Add hasattr for tensor variable

Enables tests that are now running sucessfully under dynamo

ghstack-source-id: 3fcdb33d957c30b3e740e1d83c148c1572279360
Pull Request resolved: https://github.com/pytorch/pytorch/pull/131008

.ci/docker/README.md

@@ -1,4 +1,4 @@
-# Docker images for GitHub CI and CD
+# Docker images for GitHub CI
 
 This directory contains everything needed to build the Docker images
 that are used in our CI.
@@ -12,7 +12,7 @@ each image as the `BUILD_ENVIRONMENT` environment variable.
 
 See `build.sh` for valid build environments (it's the giant switch).
 
-## Docker CI builds
+## Contents
 
 * `build.sh` -- dispatch script to launch all builds
 * `common` -- scripts used to execute individual Docker build stages
@@ -21,12 +21,6 @@ See `build.sh` for valid build environments (it's the giant switch).
 * `ubuntu-rocm` -- Dockerfile for Ubuntu image with ROCm support
 * `ubuntu-xpu` -- Dockerfile for Ubuntu image with XPU support
 
-### Docker CD builds
-
-* `conda` - Dockerfile and build.sh to build Docker images used in nightly conda builds
-* `manywheel` - Dockerfile and build.sh to build Docker images used in nightly manywheel builds
-* `libtorch` - Dockerfile and build.sh to build Docker images used in nightly libtorch builds
-
 ## Usage
 
 ```bash

.ci/docker/aotriton_version.txt

@@ -1,5 +1,5 @@
-0.7b
+0.6b
 manylinux_2_17
-rocm6.2
-9be04068c3c0857a4cfd17d7e39e71d0423ebac2
-3e9e1959d23b93d78a08fcc5f868125dc3854dece32fd9458be9ef4467982291
+rocm6.1
+7f07e8a1cb1f99627eb6d77f5c0e9295c775f3c7
+77c29fa3f3b614e187d7213d745e989a92708cee2bc6020419ab49019af399d1

.ci/docker/build.sh

@@ -92,7 +92,7 @@ _UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
 # from scratch
 case "$image" in
   pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.4.1
+    CUDA_VERSION=12.4.0
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
@@ -120,7 +120,7 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.4.1
+    CUDA_VERSION=12.4.0
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
@@ -165,7 +165,7 @@ case "$image" in
     INDUCTOR_BENCHMARKS=yes
     ;;
   pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.4.1
+    CUDA_VERSION=12.4.0
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=9
@@ -194,7 +194,7 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.4.1
+    CUDA_VERSION=12.4.0
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
@@ -222,7 +222,7 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.4.1
+    CUDA_VERSION=12.4.0
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
@@ -236,7 +236,7 @@ case "$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)
-    ANACONDA_PYTHON_VERSION=3.9
+  pytorch-linux-focal-py3.8-clang10)
+    ANACONDA_PYTHON_VERSION=3.8
     CLANG_VERSION=10
     PROTOBUF=yes
     DB=yes
@@ -276,8 +276,8 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-focal-py3.9-gcc9)
-    ANACONDA_PYTHON_VERSION=3.9
+  pytorch-linux-focal-py3.8-gcc9)
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
@@ -286,7 +286,18 @@ case "$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=6.0
+    NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-focal-rocm-n-py3)
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
@@ -296,19 +307,8 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-focal-rocm-n-py3)
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    ROCM_VERSION=6.2
-    NINJA_VERSION=1.9.0
-    CONDA_CMAKE=yes
-    TRITON=yes
-    ;;
   pytorch-linux-jammy-xpu-2024.0-py3)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
@@ -318,8 +318,8 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
-    pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
-    ANACONDA_PYTHON_VERSION=3.9
+    pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks)
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
@@ -330,8 +330,8 @@ case "$image" in
     DOCS=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-clang12)
-    ANACONDA_PYTHON_VERSION=3.9
+  pytorch-linux-jammy-cuda11.8-cudnn9-py3.8-clang12)
+    ANACONDA_PYTHON_VERSION=3.8
     CUDA_VERSION=11.8
     CUDNN_VERSION=9
     CLANG_VERSION=12
@@ -355,8 +355,8 @@ case "$image" in
     CONDA_CMAKE=yes
     VISION=yes
     ;;
-  pytorch-linux-jammy-py3.9-gcc11)
-    ANACONDA_PYTHON_VERSION=3.9
+  pytorch-linux-jammy-py3.8-gcc11)
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
@@ -407,22 +407,6 @@ case "$image" in
     # from pytorch/llvm:9.0.1 is x86 specific
     SKIP_LLVM_SRC_BUILD_INSTALL=yes
     ;;
-  pytorch-linux-jammy-aarch64-py3.10-gcc11-inductor-benchmarks)
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
-    ACL=yes
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    CONDA_CMAKE=yes
-    # snadampal: skipping sccache due to the following issue
-    # https://github.com/pytorch/pytorch/issues/121559
-    SKIP_SCCACHE_INSTALL=yes
-    # snadampal: skipping llvm src build install because the current version
-    # from pytorch/llvm:9.0.1 is x86 specific
-    SKIP_LLVM_SRC_BUILD_INSTALL=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
   *)
     # Catch-all for builds that are not hardcoded.
     PROTOBUF=yes

.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
+c572f9e509b5ec5d56f4d218271e36269bba244f

.ci/docker/ci_commit_pins/halide.txt

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

.ci/docker/ci_commit_pins/timm.txt

@@ -1 +1 @@
-ac3470188b914c5d7a5058a7e28b9eb685a62427
+730b907b4d45a4713cbc425cbf224c46089fd514

.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_conda.sh

@@ -5,22 +5,32 @@ set -ex
 # Optionally install conda
 if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   BASE_URL="https://repo.anaconda.com/miniconda"
-  CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
-  if [[ $(uname -m) == "aarch64" ]] || [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
-    BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"
-    CONDA_FILE="Miniforge3-Linux-$(uname -m).sh"
-  fi
 
   MAJOR_PYTHON_VERSION=$(echo "$ANACONDA_PYTHON_VERSION" | cut -d . -f 1)
   MINOR_PYTHON_VERSION=$(echo "$ANACONDA_PYTHON_VERSION" | cut -d . -f 2)
 
+if [[ $(uname -m) == "aarch64" ]]; then
+  BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"
   case "$MAJOR_PYTHON_VERSION" in
-    3);;
+    3)
+      CONDA_FILE="Miniforge3-Linux-aarch64.sh"
+    ;;
     *)
       echo "Unsupported ANACONDA_PYTHON_VERSION: $ANACONDA_PYTHON_VERSION"
       exit 1
       ;;
   esac
+else
+  case "$MAJOR_PYTHON_VERSION" in
+    3)
+      CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
+    ;;
+    *)
+      echo "Unsupported ANACONDA_PYTHON_VERSION: $ANACONDA_PYTHON_VERSION"
+      exit 1
+      ;;
+  esac
+fi
 
   mkdir -p /opt/conda
   chown jenkins:jenkins /opt/conda
@@ -68,20 +78,19 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
     CONDA_COMMON_DEPS="astunparse pyyaml setuptools openblas==0.3.25=*openmp* ninja==1.11.1 scons==4.5.2"
 
     if [ "$ANACONDA_PYTHON_VERSION" = "3.8" ]; then
-      NUMPY_VERSION=1.24.4
+      conda_install numpy=1.24.4 ${CONDA_COMMON_DEPS}
     else
-      NUMPY_VERSION=1.26.2
+      conda_install numpy=1.26.2 ${CONDA_COMMON_DEPS}
     fi
   else
     CONDA_COMMON_DEPS="astunparse pyyaml mkl=2021.4.0 mkl-include=2021.4.0 setuptools"
 
     if [ "$ANACONDA_PYTHON_VERSION" = "3.11" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.12" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.13" ]; then
-      NUMPY_VERSION=1.26.0
+      conda_install numpy=1.26.0 ${CONDA_COMMON_DEPS}
     else
-      NUMPY_VERSION=1.21.2
+      conda_install numpy=1.21.2 ${CONDA_COMMON_DEPS}
     fi
   fi
-  conda_install ${CONDA_COMMON_DEPS}
 
   # Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
   # and libpython-static for torch deploy
@@ -103,7 +112,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
 
   # Install some other packages, including those needed for Python test reporting
   pip_install -r /opt/conda/requirements-ci.txt
-  pip_install numpy=="$NUMPY_VERSION"
+
   pip_install -U scikit-learn
 
   if [ -n "$DOCS" ]; then

.ci/docker/common/install_conda_docker.sh

@@ -1,20 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-set -ex
-
-# Anaconda
-# Latest anaconda is using openssl-3 which is incompatible with all currently published versions of git
-# Which are using openssl-1.1.1, see https://anaconda.org/anaconda/git/files?version=2.40.1 for example
-MINICONDA_URL=https://repo.anaconda.com/miniconda/Miniconda3-py311_23.5.2-0-Linux-x86_64.sh
-wget -q $MINICONDA_URL
-# NB: Manually invoke bash per https://github.com/conda/conda/issues/10431
-bash $(basename "$MINICONDA_URL") -b -p /opt/conda
-rm $(basename "$MINICONDA_URL")
-export PATH=/opt/conda/bin:$PATH
-# See https://github.com/pytorch/builder/issues/1473
-# Pin conda to 23.5.2 as it's the last one compatible with openssl-1.1.1
-conda install -y conda=23.5.2 conda-build anaconda-client git ninja
-# The cmake version here needs to match with the minimum version of cmake
-# supported by PyTorch (3.18). There is only 3.18.2 on anaconda
-/opt/conda/bin/pip3 install cmake==3.18.2
-conda remove -y --force patchelf

.ci/docker/common/install_cpython.sh

@@ -1,96 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-set -uex -o pipefail
-
-PYTHON_DOWNLOAD_URL=https://www.python.org/ftp/python
-PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads
-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"}
-
-function check_var {
-    if [ -z "$1" ]; then
-        echo "required variable not defined"
-        exit 1
-    fi
-}
-
-function do_cpython_build {
-    local py_ver=$1
-    local py_folder=$2
-    check_var $py_ver
-    check_var $py_folder
-    tar -xzf Python-$py_ver.tgz
-    pushd $py_folder
-
-    local prefix="/opt/_internal/cpython-${py_ver}"
-    mkdir -p ${prefix}/lib
-    if [[ -n $(which patchelf) ]]; then
-        local shared_flags="--enable-shared"
-    else
-        local shared_flags="--disable-shared"
-    fi
-    if [[ -z  "${WITH_OPENSSL+x}" ]]; then
-        local openssl_flags=""
-    else
-        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} ${shared_flags} > /dev/null
-
-    make -j40 > /dev/null
-    make install > /dev/null
-
-    if [[ "${shared_flags}" == "--enable-shared" ]]; then
-        patchelf --set-rpath '$ORIGIN/../lib' ${prefix}/bin/python3
-    fi
-
-    popd
-    rm -rf $py_folder
-    # Some python's install as bin/python3. Make them available as
-    # bin/python.
-    if [ -e ${prefix}/bin/python3 ]; then
-        ln -s python3 ${prefix}/bin/python
-    fi
-    ${prefix}/bin/python get-pip.py
-    if [ -e ${prefix}/bin/pip3 ] && [ ! -e ${prefix}/bin/pip ]; then
-        ln -s pip3 ${prefix}/bin/pip
-    fi
-    # install setuptools since python 3.12 is required to use distutils
-    ${prefix}/bin/pip install wheel==0.34.2 setuptools==68.2.2
-    local abi_tag=$(${prefix}/bin/python -c "from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag; print('{0}{1}-{2}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag()))")
-    ln -s ${prefix} /opt/python/${abi_tag}
-}
-
-function build_cpython {
-    local py_ver=$1
-    check_var $py_ver
-    check_var $PYTHON_DOWNLOAD_URL
-    local py_ver_folder=$py_ver
-    if [ "$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
-        do_cpython_build $py_ver cpython-$PY_VER_SHORT
-    else
-        wget -q $PYTHON_DOWNLOAD_URL/$py_ver_folder/Python-$py_ver.tgz
-        do_cpython_build $py_ver Python-$py_ver
-    fi
-
-    rm -f Python-$py_ver.tgz
-}
-
-function build_cpythons {
-    check_var $GET_PIP_URL
-    curl -sLO $GET_PIP_URL
-    for py_ver in $@; do
-        build_cpython $py_ver
-    done
-    rm -f get-pip.py
-}
-
-mkdir -p /opt/python
-mkdir -p /opt/_internal
-build_cpythons $CPYTHON_VERSIONS

.ci/docker/common/install_cuda.sh

@@ -1,250 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-NCCL_VERSION=v2.21.5-1
-CUDNN_VERSION=9.1.0.70
-
-function install_cusparselt_040 {
-    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
-    mkdir tmp_cusparselt && pushd tmp_cusparselt
-    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.4.0.7-archive.tar.xz
-    tar xf libcusparse_lt-linux-x86_64-0.4.0.7-archive.tar.xz
-    cp -a libcusparse_lt-linux-x86_64-0.4.0.7-archive/include/* /usr/local/cuda/include/
-    cp -a libcusparse_lt-linux-x86_64-0.4.0.7-archive/lib/* /usr/local/cuda/lib64/
-    popd
-    rm -rf tmp_cusparselt
-}
-
-function install_cusparselt_052 {
-    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
-    mkdir tmp_cusparselt && pushd tmp_cusparselt
-    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.5.2.1-archive.tar.xz
-    tar xf libcusparse_lt-linux-x86_64-0.5.2.1-archive.tar.xz
-    cp -a libcusparse_lt-linux-x86_64-0.5.2.1-archive/include/* /usr/local/cuda/include/
-    cp -a libcusparse_lt-linux-x86_64-0.5.2.1-archive/lib/* /usr/local/cuda/lib64/
-    popd
-    rm -rf tmp_cusparselt
-}
-
-function install_cusparselt_062 {
-    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
-    mkdir tmp_cusparselt && pushd tmp_cusparselt
-    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
-    tar xf libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
-    cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/include/* /usr/local/cuda/include/
-    cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/lib/* /usr/local/cuda/lib64/
-    popd
-    rm -rf tmp_cusparselt
-}
-
-function install_118 {
-    echo "Installing CUDA 11.8 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.4.0"
-    rm -rf /usr/local/cuda-11.8 /usr/local/cuda
-    # install CUDA 11.8.0 in the same container
-    wget -q https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
-    chmod +x cuda_11.8.0_520.61.05_linux.run
-    ./cuda_11.8.0_520.61.05_linux.run --toolkit --silent
-    rm -f cuda_11.8.0_520.61.05_linux.run
-    rm -f /usr/local/cuda && ln -s /usr/local/cuda-11.8 /usr/local/cuda
-
-    # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-    mkdir tmp_cudnn && cd tmp_cudnn
-    wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
-    tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
-    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/include/* /usr/local/cuda/include/
-    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/lib/* /usr/local/cuda/lib64/
-    cd ..
-    rm -rf tmp_cudnn
-
-    # NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
-    # Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
-    git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
-    cd nccl && make -j src.build
-    cp -a build/include/* /usr/local/cuda/include/
-    cp -a build/lib/* /usr/local/cuda/lib64/
-    cd ..
-    rm -rf nccl
-
-    install_cusparselt_040
-
-    ldconfig
-}
-
-function install_121 {
-    echo "Installing CUDA 12.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.5.2"
-    rm -rf /usr/local/cuda-12.1 /usr/local/cuda
-    # install CUDA 12.1.0 in the same container
-    wget -q https://developer.download.nvidia.com/compute/cuda/12.1.1/local_installers/cuda_12.1.1_530.30.02_linux.run
-    chmod +x cuda_12.1.1_530.30.02_linux.run
-    ./cuda_12.1.1_530.30.02_linux.run --toolkit --silent
-    rm -f cuda_12.1.1_530.30.02_linux.run
-    rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.1 /usr/local/cuda
-
-    # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-    mkdir tmp_cudnn && cd tmp_cudnn
-    wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
-    tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
-    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
-    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
-    cd ..
-    rm -rf tmp_cudnn
-
-    # NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
-    # Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
-    git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
-    cd nccl && make -j src.build
-    cp -a build/include/* /usr/local/cuda/include/
-    cp -a build/lib/* /usr/local/cuda/lib64/
-    cd ..
-    rm -rf nccl
-
-    install_cusparselt_052
-
-    ldconfig
-}
-
-function install_124 {
-  echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.5.2"
-  rm -rf /usr/local/cuda-12.4 /usr/local/cuda
-  # install CUDA 12.4.1 in the same container
-  wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run
-  chmod +x cuda_12.4.1_550.54.15_linux.run
-  ./cuda_12.4.1_550.54.15_linux.run --toolkit --silent
-  rm -f cuda_12.4.1_550.54.15_linux.run
-  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
-
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  mkdir tmp_cudnn && cd tmp_cudnn
-  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
-  tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
-  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
-  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
-  cd ..
-  rm -rf tmp_cudnn
-
-  # NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
-  # Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
-  git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
-  cd nccl && make -j src.build
-  cp -a build/include/* /usr/local/cuda/include/
-  cp -a build/lib/* /usr/local/cuda/lib64/
-  cd ..
-  rm -rf nccl
-
-  install_cusparselt_062
-
-  ldconfig
-}
-
-function prune_118 {
-    echo "Pruning CUDA 11.8 and cuDNN"
-    #####################################################################################
-    # CUDA 11.8 prune static libs
-    #####################################################################################
-    export NVPRUNE="/usr/local/cuda-11.8/bin/nvprune"
-    export CUDA_LIB_DIR="/usr/local/cuda-11.8/lib64"
-
-    export GENCODE="-gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
-    export GENCODE_CUDNN="-gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
-
-    if [[ -n "$OVERRIDE_GENCODE" ]]; then
-        export GENCODE=$OVERRIDE_GENCODE
-    fi
-
-    # all CUDA libs except CuDNN and CuBLAS (cudnn and cublas need arch 3.7 included)
-    ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
-      | xargs -I {} bash -c \
-                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
-
-    # prune CuDNN and CuBLAS
-    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
-    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
-
-    #####################################################################################
-    # CUDA 11.8 prune visual tools
-    #####################################################################################
-    export CUDA_BASE="/usr/local/cuda-11.8/"
-    rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.3.0 $CUDA_BASE/nsight-systems-2022.4.2/
-}
-
-function prune_121 {
-  echo "Pruning CUDA 12.1"
-  #####################################################################################
-  # CUDA 12.1 prune static libs
-  #####################################################################################
-    export NVPRUNE="/usr/local/cuda-12.1/bin/nvprune"
-    export CUDA_LIB_DIR="/usr/local/cuda-12.1/lib64"
-
-    export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
-    export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
-
-    if [[ -n "$OVERRIDE_GENCODE" ]]; then
-        export GENCODE=$OVERRIDE_GENCODE
-    fi
-
-    # all CUDA libs except CuDNN and CuBLAS
-    ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
-      | xargs -I {} bash -c \
-                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
-
-    # prune CuDNN and CuBLAS
-    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
-    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
-
-    #####################################################################################
-    # CUDA 12.1 prune visual tools
-    #####################################################################################
-    export CUDA_BASE="/usr/local/cuda-12.1/"
-    rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2023.1.0 $CUDA_BASE/nsight-systems-2023.1.2/
-}
-
-function prune_124 {
-  echo "Pruning CUDA 12.4"
-  #####################################################################################
-  # CUDA 12.4 prune static libs
-  #####################################################################################
-  export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
-  export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
-
-  export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
-  export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
-
-  if [[ -n "$OVERRIDE_GENCODE" ]]; then
-      export GENCODE=$OVERRIDE_GENCODE
-  fi
-  if [[ -n "$OVERRIDE_GENCODE_CUDNN" ]]; then
-      export GENCODE_CUDNN=$OVERRIDE_GENCODE_CUDNN
-  fi
-
-  # all CUDA libs except CuDNN and CuBLAS
-  ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
-      | xargs -I {} bash -c \
-                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
-
-  # prune CuDNN and CuBLAS
-  $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
-  $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
-
-  #####################################################################################
-  # CUDA 12.1 prune visual tools
-  #####################################################################################
-  export CUDA_BASE="/usr/local/cuda-12.4/"
-  rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.1.0 $CUDA_BASE/nsight-systems-2023.4.4/
-}
-
-# idiomatic parameter and option handling in sh
-while test $# -gt 0
-do
-    case "$1" in
-    11.8) install_118; prune_118
-        ;;
-    12.1) install_121; prune_121
-        ;;
-    12.4) install_124; prune_124
-        ;;
-    *) echo "bad argument $1"; exit 1
-        ;;
-    esac
-    shift
-done

.ci/docker/common/install_cuda_aarch64.sh

@@ -1,93 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-
-set -ex
-
-NCCL_VERSION=v2.21.5-1
-
-function install_cusparselt_052 {
-    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
-    mkdir tmp_cusparselt && pushd tmp_cusparselt
-    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-sbsa/libcusparse_lt-linux-sbsa-0.5.2.1-archive.tar.xz
-    tar xf libcusparse_lt-linux-sbsa-0.5.2.1-archive.tar.xz
-    cp -a libcusparse_lt-linux-sbsa-0.5.2.1-archive/include/* /usr/local/cuda/include/
-    cp -a libcusparse_lt-linux-sbsa-0.5.2.1-archive/lib/* /usr/local/cuda/lib64/
-    popd
-    rm -rf tmp_cusparselt
-}
-
-function install_124 {
-  echo "Installing CUDA 12.4.1 and cuDNN 9.1 and NCCL ${NCCL_VERSION} and cuSparseLt-0.5.2"
-  rm -rf /usr/local/cuda-12.4 /usr/local/cuda
-  # install CUDA 12.4.1 in the same container
-  wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux_sbsa.run
-  chmod +x cuda_12.4.1_550.54.15_linux_sbsa.run
-  ./cuda_12.4.1_550.54.15_linux_sbsa.run --toolkit --silent
-  rm -f cuda_12.4.1_550.54.15_linux_sbsa.run
-  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
-
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  mkdir tmp_cudnn && cd tmp_cudnn
-  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-sbsa/cudnn-linux-sbsa-9.1.0.70_cuda12-archive.tar.xz -O cudnn-linux-sbsa-9.1.0.70_cuda12-archive.tar.xz
-  tar xf cudnn-linux-sbsa-9.1.0.70_cuda12-archive.tar.xz
-  cp -a cudnn-linux-sbsa-9.1.0.70_cuda12-archive/include/* /usr/local/cuda/include/
-  cp -a cudnn-linux-sbsa-9.1.0.70_cuda12-archive/lib/* /usr/local/cuda/lib64/
-  cd ..
