are GitHub usernames with the @ prefix. Each user is also a comma-separated list of features/experiments to enable.
-                  - Example line: "@User1,lf,split_build"
-                  - A "#" prefix indicates the user is opted out of all experiments
-
-
-              """
-              optins = UserOptins()
-              for user in user_optin_text.split("\n"):
-                  user = user.strip("\r\n\t -")
-                  if not user or not user.startswith("@"):
-                      # Not a valid user. Skip
-                      continue
-
-                  if user:
-                      usr_name = user.split(",")[0].strip("@")
-                      optins[usr_name] = [exp.strip(" ") for exp in user.split(",")[1:]]
-
-              return optins
-
-
-          def parse_settings_from_text(settings_text: str) -> Settings:
-              """
-              Parse the experiments from the issue body into a list of ExperimentSettings
-              """
-              try:
-                  if settings_text:
-                      # Escape the backtick as well so that we can have the settings in a code block on the GH issue
-                      # for easy reading
-                      # Note: Using ascii for the backtick so that the cat step in _runner-determinator.yml doesn't choke on
-                      #       the backtick character in shell commands.
-                      backtick = chr(96)  # backtick character
-                      settings_text = settings_text.strip(f"\r\n\t{backtick} ")
-                      settings = load_yaml(settings_text)
-
-                      # For now we just load experiments. We can expand this if/when we add more settings
-                      experiments = {}
-
-                      for exp_name, exp_settings in settings.get(SETTING_EXPERIMENTS).items():
-                          valid_settings = {}
-                          for setting in exp_settings:
-                              if setting not in Experiment._fields:
-                                  log.warning(
-                                      f"Unexpected setting in experiment: {setting} = {exp_settings[setting]}"
-                                  )
-                              else:
-                                  valid_settings[setting] = exp_settings[setting]
-
-                          experiments[exp_name] = Experiment(**valid_settings)
-                      return Settings(experiments)
-
-              except Exception:
-                  log.exception("Failed to parse settings")
-
-              return Settings()
-
-
-          def parse_settings(rollout_state: str) -> Settings:
-              """
-              Parse settings, if any, from the rollout state.
-
-              If the issue body contains "---" then the text above that is the settings
-              and the text below is the list of opted in users.
-
-              If it doesn't contain "---" then the settings are empty and the default values are used.
-              """
-              settings_text, _ = extract_settings_user_opt_in_from_text(rollout_state)
-              return parse_settings_from_text(settings_text)
-
-
-          def parse_users(rollout_state: str) -> UserOptins:
-              """
-              Parse users from the rollout state.
-
-              """
-              _, users_text = extract_settings_user_opt_in_from_text(rollout_state)
-              return parse_user_opt_in_from_text(users_text)
-
-
-          def is_user_opted_in(user: str, user_optins: UserOptins, experiment_name: str) -> bool:
-              """
-              Check if a user is opted into an experiment
-              """
-              return experiment_name in user_optins.get(user, [])
-
-
-          def get_runner_prefix(
-              rollout_state: str, workflow_requestors: Iterable[str], is_canary: bool = False
-          ) -> str:
-              settings = parse_settings(rollout_state)
-              user_optins = parse_users(rollout_state)
-
-              fleet_prefix = ""
-              prefixes = []
-              for experiment_name, experiment_settings in settings.experiments.items():
-                  enabled = False
-
-                  # Is any workflow_requestor opted in to this experiment?
-                  opted_in_users = [
-                      requestor
-                      for requestor in workflow_requestors
-                      if is_user_opted_in(requestor, user_optins, experiment_name)
-                  ]
-
-                  if opted_in_users:
-                      log.info(
-                          f"{', '.join(opted_in_users)} have opted into experiment {experiment_name}."
-                      )
-                      enabled = True
-                  elif experiment_settings.rollout_perc:
-                      # If no user is opted in, then we randomly enable the experiment based on the rollout percentage
-                      if random.uniform(0, 100) <= experiment_settings.rollout_perc:
                           log.info(
-                              f"Based on rollout percentage of {experiment_settings.rollout_perc}%, enabling experiment {experiment_name}."
+                              f"LF Workflows are enabled for {', '.join(opted_in_requestors)}. Using LF runners."
                           )
-                          enabled = True
+                          return WORKFLOW_LABEL_LF
-
-                  if enabled:
-                      label = experiment_name
-                      if experiment_name == LF_FLEET_EXPERIMENT:
-                          # We give some special treatment to the "lf" experiment since determines the fleet we use
-                          #  - If it's enabled, then we always list it's prefix first
-                          #  - If we're in the canary branch, then we append ".c" to the lf prefix
-                          if is_canary:
-                              label += CANARY_FLEET_SUFFIX
-                          fleet_prefix = label
                       else:
-                          prefixes.append(label)
+                          log.info(
+                              f"LF Workflows are disabled for {', '.join(workflow_requestors)}. Using meta runners."
+                          )
+                          return WORKFLOW_LABEL_META
 
-              if len(prefixes) > 1:
+              except Exception as e:
                   log.error(
-                      f"Only a fleet and one other experiment can be enabled for a job at any time. Enabling {prefixes[0]} and ignoring the rest, which are {', '.join(prefixes[1:])}"
+                      f"Failed to get determine workflow type. Falling back to meta runners. Exception: {e}"
                   )
-                  prefixes = prefixes[:1]
+                  return WORKFLOW_LABEL_META
-
-              # Fleet always comes first
-              if fleet_prefix:
-                  prefixes.insert(0, fleet_prefix)
-
-              return ".".join(prefixes) + "." if prefixes else ""
 
 
-          def get_rollout_state_from_issue(github_token: str, repo: str, issue_num: int) -> str:
+          def get_optin_feature(
-              """
+              issue: Issue, workflow_requestors: Iterable[str], feature: str, fallback: str
-              Gets the first comment of the issue, which contains the desired rollout state.
+          ) -> str:
+              try:
+                  first_comment = issue.get_comments()[0].body.strip("\n\t ")
+                  userlist = {u.lstrip("#").strip("\n\t@ ") for u in first_comment.split()}
+                  all_opted_in_users = set()
+                  for user in userlist:
+                      for i in user.split(","):
+                          if i == feature:
+                              all_opted_in_users.add(user.split(",")[0])
+                  opted_in_requestors = {
+                      usr for usr in workflow_requestors if usr in all_opted_in_users
+                  }
 
-              The default issue we use - https://github.com/pytorch/test-infra/issues/5132
+                  if opted_in_requestors:
-              """
+                      log.info(
-              gh = get_gh_client(github_token)
+                          f"Feature {feature} is enabled for {', '.join(opted_in_requestors)}. Using feature {feature}."
-              issue = get_issue(gh, repo, issue_num)
+                      )
-              return str(issue.get_comments()[0].body.strip("\n\t "))
+                      return feature
+                  else:
+                      log.info(
+                          f"Feature {feature} is disabled for {', '.join(workflow_requestors)}. Using fallback \"{fallback}\"."
+                      )
+                      return fallback
+
+              except Exception as e:
+                  log.error(
+                      f'Failed to determine if user has opted-in to feature {feature}. Using fallback "{fallback}". Exception: {e}'
+                  )
+                  return fallback
 
 
           def main() -> None:
               args = parse_args()
 
               if args.github_ref_type == "branch" and is_exception_branch(args.github_branch):
-                  log.info(
+                  log.info(f"Exception branch: '{args.github_branch}', using meta runners")
-                      f"Exception branch: '{args.github_branch}', using Meta runners and no experiments."
+                  label_type = WORKFLOW_LABEL_META
-                  )
+                  runner_ami = RUNNER_AMI_LEGACY
-                  runner_label_prefix = DEFAULT_LABEL_PREFIX
               else:
                   try:
-                      rollout_state = get_rollout_state_from_issue(
+                      gh = get_gh_client(args.github_token)
-                          args.github_token, args.github_issue_repo, args.github_issue
+                      # The default issue we use - https://github.com/pytorch/test-infra/issues/5132
-                      )
+                      issue = get_issue(gh, args.github_issue_repo, args.github_issue)
-
                       username = get_potential_pr_author(
-                          args.github_token,
+                          gh,
                           args.github_repo,
                           args.github_actor,
                           args.github_ref_type,
                           args.github_branch,
                       )
-
+                      label_type = get_workflow_type(
-                      is_canary = args.github_repo == "pytorch/pytorch-canary"
+                          issue,
-
+                          (
-                      runner_label_prefix = get_runner_prefix(
+                              args.github_issue_owner,
-                          rollout_state, (args.github_issue_owner, username), is_canary
+                              username,
+                          ),
+                      )
+                      runner_ami = get_optin_feature(
+                          issue=issue,
+                          workflow_requestors=(
+                              args.github_issue_owner,
+                              username,
+                          ),
+                          feature=RUNNER_AMI_AMZ2023,
+                          fallback=RUNNER_AMI_LEGACY,
                       )
-
                   except Exception as e:
                       log.error(
-                          f"Failed to get issue. Defaulting to Meta runners and no experiments. Exception: {e}"
+                          f"Failed to get issue. Falling back to meta runners. Exception: {e}"
                       )
+                      label_type = WORKFLOW_LABEL_META
+                      runner_ami = RUNNER_AMI_LEGACY
 