-  rm -rf tmp_cudnn
-
-  # NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
-  # Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
-  git clone -b ${NCCL_VERSION} --depth 1 https://github.com/NVIDIA/nccl.git
-  cd nccl && make -j src.build
-  cp -a build/include/* /usr/local/cuda/include/
-  cp -a build/lib/* /usr/local/cuda/lib64/
-  cd ..
-  rm -rf nccl
-
-  install_cusparselt_052
-
-  ldconfig
-}
-
-function prune_124 {
-  echo "Pruning CUDA 12.4"
-  #####################################################################################
-  # CUDA 12.4 prune static libs
-  #####################################################################################
-  export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
-  export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
-
-  export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
-  export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
-
-  if [[ -n "$OVERRIDE_GENCODE" ]]; then
-      export GENCODE=$OVERRIDE_GENCODE
-  fi
-
-  # all CUDA libs except CuDNN and CuBLAS
-  ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
-      | xargs -I {} bash -c \
-                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
-
-  # prune CuDNN and CuBLAS
-  $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
-  $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
-
-  #####################################################################################
-  # CUDA 12.1 prune visual tools
-  #####################################################################################
-  export CUDA_BASE="/usr/local/cuda-12.4/"
-  rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.1.0 $CUDA_BASE/nsight-systems-2023.4.4/
-}
-
-# idiomatic parameter and option handling in sh
-while test $# -gt 0
-do
-    case "$1" in
-    12.4) install_124; prune_124
-        ;;
-    *) echo "bad argument $1"; exit 1
-        ;;
-    esac
-    shift
-done

.ci/docker/common/install_cudss.sh

@@ -1,25 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-# cudss license: https://docs.nvidia.com/cuda/cudss/license.html
-mkdir tmp_cudss && cd tmp_cudss
-
-if [[ ${CUDA_VERSION:0:4} =~ ^12\.[1-4]$ ]]; then
-    arch_path='sbsa'
-    export TARGETARCH=${TARGETARCH:-$(uname -m)}
-    if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
-        arch_path='x86_64'
-    fi
-    CUDSS_NAME="libcudss-linux-${arch_path}-0.3.0.9_cuda12-archive"
-    curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudss/redist/libcudss/linux-${arch_path}/${CUDSS_NAME}.tar.xz
-
-    # only for cuda 12
-    tar xf ${CUDSS_NAME}.tar.xz
-    cp -a ${CUDSS_NAME}/include/* /usr/local/cuda/include/
-    cp -a ${CUDSS_NAME}/lib/* /usr/local/cuda/lib64/
-fi
-
-cd ..
-rm -rf tmp_cudss
-ldconfig

.ci/docker/common/install_cusparselt.sh

@@ -5,15 +5,7 @@ set -ex
 # cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
 mkdir tmp_cusparselt && cd tmp_cusparselt
 
-if [[ ${CUDA_VERSION:0:4} =~ ^12\.[2-4]$ ]]; then
-    arch_path='sbsa'
-    export TARGETARCH=${TARGETARCH:-$(uname -m)}
-    if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
-        arch_path='x86_64'
-    fi
-    CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.2.3-archive"
-    curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
-elif [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
+if [[ ${CUDA_VERSION:0:4} =~ ^12\.[1-4]$ ]]; then
     arch_path='sbsa'
     export TARGETARCH=${TARGETARCH:-$(uname -m)}
     if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then

.ci/docker/common/install_libpng.sh

@@ -1,23 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-
-set -ex
-
-LIBPNG_VERSION=1.6.37
-
-mkdir -p libpng
-pushd libpng
-
-wget http://download.sourceforge.net/libpng/libpng-$LIBPNG_VERSION.tar.gz
-tar -xvzf libpng-$LIBPNG_VERSION.tar.gz
-
-pushd libpng-$LIBPNG_VERSION
-
-./configure
-make
-make install
-
-popd
-
-popd
-rm -rf libpng

.ci/docker/common/install_magma.sh

@@ -1,29 +0,0 @@
-#!/usr/bin/env bash
-# Script used only in CD pipeline
-
-set -eou pipefail
-
-MAGMA_VERSION="2.5.2"
-
-function do_install() {
-    cuda_version=$1
-    cuda_version_nodot=${1/./}
-
-    MAGMA_VERSION="2.6.1"
-    magma_archive="magma-cuda${cuda_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
-
-    cuda_dir="/usr/local/cuda-${cuda_version}"
-    (
-        set -x
-        tmp_dir=$(mktemp -d)
-        pushd ${tmp_dir}
-        curl -OLs https://anaconda.org/pytorch/magma-cuda${cuda_version_nodot}/${MAGMA_VERSION}/download/linux-64/${magma_archive}
-        tar -xvf "${magma_archive}"
-        mkdir -p "${cuda_dir}/magma"
-        mv include "${cuda_dir}/magma/include"
-        mv lib "${cuda_dir}/magma/lib"
-        popd
-    )
-}
-
-do_install $1

.ci/docker/common/install_miopen.sh

@@ -1,169 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-
-set -ex
-
-ROCM_VERSION=$1
-
-if [[ -z $ROCM_VERSION ]]; then
-    echo "missing ROCM_VERSION"
-    exit 1;
-fi
-
-IS_UBUNTU=0
-ID=$(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=(${ROCM_VERSION})
-IFS="$save_IFS"
-if [[ ${#ROCM_VERSION_ARRAY[@]} == 2 ]]; then
-    ROCM_VERSION_MAJOR=${ROCM_VERSION_ARRAY[0]}
-    ROCM_VERSION_MINOR=${ROCM_VERSION_ARRAY[1]}
-    ROCM_VERSION_PATCH=0
-elif [[ ${#ROCM_VERSION_ARRAY[@]} == 3 ]]; then
-    ROCM_VERSION_MAJOR=${ROCM_VERSION_ARRAY[0]}
-    ROCM_VERSION_MINOR=${ROCM_VERSION_ARRAY[1]}
-    ROCM_VERSION_PATCH=${ROCM_VERSION_ARRAY[2]}
-else
-    echo "Unhandled ROCM_VERSION ${ROCM_VERSION}"
-    exit 1
-fi
-ROCM_INT=$(($ROCM_VERSION_MAJOR * 10000 + $ROCM_VERSION_MINOR * 100 + $ROCM_VERSION_PATCH))
-
-# Install custom MIOpen + COMgr for ROCm >= 4.0.1
-if [[ $ROCM_INT -lt 40001 ]]; then
-    echo "ROCm version < 4.0.1; will not install custom MIOpen"
-    exit 0
-fi
-
-# Function to retry functions that sometimes timeout or have flaky failures
-retry () {
-    $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
-}
-
-# Build custom MIOpen to use comgr for offline compilation.
-
-## Need a sanitized ROCM_VERSION without patchlevel; patchlevel version 0 must be added to paths.
-ROCM_DOTS=$(echo ${ROCM_VERSION} | tr -d -c '.' | wc -c)
-if [[ ${ROCM_DOTS} == 1 ]]; then
-    ROCM_VERSION_NOPATCH="${ROCM_VERSION}"
-    ROCM_INSTALL_PATH="/opt/rocm-${ROCM_VERSION}.0"
-else
-    ROCM_VERSION_NOPATCH="${ROCM_VERSION%.*}"
-    ROCM_INSTALL_PATH="/opt/rocm-${ROCM_VERSION}"
-fi
-
-# MIOPEN_USE_HIP_KERNELS is a Workaround for COMgr issues
-MIOPEN_CMAKE_COMMON_FLAGS="
--DMIOPEN_USE_COMGR=ON
--DMIOPEN_BUILD_DRIVER=OFF
-"
-# Pull MIOpen repo and set DMIOPEN_EMBED_DB based on ROCm version
-if [[ $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
-elif [[ $ROCM_INT -ge 60000 ]] && [[ $ROCM_INT -lt 60100 ]]; then
-    echo "ROCm 6.0 MIOpen does not need any patches, do not build from source"
-    exit 0
-elif [[ $ROCM_INT -ge 50700 ]] && [[ $ROCM_INT -lt 60000 ]]; then
-    echo "ROCm 5.7 MIOpen does not need any patches, do not build from source"
-    exit 0
-elif [[ $ROCM_INT -ge 50600 ]] && [[ $ROCM_INT -lt 50700 ]]; then
-    MIOPEN_BRANCH="release/rocm-rel-5.6-staging"
-elif [[ $ROCM_INT -ge 50500 ]] && [[ $ROCM_INT -lt 50600 ]]; then
-    MIOPEN_BRANCH="release/rocm-rel-5.5-gfx11"
-elif [[ $ROCM_INT -ge 50400 ]] && [[ $ROCM_INT -lt 50500 ]]; then
-    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
-    MIOPEN_BRANCH="release/rocm-rel-5.4-staging"
-elif [[ $ROCM_INT -ge 50300 ]] && [[ $ROCM_INT -lt 50400 ]]; then
-    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
-    MIOPEN_BRANCH="release/rocm-rel-5.3-staging"
-elif [[ $ROCM_INT -ge 50200 ]] && [[ $ROCM_INT -lt 50300 ]]; then
-    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
-    MIOPEN_BRANCH="release/rocm-rel-5.2-staging"
-elif [[ $ROCM_INT -ge 50100 ]] && [[ $ROCM_INT -lt 50200 ]]; then
-    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36"
-    MIOPEN_BRANCH="release/rocm-rel-5.1-staging"
-elif [[ $ROCM_INT -ge 50000 ]] && [[ $ROCM_INT -lt 50100 ]]; then
-    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36"
-    MIOPEN_BRANCH="release/rocm-rel-5.0-staging"
-else
-    echo "Unhandled ROCM_VERSION ${ROCM_VERSION}"
-    exit 1
-fi
-
-
-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
-    sed -i '/rocMLIR/d' requirements.txt
-elif [[ $ROCM_INT -ge 50200 ]] && [[ $ROCM_INT -lt 50400 ]]; then
-    sed -i '/llvm-project-mlir/d' requirements.txt
-fi
-## MIOpen minimum requirements
-cmake -P install_deps.cmake --minimum
-
-# clean up since CI runner was running out of disk space
-rm -rf /tmp/*
-if [[ ${IS_UBUNTU} == 1 ]]; then
-  apt-get autoclean && apt-get clean
-  rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
-else
-  yum clean all
-  rm -rf /var/cache/yum
-  rm -rf /var/lib/yum/yumdb
-  rm -rf /var/lib/yum/history
-fi
-
-## Build MIOpen
-mkdir -p build
-cd build
-PKG_CONFIG_PATH=/usr/local/lib/pkgconfig CXX=${ROCM_INSTALL_PATH}/llvm/bin/clang++ cmake .. \
-    ${MIOPEN_CMAKE_COMMON_FLAGS} \
-    ${MIOPEN_CMAKE_DB_FLAGS} \
-    -DCMAKE_PREFIX_PATH="${ROCM_INSTALL_PATH}/hip;${ROCM_INSTALL_PATH}"
-make MIOpen -j $(nproc)
-
-# Build MIOpen package
-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
-  sudo dpkg -i miopen-hip*.deb
-else
-  yum install -y miopen-*.rpm
-fi
-
-popd
-rm -rf MIOpen

.ci/docker/common/install_mkl.sh

@@ -1,16 +0,0 @@
-#!/bin/bash
-set -ex
-
-# MKL
-MKL_VERSION=2024.2.0
-
-MKLROOT=/opt/intel
-mkdir -p ${MKLROOT}
-pushd /tmp
-
-python3 -mpip install wheel
-python3 -mpip download -d . mkl-static==${MKL_VERSION}
-python3 -m wheel unpack mkl_static-${MKL_VERSION}-py2.py3-none-manylinux1_x86_64.whl
-python3 -m wheel unpack mkl_include-${MKL_VERSION}-py2.py3-none-manylinux1_x86_64.whl
-mv mkl_static-${MKL_VERSION}/mkl_static-${MKL_VERSION}.data/data/lib ${MKLROOT}
-mv mkl_include-${MKL_VERSION}/mkl_include-${MKL_VERSION}.data/data/include ${MKLROOT}

.ci/docker/common/install_mnist.sh

@@ -1,13 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-
-set -ex
-
-mkdir -p /usr/local/mnist/
-
-cd /usr/local/mnist
-
-for img in train-images-idx3-ubyte.gz train-labels-idx1-ubyte.gz t10k-images-idx3-ubyte.gz t10k-labels-idx1-ubyte.gz; do
-  wget -q https://ossci-datasets.s3.amazonaws.com/mnist/$img
-  gzip -d $img
-done

.ci/docker/common/install_nvpl.sh

@@ -1,20 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-function install_nvpl {
-
-    mkdir -p /opt/nvpl/lib /opt/nvpl/include
-
-    wget https://developer.download.nvidia.com/compute/nvpl/redist/nvpl_blas/linux-sbsa/nvpl_blas-linux-sbsa-0.3.0-archive.tar.xz
-    tar xf nvpl_blas-linux-sbsa-0.3.0-archive.tar.xz
-    cp -r nvpl_blas-linux-sbsa-0.3.0-archive/lib/* /opt/nvpl/lib/
-    cp -r nvpl_blas-linux-sbsa-0.3.0-archive/include/* /opt/nvpl/include/
-
-    wget https://developer.download.nvidia.com/compute/nvpl/redist/nvpl_lapack/linux-sbsa/nvpl_lapack-linux-sbsa-0.2.3.1-archive.tar.xz
-    tar xf nvpl_lapack-linux-sbsa-0.2.3.1-archive.tar.xz
-    cp -r nvpl_lapack-linux-sbsa-0.2.3.1-archive/lib/* /opt/nvpl/lib/
-    cp -r nvpl_lapack-linux-sbsa-0.2.3.1-archive/include/* /opt/nvpl/include/
-}
-
-install_nvpl

.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 onnx==1.16.2
-pip_install onnxscript==0.1.0.dev20240831 --no-deps
+pip_install onnxruntime==1.18
+pip_install onnx==1.16.0
+# 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_openblas.sh

@@ -1,22 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-
-set -ex
-
-cd /
-git clone https://github.com/OpenMathLib/OpenBLAS.git -b v0.3.25 --depth 1 --shallow-submodules
-
-
-OPENBLAS_BUILD_FLAGS="
-NUM_THREADS=128
-USE_OPENMP=1
-NO_SHARED=0
-DYNAMIC_ARCH=1
-TARGET=ARMV8
-CFLAGS=-O3
-"
-
-OPENBLAS_CHECKOUT_DIR="OpenBLAS"
-
-make -j8 ${OPENBLAS_BUILD_FLAGS} -C ${OPENBLAS_CHECKOUT_DIR}
-make -j8 ${OPENBLAS_BUILD_FLAGS} install -C ${OPENBLAS_CHECKOUT_DIR}

.ci/docker/common/install_patchelf.sh

@@ -1,16 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-
-set -ex
-
-# Pin the version to latest release 0.17.2, building newer commit starts
-# to fail on the current image
-git clone -b 0.17.2 --single-branch https://github.com/NixOS/patchelf
-cd patchelf
-sed -i 's/serial/parallel/g' configure.ac
-./bootstrap.sh
-./configure
-make
-make install
-cd ..
-rm -rf patchelf

.ci/docker/common/install_rocm_drm.sh

@@ -1,150 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-
-###########################
-### prereqs
-###########################
-# Install Python packages depending on the base OS
-ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
-case "$ID" in
-  ubuntu)
-    apt-get update -y
-    apt-get install -y libpciaccess-dev pkg-config
-    apt-get clean
-    ;;
-  centos)
-    yum install -y libpciaccess-devel pkgconfig
-    ;;
-  *)
-    echo "Unable to determine OS..."
-    exit 1
-    ;;
-esac
-python3 -m pip install meson ninja
-
-###########################
-### clone repo
-###########################
-GIT_SSL_NO_VERIFY=true git clone https://gitlab.freedesktop.org/mesa/drm.git
-pushd drm
-
-###########################
-### patch
-###########################
-patch -p1 <<'EOF'
-diff --git a/amdgpu/amdgpu_asic_id.c b/amdgpu/amdgpu_asic_id.c
-index a5007ffc..13fa07fc 100644
---- a/amdgpu/amdgpu_asic_id.c
-+++ b/amdgpu/amdgpu_asic_id.c
-@@ -22,6 +22,13 @@
-  *
-  */
-
-+#define _XOPEN_SOURCE 700
-+#define _LARGEFILE64_SOURCE
-+#define _FILE_OFFSET_BITS 64
-+#include <ftw.h>
-+#include <link.h>
-+#include <limits.h>
-+
- #include <ctype.h>
- #include <stdio.h>
- #include <stdlib.h>
-@@ -34,6 +41,19 @@
- #include "amdgpu_drm.h"
- #include "amdgpu_internal.h"
-
-+static char *amdgpuids_path = NULL;
-+static const char* amdgpuids_path_msg = NULL;
-+
-+static int check_for_location_of_amdgpuids(const char *filepath, const struct stat *info, const int typeflag, struct FTW *pathinfo)
-+{
-+	if (typeflag == FTW_F && strstr(filepath, "amdgpu.ids")) {
-+		amdgpuids_path = strdup(filepath);
-+		return 1;
-+	}
-+
-+	return 0;
-+}
-+
- static int parse_one_line(struct amdgpu_device *dev, const char *line)
- {
- 	char *buf, *saveptr;
-@@ -113,10 +133,46 @@ void amdgpu_parse_asic_ids(struct amdgpu_device *dev)
- 	int line_num = 1;
- 	int r = 0;
-
-+	// attempt to find typical location for amdgpu.ids file
- 	fp = fopen(AMDGPU_ASIC_ID_TABLE, "r");
-+
-+	// if it doesn't exist, search
-+	if (!fp) {
-+
-+	char self_path[ PATH_MAX ];
-+	ssize_t count;
-+	ssize_t i;
-+
-+	count = readlink( "/proc/self/exe", self_path, PATH_MAX );
-+	if (count > 0) {
-+		self_path[count] = '\0';
-+
-+		// remove '/bin/python' from self_path
-+		for (i=count; i>0; --i) {
-+			if (self_path[i] == '/') break;
-+			self_path[i] = '\0';
-+		}
-+		self_path[i] = '\0';
-+		for (; i>0; --i) {
-+			if (self_path[i] == '/') break;
-+			self_path[i] = '\0';
-+		}
-+		self_path[i] = '\0';
-+
-+		if (1 == nftw(self_path, check_for_location_of_amdgpuids, 5, FTW_PHYS)) {
-+			fp = fopen(amdgpuids_path, "r");
-+			amdgpuids_path_msg = amdgpuids_path;
-+		}
-+	}
-+
-+	}
-+	else {
-+		amdgpuids_path_msg = AMDGPU_ASIC_ID_TABLE;
-+	}
-+
-+	// both hard-coded location and search have failed
- 	if (!fp) {
--		fprintf(stderr, "%s: %s\n", AMDGPU_ASIC_ID_TABLE,
--			strerror(errno));
-+		fprintf(stderr, "amdgpu.ids: No such file or directory\n");
- 		return;
- 	}
-
-@@ -132,7 +188,7 @@ void amdgpu_parse_asic_ids(struct amdgpu_device *dev)
- 			continue;
- 		}
-
--		drmMsg("%s version: %s\n", AMDGPU_ASIC_ID_TABLE, line);
-+		drmMsg("%s version: %s\n", amdgpuids_path_msg, line);
- 		break;
- 	}
-
-@@ -150,7 +206,7 @@ void amdgpu_parse_asic_ids(struct amdgpu_device *dev)
-
- 	if (r == -EINVAL) {
- 		fprintf(stderr, "Invalid format: %s: line %d: %s\n",
--			AMDGPU_ASIC_ID_TABLE, line_num, line);
-+			amdgpuids_path_msg, line_num, line);
- 	} else if (r && r != -EAGAIN) {
- 		fprintf(stderr, "%s: Cannot parse ASIC IDs: %s\n",
- 			__func__, strerror(-r));
-EOF
-
-###########################
-### build
-###########################
-meson builddir --prefix=/opt/amdgpu
-pushd builddir
-ninja install
-
-popd
-popd

.ci/docker/common/install_rocm_magma.sh

@@ -1,11 +1,7 @@
 #!/bin/bash
-# Script used in CI and CD pipeline
 
 set -ex
 
-
-MKLROOT=${MKLROOT:-/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION}
-
 # "install" hipMAGMA into /opt/rocm/magma by copying after build
 git clone https://bitbucket.org/icl/magma.git
 pushd magma
@@ -15,10 +11,7 @@ git checkout a1625ff4d9bc362906bd01f805dbbe12612953f6
 
 cp make.inc-examples/make.inc.hip-gcc-mkl make.inc
 echo 'LIBDIR += -L$(MKLROOT)/lib' >> make.inc
-if [[ -f "${MKLROOT}/lib/libmkl_core.a" ]]; then
-    echo 'LIB = -Wl,--start-group -lmkl_gf_lp64 -lmkl_gnu_thread -lmkl_core -Wl,--end-group -lpthread -lstdc++ -lm -lgomp -lhipblas -lhipsparse' >> make.inc
-fi
-echo 'LIB += -Wl,--enable-new-dtags -Wl,--rpath,/opt/rocm/lib -Wl,--rpath,$(MKLROOT)/lib -Wl,--rpath,/opt/rocm/magma/lib -ldl' >> make.inc
+echo 'LIB += -Wl,--enable-new-dtags -Wl,--rpath,/opt/rocm/lib -Wl,--rpath,$(MKLROOT)/lib -Wl,--rpath,/opt/rocm/magma/lib' >> make.inc
 echo 'DEVCCFLAGS += --gpu-max-threads-per-block=256' >> make.inc
 export PATH="${PATH}:/opt/rocm/bin"
 if [[ -n "$PYTORCH_ROCM_ARCH" ]]; then
@@ -32,7 +25,7 @@ done
 # hipcc with openmp flag may cause isnan() on __device__ not to be found; depending on context, compiler may attempt to match with host definition
 sed -i 's/^FOPENMP/#FOPENMP/g' make.inc
 make -f make.gen.hipMAGMA -j $(nproc)
-LANG=C.UTF-8 make lib/libmagma.so -j $(nproc) MKLROOT="${MKLROOT}"
-make testing/testing_dgemm -j $(nproc) MKLROOT="${MKLROOT}"
+LANG=C.UTF-8 make lib/libmagma.so -j $(nproc) MKLROOT=/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION
+make testing/testing_dgemm -j $(nproc) MKLROOT=/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION
 popd
 mv magma /opt/rocm

.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 "${XPU_VERSION}" ]; then
   TRITON_REPO="https://github.com/intel/intel-xpu-backend-for-triton"
   TRITON_TEXT_FILE="triton-xpu"
 else
@@ -38,33 +41,19 @@ if [ -z "${MAX_JOBS}" ]; then
     export MAX_JOBS=$(nproc)
 fi
 
-# Git checkout triton
-mkdir /var/lib/jenkins/triton
-chown -R jenkins /var/lib/jenkins/triton
-chgrp -R jenkins /var/lib/jenkins/triton
-pushd /var/lib/jenkins/
-
-as_jenkins git clone ${TRITON_REPO} triton
-cd triton
-as_jenkins git checkout ${TRITON_PINNED_COMMIT}
-cd python
-
-# TODO: remove patch setup.py once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
-as_jenkins sed -i -e 's/https:\/\/tritonlang.blob.core.windows.net\/llvm-builds/https:\/\/oaitriton.blob.core.windows.net\/public\/llvm-builds/g' setup.py
-
 if [ -n "${UBUNTU_VERSION}" ] && [ -n "${GCC_VERSION}" ] && [[ "${GCC_VERSION}" == "7" ]]; then
   # Triton needs at least gcc-9 to build
   apt-get install -y g++-9
 
-  CXX=g++-9 pip_install -e .
+  CXX=g++-9 pip_install "git+${TRITON_REPO}@${TRITON_PINNED_COMMIT}#subdirectory=python"
 elif [ -n "${UBUNTU_VERSION}" ] && [ -n "${CLANG_VERSION}" ]; then
   # Triton needs <filesystem> which surprisingly is not available with clang-9 toolchain
   add-apt-repository -y ppa:ubuntu-toolchain-r/test
   apt-get install -y g++-9
 
-  CXX=g++-9 pip_install -e .
+  CXX=g++-9 pip_install "git+${TRITON_REPO}@${TRITON_PINNED_COMMIT}#subdirectory=python"
 else
-  pip_install -e .
+  pip_install "git+${TRITON_REPO}@${TRITON_PINNED_COMMIT}#subdirectory=python"
 fi
 
 if [ -n "${CONDA_CMAKE}" ]; then

.ci/docker/common/install_xpu.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 set -xe
-# Script used in CI and CD pipeline
+
 
 # Intel® software for general purpose GPU capabilities.
 # Refer to https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html
@@ -8,23 +8,19 @@ set -xe
 # Users should update to the latest version as it becomes available
 
 function install_ubuntu() {
-    . /etc/os-release
-    if [[ ! " jammy " =~ " ${VERSION_CODENAME} " ]]; then
-        echo "Ubuntu version ${VERSION_CODENAME} not supported"
-        exit
-    fi
-
     apt-get update -y
     apt-get install -y gpg-agent wget
-    # To add the online network package repository for the GPU Driver
+
+    # Set up the repository. To do this, download the key to the system keyring
     wget -qO - https://repositories.intel.com/gpu/intel-graphics.key \
-        | gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
+        | gpg --dearmor --output /usr/share/keyrings/intel-graphics.gpg
+    wget -qO - https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
+        | gpg --dearmor --output /usr/share/keyrings/intel-for-pytorch-gpu-dev-keyring.gpg
+
+    # Add the signed entry to APT sources and configure the APT client to use the Intel repository
     echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] \
-        https://repositories.intel.com/gpu/ubuntu ${VERSION_CODENAME}${XPU_DRIVER_VERSION} unified" \
-        | tee /etc/apt/sources.list.d/intel-gpu-${VERSION_CODENAME}.list
-    # To add the online network network package repository for the Intel Support Packages
-    wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
-        | gpg --dearmor > /usr/share/keyrings/intel-for-pytorch-gpu-dev-keyring.gpg
+        https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" \
+        | tee /etc/apt/sources.list.d/intel-gpu-jammy.list
     echo "deb [signed-by=/usr/share/keyrings/intel-for-pytorch-gpu-dev-keyring.gpg] \
         https://apt.repos.intel.com/intel-for-pytorch-gpu-dev all main" \
         | tee /etc/apt/sources.list.d/intel-for-pytorch-gpu-dev.list
@@ -45,9 +41,9 @@ function install_ubuntu() {
     apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev level-zero-dev
     # Install Intel Support Packages
     if [ -n "$XPU_VERSION" ]; then
-        apt-get install -y intel-for-pytorch-gpu-dev-${XPU_VERSION} intel-pti-dev
+        apt-get install -y intel-for-pytorch-gpu-dev-${XPU_VERSION}
     else
-        apt-get install -y intel-for-pytorch-gpu-dev intel-pti-dev
+        apt-get install -y intel-for-pytorch-gpu-dev
     fi
 
     # Cleanup
@@ -55,49 +51,44 @@ function install_ubuntu() {
     rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
 }
 
-function install_rhel() {
-    . /etc/os-release
-    if [[ "${ID}" == "rhel" ]]; then
-        if [[ ! " 8.6 8.8 8.9 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
-            echo "RHEL version ${VERSION_ID} not supported"
-            exit
-        fi
-    elif [[ "${ID}" == "almalinux" ]]; then
-        # Workaround for almalinux8 which used by quay.io/pypa/manylinux_2_28_x86_64
-        VERSION_ID="8.6"
-    fi
-
+function install_centos() {
     dnf install -y 'dnf-command(config-manager)'
-    # To add the online network package repository for the GPU Driver
     dnf config-manager --add-repo \
-        https://repositories.intel.com/gpu/rhel/${VERSION_ID}${XPU_DRIVER_VERSION}/unified/intel-gpu-${VERSION_ID}.repo
-    # To add the online network network package repository for the Intel Support Packages
-    tee > /etc/yum.repos.d/intel-for-pytorch-gpu-dev.repo << EOF
-[intel-for-pytorch-gpu-dev]
-name=Intel for Pytorch GPU dev repository
-baseurl=https://yum.repos.intel.com/intel-for-pytorch-gpu-dev
+        https://repositories.intel.com/gpu/rhel/8.6/production/2328/unified/intel-gpu-8.6.repo
+    # To add the EPEL repository needed for DKMS
+    dnf -y install https://dl.fedoraproject.org/pub/epel/epel-release-latest-8.noarch.rpm
+        # https://dl.fedoraproject.org/pub/epel/epel-release-latest-9.noarch.rpm
+
+    # Create the YUM repository file in the /temp directory as a normal user
+    tee > /tmp/oneAPI.repo << EOF
+[oneAPI]
+name=Intel® oneAPI repository
+baseurl=https://yum.repos.intel.com/oneapi
 enabled=1
 gpgcheck=1
 repo_gpgcheck=1
 gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
 EOF
 
+    # Move the newly created oneAPI.repo file to the YUM configuration directory /etc/yum.repos.d
+    mv /tmp/oneAPI.repo /etc/yum.repos.d
+
     # The xpu-smi packages
-    dnf install -y xpu-smi
+    dnf install -y flex bison xpu-smi
     # Compute and Media Runtimes
-    dnf install --skip-broken -y \
+    dnf install -y \
         intel-opencl intel-media intel-mediasdk libmfxgen1 libvpl2\
         level-zero intel-level-zero-gpu mesa-dri-drivers mesa-vulkan-drivers \
         mesa-vdpau-drivers libdrm mesa-libEGL mesa-libgbm mesa-libGL \
         mesa-libxatracker libvpl-tools intel-metrics-discovery \
         intel-metrics-library intel-igc-core intel-igc-cm \
-        libva libva-utils intel-gmmlib libmetee intel-gsc intel-ocloc
+        libva libva-utils intel-gmmlib libmetee intel-gsc intel-ocloc hwinfo clinfo
     # Development packages
     dnf install -y --refresh \
         intel-igc-opencl-devel level-zero-devel intel-gsc-devel libmetee-devel \
         level-zero-devel
-    # Install Intel Support Packages
-    yum install -y intel-for-pytorch-gpu-dev intel-pti-dev
+    # Install Intel® oneAPI Base Toolkit
+    dnf install intel-basekit -y
 
     # Cleanup
     dnf clean all
@@ -106,41 +97,6 @@ EOF
     rm -rf /var/lib/yum/history
 }
 
-function install_sles() {
-    . /etc/os-release
-    VERSION_SP=${VERSION_ID//./sp}
-    if [[ ! " 15sp4 15sp5 " =~ " ${VERSION_SP} " ]]; then
-        echo "SLES version ${VERSION_ID} not supported"
-        exit
-    fi
-
-    # To add the online network package repository for the GPU Driver
-    zypper addrepo -f -r \
-        https://repositories.intel.com/gpu/sles/${VERSION_SP}${XPU_DRIVER_VERSION}/unified/intel-gpu-${VERSION_SP}.repo
-    rpm --import https://repositories.intel.com/gpu/intel-graphics.key
-    # To add the online network network package repository for the Intel Support Packages
-    zypper addrepo https://yum.repos.intel.com/intel-for-pytorch-gpu-dev intel-for-pytorch-gpu-dev
-    rpm --import https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
-
-    # The xpu-smi packages
-    zypper install -y lsb-release flex bison xpu-smi
-    # Compute and Media Runtimes
-    zypper install -y intel-level-zero-gpu level-zero intel-gsc intel-opencl intel-ocloc \
-        intel-media-driver libigfxcmrt7 libvpl2 libvpl-tools libmfxgen1 libmfx1
-    # Development packages
-    zypper install -y libigdfcl-devel intel-igc-cm libigfxcmrt-devel level-zero-devel
-
-    # Install Intel Support Packages
-    zypper install -y intel-for-pytorch-gpu-dev intel-pti-dev
-
-}
-
-# Default use GPU driver LTS releases
-XPU_DRIVER_VERSION="/lts/2350"
-if [[ "${XPU_DRIVER_TYPE,,}" == "rolling" ]]; then
-    # Use GPU driver rolling releases
-    XPU_DRIVER_VERSION=""
-fi
 
 # The installation depends on the base OS
 ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
@@ -148,11 +104,8 @@ case "$ID" in
     ubuntu)
         install_ubuntu
     ;;
-    rhel|almalinux)
-        install_rhel
-    ;;
-    sles)
-        install_sles
+    centos)
+        install_centos
     ;;
     *)
         echo "Unable to determine OS..."

.ci/docker/conda/Dockerfile

@@ -1,100 +0,0 @@
-ARG CUDA_VERSION=10.2
-ARG BASE_TARGET=cuda${CUDA_VERSION}
-FROM centos:7 as base
-
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-
-ARG DEVTOOLSET_VERSION=9
-RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
-RUN yum update -y
-RUN yum install -y wget curl perl util-linux xz bzip2 git patch which unzip
-# Just add everything as a safe.directory for git since these will be used in multiple places with git
-RUN git config --global --add safe.directory '*'
-RUN yum install -y yum-utils centos-release-scl
-RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
-RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
-RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
-# EPEL for cmake
-RUN yum --enablerepo=extras install -y epel-release
-
-# cmake
-RUN yum install -y cmake3 && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
-
-RUN yum install -y autoconf aclocal automake make sudo
-RUN rm -rf /usr/local/cuda-*
-
-FROM base as patchelf
-# Install patchelf
-ADD ./common/install_patchelf.sh install_patchelf.sh
-RUN bash ./install_patchelf.sh && rm install_patchelf.sh && cp $(which patchelf) /patchelf
-
-FROM base as openssl
-# Install openssl
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-
-FROM base as conda
-# Install Anaconda
-ADD ./common/install_conda_docker.sh install_conda.sh
-RUN bash ./install_conda.sh && rm install_conda.sh
-
-# Install CUDA
-FROM base as cuda
-ARG CUDA_VERSION=10.2
-RUN rm -rf /usr/local/cuda-*
-ADD ./common/install_cuda.sh install_cuda.sh
-ENV CUDA_HOME=/usr/local/cuda-${CUDA_VERSION}
-# Preserve CUDA_VERSION for the builds
-ENV CUDA_VERSION=${CUDA_VERSION}
-# Make things in our path by default
-ENV PATH=/usr/local/cuda-${CUDA_VERSION}/bin:$PATH
-
-FROM cuda as cuda11.8
-RUN bash ./install_cuda.sh 11.8
-ENV DESIRED_CUDA=11.8
-
-FROM cuda as cuda12.1
-RUN bash ./install_cuda.sh 12.1
-ENV DESIRED_CUDA=12.1
-
-FROM cuda as cuda12.4
-RUN bash ./install_cuda.sh 12.4
-ENV DESIRED_CUDA=12.4
-
-# Install MNIST test data
-FROM base as mnist
-ADD ./common/install_mnist.sh install_mnist.sh
-RUN bash ./install_mnist.sh
-
-FROM base as all_cuda
-COPY --from=cuda11.8  /usr/local/cuda-11.8 /usr/local/cuda-11.8
-COPY --from=cuda12.1  /usr/local/cuda-12.1 /usr/local/cuda-12.1
-COPY --from=cuda12.4  /usr/local/cuda-12.4 /usr/local/cuda-12.4
-
-# Final step
-FROM ${BASE_TARGET} as final
-COPY --from=openssl            /opt/openssl           /opt/openssl
-COPY --from=patchelf           /patchelf              /usr/local/bin/patchelf
-COPY --from=conda              /opt/conda             /opt/conda
-
-# Add jni.h for java host build.
-COPY ./common/install_jni.sh install_jni.sh
-COPY ./java/jni.h jni.h
-RUN bash ./install_jni.sh && rm install_jni.sh
-
-ENV  PATH /opt/conda/bin:$PATH
-COPY --from=mnist  /usr/local/mnist /usr/local/mnist
-RUN rm -rf /usr/local/cuda
-RUN chmod o+rw /usr/local
-RUN touch /.condarc && \
-    chmod o+rw /.condarc && \
-    chmod -R o+rw /opt/conda

.ci/docker/conda/build.sh

@@ -1,76 +0,0 @@
-#!/usr/bin/env bash
-# Script used only in CD pipeline
-
-set -eou pipefail
-
-image="$1"
-shift
-
-if [ -z "${image}" ]; then
-  echo "Usage: $0 IMAGE"
-  exit 1
-fi
-
-DOCKER_IMAGE_NAME="pytorch/${image}"
-
-
-export DOCKER_BUILDKIT=1
-TOPDIR=$(git rev-parse --show-toplevel)
-
-CUDA_VERSION=${CUDA_VERSION:-12.1}
-
-case ${CUDA_VERSION} in
-  cpu)
-    BASE_TARGET=base
-    DOCKER_TAG=cpu
-    ;;
-  all)
-    BASE_TARGET=all_cuda
-    DOCKER_TAG=latest
-    ;;
-  *)
-    BASE_TARGET=cuda${CUDA_VERSION}
-    DOCKER_TAG=cuda${CUDA_VERSION}
-    ;;
-esac
-
-
-(
-  set -x
-  docker build \
-    --target final \
-    --progress plain \
-    --build-arg "BASE_TARGET=${BASE_TARGET}" \
-    --build-arg "CUDA_VERSION=${CUDA_VERSION}" \
-    --build-arg "DEVTOOLSET_VERSION=9" \
-    -t ${DOCKER_IMAGE_NAME} \
-    $@ \
-    -f "${TOPDIR}/.ci/docker/conda/Dockerfile" \
-    ${TOPDIR}/.ci/docker/
-)
-
-if [[ "${DOCKER_TAG}" =~ ^cuda* ]]; then
-  # Test that we're using the right CUDA compiler
-  (
-    set -x
-    docker run --rm "${DOCKER_IMAGE_NAME}" nvcc --version | grep "cuda_${CUDA_VERSION}"
-  )
-fi
-
-GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
-GIT_BRANCH_NAME=${GITHUB_REF##*/}
-GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
-DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE_NAME}-${GIT_BRANCH_NAME}
-DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE_NAME}-${GIT_COMMIT_SHA}
-if [[ "${WITH_PUSH:-}" == true ]]; then
-  (
-    set -x
-    docker push "${DOCKER_IMAGE_NAME}"
-    if [[ -n ${GITHUB_REF} ]]; then
-        docker tag ${DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_BRANCH_TAG}
-        docker tag ${DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_SHA_TAG}
-        docker push "${DOCKER_IMAGE_BRANCH_TAG}"
-        docker push "${DOCKER_IMAGE_SHA_TAG}"
-    fi
-  )
-fi

.ci/docker/libtorch/Dockerfile

@@ -1,107 +0,0 @@
-ARG BASE_TARGET=base
-ARG GPU_IMAGE=ubuntu:20.04
-FROM ${GPU_IMAGE} as base
-
-ENV DEBIAN_FRONTEND=noninteractive
-
-RUN apt-get clean && apt-get update
-RUN apt-get install -y curl locales g++ git-all autoconf automake make cmake wget unzip sudo
-# Just add everything as a safe.directory for git since these will be used in multiple places with git
-RUN git config --global --add safe.directory '*'
-
-RUN locale-gen en_US.UTF-8
-
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-
-# Install openssl
-FROM base as openssl
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-
-# Install python
-FROM base as python
-ADD common/install_cpython.sh install_cpython.sh
-RUN apt-get update -y && \
-    apt-get install build-essential gdb lcov libbz2-dev libffi-dev \
-        libgdbm-dev liblzma-dev libncurses5-dev libreadline6-dev \
-        libsqlite3-dev libssl-dev lzma lzma-dev tk-dev uuid-dev zlib1g-dev -y && \
-    bash ./install_cpython.sh && \
-    rm install_cpython.sh && \
-    apt-get clean
-
-FROM base as conda
-ADD ./common/install_conda_docker.sh install_conda.sh
-RUN bash ./install_conda.sh && rm install_conda.sh
-
-FROM base as cpu
-# Install Anaconda
-COPY --from=conda /opt/conda /opt/conda
-# Install python
-COPY --from=python /opt/python    /opt/python
-COPY --from=python /opt/_internal /opt/_internal
-ENV PATH=/opt/conda/bin:/usr/local/cuda/bin:$PATH
-# Install MKL
-ADD ./common/install_mkl.sh install_mkl.sh
-RUN bash ./install_mkl.sh && rm install_mkl.sh
-
-FROM cpu as cuda
-ADD ./common/install_cuda.sh install_cuda.sh
-ADD ./common/install_magma.sh install_magma.sh
-ENV CUDA_HOME /usr/local/cuda
-
-FROM cuda as cuda11.8
-RUN bash ./install_cuda.sh 11.8
-RUN bash ./install_magma.sh 11.8
-RUN ln -sf /usr/local/cuda-11.8 /usr/local/cuda
-
-FROM cuda as cuda12.1
-RUN bash ./install_cuda.sh 12.1
-RUN bash ./install_magma.sh 12.1
-RUN ln -sf /usr/local/cuda-12.1 /usr/local/cuda
-
-FROM cuda as cuda12.4
-RUN bash ./install_cuda.sh 12.4
-RUN bash ./install_magma.sh 12.4
-RUN ln -sf /usr/local/cuda-12.4 /usr/local/cuda
-
-FROM cpu as rocm
-ARG PYTORCH_ROCM_ARCH
-ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
-ENV MKLROOT /opt/intel
-# Adding ROCM_PATH env var so that LoadHip.cmake (even with logic updated for ROCm6.0)
-# find HIP works for ROCm5.7. Not needed for ROCm6.0 and above.