-              set_github_output(GH_OUTPUT_KEY_LABEL_TYPE, runner_label_prefix)
+              # For Canary builds use canary runners
+              if args.github_repo == "pytorch/pytorch-canary" and label_type == WORKFLOW_LABEL_LF:
+                  label_type = WORKFLOW_LABEL_LF_CANARY
+
+              set_github_output(GH_OUTPUT_KEY_LABEL_TYPE, label_type)
+              set_github_output(GH_OUTPUT_KEY_AMI, runner_ami)
 
 
           if __name__ == "__main__":
               main()
-
           EOF
 
           cat runner_determinator.py

.github/workflows/_win-build.yml

@@ -11,16 +11,6 @@ on:
         required: true
         type: string
         description: What CUDA version to build with, "cpu" for none.
-      use-xpu:
-        required: false
-        type: boolean
-        default: false
-        description: If set, build with XPU support.
-      vc-year:
-        required: false
-        type: string
-        default: "2019"
-        description: The Visual Studio year to use for building.
       build-with-debug:
         required: false
         type: boolean
@@ -151,7 +141,7 @@ jobs:
           SCCACHE_REGION: us-east-1
           VC_PRODUCT: "BuildTools"
           VC_VERSION: ""
-          VC_YEAR: "${{ inputs.vc-year }}"
+          VC_YEAR: "2019"
           ALPINE_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/tool/alpine"
           AWS_DEFAULT_REGION: us-east-1
           PR_NUMBER: ${{ github.event.pull_request.number }}
@@ -159,7 +149,6 @@ jobs:
           DEBUG: ${{ inputs.build-with-debug && '1' || '0' }}
           TORCH_CUDA_ARCH_LIST: "8.6"
           USE_CUDA: ${{ inputs.cuda-version != 'cpu' && '1' || '0' }}
-          USE_XPU: ${{ inputs.use-xpu == true && '1' || '0' }}
           OUR_GITHUB_JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
         run: |
           .ci/pytorch/win-build.sh

.github/workflows/build-conda-images.yml

@@ -32,7 +32,7 @@ concurrency:
 jobs:
   build-docker:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    runs-on: linux.9xlarge.ephemeral
+    runs-on: am2.linux.9xlarge.ephemeral
     strategy:
       matrix:
         cuda_version: ["11.8", "12.1", "12.4", "cpu"]

.github/workflows/build-libtorch-images.yml

@@ -29,19 +29,9 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   build-docker-cuda:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     strategy:
       matrix:
         cuda_version: ["12.4", "12.1", "11.8"]
@@ -76,8 +66,7 @@ jobs:
           .ci/docker/libtorch/build.sh libtorch-cxx11-builder:cuda${{matrix.cuda_version}}
   build-docker-rocm:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     strategy:
       matrix:
         rocm_version: ["6.1", "6.2"]
@@ -112,8 +101,7 @@ jobs:
           .ci/docker/libtorch/build.sh libtorch-cxx11-builder:rocm${{matrix.rocm_version}}
   build-docker-cpu:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     steps:
       - name: Checkout PyTorch
         uses: pytorch/pytorch/.github/actions/checkout-pytorch@main

.github/workflows/build-manywheel-images.yml

@@ -33,19 +33,9 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   build-docker-cuda:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: am2.linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     strategy:
       matrix:
         cuda_version: ["12.4", "12.1", "11.8"]
@@ -83,8 +73,7 @@ jobs:
   # NOTE: manylinux_2_28 are still experimental, see https://github.com/pytorch/pytorch/issues/123649
   build-docker-cuda-manylinux_2_28:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     strategy:
       matrix:
         cuda_version: ["12.4", "12.1", "11.8"]
@@ -121,8 +110,7 @@ jobs:
           .ci/docker/manywheel/build.sh manylinux2_28-builder:cuda${{matrix.cuda_version}}
   build-docker-cuda-aarch64:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.arm64.2xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.arm64.2xlarge.ephemeral"
     strategy:
       matrix:
         cuda_version: ["12.4"]
@@ -155,8 +143,7 @@ jobs:
           .ci/docker/manywheel/build.sh manylinuxaarch64-builder:cuda${{matrix.cuda_version}}
   build-docker-rocm:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: am2.linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     strategy:
       matrix:
         rocm_version: ["6.1", "6.2"]
@@ -191,8 +178,7 @@ jobs:
           .ci/docker/manywheel/build.sh manylinux-builder:rocm${{matrix.rocm_version}}
   build-docker-cpu:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: am2.linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     steps:
       - name: Checkout PyTorch
         uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
@@ -221,8 +207,7 @@ jobs:
           .ci/docker/manywheel/build.sh manylinux-builder:cpu
   build-docker-cpu-manylinux_2_28:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     env:
       GPU_ARCH_TYPE: cpu-manylinux_2_28
     steps:
@@ -253,8 +238,7 @@ jobs:
           .ci/docker/manywheel/build.sh manylinux2_28-builder:cpu
   build-docker-cpu-aarch64:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.arm64.2xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.arm64.2xlarge.ephemeral"
     env:
       GPU_ARCH_TYPE: cpu-aarch64
     steps:
@@ -285,8 +269,7 @@ jobs:
           .ci/docker/manywheel/build.sh manylinuxaarch64-builder:cpu-aarch64
   build-docker-cpu-aarch64-2_28:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.arm64.2xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.arm64.2xlarge.ephemeral"
     env:
       GPU_ARCH_TYPE: cpu-aarch64-2_28
     steps:
@@ -320,8 +303,7 @@ jobs:
           .ci/docker/manywheel/build.sh manylinux2_28_aarch64-builder:cpu-aarch64
   build-docker-cpu-cxx11-abi:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     env:
       GPU_ARCH_TYPE: cpu-cxx11-abi
     steps:
@@ -352,8 +334,7 @@ jobs:
           .ci/docker/manywheel/build.sh manylinuxcxx11-abi-builder:cpu-cxx11-abi
   build-docker-xpu:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
+    runs-on: linux.9xlarge.ephemeral
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
     env:
       GPU_ARCH_TYPE: xpu
     steps:

.github/workflows/build-triton-wheel.yml

@@ -13,6 +13,7 @@ on:
       - .github/scripts/build_triton_wheel.py
       - .github/ci_commit_pins/triton.txt
       - .ci/docker/ci_commit_pins/triton.txt
+      - .ci/docker/ci_commit_pins/triton-rocm.txt
       - .ci/docker/ci_commit_pins/triton-xpu.txt
   pull_request:
     paths:
@@ -20,6 +21,7 @@ on:
       - .github/scripts/build_triton_wheel.py
       - .github/ci_commit_pins/triton.txt
       - .ci/docker/ci_commit_pins/triton.txt
+      - .ci/docker/ci_commit_pins/triton-rocm.txt
       - .ci/docker/ci_commit_pins/triton-xpu.txt
 
 concurrency:
@@ -27,19 +29,9 @@ concurrency:
   cancel-in-progress: true
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   build-wheel:
     name: "Build Triton Wheel"
-    needs: get-label-type
+    runs-on: [self-hosted, linux.2xlarge]
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.4xlarge"
     strategy:
       fail-fast: false
       matrix:
@@ -128,7 +120,7 @@ jobs:
           fi
           docker exec -t "${container_name}" chown -R 1000.1000 /artifacts
 