-# Remove below when ROCm5.7 is not in support matrix anymore.
-ENV ROCM_PATH /opt/rocm
-# No need to install ROCm as base docker image should have full ROCm install
-#ADD ./common/install_rocm.sh install_rocm.sh
-ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
-ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
-# gfortran and python needed for building magma from source for ROCm
-RUN apt-get update -y && \
-    apt-get install gfortran -y && \
-    apt-get install python -y && \
-    apt-get clean
-
-RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
-RUN bash ./install_rocm_magma.sh && rm install_rocm_magma.sh
-
-# Install AOTriton
-COPY ./common/common_utils.sh common_utils.sh
-COPY ./aotriton_version.txt aotriton_version.txt
-COPY ./common/install_aotriton.sh install_aotriton.sh
-RUN bash ./install_aotriton.sh /opt/rocm && rm install_aotriton.sh aotriton_version.txt
-ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
-
-FROM ${BASE_TARGET} as final
-COPY --from=openssl            /opt/openssl           /opt/openssl
-# Install patchelf
-ADD ./common/install_patchelf.sh install_patchelf.sh
-RUN bash ./install_patchelf.sh && rm install_patchelf.sh
-# Install Anaconda
-COPY --from=conda /opt/conda /opt/conda
-# Install python
-COPY --from=python /opt/python    /opt/python
-COPY --from=python /opt/_internal /opt/_internal
-ENV PATH=/opt/conda/bin:/usr/local/cuda/bin:$PATH

.ci/docker/libtorch/build.sh

@@ -1,93 +0,0 @@
-#!/usr/bin/env bash
-# Script used only in CD pipeline
-
-set -eou pipefail
-
-image="$1"
-shift
-
-if [ -z "${image}" ]; then
-  echo "Usage: $0 IMAGE"
-  exit 1
-fi
-
-DOCKER_IMAGE="pytorch/${image}"
-
-TOPDIR=$(git rev-parse --show-toplevel)
-
-GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
-GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
-
-WITH_PUSH=${WITH_PUSH:-}
-
-DOCKER=${DOCKER:-docker}
-
-case ${GPU_ARCH_TYPE} in
-    cpu)
-        BASE_TARGET=cpu
-        DOCKER_TAG=cpu
-        GPU_IMAGE=ubuntu:20.04
-        DOCKER_GPU_BUILD_ARG=""
-        ;;
-    cuda)
-        BASE_TARGET=cuda${GPU_ARCH_VERSION}
-        DOCKER_TAG=cuda${GPU_ARCH_VERSION}
-        GPU_IMAGE=ubuntu:20.04
-        DOCKER_GPU_BUILD_ARG=""
-        ;;
-    rocm)
-        BASE_TARGET=rocm
-        DOCKER_TAG=rocm${GPU_ARCH_VERSION}
-        GPU_IMAGE=rocm/dev-ubuntu-20.04:${GPU_ARCH_VERSION}-complete
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx1030;gfx1100"
-        ROCM_REGEX="([0-9]+)\.([0-9]+)[\.]?([0-9]*)"
-        if [[ $GPU_ARCH_VERSION =~ $ROCM_REGEX ]]; then
-            ROCM_VERSION_INT=$((${BASH_REMATCH[1]}*10000 + ${BASH_REMATCH[2]}*100 + ${BASH_REMATCH[3]:-0}))
-        else
-            echo "ERROR: rocm regex failed"
-            exit 1
-        fi
-        if [[ $ROCM_VERSION_INT -ge 60000 ]]; then
-            PYTORCH_ROCM_ARCH+=";gfx942"
-        fi
-        DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}"
-        ;;
-    *)
-        echo "ERROR: Unrecognized GPU_ARCH_TYPE: ${GPU_ARCH_TYPE}"
-        exit 1
-        ;;
-esac
-
-
-(
-    set -x
-    DOCKER_BUILDKIT=1 ${DOCKER} build \
-         --target final \
-        ${DOCKER_GPU_BUILD_ARG} \
-        --build-arg "GPU_IMAGE=${GPU_IMAGE}" \
-        --build-arg "BASE_TARGET=${BASE_TARGET}" \
-        -t "${DOCKER_IMAGE}" \
-        $@ \
-        -f "${TOPDIR}/.ci/docker/libtorch/Dockerfile" \
-        "${TOPDIR}/.ci/docker/"
-
-)
-
-GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
-GIT_BRANCH_NAME=${GITHUB_REF##*/}
-GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
-DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE}-${GIT_BRANCH_NAME}
-DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE}-${GIT_COMMIT_SHA}
-
-if [[ "${WITH_PUSH}" == true ]]; then
-  (
-    set -x
-    ${DOCKER} push "${DOCKER_IMAGE}"
-    if [[ -n ${GITHUB_REF} ]]; then
-        ${DOCKER} tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_BRANCH_TAG}
-        ${DOCKER} tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_SHA_TAG}
-        ${DOCKER} push "${DOCKER_IMAGE_BRANCH_TAG}"
-        ${DOCKER} push "${DOCKER_IMAGE_SHA_TAG}"
-    fi
-  )
-fi

.ci/docker/linter-cuda/Dockerfile

@@ -29,7 +29,7 @@ RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/re
 
 # Install cuda and cudnn
 ARG CUDA_VERSION
-COPY ./common/install_cuda.sh install_cuda.sh
+RUN wget -q https://raw.githubusercontent.com/pytorch/builder/main/common/install_cuda.sh -O install_cuda.sh
 RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh
 ENV DESIRED_CUDA ${CUDA_VERSION}
 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH

.ci/docker/manywheel/Dockerfile

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

.ci/docker/manywheel/Dockerfile_2014

@@ -1,153 +0,0 @@
-# syntax = docker/dockerfile:experimental
-ARG ROCM_VERSION=3.7
-ARG BASE_CUDA_VERSION=10.2
-ARG GPU_IMAGE=nvidia/cuda:${BASE_CUDA_VERSION}-devel-centos7
-FROM quay.io/pypa/manylinux2014_x86_64 as base
-
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-
-RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
-RUN yum install -y wget curl perl util-linux xz bzip2 git patch which perl zlib-devel
-RUN yum install -y yum-utils centos-release-scl sudo
-RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
-RUN yum install -y devtoolset-7-gcc devtoolset-7-gcc-c++ devtoolset-7-gcc-gfortran devtoolset-7-binutils
-ENV PATH=/opt/rh/devtoolset-7/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-7/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib:$LD_LIBRARY_PATH
-
-# cmake
-RUN yum install -y cmake3 && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-FROM base as openssl
-# Install openssl (this must precede `build python` step)
-# (In order to have a proper SSL module, Python is compiled
-# against a recent openssl [see env vars above], which is linked
-# statically. We delete openssl afterwards.)
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-
-
-
-# remove unncessary python versions
-RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
-RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
-RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
-RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
-
-FROM base as cuda
-ARG BASE_CUDA_VERSION=10.2
-# Install CUDA
-ADD ./common/install_cuda.sh install_cuda.sh
-RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
-
-FROM base as intel
-# MKL
-ADD ./common/install_mkl.sh install_mkl.sh
-RUN bash ./install_mkl.sh && rm install_mkl.sh
-
-FROM base as magma
-ARG BASE_CUDA_VERSION=10.2
-# Install magma
-ADD ./common/install_magma.sh install_magma.sh
-RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
-
-FROM base as jni
-# Install java jni header
-ADD ./common/install_jni.sh install_jni.sh
-ADD ./java/jni.h jni.h
-RUN bash ./install_jni.sh && rm install_jni.sh
-
-FROM base as libpng
-# Install libpng
-ADD ./common/install_libpng.sh install_libpng.sh
-RUN bash ./install_libpng.sh && rm install_libpng.sh
-
-FROM ${GPU_IMAGE} as common
-RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-RUN yum install -y \
-        aclocal \
-        autoconf \
-        automake \
-        bison \
-        bzip2 \
-        curl \
-        diffutils \
-        file \
-        git \
-        make \
-        patch \
-        perl \
-        unzip \
-        util-linux \
-        wget \
-        which \
-        xz \
-        yasm
-RUN yum install -y \
-    https://repo.ius.io/ius-release-el7.rpm \
-    https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
-
-RUN yum swap -y git git236-core
-# git236+ would refuse to run git commands in repos owned by other users
-# Which causes version check to fail, as pytorch repo is bind-mounted into the image
-# Override this behaviour by treating every folder as safe
-# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
-RUN git config --global --add safe.directory "*"
-
-ENV SSL_CERT_FILE=/opt/_internal/certs.pem
-# Install LLVM version
-COPY --from=openssl            /opt/openssl                          /opt/openssl
-COPY --from=base               /opt/python                           /opt/python
-COPY --from=base               /opt/_internal                        /opt/_internal
-COPY --from=base               /usr/local/bin/auditwheel             /usr/local/bin/auditwheel
-COPY --from=intel              /opt/intel                            /opt/intel
-COPY --from=base               /usr/local/bin/patchelf               /usr/local/bin/patchelf
-COPY --from=libpng             /usr/local/bin/png*                   /usr/local/bin/
-COPY --from=libpng             /usr/local/bin/libpng*                /usr/local/bin/
-COPY --from=libpng             /usr/local/include/png*               /usr/local/include/
-COPY --from=libpng             /usr/local/include/libpng*            /usr/local/include/
-COPY --from=libpng             /usr/local/lib/libpng*                /usr/local/lib/
-COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/lib/pkgconfig
-COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
-
-FROM common as cpu_final
-ARG BASE_CUDA_VERSION=10.2
-RUN yum install -y yum-utils centos-release-scl
-RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
-RUN yum install -y devtoolset-7-gcc devtoolset-7-gcc-c++ devtoolset-7-gcc-gfortran devtoolset-7-binutils
-ENV PATH=/opt/rh/devtoolset-7/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-7/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib:$LD_LIBRARY_PATH
-
-# cmake
-RUN yum install -y cmake3 && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-
-# ninja
-RUN yum install -y http://repo.okay.com.mx/centos/7/x86_64/release/okay-release-1-1.noarch.rpm
-RUN yum install -y ninja-build
-
-FROM cpu_final as cuda_final
-RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=cuda     /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=magma    /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
-
-FROM common as rocm_final
-ARG ROCM_VERSION=3.7
-# Install ROCm
-ADD ./common/install_rocm.sh install_rocm.sh
-RUN bash ./install_rocm.sh ${ROCM_VERSION} && rm install_rocm.sh
-# cmake is already installed inside the rocm base image, but both 2 and 3 exist
-# cmake3 is needed for the later MIOpen custom build, so that step is last.
-RUN yum install -y cmake3 && \
-    rm -f /usr/bin/cmake && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-ADD ./common/install_miopen.sh install_miopen.sh
-RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh

.ci/docker/manywheel/Dockerfile_2_28

@@ -1,157 +0,0 @@
-# syntax = docker/dockerfile:experimental
-ARG ROCM_VERSION=3.7
-ARG BASE_CUDA_VERSION=11.8
-ARG GPU_IMAGE=amd64/almalinux:8
-FROM quay.io/pypa/manylinux_2_28_x86_64 as base
-
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-
-ARG DEVTOOLSET_VERSION=11
-RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel yum-utils gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
-ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
-
-# cmake-3.18.4 from pip
-RUN yum install -y python3-pip && \
-    python3 -mpip install cmake==3.18.4 && \
-    ln -s /usr/local/bin/cmake /usr/bin/cmake3
-
-FROM base as openssl
-# Install openssl (this must precede `build python` step)
-# (In order to have a proper SSL module, Python is compiled
-# against a recent openssl [see env vars above], which is linked
-# statically. We delete openssl afterwards.)
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-
-
-# remove unncessary python versions
-RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
-RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
-RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
-RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
-
-FROM base as cuda
-ARG BASE_CUDA_VERSION=11.8
-# Install CUDA
-ADD ./common/install_cuda.sh install_cuda.sh
-RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
-
-FROM base as intel
-# MKL
-ADD ./common/install_mkl.sh install_mkl.sh
-RUN bash ./install_mkl.sh && rm install_mkl.sh
-
-FROM base as magma
-ARG BASE_CUDA_VERSION=10.2
-# Install magma
-ADD ./common/install_magma.sh install_magma.sh
-RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
-
-FROM base as jni
-# Install java jni header
-ADD ./common/install_jni.sh install_jni.sh
-ADD ./java/jni.h jni.h
-RUN bash ./install_jni.sh && rm install_jni.sh
-
-FROM base as libpng
-# Install libpng
-ADD ./common/install_libpng.sh install_libpng.sh
-RUN bash ./install_libpng.sh && rm install_libpng.sh
-
-FROM ${GPU_IMAGE} as common
-ARG DEVTOOLSET_VERSION=11
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-RUN yum -y install epel-release
-RUN yum -y update
-RUN yum install -y \
-        autoconf \
-        automake \
-        bison \
-        bzip2 \
-        curl \
-        diffutils \
-        file \
-        git \
-        make \
-        patch \
-        perl \
-        unzip \
-        util-linux \
-        wget \
-        which \
-        xz \
-        gcc-toolset-${DEVTOOLSET_VERSION}-toolchain \
-        glibc-langpack-en
-RUN yum install -y \
-    https://repo.ius.io/ius-release-el7.rpm \
-    https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
-
-RUN yum swap -y git git236-core
-# git236+ would refuse to run git commands in repos owned by other users
-# Which causes version check to fail, as pytorch repo is bind-mounted into the image
-# Override this behaviour by treating every folder as safe
-# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
-RUN git config --global --add safe.directory "*"
-
-ENV SSL_CERT_FILE=/opt/_internal/certs.pem
-# Install LLVM version
-COPY --from=openssl            /opt/openssl                          /opt/openssl
-COPY --from=base               /opt/python                           /opt/python
-COPY --from=base               /opt/_internal                        /opt/_internal
-COPY --from=base               /usr/local/bin/auditwheel             /usr/local/bin/auditwheel
-COPY --from=intel              /opt/intel                            /opt/intel
-COPY --from=base               /usr/local/bin/patchelf               /usr/local/bin/patchelf
-COPY --from=libpng             /usr/local/bin/png*                   /usr/local/bin/
-COPY --from=libpng             /usr/local/bin/libpng*                /usr/local/bin/
-COPY --from=libpng             /usr/local/include/png*               /usr/local/include/
-COPY --from=libpng             /usr/local/include/libpng*            /usr/local/include/
-COPY --from=libpng             /usr/local/lib/libpng*                /usr/local/lib/
-COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/lib/pkgconfig
-COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
-
-FROM common as cpu_final
-ARG BASE_CUDA_VERSION=11.8
-ARG DEVTOOLSET_VERSION=11
-# Ensure the expected devtoolset is used
-ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
-
-# cmake-3.18.4 from pip
-RUN yum install -y python3-pip && \
-    python3 -mpip install cmake==3.18.4 && \
-    ln -s /usr/local/bin/cmake /usr/bin/cmake3
-
-FROM cpu_final as cuda_final
-RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=cuda     /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=magma    /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
-
-FROM common as rocm_final
-ARG ROCM_VERSION=3.7
-# Install ROCm
-ADD ./common/install_rocm.sh install_rocm.sh
-RUN bash ./install_rocm.sh ${ROCM_VERSION} && rm install_rocm.sh
-# cmake is already installed inside the rocm base image, but both 2 and 3 exist
-# cmake3 is needed for the later MIOpen custom build, so that step is last.
-RUN yum install -y cmake3 && \
-    rm -f /usr/bin/cmake && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-ADD ./common/install_miopen.sh install_miopen.sh
-RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh
-
-FROM cpu_final as xpu_final
-# XPU CD use rolling driver
-ENV XPU_DRIVER_TYPE ROLLING
-# cmake-3.28.4 from pip
-RUN python3 -m pip install --upgrade pip && \
-    python3 -mpip install cmake==3.28.4
-# Install setuptools and wheel for python 3.13
-RUN /opt/python/cp313-cp313/bin/python -m pip install setuptools wheel
-ADD ./common/install_xpu.sh install_xpu.sh
-RUN bash ./install_xpu.sh && rm install_xpu.sh
-RUN pushd /opt/_internal && tar -xJf static-libs-for-embedding-only.tar.xz && popd

.ci/docker/manywheel/Dockerfile_2_28_aarch64

@@ -1,57 +0,0 @@
-FROM quay.io/pypa/manylinux_2_28_aarch64 as base
-
-# Graviton needs GCC 10 or above for the build. GCC12 is the default version in almalinux-8.
-ARG GCCTOOLSET_VERSION=11
-
-# Language variabes
-ENV LC_ALL=en_US.UTF-8
-ENV LANG=en_US.UTF-8
-ENV LANGUAGE=en_US.UTF-8
-
-# Installed needed OS packages. This is to support all
-# the binary builds (torch, vision, audio, text, data)
-RUN yum -y install epel-release
-RUN yum -y update
-RUN yum install -y \
-  autoconf \
-  automake \
-  bison \
-  bzip2 \
-  curl \
-  diffutils \
-  file \
-  git \
-  less \
-  libffi-devel \
-  libgomp \
-  make \
-  openssl-devel \
-  patch \
-  perl \
-  unzip \
-  util-linux \
-  wget \
-  which \
-  xz \
-  yasm \
-  zstd \
-  sudo \
-  gcc-toolset-${GCCTOOLSET_VERSION}-toolchain
-
-# Ensure the expected devtoolset is used
-ENV PATH=/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
-
-# git236+ would refuse to run git commands in repos owned by other users
-# Which causes version check to fail, as pytorch repo is bind-mounted into the image
-# Override this behaviour by treating every folder as safe
-# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
-RUN git config --global --add safe.directory "*"
-
-FROM base as final
-
-# remove unncessary python versions
-RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
-RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
-RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
-RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6

.ci/docker/manywheel/Dockerfile_aarch64

@@ -1,94 +0,0 @@
-FROM quay.io/pypa/manylinux2014_aarch64 as base
-
-
-# Graviton needs GCC 10 for the build
-ARG DEVTOOLSET_VERSION=10
-
-# Language variabes
-ENV LC_ALL=en_US.UTF-8
-ENV LANG=en_US.UTF-8
-ENV LANGUAGE=en_US.UTF-8
-
-# Installed needed OS packages. This is to support all
-# the binary builds (torch, vision, audio, text, data)
-RUN yum -y install epel-release
-RUN yum -y update
-RUN yum install -y \
-  autoconf \
-  automake \
-  bison \
-  bzip2 \
-  curl \
-  diffutils \
-  file \
-  git \
-  make \
-  patch \
-  perl \
-  unzip \
-  util-linux \
-  wget \
-  which \
-  xz \
-  yasm \
-  less \
-  zstd \
-  libgomp \
-  sudo \
-  devtoolset-${DEVTOOLSET_VERSION}-gcc \
-  devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ \
-  devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
-  devtoolset-${DEVTOOLSET_VERSION}-binutils
-
-# Ensure the expected devtoolset is used
-ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
-
-
-# git236+ would refuse to run git commands in repos owned by other users
-# Which causes version check to fail, as pytorch repo is bind-mounted into the image
-# Override this behaviour by treating every folder as safe
-# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
-RUN git config --global --add safe.directory "*"
-
-
-###############################################################################
-# libglfortran.a hack
-#
-# libgfortran.a from quay.io/pypa/manylinux2014_aarch64 is not compiled with -fPIC.
-# This causes __stack_chk_guard@@GLIBC_2.17 on pytorch build. To solve, get
-# ubuntu's libgfortran.a which is compiled with -fPIC
-# NOTE: Need a better way to get this library as Ubuntu's package can be removed by the vender, or changed
-###############################################################################
-RUN cd ~/ \
-  && curl -L -o ~/libgfortran-10-dev.deb http://ports.ubuntu.com/ubuntu-ports/pool/universe/g/gcc-10/libgfortran-10-dev_10.5.0-1ubuntu1_arm64.deb \
-  && ar x ~/libgfortran-10-dev.deb \
-  && tar --use-compress-program=unzstd -xvf data.tar.zst -C ~/ \
-  && cp -f ~/usr/lib/gcc/aarch64-linux-gnu/10/libgfortran.a /opt/rh/devtoolset-10/root/usr/lib/gcc/aarch64-redhat-linux/10/
-
-# install cmake
-RUN yum install -y cmake3 && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-
-FROM base as openssl
-# Install openssl (this must precede `build python` step)
-# (In order to have a proper SSL module, Python is compiled
-# against a recent openssl [see env vars above], which is linked
-# statically. We delete openssl afterwards.)
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-ENV SSL_CERT_FILE=/opt/_internal/certs.pem
-
-FROM base as openblas
-# Install openblas
-ADD ./common/install_openblas.sh install_openblas.sh
-RUN bash ./install_openblas.sh && rm install_openblas.sh
-
-FROM openssl as final
-# remove unncessary python versions
-RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
-RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
-RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
-RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
-COPY --from=openblas     /opt/OpenBLAS/  /opt/OpenBLAS/
-ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH

.ci/docker/manywheel/Dockerfile_cuda_aarch64

@@ -1,91 +0,0 @@
-FROM quay.io/pypa/manylinux_2_28_aarch64 as base
-
-# Cuda ARM build needs gcc 11
-ARG DEVTOOLSET_VERSION=11
-
-# Language variables
-ENV LC_ALL=en_US.UTF-8
-ENV LANG=en_US.UTF-8
-ENV LANGUAGE=en_US.UTF-8
-
-# Installed needed OS packages. This is to support all
-# the binary builds (torch, vision, audio, text, data)
-RUN yum -y install epel-release
-RUN yum -y update
-RUN yum install -y \
-  autoconf \
-  automake \
-  bison \
-  bzip2 \
-  curl \
-  diffutils \
-  file \
-  git \
-  make \
-  patch \
-  perl \
-  unzip \
-  util-linux \
-  wget \
-  which \
-  xz \
-  yasm \
-  less \
-  zstd \
-  libgomp \
-  sudo \
-  gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
-
-# Ensure the expected devtoolset is used
-ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
-
-# git236+ would refuse to run git commands in repos owned by other users
-# Which causes version check to fail, as pytorch repo is bind-mounted into the image
-# Override this behaviour by treating every folder as safe
-# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
-RUN git config --global --add safe.directory "*"
-
-
-FROM base as openssl
-# Install openssl (this must precede `build python` step)
-# (In order to have a proper SSL module, Python is compiled
-# against a recent openssl [see env vars above], which is linked
-# statically. We delete openssl afterwards.)
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-ENV SSL_CERT_FILE=/opt/_internal/certs.pem
-
-FROM openssl as final
-# remove unncessary python versions
-RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
-RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
-RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
-RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
-
-FROM base as cuda
-ARG BASE_CUDA_VERSION
-# Install CUDA
-ADD ./common/install_cuda_aarch64.sh install_cuda_aarch64.sh
-RUN bash ./install_cuda_aarch64.sh ${BASE_CUDA_VERSION} && rm install_cuda_aarch64.sh
-
-FROM base as magma
-ARG BASE_CUDA_VERSION
-# Install magma
-ADD ./common/install_magma.sh install_magma.sh
-RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
-
-FROM base as nvpl
-# Install nvpl
-ADD ./common/install_nvpl.sh install_nvpl.sh
-RUN bash ./install_nvpl.sh && rm install_nvpl.sh
-
-FROM final as cuda_final
-ARG BASE_CUDA_VERSION
-RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=cuda     /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=magma    /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=nvpl /opt/nvpl/lib/  /usr/local/lib/
-COPY --from=nvpl /opt/nvpl/include/  /usr/local/include/
-RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
-ENV PATH=/usr/local/cuda/bin:$PATH

.ci/docker/manywheel/Dockerfile_cxx11-abi

@@ -1,71 +0,0 @@
-FROM centos:8 as base
-
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-ENV PATH /opt/rh/gcc-toolset-11/root/bin/:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
-
-# change to a valid repo
-RUN sed -i 's|#baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-Linux-*.repo
-# enable to install ninja-build
-RUN sed -i 's|enabled=0|enabled=1|g' /etc/yum.repos.d/CentOS-Linux-PowerTools.repo
-
-RUN yum -y update
-RUN yum install -y wget curl perl util-linux xz bzip2 git patch which zlib-devel sudo
-RUN yum install -y autoconf automake make cmake gdb gcc-toolset-11-gcc-c++
-
-
-FROM base as openssl
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-
-# Install python
-FROM base as python
-RUN yum install -y openssl-devel zlib-devel bzip2-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel libpcap-devel xz-devel libffi-devel
-ADD common/install_cpython.sh install_cpython.sh
-RUN bash ./install_cpython.sh && rm install_cpython.sh
-
-FROM base as conda
-ADD ./common/install_conda_docker.sh install_conda.sh
-RUN bash ./install_conda.sh && rm install_conda.sh
-RUN /opt/conda/bin/conda install -y cmake
-
-FROM base as intel
-# Install MKL
-COPY --from=python             /opt/python                           /opt/python
-COPY --from=python             /opt/_internal                        /opt/_internal
-COPY --from=conda              /opt/conda                            /opt/conda
-ENV PATH=/opt/conda/bin:$PATH
-ADD ./common/install_mkl.sh install_mkl.sh
-RUN bash ./install_mkl.sh && rm install_mkl.sh
-
-FROM base as patchelf
-ADD ./common/install_patchelf.sh install_patchelf.sh
-RUN bash ./install_patchelf.sh && rm install_patchelf.sh
-RUN cp $(which patchelf) /patchelf
-
-FROM base as jni
-ADD ./common/install_jni.sh install_jni.sh
-ADD ./java/jni.h jni.h
-RUN bash ./install_jni.sh && rm install_jni.sh
-
-FROM base as libpng
-ADD ./common/install_libpng.sh install_libpng.sh
-RUN bash ./install_libpng.sh && rm install_libpng.sh
-
-FROM base as final
-COPY --from=openssl            /opt/openssl                          /opt/openssl
-COPY --from=python             /opt/python                           /opt/python
-COPY --from=python             /opt/_internal                        /opt/_internal
-COPY --from=intel              /opt/intel                            /opt/intel
-COPY --from=conda              /opt/conda                            /opt/conda
-COPY --from=patchelf           /usr/local/bin/patchelf               /usr/local/bin/patchelf
-COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
-COPY --from=libpng             /usr/local/bin/png*                   /usr/local/bin/
-COPY --from=libpng             /usr/local/bin/libpng*                /usr/local/bin/
-COPY --from=libpng             /usr/local/include/png*               /usr/local/include/
-COPY --from=libpng             /usr/local/include/libpng*            /usr/local/include/
-COPY --from=libpng             /usr/local/lib/libpng*                /usr/local/lib/
-COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/lib/pkgconfig
-
-RUN yum install -y ninja-build

.ci/docker/manywheel/Dockerfile_s390x

@@ -1,73 +0,0 @@
-FROM --platform=linux/s390x docker.io/ubuntu:24.04 as base
-
-# Language variables
-ENV LC_ALL=C.UTF-8
-ENV LANG=C.UTF-8
-ENV LANGUAGE=C.UTF-8
-
-# Installed needed OS packages. This is to support all
-# the binary builds (torch, vision, audio, text, data)
-RUN apt update ; apt upgrade -y
-RUN apt install -y \
-  build-essential \
-  autoconf \
-  automake \
-  bzip2 \
-  curl \
-  diffutils \
-  file \
-  git \
-  make \
-  patch \
-  perl \
-  unzip \
-  util-linux \
-  wget \
-  which \
-  xz-utils \
-  less \
-  zstd \
-  cmake \
-  python3 \
-  python3-dev \
-  python3-setuptools \
-  python3-yaml \
-  python3-typing-extensions \
-  libblas-dev \
-  libopenblas-dev \
-  liblapack-dev \
-  libatlas-base-dev
-
-# git236+ would refuse to run git commands in repos owned by other users
-# Which causes version check to fail, as pytorch repo is bind-mounted into the image
-# Override this behaviour by treating every folder as safe
-# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
-RUN git config --global --add safe.directory "*"
-
-FROM base as openssl
-# Install openssl (this must precede `build python` step)
-# (In order to have a proper SSL module, Python is compiled
-# against a recent openssl [see env vars above], which is linked
-# statically. We delete openssl afterwards.)
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-ENV SSL_CERT_FILE=/opt/_internal/certs.pem
-
-# EPEL for cmake
-FROM base as patchelf
-# Install patchelf
-ADD ./common/install_patchelf.sh install_patchelf.sh
-RUN bash ./install_patchelf.sh && rm install_patchelf.sh
-RUN cp $(which patchelf) /patchelf
-
-FROM patchelf as python
-# build python
-COPY manywheel/build_scripts /build_scripts
-ADD ./common/install_cpython.sh /build_scripts/install_cpython.sh
-RUN bash build_scripts/build.sh && rm -r build_scripts
-
-FROM openssl as final
-COPY --from=python             /opt/python                           /opt/python
-COPY --from=python             /opt/_internal                        /opt/_internal
-COPY --from=python             /opt/python/cp39-cp39/bin/auditwheel /usr/local/bin/auditwheel
-COPY --from=patchelf           /usr/local/bin/patchelf               /usr/local/bin/patchelf

.ci/docker/manywheel/build.sh

@@ -1,154 +0,0 @@
-#!/usr/bin/env bash
-# Script used only in CD pipeline
-
-set -eou pipefail
-
-TOPDIR=$(git rev-parse --show-toplevel)
-
-image="$1"
-shift
-
-if [ -z "${image}" ]; then
-  echo "Usage: $0 IMAGE"
-  exit 1
-fi
-
-DOCKER_IMAGE="pytorch/${image}"
-
-DOCKER_REGISTRY="${DOCKER_REGISTRY:-docker.io}"
-
-GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
-GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
-MANY_LINUX_VERSION=${MANY_LINUX_VERSION:-}
-DOCKERFILE_SUFFIX=${DOCKERFILE_SUFFIX:-}
-WITH_PUSH=${WITH_PUSH:-}
-
-case ${GPU_ARCH_TYPE} in
-    cpu)
-        TARGET=cpu_final
-        DOCKER_TAG=cpu
-        GPU_IMAGE=centos:7
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
-        ;;
-    cpu-manylinux_2_28)
-        TARGET=cpu_final
-        DOCKER_TAG=cpu
-        GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
-        MANY_LINUX_VERSION="2_28"
-        ;;
-    cpu-aarch64)
-        TARGET=final
-        DOCKER_TAG=cpu-aarch64
-        GPU_IMAGE=arm64v8/centos:7
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=10"
-        MANY_LINUX_VERSION="aarch64"
-        ;;
-    cpu-aarch64-2_28)
-        TARGET=final
-        DOCKER_TAG=cpu-aarch64
-        GPU_IMAGE=arm64v8/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
-        MANY_LINUX_VERSION="2_28_aarch64"
-        ;;
-    cpu-cxx11-abi)
-        TARGET=final
-        DOCKER_TAG=cpu-cxx11-abi
-        GPU_IMAGE=""
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
-        MANY_LINUX_VERSION="cxx11-abi"
-        ;;
-    cpu-s390x)
-        TARGET=final
-        DOCKER_TAG=cpu-s390x
-        GPU_IMAGE=redhat/ubi9
-        DOCKER_GPU_BUILD_ARG=""
-        MANY_LINUX_VERSION="s390x"
-        ;;
-    cuda)
-        TARGET=cuda_final
-        DOCKER_TAG=cuda${GPU_ARCH_VERSION}
-        # Keep this up to date with the minimum version of CUDA we currently support
-        GPU_IMAGE=centos:7
-        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=9"
-        ;;
-    cuda-manylinux_2_28)
-        TARGET=cuda_final
-        DOCKER_TAG=cuda${GPU_ARCH_VERSION}
-        GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
-        MANY_LINUX_VERSION="2_28"
-        ;;
-    cuda-aarch64)
-        TARGET=cuda_final
-        DOCKER_TAG=cuda${GPU_ARCH_VERSION}
-        GPU_IMAGE=arm64v8/centos:7
-        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
-        MANY_LINUX_VERSION="aarch64"
-        DOCKERFILE_SUFFIX="_cuda_aarch64"
-        ;;
-    rocm)
-        TARGET=rocm_final
-        DOCKER_TAG=rocm${GPU_ARCH_VERSION}
-        GPU_IMAGE=rocm/dev-centos-7:${GPU_ARCH_VERSION}-complete
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx1030;gfx1100"
-        ROCM_REGEX="([0-9]+)\.([0-9]+)[\.]?([0-9]*)"
-        if [[ $GPU_ARCH_VERSION =~ $ROCM_REGEX ]]; then
-            ROCM_VERSION_INT=$((${BASH_REMATCH[1]}*10000 + ${BASH_REMATCH[2]}*100 + ${BASH_REMATCH[3]:-0}))
-        else
-            echo "ERROR: rocm regex failed"
-            exit 1
-        fi
-        if [[ $ROCM_VERSION_INT -ge 60000 ]]; then
-            PYTORCH_ROCM_ARCH+=";gfx942"
-        fi
-        DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=9"
-        ;;
-    xpu)
-        TARGET=xpu_final
-        DOCKER_TAG=xpu
-        GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
-        MANY_LINUX_VERSION="2_28"
-        ;;
-    *)
-        echo "ERROR: Unrecognized GPU_ARCH_TYPE: ${GPU_ARCH_TYPE}"
-        exit 1
-        ;;
-esac
-
-IMAGES=''
-
-if [[ -n ${MANY_LINUX_VERSION} && -z ${DOCKERFILE_SUFFIX} ]]; then
-    DOCKERFILE_SUFFIX=_${MANY_LINUX_VERSION}
-fi
-(
-    set -x
-    DOCKER_BUILDKIT=1 docker build \
-        ${DOCKER_GPU_BUILD_ARG} \
-        --build-arg "GPU_IMAGE=${GPU_IMAGE}" \
-        --target "${TARGET}" \
-        -t "${DOCKER_IMAGE}" \
-        $@ \
-        -f "${TOPDIR}/.ci/docker/manywheel/Dockerfile${DOCKERFILE_SUFFIX}" \
-        "${TOPDIR}/.ci/docker/"
-)
-
-GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
-GIT_BRANCH_NAME="2.5"
-GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
-DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE}-${GIT_BRANCH_NAME}
-DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE}-${GIT_COMMIT_SHA}
-
-if [[ "${WITH_PUSH}" == true ]]; then
-    (
-        set -x
-        docker push "${DOCKER_IMAGE}"
-        if [[ -n ${GITHUB_REF} ]]; then
-            docker tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_BRANCH_TAG}
-            docker tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_SHA_TAG}
-            docker push "${DOCKER_IMAGE_BRANCH_TAG}"
-            docker push "${DOCKER_IMAGE_SHA_TAG}"
-        fi
-    )
-fi

.ci/docker/manywheel/build_scripts/build.sh

@@ -1,131 +0,0 @@
-#!/bin/bash
-# Top-level build script called from Dockerfile
-# Script used only in CD pipeline
-
-# Stop at any error, show all commands
-set -ex
-
-# openssl version to build, with expected sha256 hash of .tar.gz
-# archive
-OPENSSL_ROOT=openssl-1.1.1l
-OPENSSL_HASH=0b7a3e5e59c34827fe0c3a74b7ec8baef302b98fa80088d7f9153aa16fa76bd1
-DEVTOOLS_HASH=a8ebeb4bed624700f727179e6ef771dafe47651131a00a78b342251415646acc
-PATCHELF_HASH=d9afdff4baeacfbc64861454f368b7f2c15c44d245293f7587bbf726bfe722fb
-CURL_ROOT=curl-7.73.0
-CURL_HASH=cf34fe0b07b800f1c01a499a6e8b2af548f6d0e044dca4a29d88a4bee146d131
-AUTOCONF_ROOT=autoconf-2.69
-AUTOCONF_HASH=954bd69b391edc12d6a4a51a2dd1476543da5c6bbf05a95b59dc0dd6fd4c2969
-
-# Get build utilities
-MY_DIR=$(dirname "${BASH_SOURCE[0]}")
-source $MY_DIR/build_utils.sh
-
-if [ "$(uname -m)" != "s390x" ] ; then
-    # Dependencies for compiling Python that we want to remove from
-    # the final image after compiling Python
-    PYTHON_COMPILE_DEPS="zlib-devel bzip2-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel db4-devel libpcap-devel xz-devel libffi-devel"
-
-    # Libraries that are allowed as part of the manylinux1 profile
-    MANYLINUX1_DEPS="glibc-devel libstdc++-devel glib2-devel libX11-devel libXext-devel libXrender-devel  mesa-libGL-devel libICE-devel libSM-devel ncurses-devel"
-
-    # Development tools and libraries
-    yum -y install bzip2 make git patch unzip bison yasm diffutils \
-        automake which file cmake28 \
-        kernel-devel-`uname -r` \
-        ${PYTHON_COMPILE_DEPS}
-else
-    # Dependencies for compiling Python that we want to remove from
-    # the final image after compiling Python
-    PYTHON_COMPILE_DEPS="zlib1g-dev libbz2-dev libncurses-dev libsqlite3-dev libdb-dev libpcap-dev liblzma-dev libffi-dev"
-
-    # Libraries that are allowed as part of the manylinux1 profile
-    MANYLINUX1_DEPS="libglib2.0-dev libX11-dev libncurses-dev"
-
-    # Development tools and libraries
-    apt install -y bzip2 make git patch unzip diffutils \
-        automake which file cmake \
-        linux-headers-virtual \
-        ${PYTHON_COMPILE_DEPS}
-fi
-
-# Install newest autoconf
-build_autoconf $AUTOCONF_ROOT $AUTOCONF_HASH
-autoconf --version
-
-# Compile the latest Python releases.
-# (In order to have a proper SSL module, Python is compiled
-# against a recent openssl [see env vars above], which is linked
-# statically. We delete openssl afterwards.)
-build_openssl $OPENSSL_ROOT $OPENSSL_HASH
-/build_scripts/install_cpython.sh
-
-PY39_BIN=/opt/python/cp39-cp39/bin
-
-# Our openssl doesn't know how to find the system CA trust store
-#   (https://github.com/pypa/manylinux/issues/53)
-# And it's not clear how up-to-date that is anyway
-# So let's just use the same one pip and everyone uses
-$PY39_BIN/pip install certifi
-ln -s $($PY39_BIN/python -c 'import certifi; print(certifi.where())') \
-      /opt/_internal/certs.pem
-# If you modify this line you also have to modify the versions in the
-# Dockerfiles:
-export SSL_CERT_FILE=/opt/_internal/certs.pem
-
-# Install newest curl
-build_curl $CURL_ROOT $CURL_HASH
-rm -rf /usr/local/include/curl /usr/local/lib/libcurl* /usr/local/lib/pkgconfig/libcurl.pc
-hash -r
-curl --version
-curl-config --features
-
-# Install patchelf (latest with unreleased bug fixes)
-curl -sLOk https://nixos.org/releases/patchelf/patchelf-0.10/patchelf-0.10.tar.gz
-# check_sha256sum patchelf-0.9njs2.tar.gz $PATCHELF_HASH
-tar -xzf patchelf-0.10.tar.gz
-(cd patchelf-0.10 && ./configure && make && make install)
-rm -rf patchelf-0.10.tar.gz patchelf-0.10
-
-# Install latest pypi release of auditwheel
-$PY39_BIN/pip install auditwheel
-ln -s $PY39_BIN/auditwheel /usr/local/bin/auditwheel
-
-# Clean up development headers and other unnecessary stuff for
-# final image
-if [ "$(uname -m)" != "s390x" ] ; then
-    yum -y erase wireless-tools gtk2 libX11 hicolor-icon-theme \
-        avahi freetype bitstream-vera-fonts \
-        ${PYTHON_COMPILE_DEPS} || true > /dev/null 2>&1
-    yum -y install ${MANYLINUX1_DEPS}
-    yum -y clean all > /dev/null 2>&1
-    yum list installed
-else
-    apt purge -y ${PYTHON_COMPILE_DEPS} || true > /dev/null 2>&1
-fi
-# we don't need libpython*.a, and they're many megabytes
-find /opt/_internal -name '*.a' -print0 | xargs -0 rm -f
-# Strip what we can -- and ignore errors, because this just attempts to strip
-# *everything*, including non-ELF files:
-find /opt/_internal -type f -print0 \
-    | xargs -0 -n1 strip --strip-unneeded 2>/dev/null || true
-# We do not need the Python test suites, or indeed the precompiled .pyc and
-# .pyo files. Partially cribbed from:
-#    https://github.com/docker-library/python/blob/master/3.4/slim/Dockerfile
-find /opt/_internal \
-     \( -type d -a -name test -o -name tests \) \
-  -o \( -type f -a -name '*.pyc' -o -name '*.pyo' \) \
-  -print0 | xargs -0 rm -f
-
-for PYTHON in /opt/python/*/bin/python; do
-    # Smoke test to make sure that our Pythons work, and do indeed detect as
-    # being manylinux compatible:
-    $PYTHON $MY_DIR/manylinux1-check.py
-    # Make sure that SSL cert checking works
-    $PYTHON $MY_DIR/ssl-check.py
-done
-
-# Fix libc headers to remain compatible with C99 compilers.