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         with:
           name: pytorch-triton-wheel-${{ matrix.py_vers }}-${{ matrix.device }}
           if-no-files-found: error
@@ -165,7 +157,7 @@ jobs:
           aws-region: us-east-1
 
       - name: Download Build Artifacts
-        uses: actions/download-artifact@v4.1.7
+        uses: actions/download-artifact@v3
         with:
           # Download all available artifacts
           path: ${{ runner.temp }}/artifacts-all
@@ -209,8 +201,7 @@ jobs:
 
   build-conda:
     name: "Build Triton Conda"
-    needs: get-label-type
+    runs-on: [self-hosted, linux.2xlarge]
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
     strategy:
       fail-fast: false
       matrix:
@@ -262,7 +253,7 @@ jobs:
           docker exec -t "${container_name}" python /pytorch/.github/scripts/build_triton_wheel.py --build-conda --py-version="${PY_VERS}" $RELEASE
           docker exec -t "${container_name}" chown -R 1000.1000 /artifacts
 
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         with:
           name: pytorch-triton-conda-${{ matrix.py_vers }}
           if-no-files-found: error
@@ -282,7 +273,7 @@ jobs:
       - uses: actions/checkout@v3
 
       - name: Download Build Artifacts
-        uses: actions/download-artifact@v4.1.7
+        uses: actions/download-artifact@v3
         with:
           # Download all available artifacts
           path: ${{ runner.temp }}/artifacts-all

.github/workflows/check-labels.yml

@@ -30,9 +30,6 @@ concurrency:
 
 jobs:
   check-labels:
-    permissions:
-      contents: read
-      pull-requests: write
     name: Check labels
     if: github.repository_owner == 'pytorch'
     runs-on: linux.20_04.4x

.github/workflows/create_release.yml

@@ -16,15 +16,6 @@ on:
     paths: [.github/workflows/create_release.yml]
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   release:
     if: ${{ github.repository == 'pytorch/pytorch' }}
     name: Create Release
@@ -72,7 +63,7 @@ jobs:
           files: ${{env.PT_RELEASE_FILE}}
       - name: Upload source distribution to GHA artifacts for release tags
         if: ${{ github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && contains(github.ref, 'rc') }}
-        uses: actions/upload-artifact@v4.4.0
+        uses: actions/upload-artifact@v2
         with:
           name: ${{ env.PT_RELEASE_FILE }}
           path: ${{ env.PT_RELEASE_FILE }}
@@ -82,16 +73,14 @@ jobs:
 
   upload_source_code_to_s3:
     if: ${{ github.repository == 'pytorch/pytorch' && github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') && contains(github.ref, 'rc') }}
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
+    runs-on: linux.2xlarge
     environment: sourcecode-upload
     name: Upload source code to S3 for release tags
     permissions:
       id-token: write
-    needs:
+    needs: release
-      - get-label-type
-      - release
     steps:
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v2
         with:
           name: ${{ needs.release.outputs.pt_release_name }}
       - name: Configure AWS credentials(PyTorch account)

.github/workflows/docker-builds.yml

@@ -30,18 +30,8 @@ env:
 permissions: read-all
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   docker-build:
     environment: ${{ (github.ref == 'refs/heads/main' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
-    needs: get-label-type
     timeout-minutes: 240
     strategy:
       fail-fast: false
@@ -55,15 +45,15 @@ jobs:
           pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks,
           pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks,
           pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9,
-          pytorch-linux-focal-py3.9-clang10,
+          pytorch-linux-focal-py3.8-clang10,
           pytorch-linux-focal-py3.11-clang10,
           pytorch-linux-focal-py3.12-clang10,
           pytorch-linux-focal-rocm-n-1-py3,
           pytorch-linux-focal-rocm-n-py3,
-          pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-clang12,
+          pytorch-linux-jammy-cuda11.8-cudnn9-py3.8-clang12,
           pytorch-linux-focal-py3-clang9-android-ndk-r21e,
-          pytorch-linux-jammy-py3.9-gcc11,
+          pytorch-linux-jammy-py3.8-gcc11,
-          pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks,
+          pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks,
           pytorch-linux-jammy-py3.12-halide,
           pytorch-linux-jammy-xpu-2024.0-py3,
           pytorch-linux-jammy-py3-clang15-asan,
@@ -78,7 +68,7 @@ jobs:
           - docker-image-name: pytorch-linux-jammy-aarch64-py3.10-gcc11-inductor-benchmarks
             runner: linux.arm64.m7g.4xlarge
             timeout-minutes: 600
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}${{ matrix.runner }}"
+    runs-on: [self-hosted, "${{ matrix.runner }}"]
     env:
       DOCKER_IMAGE_BASE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/${{ matrix.docker-image-name }}
     steps:

.github/workflows/docker-release.yml

@@ -34,19 +34,9 @@ env:
 permissions: read-all
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   generate-matrix:
     if: github.repository_owner == 'pytorch'
-    needs: get-label-type
+    runs-on: [self-hosted, linux.large]
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.large"
     outputs:
       matrix: ${{ steps.generate-matrix.outputs.matrix }}
     steps:
@@ -64,12 +54,10 @@ jobs:
 
   build:
     if: ${{ github.repository == 'pytorch/pytorch' }}
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.2xlarge"
+    runs-on: [self-hosted, linux.2xlarge]
     environment: ${{ (github.ref == 'refs/heads/nightly' || startsWith(github.event.ref, 'refs/tags/v')) && 'docker-build' || '' }}
     timeout-minutes: 240
-    needs:
+    needs: generate-matrix
-      - generate-matrix
-      - get-label-type
     strategy:
       matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix) }}
       fail-fast: false

.github/workflows/generated-linux-aarch64-binary-manywheel-nightly.yml

@@ -58,7 +58,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       runs_on: linux.arm64.m7g.4xlarge.ephemeral
       ALPINE_IMAGE: "arm64v8/alpine"
@@ -82,7 +81,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       build_name: manywheel-py3_9-cpu-aarch64
       build_environment: linux-aarch64-binary-manywheel
@@ -105,7 +103,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       build_name: manywheel-py3_9-cpu-aarch64
     secrets:
@@ -128,7 +125,6 @@ jobs:
       GPU_ARCH_TYPE: cuda-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
       DESIRED_DEVTOOLSET: cxx11-abi
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       runs_on: linux.arm64.m7g.4xlarge.ephemeral
       ALPINE_IMAGE: "arm64v8/alpine"
@@ -153,7 +149,6 @@ jobs:
       GPU_ARCH_TYPE: cuda-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
       DESIRED_DEVTOOLSET: cxx11-abi
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       build_name: manywheel-py3_9-cuda-aarch64
     secrets:
@@ -175,7 +170,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.10"
       runs_on: linux.arm64.m7g.4xlarge.ephemeral
       ALPINE_IMAGE: "arm64v8/alpine"
@@ -199,7 +193,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.10"
       build_name: manywheel-py3_10-cpu-aarch64
       build_environment: linux-aarch64-binary-manywheel
@@ -222,7 +215,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.10"
       build_name: manywheel-py3_10-cpu-aarch64
     secrets:
@@ -245,7 +237,6 @@ jobs:
       GPU_ARCH_TYPE: cuda-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
       DESIRED_DEVTOOLSET: cxx11-abi
-      use_split_build: False
       DESIRED_PYTHON: "3.10"
       runs_on: linux.arm64.m7g.4xlarge.ephemeral
       ALPINE_IMAGE: "arm64v8/alpine"
@@ -270,7 +261,6 @@ jobs:
       GPU_ARCH_TYPE: cuda-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
       DESIRED_DEVTOOLSET: cxx11-abi
-      use_split_build: False
       DESIRED_PYTHON: "3.10"
       build_name: manywheel-py3_10-cuda-aarch64
     secrets:
@@ -292,7 +282,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.11"
       runs_on: linux.arm64.m7g.4xlarge.ephemeral
       ALPINE_IMAGE: "arm64v8/alpine"
@@ -316,7 +305,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.11"
       build_name: manywheel-py3_11-cpu-aarch64
       build_environment: linux-aarch64-binary-manywheel
@@ -339,7 +327,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.11"
       build_name: manywheel-py3_11-cpu-aarch64
     secrets:
@@ -362,7 +349,6 @@ jobs:
       GPU_ARCH_TYPE: cuda-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
       DESIRED_DEVTOOLSET: cxx11-abi
-      use_split_build: False
       DESIRED_PYTHON: "3.11"
       runs_on: linux.arm64.m7g.4xlarge.ephemeral
       ALPINE_IMAGE: "arm64v8/alpine"
@@ -387,7 +373,6 @@ jobs:
       GPU_ARCH_TYPE: cuda-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
       DESIRED_DEVTOOLSET: cxx11-abi
-      use_split_build: False
       DESIRED_PYTHON: "3.11"
       build_name: manywheel-py3_11-cuda-aarch64
     secrets:
@@ -409,7 +394,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.12"
       runs_on: linux.arm64.m7g.4xlarge.ephemeral
       ALPINE_IMAGE: "arm64v8/alpine"
@@ -433,7 +417,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.12"
       build_name: manywheel-py3_12-cpu-aarch64
       build_environment: linux-aarch64-binary-manywheel
@@ -456,7 +439,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cpu-aarch64-main
-      use_split_build: False
       DESIRED_PYTHON: "3.12"
       build_name: manywheel-py3_12-cpu-aarch64
     secrets:
@@ -479,7 +461,6 @@ jobs:
       GPU_ARCH_TYPE: cuda-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
       DESIRED_DEVTOOLSET: cxx11-abi
-      use_split_build: False
       DESIRED_PYTHON: "3.12"
       runs_on: linux.arm64.m7g.4xlarge.ephemeral
       ALPINE_IMAGE: "arm64v8/alpine"
@@ -504,7 +485,6 @@ jobs:
       GPU_ARCH_TYPE: cuda-aarch64
       DOCKER_IMAGE: pytorch/manylinuxaarch64-builder:cuda12.4-main
       DESIRED_DEVTOOLSET: cxx11-abi
-      use_split_build: False
       DESIRED_PYTHON: "3.12"
       build_name: manywheel-py3_12-cuda-aarch64
     secrets:

.github/workflows/generated-linux-binary-libtorch-cxx11-abi-nightly.yml

@@ -366,7 +366,7 @@ jobs:
     steps:
       - name: Setup ROCm
         uses: ./.github/actions/setup-rocm
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-rocm6_1-shared-with-deps-cxx11-abi
@@ -476,7 +476,7 @@ jobs:
     steps:
       - name: Setup ROCm
         uses: ./.github/actions/setup-rocm
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-rocm6_2-shared-with-deps-cxx11-abi

.github/workflows/generated-linux-binary-libtorch-pre-cxx11-nightly.yml

@@ -366,7 +366,7 @@ jobs:
     steps:
       - name: Setup ROCm
         uses: ./.github/actions/setup-rocm
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-rocm6_1-shared-with-deps-pre-cxx11
@@ -476,7 +476,7 @@ jobs:
     steps:
       - name: Setup ROCm
         uses: ./.github/actions/setup-rocm
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-rocm6_2-shared-with-deps-pre-cxx11

.github/workflows/generated-linux-binary-manywheel-main.yml

@@ -54,7 +54,6 @@ jobs:
       GPU_ARCH_VERSION: 11.8
       GPU_ARCH_TYPE: cuda
       DOCKER_IMAGE: pytorch/manylinux-builder:cuda11.8-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       build_name: manywheel-py3_9-cuda11_8
@@ -78,7 +77,6 @@ jobs:
       GPU_ARCH_VERSION: 11.8
       GPU_ARCH_TYPE: cuda
       DOCKER_IMAGE: pytorch/manylinux-builder:cuda11.8-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       build_name: manywheel-py3_9-cuda11_8
       build_environment: linux-binary-manywheel
@@ -87,6 +85,53 @@ jobs:
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
 
+  manywheel-py3_9-cuda11_8-split-build:
+    if: ${{ github.repository_owner == 'pytorch' }}
+    uses: ./.github/workflows/_binary-build-linux.yml
+    needs: get-label-type
+    with:
+      PYTORCH_ROOT: /pytorch
+      BUILDER_ROOT: /builder
+      PACKAGE_TYPE: manywheel
+      # TODO: This is a legacy variable that we eventually want to get rid of in
+      #       favor of GPU_ARCH_VERSION
+      DESIRED_CUDA: cu118
+      GPU_ARCH_VERSION: 11.8
+      GPU_ARCH_TYPE: cuda
+      DOCKER_IMAGE: pytorch/manylinux-builder:cuda11.8-main
+      use_split_build: True
+      DESIRED_PYTHON: "3.9"
+      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
+      build_name: manywheel-py3_9-cuda11_8-split
+      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==2.21.5; 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-split-test:  # Testing
+    if: ${{ github.repository_owner == 'pytorch' }}
+    needs:
+      - manywheel-py3_9-cuda11_8-split-build
+      - get-label-type
+    uses: ./.github/workflows/_binary-test-linux.yml
+    with:
+      PYTORCH_ROOT: /pytorch
+      BUILDER_ROOT: /builder
+      PACKAGE_TYPE: manywheel
+      # TODO: This is a legacy variable that we eventually want to get rid of in
+      #       favor of GPU_ARCH_VERSION
+      DESIRED_CUDA: cu118
+      GPU_ARCH_VERSION: 11.8
+      GPU_ARCH_TYPE: cuda
+      DOCKER_IMAGE: pytorch/manylinux-builder:cuda11.8-main
+      use_split_build: True
+      DESIRED_PYTHON: "3.9"
+      build_name: manywheel-py3_9-cuda11_8-split
+      build_environment: linux-binary-manywheel
+      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
+      runs_on: linux.4xlarge.nvidia.gpu
+    secrets:
+      github-token: ${{ secrets.GITHUB_TOKEN }}
+
   manywheel-py3_9-cuda12_1-build:
     if: ${{ github.repository_owner == 'pytorch' }}
     uses: ./.github/workflows/_binary-build-linux.yml
@@ -101,7 +146,6 @@ jobs:
       GPU_ARCH_VERSION: 12.1
       GPU_ARCH_TYPE: cuda
       DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.1-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       build_name: manywheel-py3_9-cuda12_1
@@ -125,7 +169,6 @@ jobs:
       GPU_ARCH_VERSION: 12.1
       GPU_ARCH_TYPE: cuda
       DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.1-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       build_name: manywheel-py3_9-cuda12_1
       build_environment: linux-binary-manywheel
@@ -134,6 +177,53 @@ jobs:
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
 
+  manywheel-py3_9-cuda12_1-split-build:
+    if: ${{ github.repository_owner == 'pytorch' }}
+    uses: ./.github/workflows/_binary-build-linux.yml
+    needs: get-label-type
+    with:
+      PYTORCH_ROOT: /pytorch
+      BUILDER_ROOT: /builder
+      PACKAGE_TYPE: manywheel
+      # TODO: This is a legacy variable that we eventually want to get rid of in
+      #       favor of GPU_ARCH_VERSION
+      DESIRED_CUDA: cu121
+      GPU_ARCH_VERSION: 12.1
+      GPU_ARCH_TYPE: cuda
+      DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.1-main
+      use_split_build: True
+      DESIRED_PYTHON: "3.9"
+      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
+      build_name: manywheel-py3_9-cuda12_1-split
+      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==2.21.5; 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-split-test:  # Testing
+    if: ${{ github.repository_owner == 'pytorch' }}
+    needs:
+      - manywheel-py3_9-cuda12_1-split-build
+      - get-label-type
+    uses: ./.github/workflows/_binary-test-linux.yml
+    with:
+      PYTORCH_ROOT: /pytorch
+      BUILDER_ROOT: /builder
+      PACKAGE_TYPE: manywheel
+      # TODO: This is a legacy variable that we eventually want to get rid of in
+      #       favor of GPU_ARCH_VERSION
+      DESIRED_CUDA: cu121
+      GPU_ARCH_VERSION: 12.1
+      GPU_ARCH_TYPE: cuda
+      DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.1-main
+      use_split_build: True
+      DESIRED_PYTHON: "3.9"
+      build_name: manywheel-py3_9-cuda12_1-split
+      build_environment: linux-binary-manywheel
+      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
+      runs_on: linux.4xlarge.nvidia.gpu
+    secrets:
+      github-token: ${{ secrets.GITHUB_TOKEN }}
+
   manywheel-py3_9-cuda12_4-build:
     if: ${{ github.repository_owner == 'pytorch' }}
     uses: ./.github/workflows/_binary-build-linux.yml
@@ -148,7 +238,6 @@ jobs:
       GPU_ARCH_VERSION: 12.4
       GPU_ARCH_TYPE: cuda
       DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       build_name: manywheel-py3_9-cuda12_4
@@ -172,7 +261,6 @@ jobs:
       GPU_ARCH_VERSION: 12.4
       GPU_ARCH_TYPE: cuda
       DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       build_name: manywheel-py3_9-cuda12_4
       build_environment: linux-binary-manywheel
@@ -180,3 +268,50 @@ jobs:
       runs_on: linux.4xlarge.nvidia.gpu
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
+
+  manywheel-py3_9-cuda12_4-split-build:
+    if: ${{ github.repository_owner == 'pytorch' }}
+    uses: ./.github/workflows/_binary-build-linux.yml
+    needs: get-label-type
+    with:
+      PYTORCH_ROOT: /pytorch
+      BUILDER_ROOT: /builder
+      PACKAGE_TYPE: manywheel
+      # TODO: This is a legacy variable that we eventually want to get rid of in
+      #       favor of GPU_ARCH_VERSION
+      DESIRED_CUDA: cu124
+      GPU_ARCH_VERSION: 12.4
+      GPU_ARCH_TYPE: cuda
+      DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
+      use_split_build: True
+      DESIRED_PYTHON: "3.9"
+      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
+      build_name: manywheel-py3_9-cuda12_4-split
+      build_environment: linux-binary-manywheel
+      PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.127; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.127; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.127; 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==12.4.5.8; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.1.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.147; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.1.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.1.170; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.127; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.127; platform_system == 'Linux' and platform_machine == 'x86_64'
+    secrets:
+      github-token: ${{ secrets.GITHUB_TOKEN }}
+  manywheel-py3_9-cuda12_4-split-test:  # Testing
+    if: ${{ github.repository_owner == 'pytorch' }}
+    needs:
+      - manywheel-py3_9-cuda12_4-split-build
+      - get-label-type
+    uses: ./.github/workflows/_binary-test-linux.yml
+    with:
+      PYTORCH_ROOT: /pytorch
+      BUILDER_ROOT: /builder
+      PACKAGE_TYPE: manywheel
+      # TODO: This is a legacy variable that we eventually want to get rid of in
+      #       favor of GPU_ARCH_VERSION
+      DESIRED_CUDA: cu124
+      GPU_ARCH_VERSION: 12.4
+      GPU_ARCH_TYPE: cuda
+      DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
+      use_split_build: True
+      DESIRED_PYTHON: "3.9"
+      build_name: manywheel-py3_9-cuda12_4-split
+      build_environment: linux-binary-manywheel
+      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
+      runs_on: linux.4xlarge.nvidia.gpu
+    secrets:
+      github-token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/generated-linux-binary-manywheel-split-main.yml

@@ -1,182 +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-binary-manywheel-split
-
-
-on:
-  push:
-    branches:
-      - main
-    tags:
-      - 'ciflow/periodic/*'
-  workflow_dispatch:
-
-env:
-  # Needed for conda builds
-  ALPINE_IMAGE: "308535385114.dkr.ecr.us-east-1.amazonaws.com/tool/alpine"
-  ANACONDA_USER: pytorch
-  AWS_DEFAULT_REGION: us-east-1
-  BINARY_ENV_FILE: /tmp/env
-  BUILD_ENVIRONMENT: linux-binary-manywheel-split
-  BUILDER_ROOT: /builder
-  GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-  PR_NUMBER: ${{ github.event.pull_request.number }}
-  PYTORCH_FINAL_PACKAGE_DIR: /artifacts
-  PYTORCH_ROOT: /pytorch
-  SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
-  SKIP_ALL_TESTS: 0
-concurrency:
-  group: linux-binary-manywheel-split-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}
-  cancel-in-progress: true
-
-jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-  manywheel-py3_9-cuda11_8-build:
-    if: ${{ github.repository_owner == 'pytorch' }}
-    uses: ./.github/workflows/_binary-build-linux.yml
-    needs: get-label-type
-    with:
-      PYTORCH_ROOT: /pytorch
-      BUILDER_ROOT: /builder
-      PACKAGE_TYPE: manywheel
-      # TODO: This is a legacy variable that we eventually want to get rid of in
-      #       favor of GPU_ARCH_VERSION
-      DESIRED_CUDA: cu118
-      GPU_ARCH_VERSION: 11.8
-      GPU_ARCH_TYPE: cuda
-      DOCKER_IMAGE: pytorch/manylinux-builder:cuda11.8-main
-      use_split_build: True
-      DESIRED_PYTHON: "3.9"
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
-      build_name: manywheel-py3_9-cuda11_8
-      build_environment: linux-binary-manywheel-split
-      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==2.21.5; 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
-    if: ${{ github.repository_owner == 'pytorch' }}
-    needs:
-      - manywheel-py3_9-cuda11_8-build
-      - get-label-type
-    uses: ./.github/workflows/_binary-test-linux.yml
-    with:
-      PYTORCH_ROOT: /pytorch
-      BUILDER_ROOT: /builder
-      PACKAGE_TYPE: manywheel
-      # TODO: This is a legacy variable that we eventually want to get rid of in
-      #       favor of GPU_ARCH_VERSION
-      DESIRED_CUDA: cu118
-      GPU_ARCH_VERSION: 11.8
-      GPU_ARCH_TYPE: cuda
-      DOCKER_IMAGE: pytorch/manylinux-builder:cuda11.8-main
-      use_split_build: True
-      DESIRED_PYTHON: "3.9"
-      build_name: manywheel-py3_9-cuda11_8
-      build_environment: linux-binary-manywheel-split
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
-      runs_on: linux.4xlarge.nvidia.gpu
-    secrets:
-      github-token: ${{ secrets.GITHUB_TOKEN }}
-
-  manywheel-py3_9-cuda12_1-build:
-    if: ${{ github.repository_owner == 'pytorch' }}
-    uses: ./.github/workflows/_binary-build-linux.yml
-    needs: get-label-type
-    with:
-      PYTORCH_ROOT: /pytorch
-      BUILDER_ROOT: /builder
-      PACKAGE_TYPE: manywheel
-      # TODO: This is a legacy variable that we eventually want to get rid of in
-      #       favor of GPU_ARCH_VERSION
-      DESIRED_CUDA: cu121
-      GPU_ARCH_VERSION: 12.1
-      GPU_ARCH_TYPE: cuda
-      DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.1-main
-      use_split_build: True
-      DESIRED_PYTHON: "3.9"
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
-      build_name: manywheel-py3_9-cuda12_1
-      build_environment: linux-binary-manywheel-split
-      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==2.21.5; 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
-    if: ${{ github.repository_owner == 'pytorch' }}
-    needs:
-      - manywheel-py3_9-cuda12_1-build
-      - get-label-type
-    uses: ./.github/workflows/_binary-test-linux.yml
-    with:
-      PYTORCH_ROOT: /pytorch
-      BUILDER_ROOT: /builder
-      PACKAGE_TYPE: manywheel
-      # TODO: This is a legacy variable that we eventually want to get rid of in
-      #       favor of GPU_ARCH_VERSION
-      DESIRED_CUDA: cu121
-      GPU_ARCH_VERSION: 12.1
-      GPU_ARCH_TYPE: cuda
-      DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.1-main
-      use_split_build: True
-      DESIRED_PYTHON: "3.9"
-      build_name: manywheel-py3_9-cuda12_1
-      build_environment: linux-binary-manywheel-split
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
-      runs_on: linux.4xlarge.nvidia.gpu
-    secrets:
-      github-token: ${{ secrets.GITHUB_TOKEN }}
-
-  manywheel-py3_9-cuda12_4-build:
-    if: ${{ github.repository_owner == 'pytorch' }}
-    uses: ./.github/workflows/_binary-build-linux.yml
-    needs: get-label-type
-    with:
-      PYTORCH_ROOT: /pytorch
-      BUILDER_ROOT: /builder
-      PACKAGE_TYPE: manywheel
-      # TODO: This is a legacy variable that we eventually want to get rid of in
-      #       favor of GPU_ARCH_VERSION
-      DESIRED_CUDA: cu124
-      GPU_ARCH_VERSION: 12.4
-      GPU_ARCH_TYPE: cuda
-      DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
-      use_split_build: True
-      DESIRED_PYTHON: "3.9"
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
-      build_name: manywheel-py3_9-cuda12_4
-      build_environment: linux-binary-manywheel-split
-      PYTORCH_EXTRA_INSTALL_REQUIREMENTS: nvidia-cuda-nvrtc-cu12==12.4.127; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-runtime-cu12==12.4.127; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cuda-cupti-cu12==12.4.127; 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==12.4.5.8; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cufft-cu12==11.2.1.3; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-curand-cu12==10.3.5.147; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusolver-cu12==11.6.1.9; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-cusparse-cu12==12.3.1.170; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nccl-cu12==2.21.5; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvtx-cu12==12.4.127; platform_system == 'Linux' and platform_machine == 'x86_64' | nvidia-nvjitlink-cu12==12.4.127; platform_system == 'Linux' and platform_machine == 'x86_64'
-    secrets:
-      github-token: ${{ secrets.GITHUB_TOKEN }}
-  manywheel-py3_9-cuda12_4-test:  # Testing
-    if: ${{ github.repository_owner == 'pytorch' }}
-    needs:
-      - manywheel-py3_9-cuda12_4-build
-      - get-label-type
-    uses: ./.github/workflows/_binary-test-linux.yml
-    with:
-      PYTORCH_ROOT: /pytorch
-      BUILDER_ROOT: /builder
-      PACKAGE_TYPE: manywheel
-      # TODO: This is a legacy variable that we eventually want to get rid of in
-      #       favor of GPU_ARCH_VERSION
-      DESIRED_CUDA: cu124
-      GPU_ARCH_VERSION: 12.4
-      GPU_ARCH_TYPE: cuda
-      DOCKER_IMAGE: pytorch/manylinux-builder:cuda12.4-main
-      use_split_build: True
-      DESIRED_PYTHON: "3.9"
-      build_name: manywheel-py3_9-cuda12_4
-      build_environment: linux-binary-manywheel-split
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
-      runs_on: linux.4xlarge.nvidia.gpu
-    secrets:
-      github-token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/generated-linux-s390x-binary-manywheel-nightly.yml