-find /usr/include/ -type f -exec sed -i 's/\bextern _*inline_*\b/extern __inline __attribute__ ((__gnu_inline__))/g' {} +
-
-# Now we can delete our built SSL
-rm -rf /usr/local/ssl

.ci/docker/manywheel/build_scripts/build_utils.sh

@@ -1,91 +0,0 @@
-#!/bin/bash
-# Helper utilities for build
-# Script used only in CD pipeline
-
-OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/
-CURL_DOWNLOAD_URL=https://curl.askapache.com/download
-
-AUTOCONF_DOWNLOAD_URL=https://ftp.gnu.org/gnu/autoconf
-
-
-function check_var {
-    if [ -z "$1" ]; then
-        echo "required variable not defined"
-        exit 1
-    fi
-}
-
-
-function do_openssl_build {
-    ./config no-ssl2 no-shared -fPIC --prefix=/usr/local/ssl > /dev/null
-    make > /dev/null
-    make install > /dev/null
-}
-
-
-function check_sha256sum {
-    local fname=$1
-    check_var ${fname}
-    local sha256=$2
-    check_var ${sha256}
-
-    echo "${sha256}  ${fname}" > ${fname}.sha256
-    sha256sum -c ${fname}.sha256
-    rm -f ${fname}.sha256
-}
-
-
-function build_openssl {
-    local openssl_fname=$1
-    check_var ${openssl_fname}
-    local openssl_sha256=$2
-    check_var ${openssl_sha256}
-    check_var ${OPENSSL_DOWNLOAD_URL}
-    curl -sLO ${OPENSSL_DOWNLOAD_URL}/${openssl_fname}.tar.gz
-    check_sha256sum ${openssl_fname}.tar.gz ${openssl_sha256}
-    tar -xzf ${openssl_fname}.tar.gz
-    (cd ${openssl_fname} && do_openssl_build)
-    rm -rf ${openssl_fname} ${openssl_fname}.tar.gz
-}
-
-
-function do_curl_build {
-    LIBS=-ldl ./configure --with-ssl --disable-shared > /dev/null
-    make > /dev/null
-    make install > /dev/null
-}
-
-
-function build_curl {
-    local curl_fname=$1
-    check_var ${curl_fname}
-    local curl_sha256=$2
-    check_var ${curl_sha256}
-    check_var ${CURL_DOWNLOAD_URL}
-    curl -sLO ${CURL_DOWNLOAD_URL}/${curl_fname}.tar.bz2
-    check_sha256sum ${curl_fname}.tar.bz2 ${curl_sha256}
-    tar -jxf ${curl_fname}.tar.bz2
-    (cd ${curl_fname} && do_curl_build)
-    rm -rf ${curl_fname} ${curl_fname}.tar.bz2
-}
-
-
-function do_standard_install {
-    ./configure > /dev/null
-    make > /dev/null
-    make install > /dev/null
-}
-
-
-function build_autoconf {
-    local autoconf_fname=$1
-    check_var ${autoconf_fname}
-    local autoconf_sha256=$2
-    check_var ${autoconf_sha256}
-    check_var ${AUTOCONF_DOWNLOAD_URL}
-    curl -sLO ${AUTOCONF_DOWNLOAD_URL}/${autoconf_fname}.tar.gz
-    check_sha256sum ${autoconf_fname}.tar.gz ${autoconf_sha256}
-    tar -zxf ${autoconf_fname}.tar.gz
-    (cd ${autoconf_fname} && do_standard_install)
-    rm -rf ${autoconf_fname} ${autoconf_fname}.tar.gz
-}

.ci/docker/manywheel/build_scripts/manylinux1-check.py

@@ -1,60 +0,0 @@
-# Logic copied from PEP 513
-
-
-def is_manylinux1_compatible():
-    # Only Linux, and only x86-64 / i686
-    from distutils.util import get_platform
-
-    if get_platform() not in ["linux-x86_64", "linux-i686", "linux-s390x"]:
-        return False
-
-    # Check for presence of _manylinux module
-    try:
-        import _manylinux
-
-        return bool(_manylinux.manylinux1_compatible)
-    except (ImportError, AttributeError):
-        # Fall through to heuristic check below
-        pass
-
-    # Check glibc version. CentOS 5 uses glibc 2.5.
-    return have_compatible_glibc(2, 5)
-
-
-def have_compatible_glibc(major, minimum_minor):
-    import ctypes
-
-    process_namespace = ctypes.CDLL(None)
-    try:
-        gnu_get_libc_version = process_namespace.gnu_get_libc_version
-    except AttributeError:
-        # Symbol doesn't exist -> therefore, we are not linked to
-        # glibc.
-        return False
-
-    # Call gnu_get_libc_version, which returns a string like "2.5".
-    gnu_get_libc_version.restype = ctypes.c_char_p
-    version_str = gnu_get_libc_version()
-    # py2 / py3 compatibility:
-    if not isinstance(version_str, str):
-        version_str = version_str.decode("ascii")
-
-    # Parse string and check against requested version.
-    version = [int(piece) for piece in version_str.split(".")]
-    assert len(version) == 2
-    if major != version[0]:
-        return False
-    if minimum_minor > version[1]:
-        return False
-    return True
-
-
-import sys
-
-
-if is_manylinux1_compatible():
-    print(f"{sys.executable} is manylinux1 compatible")
-    sys.exit(0)
-else:
-    print(f"{sys.executable} is NOT manylinux1 compatible")
-    sys.exit(1)

.ci/docker/manywheel/build_scripts/ssl-check.py

@@ -1,35 +0,0 @@
-# cf. https://github.com/pypa/manylinux/issues/53
-
-GOOD_SSL = "https://google.com"
-BAD_SSL = "https://self-signed.badssl.com"
-
-import sys
-
-
-print("Testing SSL certificate checking for Python:", sys.version)
-
-if sys.version_info[:2] < (2, 7) or sys.version_info[:2] < (3, 4):
-    print("This version never checks SSL certs; skipping tests")
-    sys.exit(0)
-
-if sys.version_info[0] >= 3:
-    from urllib.request import urlopen
-
-    EXC = OSError
-else:
-    from urllib import urlopen
-
-    EXC = IOError
-
-print(f"Connecting to {GOOD_SSL} should work")
-urlopen(GOOD_SSL)
-print("...it did, yay.")
-
-print(f"Connecting to {BAD_SSL} should fail")
-try:
-    urlopen(BAD_SSL)
-    # If we get here then we failed:
-    print("...it DIDN'T!!!!!11!!1one!")
-    sys.exit(1)
-except EXC:
-    print("...it did, yay.")

.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:
 
@@ -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
@@ -139,9 +134,9 @@ opt-einsum==3.3
 #Pinned versions: 3.3
 #test that import: test_linalg.py
 
-optree==0.12.1
+optree==0.11.0
 #Description: A library for tree manipulation
-#Pinned versions: 0.12.1
+#Pinned versions: 0.11.0
 #test that import: test_vmap.py, test_aotdispatch.py, test_dynamic_shapes.py,
 #test_pytree.py, test_ops.py, test_control_flow.py, test_modules.py,
 #common_utils.py, test_eager_transforms.py, test_python_dispatch.py,
@@ -223,7 +218,7 @@ pygments==2.15.0
 #test that import:
 
 scikit-image==0.19.3 ; python_version < "3.10"
-scikit-image==0.22.0 ; python_version >= "3.10"
+scikit-image==0.20.0 ; python_version >= "3.10"
 #Description: image processing routines
 #Pinned versions:
 #test that import: test_nn.py
@@ -274,10 +269,6 @@ lintrunner==0.12.5
 #Pinned versions: 0.12.5
 #test that import:
 
-redis>=4.0.0
-#Description: redis database
-#test that import: anything that tests OSS caching/mocking (inductor/test_codecache.py, inductor/test_max_autotune.py)
-
 rockset==1.0.3
 #Description: queries Rockset
 #Pinned versions: 1.0.3
@@ -321,19 +312,3 @@ lxml==5.0.0
 # Python-3.9 binaries
 
 PyGithub==2.3.0
-
-sympy==1.12.1 ; python_version == "3.8"
-sympy==1.13.1 ; python_version >= "3.9"
-#Description: Required by coremltools, also pinned in .github/requirements/pip-requirements-macOS.txt
-#Pinned versions:
-#test that import:
-
-onnx==1.16.1
-#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
-#Pinned versions:
-#test that import:
-
-onnxscript==0.1.0.dev20240817
-#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
-#Pinned versions:
-#test that import:

.ci/docker/triton_version.txt

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

.ci/docker/ubuntu-cuda/Dockerfile

@@ -156,12 +156,6 @@ COPY ./common/install_cusparselt.sh install_cusparselt.sh
 RUN bash install_cusparselt.sh
 RUN rm install_cusparselt.sh
 
-# Install CUDSS
-ARG CUDA_VERSION
-COPY ./common/install_cudss.sh install_cudss.sh
-RUN bash install_cudss.sh
-RUN rm install_cudss.sh
-
 # Delete /usr/local/cuda-11.X/cuda-11.X symlinks
 RUN if [ -h /usr/local/cuda-11.6/cuda-11.6 ]; then rm /usr/local/cuda-11.6/cuda-11.6; fi
 RUN if [ -h /usr/local/cuda-11.7/cuda-11.7 ]; then rm /usr/local/cuda-11.7/cuda-11.7; fi

.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/docker/ubuntu-xpu/Dockerfile

@@ -30,7 +30,6 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
 ARG ANACONDA_PYTHON_VERSION
 ARG CONDA_CMAKE
 ARG DOCS
-ARG BUILD_ENVIRONMENT
 ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
 ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
 ENV DOCS=$DOCS

.ci/docker/ubuntu/Dockerfile

@@ -50,7 +50,7 @@ RUN  bash ./install_lcov.sh && rm install_lcov.sh
 
 # Install cuda and cudnn
 ARG CUDA_VERSION
-COPY ./common/install_cuda.sh install_cuda.sh
+RUN wget -q https://raw.githubusercontent.com/pytorch/builder/main/common/install_cuda.sh -O install_cuda.sh
 RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh
 ENV DESIRED_CUDA ${CUDA_VERSION}
 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH

.ci/pytorch/README.md

@@ -1 +1,42 @@
 This directory contains scripts for our continuous integration.
+
+One important thing to keep in mind when reading the scripts here is
+that they are all based off of Docker images, which we build for each of
+the various system configurations we want to run on Jenkins.  This means
+it is very easy to run these tests yourself:
+
+1. Figure out what Docker image you want.  The general template for our
+   images look like:
+   ``registry.pytorch.org/pytorch/pytorch-$BUILD_ENVIRONMENT:$DOCKER_VERSION``,
+   where ``$BUILD_ENVIRONMENT`` is one of the build environments
+   enumerated in
+   [pytorch-dockerfiles](https://github.com/pytorch/pytorch/blob/master/.ci/docker/build.sh). The dockerfile used by jenkins can be found under the `.ci` [directory](https://github.com/pytorch/pytorch/blob/master/.ci/docker)
+
+2. Run ``docker run -it -u jenkins $DOCKER_IMAGE``, clone PyTorch and
+   run one of the scripts in this directory.
+
+The Docker images are designed so that any "reasonable" build commands
+will work; if you look in [build.sh](build.sh) you will see that it is a
+very simple script.  This is intentional.  Idiomatic build instructions
+should work inside all of our Docker images.  You can tweak the commands
+however you need (e.g., in case you want to rebuild with DEBUG, or rerun
+the build with higher verbosity, etc.).
+
+We have to do some work to make this so.  Here is a summary of the
+mechanisms we use:
+
+- We install binaries to directories like `/usr/local/bin` which
+  are automatically part of your PATH.
+
+- We add entries to the PATH using Docker ENV variables (so
+  they apply when you enter Docker) and `/etc/environment` (so they
+  continue to apply even if you sudo), instead of modifying
+  `PATH` in our build scripts.
+
+- We use `/etc/ld.so.conf.d` to register directories containing
+  shared libraries, instead of modifying `LD_LIBRARY_PATH` in our
+  build scripts.
+
+- We reroute well known paths like `/usr/bin/gcc` to alternate
+  implementations with `update-alternatives`, instead of setting
+  `CC` and `CXX` in our implementations.

.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
-export LLVM_DIR=/opt/llvm/lib/cmake/llvm
+if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
+  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 [[ "$BUILD_ENVIRONMENT" == *executorch* ]]; then
   # To build test_edge_op_registration
@@ -171,8 +176,7 @@ fi
 if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   # shellcheck disable=SC1091
   source /opt/intel/oneapi/compiler/latest/env/vars.sh
-  # XPU kineto feature dependencies are not fully ready, disable kineto build as temp WA
-  export USE_KINETO=0
+  export USE_XPU=1
 fi
 
 # sccache will fail for CUDA builds if all cores are used for compiling
@@ -280,8 +284,9 @@ else
     if [[ "$BUILD_ENVIRONMENT" != *rocm*  &&
           "$BUILD_ENVIRONMENT" != *xla* ]]; then
       if [[ "$BUILD_ENVIRONMENT" != *py3.8* ]]; then
-        # Install numpy-2.0.2 for builds which are backward compatible with 1.X
-        python -mpip install --pre numpy==2.0.2
+        # Install numpy-2.0 release candidate for builds
+        # Which should be backward compatible with Numpy-1.X
+        python -mpip install --pre numpy==2.0.0rc1
       fi
 
       WERROR=1 python setup.py clean

.ci/pytorch/common_utils.sh

@@ -179,7 +179,7 @@ function install_torchvision() {
 }
 
 function install_tlparse() {
-  pip_install --user "tlparse==0.3.25"
+  pip_install --user "tlparse==0.3.7"
   PATH="$(python -m site --user-base)/bin:$PATH"
 }
 
@@ -198,7 +198,7 @@ function install_torchrec_and_fbgemm() {
 
 function clone_pytorch_xla() {
   if [[ ! -d ./xla ]]; then
-    git clone --recursive -b r2.5 https://github.com/pytorch/xla.git
+    git clone --recursive --quiet https://github.com/pytorch/xla.git
     pushd xla
     # pin the xla hash so that we don't get broken by changes to xla
     git checkout "$(cat ../.github/ci_commit_pins/xla.txt)"

.ci/pytorch/multigpu-test.sh

@@ -44,15 +44,16 @@ time python test/run_test.py --verbose -i distributed/_tensor/test_dtensor_compi
 time python test/run_test.py --verbose -i distributed/test_device_mesh
 
 # DTensor/TP tests
+time python test/run_test.py --verbose -i distributed/tensor/parallel/test_ddp_2d_parallel
+time python test/run_test.py --verbose -i distributed/tensor/parallel/test_fsdp_2d_parallel
 time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_examples
 time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_random_state
 
 # FSDP2 tests
 time python test/run_test.py --verbose -i distributed/_composable/fsdp/test_fully_shard_training -- -k test_2d_mlp_with_nd_mesh
 
-# ND composability tests
-time python test/run_test.py --verbose -i distributed/_composable/test_composability/test_2d_composability
-time python test/run_test.py --verbose -i distributed/_composable/test_composability/test_pp_composability
+# Pipelining composability tests
+time python test/run_test.py --verbose -i distributed/pipelining/test_composability.py
 
 # Other tests
 time python test/run_test.py --verbose -i test_cuda_primary_ctx

.ci/pytorch/test.sh

@@ -6,9 +6,6 @@
 
 set -ex
 
-# Suppress ANSI color escape sequences
-export TERM=vt100
-
 # shellcheck source=./common.sh
 source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
 
@@ -169,7 +166,7 @@ fi
 
 if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   # Source Intel oneAPI envrioment script to enable xpu runtime related libraries
-  # refer to https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-5.html
+  # refer to https://www.intel.com/content/www/us/en/docs/oneapi/programming-guide/2024-0/use-the-setvars-and-oneapi-vars-scripts-with-linux.html
   # shellcheck disable=SC1091
   source /opt/intel/oneapi/compiler/latest/env/vars.sh
   # Check XPU status before testing
@@ -319,14 +316,14 @@ test_inductor_distributed() {
   python test/run_test.py -i inductor/test_aot_inductor.py -k test_replicate_on_devices --verbose
   python test/run_test.py -i distributed/test_c10d_functional_native.py --verbose
   python test/run_test.py -i distributed/_tensor/test_dtensor_compile.py --verbose
-  python test/run_test.py -i distributed/tensor/parallel/test_micro_pipeline_tp.py --verbose
+  python test/run_test.py -i distributed/tensor/parallel/test_fsdp_2d_parallel.py --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_comm.py --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_multi_group --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_with_activation_checkpointing --verbose
+  python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_2d_mlp --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_hsdp --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_train_parity_2d_transformer_checkpoint_resume --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_training.py -k test_gradient_accumulation --verbose
-  python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_state_dict.py -k test_dp_state_dict_save_load --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_frozen.py --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_mixed_precision.py -k test_compute_dtype --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_mixed_precision.py -k test_reduce_dtype --verbose
@@ -361,12 +358,10 @@ test_inductor_shard() {
 test_inductor_aoti() {
   # docker build uses bdist_wheel which does not work with test_aot_inductor
   # TODO: need a faster way to build
-  if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
-    # We need to hipify before building again
-    python3 tools/amd_build/build_amd.py
+  if [[ "$BUILD_ENVIRONMENT" != *rocm* ]]; then
+    BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
+    CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference
   fi
-  BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
-  CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference
 }
 
 test_inductor_cpp_wrapper_abi_compatible() {
@@ -395,22 +390,7 @@ test_inductor_cpp_wrapper_abi_compatible() {
 # .github/workflows/inductor-perf-test-nightly.yml
 DYNAMO_BENCHMARK_FLAGS=()
 
-pr_time_benchmarks() {
-
-  pip_install --user "fbscribelogger"
-
-  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_after.txt" "benchmarks/dynamo/pr_time_benchmarks/benchmarks"
-  echo "benchmark results on current PR: "
-  cat  "$TEST_REPORTS_DIR/pr_time_benchmarks_after.txt"
-
-}
-
-if [[ "${TEST_CONFIG}" == *pr_time_benchmarks* ]]; then
-  pr_time_benchmarks
-  exit 0
-elif [[ "${TEST_CONFIG}" == *dynamo_eager* ]]; then
+if [[ "${TEST_CONFIG}" == *dynamo_eager* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--backend eager)
 elif [[ "${TEST_CONFIG}" == *aot_eager* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--backend aot_eager)
@@ -424,7 +404,7 @@ if [[ "${TEST_CONFIG}" == *dynamic* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--dynamic-shapes --dynamic-batch-only)
 fi
 
-if [[ "${TEST_CONFIG}" == *cpu* ]]; then
+if [[ "${TEST_CONFIG}" == *cpu_inductor* || "${TEST_CONFIG}" == *cpu_aot_inductor* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--device cpu)
 else
   DYNAMO_BENCHMARK_FLAGS+=(--device cuda)
@@ -448,18 +428,6 @@ test_perf_for_dashboard() {
   # TODO: All the accuracy tests can be skipped once the CI accuracy checking is stable enough
   local targets=(accuracy performance)
 
-  local device=cuda
-  if [[ "${TEST_CONFIG}" == *cpu* ]]; then
-    if [[ "${TEST_CONFIG}" == *cpu_x86* ]]; then
-      device=cpu_x86
-    elif [[ "${TEST_CONFIG}" == *cpu_aarch64* ]]; then
-      device=cpu_aarch64
-    fi
-    test_inductor_set_cpu_affinity
-  elif [[ "${TEST_CONFIG}" == *cuda_a10g* ]]; then
-    device=cuda_a10g
-  fi
-
   for mode in "${modes[@]}"; do
     if [[ "$mode" == "inference" ]]; then
       dtype=bfloat16
@@ -475,62 +443,56 @@ test_perf_for_dashboard() {
       fi
 
       if [[ "$DASHBOARD_TAG" == *default-true* ]]; then
-        $TASKSET python "benchmarks/dynamo/$suite.py" \
+        python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs "$@" \
-            --output "$TEST_REPORTS_DIR/${backend}_no_cudagraphs_${suite}_${dtype}_${mode}_${device}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_no_cudagraphs_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
       if [[ "$DASHBOARD_TAG" == *cudagraphs-true* ]]; then
-        $TASKSET python "benchmarks/dynamo/$suite.py" \
+        python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" "$@" \
-            --output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_${suite}_${dtype}_${mode}_${device}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
       if [[ "$DASHBOARD_TAG" == *dynamic-true* ]]; then
-        $TASKSET python "benchmarks/dynamo/$suite.py" \
+        python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --dynamic-shapes \
             --dynamic-batch-only "$@" \
-            --output "$TEST_REPORTS_DIR/${backend}_dynamic_${suite}_${dtype}_${mode}_${device}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_dynamic_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
       if [[ "$DASHBOARD_TAG" == *cppwrapper-true* ]] && [[ "$mode" == "inference" ]]; then
-        TORCHINDUCTOR_CPP_WRAPPER=1 $TASKSET python "benchmarks/dynamo/$suite.py" \
+        TORCHINDUCTOR_CPP_WRAPPER=1 python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs "$@" \
-            --output "$TEST_REPORTS_DIR/${backend}_cpp_wrapper_${suite}_${dtype}_${mode}_${device}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_cpp_wrapper_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
       if [[ "$DASHBOARD_TAG" == *freezing_cudagraphs-true* ]] && [[ "$mode" == "inference" ]]; then
-        $TASKSET python "benchmarks/dynamo/$suite.py" \
+        python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" "$@" --freezing \
-            --output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_freezing_${suite}_${dtype}_${mode}_${device}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_freezing_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
       if [[ "$DASHBOARD_TAG" == *freeze_autotune_cudagraphs-true* ]] && [[ "$mode" == "inference" ]]; then
-        TORCHINDUCTOR_MAX_AUTOTUNE=1 $TASKSET python "benchmarks/dynamo/$suite.py" \
+        TORCHINDUCTOR_MAX_AUTOTUNE=1 python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" "$@" --freezing \
-            --output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_freezing_autotune_${suite}_${dtype}_${mode}_${device}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_freezing_autotune_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
       if [[ "$DASHBOARD_TAG" == *aotinductor-true* ]] && [[ "$mode" == "inference" ]]; then
-        if [[ "$target" == "accuracy" ]]; then
-          # Also collect Export pass rate and display as a separate row
-          $TASKSET python "benchmarks/dynamo/$suite.py" \
-              "${target_flag[@]}" --"$mode" --"$dtype" --export --disable-cudagraphs "$@" \
-              --output "$TEST_REPORTS_DIR/${backend}_export_${suite}_${dtype}_${mode}_${device}_${target}.csv"
-        fi
-        TORCHINDUCTOR_ABI_COMPATIBLE=1 $TASKSET python "benchmarks/dynamo/$suite.py" \
+        TORCHINDUCTOR_ABI_COMPATIBLE=1 python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --export-aot-inductor --disable-cudagraphs "$@" \
-            --output "$TEST_REPORTS_DIR/${backend}_aot_inductor_${suite}_${dtype}_${mode}_${device}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_aot_inductor_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
       if [[ "$DASHBOARD_TAG" == *maxautotune-true* ]]; then
-        TORCHINDUCTOR_MAX_AUTOTUNE=1 $TASKSET python "benchmarks/dynamo/$suite.py" \
+        TORCHINDUCTOR_MAX_AUTOTUNE=1 python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" "$@" \
-            --output "$TEST_REPORTS_DIR/${backend}_max_autotune_${suite}_${dtype}_${mode}_${device}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_max_autotune_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
       if [[ "$DASHBOARD_TAG" == *cudagraphs_low_precision-true* ]] && [[ "$mode" == "inference" ]]; then