@@ -58,7 +58,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       runs_on: linux.s390x
       ALPINE_IMAGE: "docker.io/s390x/alpine"
@@ -82,7 +81,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       build_name: manywheel-py3_9-cpu-s390x
       build_environment: linux-s390x-binary-manywheel
@@ -105,7 +103,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.9"
       build_name: manywheel-py3_9-cpu-s390x
     secrets:
@@ -127,7 +124,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.10"
       runs_on: linux.s390x
       ALPINE_IMAGE: "docker.io/s390x/alpine"
@@ -151,7 +147,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.10"
       build_name: manywheel-py3_10-cpu-s390x
       build_environment: linux-s390x-binary-manywheel
@@ -174,7 +169,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.10"
       build_name: manywheel-py3_10-cpu-s390x
     secrets:
@@ -196,7 +190,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.11"
       runs_on: linux.s390x
       ALPINE_IMAGE: "docker.io/s390x/alpine"
@@ -220,7 +213,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.11"
       build_name: manywheel-py3_11-cpu-s390x
       build_environment: linux-s390x-binary-manywheel
@@ -243,7 +235,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.11"
       build_name: manywheel-py3_11-cpu-s390x
     secrets:
@@ -265,7 +256,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.12"
       runs_on: linux.s390x
       ALPINE_IMAGE: "docker.io/s390x/alpine"
@@ -289,7 +279,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.12"
       build_name: manywheel-py3_12-cpu-s390x
       build_environment: linux-s390x-binary-manywheel
@@ -312,7 +301,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.12"
       build_name: manywheel-py3_12-cpu-s390x
     secrets:
@@ -334,7 +322,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.13"
       runs_on: linux.s390x
       ALPINE_IMAGE: "docker.io/s390x/alpine"
@@ -358,7 +345,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.13"
       build_name: manywheel-py3_13-cpu-s390x
       build_environment: linux-s390x-binary-manywheel
@@ -381,7 +367,6 @@ jobs:
       DESIRED_CUDA: cpu
       GPU_ARCH_TYPE: cpu-s390x
       DOCKER_IMAGE: pytorch/manylinuxs390x-builder:cpu-s390x-main
-      use_split_build: False
       DESIRED_PYTHON: "3.13"
       build_name: manywheel-py3_13-cpu-s390x
     secrets:

.github/workflows/generated-macos-arm64-binary-conda-nightly.yml

@@ -117,7 +117,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_9-cpu
@@ -232,7 +232,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_10-cpu
@@ -347,7 +347,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_11-cpu
@@ -462,7 +462,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_12-cpu

.github/workflows/generated-macos-arm64-binary-libtorch-cxx11-abi-nightly.yml

@@ -49,7 +49,7 @@ jobs:
       DESIRED_DEVTOOLSET: cxx11-abi
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       # NOTE: These environment variables are put here so that they can be applied on every job equally
       #       They are also here because setting them at a workflow level doesn't give us access to the
@@ -121,7 +121,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cpu-shared-with-deps-cxx11-abi

.github/workflows/generated-macos-arm64-binary-wheel-nightly.yml

@@ -118,7 +118,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: wheel-py3_9-cpu
@@ -234,7 +234,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: wheel-py3_10-cpu
@@ -350,7 +350,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: wheel-py3_11-cpu
@@ -466,7 +466,7 @@ jobs:
           # shellcheck disable=SC1091
           source "${RUNNER_TEMP}/anaconda/bin/activate"
           "${PYTORCH_ROOT}/.circleci/scripts/binary_macos_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: wheel-py3_12-cpu

.github/workflows/generated-windows-binary-conda-nightly.yml

@@ -132,7 +132,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_9-cpu
@@ -213,7 +213,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_9-cpu
@@ -378,7 +378,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_9-cuda11_8
@@ -403,7 +403,7 @@ jobs:
     needs:
       - conda-py3_9-cuda11_8-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -460,7 +460,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_9-cuda11_8
@@ -626,7 +626,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_9-cuda12_1
@@ -651,7 +651,7 @@ jobs:
     needs:
       - conda-py3_9-cuda12_1-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -708,7 +708,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_9-cuda12_1
@@ -874,7 +874,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_9-cuda12_4
@@ -899,7 +899,7 @@ jobs:
     needs:
       - conda-py3_9-cuda12_4-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -956,7 +956,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_9-cuda12_4
@@ -1121,7 +1121,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_10-cpu
@@ -1202,7 +1202,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_10-cpu
@@ -1367,7 +1367,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_10-cuda11_8
@@ -1392,7 +1392,7 @@ jobs:
     needs:
       - conda-py3_10-cuda11_8-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -1449,7 +1449,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_10-cuda11_8
@@ -1615,7 +1615,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_10-cuda12_1
@@ -1640,7 +1640,7 @@ jobs:
     needs:
       - conda-py3_10-cuda12_1-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -1697,7 +1697,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_10-cuda12_1
@@ -1863,7 +1863,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_10-cuda12_4
@@ -1888,7 +1888,7 @@ jobs:
     needs:
       - conda-py3_10-cuda12_4-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -1945,7 +1945,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_10-cuda12_4
@@ -2110,7 +2110,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_11-cpu
@@ -2191,7 +2191,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_11-cpu
@@ -2356,7 +2356,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_11-cuda11_8
@@ -2381,7 +2381,7 @@ jobs:
     needs:
       - conda-py3_11-cuda11_8-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -2438,7 +2438,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_11-cuda11_8
@@ -2604,7 +2604,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_11-cuda12_1
@@ -2629,7 +2629,7 @@ jobs:
     needs:
       - conda-py3_11-cuda12_1-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -2686,7 +2686,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_11-cuda12_1
@@ -2852,7 +2852,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_11-cuda12_4
@@ -2877,7 +2877,7 @@ jobs:
     needs:
       - conda-py3_11-cuda12_4-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -2934,7 +2934,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_11-cuda12_4
@@ -3099,7 +3099,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_12-cpu
@@ -3180,7 +3180,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_12-cpu
@@ -3345,7 +3345,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_12-cuda11_8
@@ -3370,7 +3370,7 @@ jobs:
     needs:
       - conda-py3_12-cuda11_8-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -3427,7 +3427,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_12-cuda11_8
@@ -3593,7 +3593,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_12-cuda12_1
@@ -3618,7 +3618,7 @@ jobs:
     needs:
       - conda-py3_12-cuda12_1-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -3675,7 +3675,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_12-cuda12_1
@@ -3841,7 +3841,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: conda-py3_12-cuda12_4
@@ -3866,7 +3866,7 @@ jobs:
     needs:
       - conda-py3_12-cuda12_4-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -3923,7 +3923,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: conda-py3_12-cuda12_4

.github/workflows/generated-windows-binary-libtorch-debug-main.yml

@@ -51,7 +51,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -129,7 +129,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cpu-shared-with-deps-debug
@@ -169,7 +169,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -214,7 +214,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cpu-shared-with-deps-debug

.github/workflows/generated-windows-binary-libtorch-debug-nightly.yml

@@ -58,7 +58,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -136,7 +136,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cpu-shared-with-deps-debug
@@ -176,7 +176,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -221,7 +221,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cpu-shared-with-deps-debug
@@ -290,7 +290,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
       build_name: libtorch-cpu-shared-with-deps-debug
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
@@ -316,7 +316,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -394,7 +394,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cuda11_8-shared-with-deps-debug
@@ -419,7 +419,7 @@ jobs:
     needs:
       - libtorch-cuda11_8-shared-with-deps-debug-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -435,7 +435,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -480,7 +480,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cuda11_8-shared-with-deps-debug
@@ -550,7 +550,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
       build_name: libtorch-cuda11_8-shared-with-deps-debug
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
@@ -576,7 +576,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -654,7 +654,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cuda12_1-shared-with-deps-debug
@@ -679,7 +679,7 @@ jobs:
     needs:
       - libtorch-cuda12_1-shared-with-deps-debug-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -695,7 +695,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -740,7 +740,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cuda12_1-shared-with-deps-debug
@@ -810,7 +810,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
       build_name: libtorch-cuda12_1-shared-with-deps-debug
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
@@ -836,7 +836,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -914,7 +914,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cuda12_4-shared-with-deps-debug
@@ -939,7 +939,7 @@ jobs:
     needs:
       - libtorch-cuda12_4-shared-with-deps-debug-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -955,7 +955,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -1000,7 +1000,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cuda12_4-shared-with-deps-debug
@@ -1070,7 +1070,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
       build_name: libtorch-cuda12_4-shared-with-deps-debug
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/generated-windows-binary-libtorch-release-main.yml

@@ -51,7 +51,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -129,7 +129,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cpu-shared-with-deps-release
@@ -169,7 +169,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -214,7 +214,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cpu-shared-with-deps-release

.github/workflows/generated-windows-binary-libtorch-release-nightly.yml

@@ -58,7 +58,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -136,7 +136,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cpu-shared-with-deps-release
@@ -176,7 +176,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -221,7 +221,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cpu-shared-with-deps-release
@@ -290,7 +290,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
       build_name: libtorch-cpu-shared-with-deps-release
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
@@ -316,7 +316,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -394,7 +394,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cuda11_8-shared-with-deps-release
@@ -419,7 +419,7 @@ jobs:
     needs:
       - libtorch-cuda11_8-shared-with-deps-release-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -435,7 +435,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -480,7 +480,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cuda11_8-shared-with-deps-release
@@ -550,7 +550,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
       build_name: libtorch-cuda11_8-shared-with-deps-release
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
@@ -576,7 +576,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -654,7 +654,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cuda12_1-shared-with-deps-release
@@ -679,7 +679,7 @@ jobs:
     needs:
       - libtorch-cuda12_1-shared-with-deps-release-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -695,7 +695,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -740,7 +740,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cuda12_1-shared-with-deps-release
@@ -810,7 +810,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
       build_name: libtorch-cuda12_1-shared-with-deps-release
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}
@@ -836,7 +836,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -914,7 +914,7 @@ jobs:
         shell: bash
         run: |
           "${PYTORCH_ROOT}/.circleci/scripts/binary_windows_build.sh"
-      - uses: actions/upload-artifact@v4.4.0
+      - uses: actions/upload-artifact@v3
         if: always()
         with:
           name: libtorch-cuda12_4-shared-with-deps-release
@@ -939,7 +939,7 @@ jobs:
     needs:
       - libtorch-cuda12_4-shared-with-deps-release-build
       - get-label-type
-    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.g4dn.xlarge"
+    runs-on: "${{ needs.get-label-type.outputs.label-type }}windows.8xlarge.nvidia.gpu"
     timeout-minutes: 240
     env:
       PYTORCH_ROOT: ${{ github.workspace }}/pytorch
@@ -955,7 +955,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
     steps:
       - name: Display EC2 information
         shell: bash
@@ -1000,7 +1000,7 @@ jobs:
           echo "BINARY_ENV_FILE=${RUNNER_TEMP}/env" >> "${GITHUB_ENV}"
           echo "PYTORCH_FINAL_PACKAGE_DIR=${RUNNER_TEMP}/artifacts" >> "${GITHUB_ENV}"
           echo "WIN_PACKAGE_WORK_DIR=${RUNNER_TEMP}"
-      - uses: actions/download-artifact@v4.1.7
+      - uses: actions/download-artifact@v3
         name: Download Build Artifacts
         with:
           name: libtorch-cuda12_4-shared-with-deps-release
@@ -1070,7 +1070,7 @@ jobs:
       LIBTORCH_VARIANT: shared-with-deps
       # This is a dummy value for libtorch to work correctly with our batch scripts
       # without this value pip does not get installed for some reason
-      DESIRED_PYTHON: "3.9"
+      DESIRED_PYTHON: "3.8"
       build_name: libtorch-cuda12_4-shared-with-deps-release
     secrets:
       github-token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/inductor-cu124.yml

@@ -18,22 +18,11 @@ concurrency:
 permissions: read-all
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   linux-focal-cuda12_4-py3_10-gcc9-inductor-build:
     # Should be synced with the one in inductor.yml, but this doesn't run inductor_timm
     name: cuda12.4-py3.10-gcc9-sm86
     uses: ./.github/workflows/_linux-build.yml
-    needs: get-label-type
     with:
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       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

.github/workflows/inductor-micro-benchmark-x86.yml

@@ -1,40 +0,0 @@
-name: inductor-micro-benchmark-x86
-
-on:
-  schedule:
-    - cron: 0 7 * * *
-  push:
-    tags:
-      - ciflow/inductor-micro-benchmark-cpu-x86/*
-  workflow_dispatch:
-
-
-concurrency:
-  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref_name }}-${{ github.ref_type == 'branch' && github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
-  cancel-in-progress: true
-
-permissions: read-all
-
-jobs:
-  linux-jammy-cpu-py3_9-gcc11-inductor-build:
-    name: linux-jammy-cpu-py3.9-gcc11-inductor
-    uses: ./.github/workflows/_linux-build.yml
-    with:
-      build-environment: linux-jammy-py3.9-gcc11
-      docker-image-name: pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks
-      # Use metal host for benchmark jobs
-      test-matrix: |
-        { include: [
-          { config: "inductor-micro-benchmark-cpu-x86", shard: 1, num_shards: 1, runner: "linux.24xl.spr-metal" },
-        ]}
-
-  linux-jammy-cpu-py3_9-gcc11-inductor-micro-benchmark-test:
-    name: linux-jammy-cpu-py3.9-gcc11-inductor
-    uses: ./.github/workflows/_linux-test.yml
-    needs: linux-jammy-cpu-py3_9-gcc11-inductor-build
-    with:
-      build-environment: linux-jammy-py3.9-gcc11
-      docker-image: ${{ needs.linux-jammy-cpu-py3_9-gcc11-inductor-build.outputs.docker-image }}
-      test-matrix: ${{ needs.linux-jammy-cpu-py3_9-gcc11-inductor-build.outputs.test-matrix }}
-      use-gha: anything-non-empty-to-use-gha
-      timeout-minutes: 720