         # TODO: This has a new dtype called quant and the benchmarks script needs to be updated to support this.
         # The tentative command is as follows. It doesn't work now, but it's ok because we only need mock data
         # to fill the dashboard.
-        $TASKSET python "benchmarks/dynamo/$suite.py" \
+        python "benchmarks/dynamo/$suite.py" \
           "${target_flag[@]}" --"$mode" --quant --backend "$backend" "$@" \
-          --output "$TEST_REPORTS_DIR/${backend}_cudagraphs_low_precision_${suite}_quant_${mode}_${device}_${target}.csv" || true
+          --output "$TEST_REPORTS_DIR/${backend}_cudagraphs_low_precision_${suite}_quant_${mode}_cuda_${target}.csv" || true
         # Copy cudagraph results as mock data, easiest choice?
-        cp "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_${suite}_${dtype}_${mode}_${device}_${target}.csv" \
-          "$TEST_REPORTS_DIR/${backend}_cudagraphs_low_precision_${suite}_quant_${mode}_${device}_${target}.csv"
+        cp "$TEST_REPORTS_DIR/${backend}_with_cudagraphs_${suite}_${dtype}_${mode}_cuda_${target}.csv" \
+          "$TEST_REPORTS_DIR/${backend}_cudagraphs_low_precision_${suite}_quant_${mode}_cuda_${target}.csv"
       fi
     done
   done
@@ -573,13 +535,6 @@ test_single_dynamo_benchmark() {
       # For CPU device, we perfer non ABI-compatible mode on CI when testing AOTInductor.
       export TORCHINDUCTOR_ABI_COMPATIBLE=1
     fi
-
-    if [[ "${TEST_CONFIG}" == *_avx2* ]]; then
-      TEST_CONFIG=${TEST_CONFIG//_avx2/}
-    fi
-    if [[ "${TEST_CONFIG}" == *_avx512* ]]; then
-      TEST_CONFIG=${TEST_CONFIG//_avx512/}
-    fi
     python "benchmarks/dynamo/$suite.py" \
       --ci --accuracy --timing --explain \
       "${DYNAMO_BENCHMARK_FLAGS[@]}" \
@@ -596,9 +551,6 @@ 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"
 }
 
@@ -621,7 +573,7 @@ test_dynamo_benchmark() {
   elif [[ "${TEST_CONFIG}" == *perf* ]]; then
     test_single_dynamo_benchmark "dashboard" "$suite" "$shard_id" "$@"
   else
-    if [[ "${TEST_CONFIG}" == *cpu* ]]; then
+    if [[ "${TEST_CONFIG}" == *cpu_inductor* || "${TEST_CONFIG}" == *cpu_aot_inductor* ]]; then
       local dt="float32"
       if [[ "${TEST_CONFIG}" == *amp* ]]; then
         dt="amp"
@@ -668,7 +620,8 @@ test_inductor_torchbench_smoketest_perf() {
   # https://github.com/pytorch/pytorch/actions/runs/7158691360/job/19491437314,
   # and thus we lower its threshold to reduce flakiness. If this continues to be a problem,
   # we switch to use some other model.
-  python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t 4.9
+  # lowering threshold from 4.9 to 4.7 for cu124. Will bump it up after cuda 12.4.0->12.4.1 update
+  python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv" -t 4.7
 
   # Check memory compression ratio for a few models
   for test in hf_Albert timm_vision_transformer; do
@@ -691,77 +644,48 @@ test_inductor_torchbench_smoketest_perf() {
   done
 }
 
-test_inductor_get_core_number() {
-  if [[ "${TEST_CONFIG}" == *aarch64* ]]; then
-    echo "$(($(lscpu | grep 'Cluster(s):' | awk '{print $2}') * $(lscpu | grep 'Core(s) per cluster:' | awk '{print $4}')))"
-  else
-    echo "$(($(lscpu | grep 'Socket(s):' | awk '{print $2}') * $(lscpu | grep 'Core(s) per socket:' | awk '{print $4}')))"
-  fi
-}
-
-test_inductor_set_cpu_affinity(){
-  #set jemalloc
-  JEMALLOC_LIB="$(find /usr/lib -name libjemalloc.so.2)"
-  export LD_PRELOAD="$JEMALLOC_LIB":"$LD_PRELOAD"
-  export MALLOC_CONF="oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:-1,muzzy_decay_ms:-1"
-
-  if [[ "${TEST_CONFIG}" != *aarch64* ]]; then
-    # Use Intel OpenMP for x86
-    IOMP_LIB="$(dirname "$(which python)")/../lib/libiomp5.so"
-    export LD_PRELOAD="$IOMP_LIB":"$LD_PRELOAD"
-    export KMP_AFFINITY=granularity=fine,compact,1,0
-    export KMP_BLOCKTIME=1
-  fi
-  cores=$(test_inductor_get_core_number)
-  export OMP_NUM_THREADS=$cores
-  end_core=$((cores-1))
-  export TASKSET="taskset -c 0-$end_core"
-}
-
 test_inductor_torchbench_cpu_smoketest_perf(){
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
 
-  test_inductor_set_cpu_affinity
+  #set jemalloc
+  JEMALLOC_LIB="/usr/lib/x86_64-linux-gnu/libjemalloc.so.2"
+  IOMP_LIB="$(dirname "$(which python)")/../lib/libiomp5.so"
+  export LD_PRELOAD="$JEMALLOC_LIB":"$IOMP_LIB":"$LD_PRELOAD"
+  export MALLOC_CONF="oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:-1,muzzy_decay_ms:-1"
+  export KMP_AFFINITY=granularity=fine,compact,1,0
+  export KMP_BLOCKTIME=1
+  CORES=$(lscpu | grep Core | awk '{print $4}')
+  export OMP_NUM_THREADS=$CORES
+  end_core=$(( CORES-1 ))
+
   MODELS_SPEEDUP_TARGET=benchmarks/dynamo/expected_ci_speedup_inductor_torchbench_cpu.csv
 
   grep -v '^ *#' < "$MODELS_SPEEDUP_TARGET" | while IFS=',' read -r -a model_cfg
   do
     local model_name=${model_cfg[0]}
-    local data_type=${model_cfg[2]}
-    local speedup_target=${model_cfg[5]}
-    local backend=${model_cfg[1]}
-    if [[ ${model_cfg[4]} == "cpp" ]]; then
+    local data_type=${model_cfg[1]}
+    local speedup_target=${model_cfg[4]}
+    if [[ ${model_cfg[3]} == "cpp" ]]; then
       export TORCHINDUCTOR_CPP_WRAPPER=1
     else
       unset TORCHINDUCTOR_CPP_WRAPPER
     fi
     local output_name="$TEST_REPORTS_DIR/inductor_inference_${model_cfg[0]}_${model_cfg[1]}_${model_cfg[2]}_${model_cfg[3]}_cpu_smoketest.csv"
 
-    if [[ ${model_cfg[3]} == "dynamic" ]]; then
-      $TASKSET python benchmarks/dynamo/torchbench.py \
+    if [[ ${model_cfg[2]} == "dynamic" ]]; then
+      taskset -c 0-"$end_core" python benchmarks/dynamo/torchbench.py \
         --inference --performance --"$data_type" -dcpu -n50 --only "$model_name" --dynamic-shapes \
-        --dynamic-batch-only --freezing --timeout 9000 --"$backend" --output "$output_name"
+        --dynamic-batch-only --freezing --timeout 9000 --backend=inductor --output "$output_name"
     else
-      $TASKSET python benchmarks/dynamo/torchbench.py \
+      taskset -c 0-"$end_core" python benchmarks/dynamo/torchbench.py \
         --inference --performance --"$data_type" -dcpu -n50 --only "$model_name" \
-        --freezing --timeout 9000 --"$backend" --output "$output_name"
+        --freezing --timeout 9000 --backend=inductor --output "$output_name"
     fi
     cat "$output_name"
     # The threshold value needs to be actively maintained to make this check useful.
     python benchmarks/dynamo/check_perf_csv.py -f "$output_name" -t "$speedup_target"
   done
-
-  # Add a few ABI-compatible accuracy tests for CPU. These can be removed once we turn on ABI-compatible as default.
-  TORCHINDUCTOR_ABI_COMPATIBLE=1 python benchmarks/dynamo/timm_models.py --device cpu --accuracy \
-    --bfloat16 --inference --export-aot-inductor --disable-cudagraphs --only adv_inception_v3 \
-    --output "$TEST_REPORTS_DIR/aot_inductor_smoke_test.csv"
-  TORCHINDUCTOR_ABI_COMPATIBLE=1 python benchmarks/dynamo/timm_models.py --device cpu --accuracy \
-    --bfloat16 --inference --export-aot-inductor --disable-cudagraphs --only beit_base_patch16_224 \
-    --output "$TEST_REPORTS_DIR/aot_inductor_smoke_test.csv"
-  python benchmarks/dynamo/check_accuracy.py \
-    --actual "$TEST_REPORTS_DIR/aot_inductor_smoke_test.csv" \
-    --expected "benchmarks/dynamo/ci_expected_accuracy/aot_inductor_timm_inference.csv"
 }
 
 test_torchbench_gcp_smoketest(){
@@ -1075,113 +999,11 @@ test_xla() {
   assert_git_not_dirty
 }
 
-function check_public_api_test_fails {
-    test_name=$1
-    invalid_item_name=$2
-    invalid_item_desc=$3
-
-    echo "Running public API test '${test_name}'..."
-    test_output=$(python test/test_public_bindings.py -k "${test_name}" 2>&1) && ret=$? || ret=$?
-
-    # Ensure test fails correctly.
-    if [ "$ret" -eq 0 ]; then
-        cat << EOF
-Expected the public API test '${test_name}' to fail after introducing
-${invalid_item_desc}, but it succeeded! Check test/test_public_bindings.py
-for any changes that may have broken the test.
-EOF
-        return 1
-    fi
-
-    # Ensure invalid item is in the test output.
-    echo "${test_output}" | grep -q "${invalid_item_name}" && ret=$? || ret=$?
-
-    if [ $ret -ne 0 ]; then
-        cat << EOF
-Expected the public API test '${test_name}' to identify ${invalid_item_desc}, but
-it didn't! It's possible the test may not have run. Check test/test_public_bindings.py
-for any changes that may have broken the test.
-EOF
-        return 1
-    fi
-
-    echo "Success! '${test_name}' identified ${invalid_item_desc} ${invalid_item_name}."
-    return 0
-}
-
 # Do NOT run this test before any other tests, like test_python_shard, etc.
 # Because this function uninstalls the torch built from branch and installs
 # the torch built on its base commit.
 test_forward_backward_compatibility() {
   set -x
-
-  # First, validate public API tests in the torch built from branch.
-  # Step 1. Make sure the public API test "test_correct_module_names" fails when a new file
-  # introduces an invalid public API function.
-  new_filename=$(mktemp XXXXXXXX.py -p "${TORCH_INSTALL_DIR}")
-
-  BAD_PUBLIC_FUNC=$(
-  cat << 'EOF'
-def new_public_func():
-  pass
-
-# valid public API functions have __module__ set correctly
-new_public_func.__module__ = None
-EOF
-  )
-
-  echo "${BAD_PUBLIC_FUNC}" >> "${new_filename}"
-  invalid_api="torch.$(basename -s '.py' "${new_filename}").new_public_func"
-  echo "Created an invalid public API function ${invalid_api}..."
-
-  check_public_api_test_fails \
-      "test_correct_module_names" \
-      "${invalid_api}" \
-      "an invalid public API function" && ret=$? || ret=$?
-
-  rm -v "${new_filename}"
-
-  if [ "$ret" -ne 0 ]; then
-      exit 1
-  fi
-
-  # Step 2. Make sure that the public API test "test_correct_module_names" fails when an existing
-  # file is modified to introduce an invalid public API function.
-  EXISTING_FILEPATH="${TORCH_INSTALL_DIR}/nn/parameter.py"
-  cp -v "${EXISTING_FILEPATH}" "${EXISTING_FILEPATH}.orig"
-  echo "${BAD_PUBLIC_FUNC}" >> "${EXISTING_FILEPATH}"
-  invalid_api="torch.nn.parameter.new_public_func"
-  echo "Appended an invalid public API function to existing file ${EXISTING_FILEPATH}..."
-
-  check_public_api_test_fails \
-      "test_correct_module_names" \
-      "${invalid_api}" \
-      "an invalid public API function" && ret=$? || ret=$?
-
-  mv -v "${EXISTING_FILEPATH}.orig" "${EXISTING_FILEPATH}"
-
-  if [ "$ret" -ne 0 ]; then
-      exit 1
-  fi
-
-  # Step 3. Make sure that the public API test "test_modules_can_be_imported" fails when a module
-  # cannot be imported.
-  new_module_dir=$(mktemp XXXXXXXX -d -p "${TORCH_INSTALL_DIR}")
-  echo "invalid syntax garbage" > "${new_module_dir}/__init__.py"
-  invalid_module_name="torch.$(basename "${new_module_dir}")"
-
-  check_public_api_test_fails \
-      "test_modules_can_be_imported" \
-      "${invalid_module_name}" \
-      "a non-importable module" && ret=$? || ret=$?
-
-  rm -rv "${new_module_dir}"
-
-  if [ "$ret" -ne 0 ]; then
-      exit 1
-  fi
-
-  # Next, build torch from the merge base.
   REPO_DIR=$(pwd)
   if [[ "${BASE_SHA}" == "${SHA1}" ]]; then
     echo "On trunk, we should compare schemas with torch built from the parent commit"
@@ -1407,7 +1229,7 @@ if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-baze
   (cd test && python -c "import torch; print(torch.__config__.show())")
   (cd test && python -c "import torch; print(torch.__config__.parallel_info())")
 fi
-if [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" != *perf_cpu_aarch64* ]]; then
+if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
   test_linux_aarch64
 elif [[ "${TEST_CONFIG}" == *backward* ]]; then
   test_forward_backward_compatibility
@@ -1444,7 +1266,7 @@ elif [[ "${TEST_CONFIG}" == *timm* ]]; then
   id=$((SHARD_NUMBER-1))
   test_dynamo_benchmark timm_models "$id"
 elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
-  if [[ "${TEST_CONFIG}" == *cpu* ]]; then
+  if [[ "${TEST_CONFIG}" == *cpu_inductor* || "${TEST_CONFIG}" == *cpu_aot_inductor* ]]; then
     install_torchaudio cpu
   else
     install_torchaudio cuda
@@ -1459,9 +1281,9 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
     checkout_install_torchbench hf_Bert hf_Albert nanogpt timm_vision_transformer
     PYTHONPATH=$(pwd)/torchbench test_inductor_torchbench_smoketest_perf
   elif [[ "${TEST_CONFIG}" == *inductor_torchbench_cpu_smoketest_perf* ]]; then
-    checkout_install_torchbench timm_vision_transformer phlippe_densenet basic_gnn_edgecnn \
+    checkout_install_torchbench timm_vision_transformer phlippe_densenet basic_gnn_gcn \
       llama_v2_7b_16h resnet50 timm_efficientnet mobilenet_v3_large timm_resnest \
-      functorch_maml_omniglot yolov3 mobilenet_v2 resnext50_32x4d densenet121 mnasnet1_0
+      shufflenet_v2_x1_0 hf_GPT2
     PYTHONPATH=$(pwd)/torchbench test_inductor_torchbench_cpu_smoketest_perf
   elif [[ "${TEST_CONFIG}" == *torchbench_gcp_smoketest* ]]; then
     checkout_install_torchbench
@@ -1470,7 +1292,7 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
     checkout_install_torchbench
     # Do this after checkout_install_torchbench to ensure we clobber any
     # nightlies that torchbench may pull in
-    if [[ "${TEST_CONFIG}" != *cpu* ]]; then
+    if [[ "${TEST_CONFIG}" != *cpu_inductor* && "${TEST_CONFIG}" != *cpu_aot_inductor* ]]; then
       install_torchrec_and_fbgemm
     fi
     PYTHONPATH=$(pwd)/torchbench test_dynamo_benchmark torchbench "$id"
@@ -1482,9 +1304,8 @@ elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
   install_torchvision
   test_inductor_shard "${SHARD_NUMBER}"
   if [[ "${SHARD_NUMBER}" == 1 ]]; then
-    if [[ "${BUILD_ENVIRONMENT}" != linux-jammy-py3.9-gcc11-build ]]; then
-      test_inductor_distributed
-    fi
+    test_inductor_aoti
+    test_inductor_distributed
   fi
 elif [[ "${TEST_CONFIG}" == *dynamo* ]]; then
   install_torchvision

.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
 
@@ -81,6 +65,13 @@ set CUDA_PATH_V%VERSION_SUFFIX%=%CUDA_PATH%
 set CUDNN_LIB_DIR=%CUDA_PATH%\lib\x64
 set CUDA_TOOLKIT_ROOT_DIR=%CUDA_PATH%
 set CUDNN_ROOT_DIR=%CUDA_PATH%
+set NVTOOLSEXT_PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt
+set PATH=%CUDA_PATH%\bin;%CUDA_PATH%\libnvvp;%PATH%
+
+set CUDNN_LIB_DIR=%CUDA_PATH%\lib\x64
+set CUDA_TOOLKIT_ROOT_DIR=%CUDA_PATH%
+set CUDNN_ROOT_DIR=%CUDA_PATH%
+set NVTOOLSEXT_PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt
 set PATH=%CUDA_PATH%\bin;%CUDA_PATH%\libnvvp;%PATH%
 
 :cuda_build_end

.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-helpers/setup_pytorch_env.bat

@@ -40,6 +40,7 @@ set CUDA_PATH_V%VERSION_SUFFIX%=%CUDA_PATH%
 set CUDNN_LIB_DIR=%CUDA_PATH%\lib\x64
 set CUDA_TOOLKIT_ROOT_DIR=%CUDA_PATH%
 set CUDNN_ROOT_DIR=%CUDA_PATH%
+set NVTOOLSEXT_PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt
 set PATH=%CUDA_PATH%\bin;%CUDA_PATH%\libnvvp;%PATH%
 set NUMBAPRO_CUDALIB=%CUDA_PATH%\bin
 set NUMBAPRO_LIBDEVICE=%CUDA_PATH%\nvvm\libdevice

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

@@ -31,6 +31,6 @@ if ERRORLEVEL 1 exit /b 1
 
 :: Run tests C++-side and load the exported script module.
 cd build
-set PATH=%TMP_DIR_WIN%\build\torch\lib;%PATH%
+set PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt\bin\x64;%TMP_DIR_WIN%\build\torch\lib;%PATH%
 test_custom_backend.exe model.pt
 if ERRORLEVEL 1 exit /b 1

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

@@ -31,6 +31,6 @@ if ERRORLEVEL 1 exit /b 1
 
 :: Run tests C++-side and load the exported script module.