.github/workflows/inductor-micro-benchmark.yml

@@ -16,21 +16,10 @@ concurrency:
 permissions: read-all
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   linux-focal-cuda12_1-py3_10-gcc9-inductor-micro-benchmark-build:
     name: cuda12.1-py3.10-gcc9-sm80
     uses: ./.github/workflows/_linux-build.yml
-    needs: get-label-type
     with:
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
       docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
       cuda-arch-list: '8.0'

.github/workflows/inductor-perf-compare.yml

@@ -13,21 +13,10 @@ concurrency:
 permissions: read-all
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   linux-focal-cuda12_1-py3_10-gcc9-inductor-build:
     name: cuda12.1-py3.10-gcc9-sm80
     uses: ./.github/workflows/_linux-build.yml
-    needs: get-label-type
     with:
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
       docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
       cuda-arch-list: '8.0'

.github/workflows/inductor-perf-test-nightly-a10g.yml

@@ -68,21 +68,10 @@ concurrency:
 permissions: read-all
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   linux-focal-cuda12_1-py3_10-gcc9-inductor-build:
     name: cuda12.1-py3.10-gcc9-sm80
     uses: ./.github/workflows/_linux-build.yml
-    needs: get-label-type
     with:
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
       docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
       cuda-arch-list: '8.0'

.github/workflows/inductor-perf-test-nightly-aarch64.yml

@@ -5,7 +5,9 @@ on:
     # - cron: 0 7 * * 1-6
     # - cron: 0 7 * * 0
     # Does not perform max_autotune on CPU, so skip the weekly run setup
-    - cron: 0 7 * * *
+    # Run 6 times everyday to see if perf instablity can be reproduced
+    # Will change this back
+    - cron: 0 */4 * * *
   # NB: GitHub has an upper limit of 10 inputs here
   workflow_dispatch:
     inputs:
@@ -48,21 +50,10 @@ concurrency:
 permissions: read-all
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   linux-jammy-aarch64-py3_10-inductor-build:
     name: linux-jammy-aarch64-py3.10-inductor
     uses: ./.github/workflows/_linux-build.yml
-    needs: get-label-type
     with:
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       runner: linux.arm64.m7g.4xlarge
       build-environment: linux-jammy-aarch64-py3.10
       docker-image-name: pytorch-linux-jammy-aarch64-py3.10-gcc11-inductor-benchmarks
@@ -114,7 +105,7 @@ jobs:
     name: linux-jammy-aarch64-py3.10-inductor
     uses: ./.github/workflows/_linux-test.yml
     needs: linux-jammy-aarch64-py3_10-inductor-build
-    if: github.event.schedule == '0 7 * * *'
+    if: github.event.schedule == '0 */4 * * *'
     with:
       build-environment: linux-jammy-aarch64-py3.10
       # Turn off dynamic-shapes and aotinductor tests for now, to have faster iteration for debugging perf instability.

.github/workflows/inductor-perf-test-nightly-x86.yml

@@ -48,23 +48,12 @@ concurrency:
 permissions: read-all
 
 jobs:
-  get-label-type:
+  linux-jammy-cpu-py3_8-gcc11-inductor-build:
-    name: get-label-type
+    name: linux-jammy-cpu-py3.8-gcc11-inductor
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
-  linux-jammy-cpu-py3_9-gcc11-inductor-build:
-    name: linux-jammy-cpu-py3.9-gcc11-inductor
     uses: ./.github/workflows/_linux-build.yml
-    needs: get-label-type
     with:
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
+      build-environment: linux-jammy-py3.8-gcc11-build
-      build-environment: linux-jammy-py3.9-gcc11-build
+      docker-image-name: pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks
-      docker-image-name: pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks
       test-matrix: |
         { include: [
           { config: "inductor_huggingface_perf_cpu_x86", shard: 1, num_shards: 3, runner: "linux.24xl.spr-metal" },
@@ -85,32 +74,32 @@ jobs:
       HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
 
 
-  linux-jammy-cpu-py3_9-gcc11-inductor-test-nightly:
+  linux-jammy-cpu-py3_8-gcc11-inductor-test-nightly:
-    name: linux-jammy-cpu-py3.9-gcc11-inductor
+    name: linux-jammy-cpu-py3.8-gcc11-inductor
     uses: ./.github/workflows/_linux-test.yml
-    needs: linux-jammy-cpu-py3_9-gcc11-inductor-build
+    needs: linux-jammy-cpu-py3_8-gcc11-inductor-build
     if: github.event.schedule == '0 7 * * *'
     with:
-      build-environment: linux-jammy-py3.9-gcc11-build
+      build-environment: linux-jammy-py3.8-gcc11-build
       dashboard-tag: training-false-inference-true-default-true-dynamic-true-aotinductor-true
-      docker-image: ${{ needs.linux-jammy-cpu-py3_9-gcc11-inductor-build.outputs.docker-image }}
+      docker-image: ${{ needs.linux-jammy-cpu-py3_8-gcc11-inductor-build.outputs.docker-image }}
-      test-matrix: ${{ needs.linux-jammy-cpu-py3_9-gcc11-inductor-build.outputs.test-matrix }}
+      test-matrix: ${{ needs.linux-jammy-cpu-py3_8-gcc11-inductor-build.outputs.test-matrix }}
       use-gha: anything-non-empty-to-use-gha
       timeout-minutes: 720
     secrets:
       HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
 
 
-  linux-jammy-cpu-py3_9-gcc11-inductor-test:
+  linux-jammy-cpu-py3_8-gcc11-inductor-test:
-    name: linux-jammy-cpu-py3.9-gcc11-inductor
+    name: linux-jammy-cpu-py3.8-gcc11-inductor
     uses: ./.github/workflows/_linux-test.yml
-    needs: linux-jammy-cpu-py3_9-gcc11-inductor-build
+    needs: linux-jammy-cpu-py3_8-gcc11-inductor-build
     if: github.event_name == 'workflow_dispatch'
     with:
-      build-environment: linux-jammy-py3.9-gcc11-build
+      build-environment: linux-jammy-py3.8-gcc11-build
       dashboard-tag: training-${{ inputs.training }}-inference-${{ inputs.inference }}-default-${{ inputs.default }}-dynamic-${{ inputs.dynamic }}-aotinductor-${{ inputs.aotinductor }}
-      docker-image: ${{ needs.linux-jammy-cpu-py3_9-gcc11-inductor-build.outputs.docker-image }}
+      docker-image: ${{ needs.linux-jammy-cpu-py3_8-gcc11-inductor-build.outputs.docker-image }}
-      test-matrix: ${{ needs.linux-jammy-cpu-py3_9-gcc11-inductor-build.outputs.test-matrix }}
+      test-matrix: ${{ needs.linux-jammy-cpu-py3_8-gcc11-inductor-build.outputs.test-matrix }}
       use-gha: anything-non-empty-to-use-gha
       timeout-minutes: 720
     secrets:

.github/workflows/inductor-perf-test-nightly.yml

@@ -66,21 +66,10 @@ concurrency:
 permissions: read-all
 
 jobs:
-  get-label-type:
-    name: get-label-type
-    uses: ./.github/workflows/_runner-determinator.yml
-    with:
-      triggering_actor: ${{ github.triggering_actor }}
-      issue_owner: ${{ github.event.pull_request.user.login || github.event.issue.user.login }}
-      curr_branch: ${{ github.head_ref || github.ref_name }}
-      curr_ref_type: ${{ github.ref_type }}
-
   linux-focal-cuda12_1-py3_10-gcc9-inductor-build:
     name: cuda12.1-py3.10-gcc9-sm80
     uses: ./.github/workflows/_linux-build.yml
-    needs: get-label-type
     with:
-      runner_prefix: "${{ needs.get-label-type.outputs.label-type }}"
       build-environment: linux-focal-cuda12.1-py3.10-gcc9-sm80
       docker-image-name: pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks
       cuda-arch-list: '8.0'