 cd build
-set PATH=%TMP_DIR_WIN%\build\torch\lib;%PATH%
+set PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt\bin\x64;%TMP_DIR_WIN%\build\torch\lib;%PATH%
 test_custom_ops.exe model.pt
 if ERRORLEVEL 1 exit /b 1

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

@@ -5,7 +5,7 @@ if errorlevel 1 exit /b 1
 set CWD=%cd%
 
 set CPP_TESTS_DIR=%TMP_DIR_WIN%\build\torch\bin
-set PATH=%TMP_DIR_WIN%\build\torch\lib;%PATH%
+set PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt\bin\x64;%TMP_DIR_WIN%\build\torch\lib;%PATH%
 
 set TORCH_CPP_TEST_MNIST_PATH=%CWD%\test\cpp\api\mnist
 python tools\download_mnist.py --quiet -d %TORCH_CPP_TEST_MNIST_PATH%

.ci/pytorch/win-test.sh

@@ -40,9 +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
-
 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

@@ -46,12 +46,14 @@ if [[ "\$python_nodot" = *310* ]]; then
   PROTOBUF_PACKAGE="protobuf>=3.19.0"
 fi
 
-if [[ "\$python_nodot" = *39* ]]; then
+if [[ "\$python_nodot" = *39*  ]]; then
   # There's an issue with conda channel priority where it'll randomly pick 1.19 over 1.20
   # we set a lower boundary here just to be safe
   NUMPY_PIN=">=1.20"
 fi
 
+
+
 # Move debug wheels out of the package dir so they don't get installed
 mkdir -p /tmp/debug_final_pkgs
 mv /final_pkgs/debug-*.zip /tmp/debug_final_pkgs || echo "no debug packages to move"
@@ -81,7 +83,7 @@ if [[ "$PACKAGE_TYPE" == conda ]]; then
       "numpy\${NUMPY_PIN}" \
       mkl>=2018 \
       ninja \
-      sympy>=1.12 \
+      sympy \
       typing-extensions \
       ${PROTOBUF_PACKAGE}
     if [[ "$DESIRED_CUDA" == 'cpu' ]]; then
@@ -116,14 +118,15 @@ if [[ "$PACKAGE_TYPE" == libtorch ]]; then
   cd /tmp/libtorch
 fi
 
+if [[ "$GPU_ARCH_TYPE" == xpu ]]; then
+  # Workaround for __mkl_tmp_MOD unbound variable issue, refer https://github.com/pytorch/pytorch/issues/130543
+  set +u
+  source /opt/intel/oneapi/pytorch-gpu-dev-0.5/oneapi-vars.sh
+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
@@ -102,10 +102,10 @@ fi
 
 # Set triton via PYTORCH_EXTRA_INSTALL_REQUIREMENTS for triton xpu package
 if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*xpu.* && $(uname) == "Linux" ]]; then
-    TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
+    TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}"
     if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
         TRITON_SHORTHASH=$(cut -c1-10 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton-xpu.txt)
-        TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}+${TRITON_SHORTHASH}; ${TRITON_CONSTRAINT}"
+        TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}+${TRITON_SHORTHASH}"
     fi
     if [[ -z "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
         export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${TRITON_REQUIREMENT}"

.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

.devcontainer/scripts/install-dev-tools.sh

@@ -5,7 +5,7 @@ git submodule sync
 git submodule update --init --recursive
 
 # This takes some time
-make setup-lint
+make setup_lint
 
 # Add CMAKE_PREFIX_PATH to bashrc
 echo 'export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}' >> ~/.bashrc

.flake8

@@ -7,7 +7,7 @@ max-line-length = 120
 # C408 ignored because we like the dict keyword argument syntax
 # E501 is not flexible enough, we're using B950 instead
 ignore =
-    E203,E305,E402,E501,E704,E721,E741,F405,F841,F999,W503,W504,C408,E302,W291,E303,
+    E203,E305,E402,E501,E721,E741,F405,F841,F999,W503,W504,C408,E302,W291,E303,
     # shebang has extra meaning in fbcode lints, so I think it's not worth trying
     # to line this up with executable bit
     EXE001,
@@ -55,9 +55,6 @@ per-file-ignores =
     torch/distributed/_functional_collectives.py: TOR901
     torch/distributed/_spmd/data_parallel.py: TOR901
     torch/distributed/_tensor/_collective_utils.py: TOR901
-    # This is a full package that happen to live within the test
-    # folder, so ok to skip
-    test/cpp_extensions/open_registration_extension/pytorch_openreg/_aten_impl.py: TOR901
 optional-ascii-coding = True
 exclude =
     ./.git,

.github/actionlint.yaml

@@ -3,25 +3,20 @@ 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
     - linux.4xlarge
-    - linux.9xlarge.ephemeral
-    - am2.linux.9xlarge.ephemeral
     - linux.12xlarge
-    - linux.12xlarge.ephemeral
     - linux.24xlarge
-    - linux.24xlarge.ephemeral
     - linux.arm64.2xlarge
-    - linux.arm64.2xlarge.ephemeral
-    - linux.arm64.m7g.4xlarge
-    - linux.arm64.m7g.4xlarge.ephemeral
     - linux.4xlarge.nvidia.gpu
     - linux.8xlarge.nvidia.gpu
     - linux.16xlarge.nvidia.gpu
     - linux.g5.4xlarge.nvidia.gpu
-    # Pytorch/pytorch AWS Linux Runners on Linux Foundation account
+    # Organization-wide AWS Linux Runners on Linux Foundation account
     - lf.linux.large
     - lf.linux.2xlarge
     - lf.linux.4xlarge
@@ -32,36 +27,9 @@ 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
-    - windows.g4dn.xlarge
-    - windows.g4dn.xlarge.nonephemeral
-    - windows.4xlarge
     - windows.4xlarge.nonephemeral
     - windows.8xlarge.nvidia.gpu
     - windows.8xlarge.nvidia.gpu.nonephemeral

.github/actions/filter-test-configs/action.yml

@@ -41,9 +41,6 @@ outputs:
   ci-verbose-test-logs:
     description: True if ci-verbose-test-logs label was on PR or [ci-verbose-test-logs] in PR body.
     value: ${{ steps.filter.outputs.ci-verbose-test-logs }}
-  ci-test-showlocals:
-    description: True if ci-test-showlocals label was on PR or [ci-test-showlocals] in PR body.
-    value: ${{ steps.filter.outputs.ci-test-showlocals }}
   ci-no-test-timeout:
     description: True if ci-no-test-timeout label was on PR or [ci-no-test-timeout] in PR body.
     value: ${{ steps.filter.outputs.ci-no-test-timeout }}
@@ -57,7 +54,7 @@ outputs:
 runs:
   using: composite
   steps:
-    - uses: nick-fields/retry@v3.0.0
+    - uses: nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482
       name: Setup dependencies
       env:
         GITHUB_TOKEN: ${{ inputs.github-token }}

.github/actions/linux-build/action.yml

@@ -0,0 +1,226 @@
+name: linux-build
+
+inputs:
+  build-environment:
+    required: true
+    description: Top-level label for what's being built/tested.
+  docker-image-name:
+    required: true
+    description: Name of the base docker image to build with.
+  build-generates-artifacts:
+    required: false
+    default: "true"
+    description: If set, upload generated build artifacts.
+  build-with-debug:
+    required: false
+    default: "false"
+    description: If set, build in debug mode.
+  sync-tag:
+    required: false
+    default: ""
+    description: |
+      If this is set, our linter will use this to make sure that every other
+      job with the same `sync-tag` is identical.
+  cuda-arch-list:
+    required: false
+    default: "5.2"
+    description: Runner label to select worker type
+  runner:
+    required: false
+    default: "linux.2xlarge"
+    description: |
+      List of CUDA architectures CI build should target.
+  test-matrix:
+    required: false
+    type: string
+    description: |
+      An option JSON description of what test configs to run later on. This
+      is moved here from the Linux test workflow so that we can apply filter
+      logic using test-config labels earlier and skip unnecessary builds
+  s3-bucket:
+    description: S3 bucket to download artifact
+    required: false
+    default: "gha-artifacts"
+  aws-role-to-assume:
+    description: role to assume for downloading artifacts
+    required: false
+    default: ""
+  GITHUB_TOKEN:
+    description: GitHub token
+    required: true
+  HUGGING_FACE_HUB_TOKEN:
+    description: Hugging Face Hub token
+    required: false
+    default: ""
+  use_split_build:
+    description: |
+      [Experimental] Build a libtorch only wheel and build pytorch such that
+      are built from the libtorch wheel.
+    required: false
+    type: boolean
+    default: false
+outputs:
+  docker-image:
+    value: ${{ steps.calculate-docker-image.outputs.docker-image }}
+    description: The docker image containing the built PyTorch.
+  test-matrix:
+    value: ${{ steps.filter.outputs.test-matrix }}
+    description: An optional JSON description of what test configs to run later on.
+
+runs:
+  using: composite
+  steps:
+    - name: Setup Linux
+      uses: ./.github/actions/setup-linux
+
+    - name: configure aws credentials
+      uses: aws-actions/configure-aws-credentials@v3
+      if: ${{ inputs.aws-role-to-assume != '' }}
+      with:
+        role-to-assume: ${{ inputs.aws-role-to-assume }}
+        role-session-name: gha-linux-build
+        role-duration-seconds: 10800
+        aws-region: us-east-1
+
+    - name: Calculate docker image
+      id: calculate-docker-image
+      uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
+      with:
+        docker-image-name: ${{ inputs.docker-image-name }}
+
+    - name: Use following to pull public copy of the image
+      id: print-ghcr-mirror
+      env:
+        ECR_DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
+      shell: bash
+      run: |
+        tag=${ECR_DOCKER_IMAGE##*/}
+        echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}"
+
+    - name: Pull docker image
+      uses: pytorch/test-infra/.github/actions/pull-docker-image@main
+      with:
+        docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
+
+    - name: Parse ref
+      id: parse-ref
+      shell: bash
+      run: .github/scripts/parse_ref.py
+
+    - name: Get workflow job id
+      id: get-job-id
+      uses: ./.github/actions/get-workflow-job-id
+      if: always()
+      with:
+        github-token: ${{ inputs.GITHUB_TOKEN }}
+
+    # Apply the filter logic to the build step too if the test-config label is already there
+    - name: Select all requested test configurations (if the test matrix is available)
+      id: filter
+      uses: ./.github/actions/filter-test-configs
+      with:
+        github-token: ${{ inputs.GITHUB_TOKEN }}
+        test-matrix: ${{ inputs.test-matrix }}
+        job-name: ${{ steps.get-job-id.outputs.job-name }}
+
+    - name: Download pytest cache
+      uses: ./.github/actions/pytest-cache-download
+      continue-on-error: true
+      with:
+        cache_dir: .pytest_cache
+        job_identifier: ${{ github.workflow }}_${{ inputs.build-environment }}
+        s3_bucket: ${{ inputs.s3-bucket }}
+
+    - name: Build
+      if: steps.filter.outputs.is-test-matrix-empty == 'False' || inputs.test-matrix == ''
+      id: build
+      env:
+        BUILD_ENVIRONMENT: ${{ inputs.build-environment }}
+        BRANCH: ${{ steps.parse-ref.outputs.branch }}
+        # TODO duplicated
+        AWS_DEFAULT_REGION: us-east-1
+        PR_NUMBER: ${{ github.event.pull_request.number }}
+        SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
+        SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
+        SCCACHE_S3_KEY_PREFIX: ${{ github.workflow }}
+        XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla
+        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 }}
+        XLA_CUDA: ${{ contains(inputs.build-environment, 'xla') && '0' || '' }}
+        DEBUG: ${{ inputs.build-with-debug == 'true' && '1' || '0' }}
+        OUR_GITHUB_JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
+        HUGGING_FACE_HUB_TOKEN: ${{ inputs.HUGGING_FACE_HUB_TOKEN }}
+        USE_SPLIT_BUILD: ${{ inputs.use_split_build }}
+      shell: bash
+      run: |
+        # detached container should get cleaned up by teardown_ec2_linux
+        container_name=$(docker run \
+          -e BUILD_ENVIRONMENT \
+          -e MAX_JOBS="$(nproc --ignore=2)" \
+          -e AWS_DEFAULT_REGION \
+          -e PR_NUMBER \
+          -e SHA1 \
+          -e BRANCH \
+          -e SCCACHE_BUCKET \
+          -e SCCACHE_S3_KEY_PREFIX \
+          -e XLA_CUDA \
+          -e XLA_CLANG_CACHE_S3_BUCKET_NAME \
+          -e SKIP_SCCACHE_INITIALIZATION=1 \
+          -e TORCH_CUDA_ARCH_LIST \
+          -e PR_LABELS \
+          -e OUR_GITHUB_JOB_ID \
+          -e HUGGING_FACE_HUB_TOKEN \
+          -e USE_SPLIT_BUILD \
+          --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
+          --security-opt seccomp=unconfined \
+          --cap-add=SYS_PTRACE \
+          --tty \
+          --detach \
+          --user jenkins \
+          -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \
+          -w /var/lib/jenkins/workspace \
+          "${DOCKER_IMAGE}"
+        )
+        docker exec -t "${container_name}" sh -c '.ci/pytorch/build.sh'
+
+    - name: Archive artifacts into zip
+      if: inputs.build-generates-artifacts == 'true' && steps.build.outcome != 'skipped'
+      shell: bash
+      run: |
+        zip -1 -r artifacts.zip dist/ build/custom_test_artifacts build/lib build/bin .additional_ci_files
+
+    - name: Store PyTorch Build Artifacts on S3
+      uses: seemethere/upload-artifact-s3@v5
+      if: inputs.build-generates-artifacts == 'true' && steps.build.outcome != 'skipped' && inputs.use_split_build != 'true'
+      with:
+        name: ${{ inputs.build-environment }}
+        retention-days: 14
+        if-no-files-found: error
+        path: artifacts.zip
+        s3-bucket: ${{ inputs.s3-bucket }}
+
+    - name: Store PyTorch Build Artifacts on S3 for split build
+      uses: seemethere/upload-artifact-s3@v5
+      if: inputs.build-generates-artifacts == 'true' && steps.build.outcome != 'skipped' && inputs.use_split_build == 'true'
+      with:
+        name: ${{ inputs.build-environment }}-experimental-split-build
+        retention-days: 14
+        if-no-files-found: error
+        path: artifacts.zip
+        s3-bucket: ${{ inputs.s3-bucket }}
+
+    - name: Upload sccache stats
+      if: steps.build.outcome != 'skipped'
+      uses: seemethere/upload-artifact-s3@v5
+      with:
+        s3-prefix: |
+          ${{ github.repository }}/${{ github.run_id }}/${{ github.run_attempt }}/artifact
+        retention-days: 365
+        if-no-files-found: warn
+        path: sccache-stats-*.json
+        s3-bucket: ${{ inputs.s3-bucket }}
+
+    - name: Teardown Linux
+      uses: pytorch/test-infra/.github/actions/teardown-linux@main
+      if: always()

.github/actions/linux-test/action.yml

@@ -167,7 +167,6 @@ runs:
         REENABLED_ISSUES: ${{ steps.keep-going.outputs.reenabled-issues }}
         CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
         VERBOSE_TEST_LOGS: ${{ steps.keep-going.outputs.ci-verbose-test-logs }}
-        TEST_SHOWLOCALS: ${{ steps.keep-going.outputs.ci-test-showlocals }}
         NO_TEST_TIMEOUT: ${{ steps.keep-going.outputs.ci-no-test-timeout }}
         NO_TD: ${{ steps.keep-going.outputs.ci-no-td }}
         TD_DISTRIBUTED: ${{ steps.keep-going.outputs.ci-td-distributed }}

.github/actions/pytest-cache-download/action.yml

@@ -17,7 +17,7 @@ inputs:
 runs:
   using: composite
   steps:
-    - uses: nick-fields/retry@v3.0.0
+    - uses: nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482
       name: Setup dependencies
       with:
         shell: bash

.github/actions/pytest-cache-upload/action.yml

@@ -24,7 +24,7 @@ inputs:
 runs:
   using: composite
   steps:
-    - uses: nick-fields/retry@v3.0.0
+    - uses: nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482
       name: Setup dependencies
       with:
         shell: bash

.github/actions/setup-linux/action.yml

@@ -44,7 +44,7 @@ runs:
         fi
 
     - name: Log in to ECR
-      uses: nick-fields/retry@v3.0.0
+      uses: nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482
       env:
         AWS_RETRY_MODE: standard
         AWS_MAX_ATTEMPTS: "5"
@@ -59,13 +59,6 @@ runs:
           aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \
               --password-stdin "$AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com"
 
-          # For LF Runners we need to make sure we also login to Meta's ECR docker registry too.
-          META_AWS_ACCOUNT_ID=308535385114
-          if [ "$AWS_ACCOUNT_ID" != "$META_AWS_ACCOUNT_ID" ] ; then
-              aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \
-                  --password-stdin "$META_AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com"
-          fi
-
     - name: Preserve github env variables for use in docker
       shell: bash
       run: |

.github/actions/teardown-win/action.yml

@@ -31,7 +31,7 @@ runs:
     # retry this step several time similar to how checkout-pytorch GHA does
     - name: Cleanup workspace
       if: always()
-      uses: nick-fields/retry@v3.0.0
+      uses: nick-fields/retry@v2.8.2
       env:
         EXTRA_DELETE_DIR: ${{ inputs.extra-delete-dir }}
       with:

.github/ci_commit_pins/audio.txt

@@ -1 +1 @@
-97ed7b36b7a741253d4e41e4da3c901d83294503
+69b2a0adc2ec03ab99990d7e8be3d4510438c148

.github/ci_commit_pins/xla.txt

@@ -1 +1 @@
-r2.5
+6f0b61e5d782913a0fc7743812f2a8e522189111

.github/label_to_label.yml

@@ -1,50 +1,13 @@
 # Use this to auto apply labels based on other labels.  Applies to both PRs and
 # issues. Currently only supports any and all
 - any:
-  - "module: opcheck"
-  then:
-  - "module: custom-operators"
-- any:
-  - "module: custom-operators"
-  - "module: functionalization"
+  - "module: custom operators"
   - "module: aotdispatch"
-  - "module: higher order operators"
-  - "module: fakeTensor"
-  - "module: ProxyTensor"
-  - "module: library"
-  - "module: reinplacing"
   then:
   - "module: pt2-dispatcher"
-- any:
-  - "module: vmap"
-  then:
-  - "module: functorch"
-- any:
-  - "module: reinplacing"
-  then:
-  - "module: inductor"
-- any:
-  - "module: pt2 optimizer"
-  then:
-  - "module: dynamo"
-- any:
-  - "module: flex attention"
-  then:
-  - "module: higher order operators"
-- any:
-  - "module: aotinductor"
-  then:
-  - "oncall: export"
 - any:
   - "module: dynamo"
   - "module: pt2-dispatcher"
   - "module: inductor"
-  - "module: aotinductor"
-  - "module: cudagraphs"
-  - "oncall: export"
-  - "module: startup-tracing-compile"
-  - "module: compiled autograd"
-  - "module: flex attention"
-  - "module: dynamic shapes"
   then:
   - "oncall: pt2"

.github/labeler.yml

@@ -29,6 +29,7 @@
 - torch/fx/experimental/recording.py
 - torch/fx/experimental/sym_node.py
 - torch/fx/experimental/validator.py
+- torch/fx/experimental/_sym_dispatch_mode.py
 - torch/fx/experimental/proxy_tensor.py
 - test/distributed/_tensor/test_dtensor_compile.py
 - test/distributed/tensor/parallel/test_fsdp_2d_parallel.py

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

@@ -1,23 +1,13 @@
-
-# This file is generated by .github/scripts/validate_scale_config.py in test-infra
-# It defines runner types that will be provisioned by by LF Self-hosted runners
-
-# scale-config.yml:
-#   Powers what instance types are available for GHA auto-scaled
-#   runners. Runners listed here will be available as self hosted
-#   runners, configuration is directly pulled from the main branch.
+# Defines runner types that will be provisioned by by LF Self-hosted
+# runners for pytorch/pytorch-canary and their labels.
 #
-# NOTE (Apr, 5, 2021): Linux runners are currently all an amazonlinux2
+# Runners listed here will be available as self hosted runners.
+# Configuration is directly pulled from the main branch.
 #
-# NOTE (Jan 5, 2021): Linux runners are all non-ephemeral to reduce the amount of CreateInstaces calls
-#                     to avoid RequestLimitExceeded issues
-#
-# TODO: Add some documentation on how the auto-scaling works
-#
-# NOTE: Default values,
+# Default values:
 #
 # runner_types:
-#   runner_label:
+#   runner_label: # label to specify in the Github Actions workflow
 #     instance_type: m4.large
 #     os: linux
 #     max_available: 20
@@ -31,312 +21,107 @@ runner_types:
     is_ephemeral: false
     max_available: 1000
     os: linux
-    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-2023.5.20240701.0-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
+    max_available: 30
     os: linux
-    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
+    max_available: 30
     os: linux
-    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-2023.5.20240701.0-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:
     disk_size: 200
     instance_type: c5.12xlarge
     is_ephemeral: true
     max_available: 300
     os: linux
-    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
+    max_available: 30
     os: linux
-    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
+    max_available: 250
     os: linux
-    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-2023.5.20240701.0-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-2023.5.20240701.0-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-2023.5.20240701.0-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
+    max_available: 520
     os: linux
-    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-2023.5.20240701.0-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
+    max_available: 50
     os: linux
-    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
+    max_available: 30
     os: linux
-    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
+    max_available: 20
     os: linux
-    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-2023.5.20240701.0-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-2023.5.20240701.0-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-2023.5.20240701.0-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
+    os: linux
+  lf.c.linux.large:
     disk_size: 15
     instance_type: c5.large
     is_ephemeral: false
     os: linux
-    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-2023.5.20240701.0-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:
+  lf.c.linux.arm64.m7g.2xlarge:
     disk_size: 256
-    instance_type: m7g.4xlarge
+    instance_type: m7g.2xlarge
     is_ephemeral: false
-    max_available: 200
+    max_available: 20
     os: linux
-    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-2023.5.20240701.0-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-2023.5.20240701.0-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-2023.5.20240701.0-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
-    is_ephemeral: true
-    max_available: 100
-    os: windows
-  lf.c.windows.g4dn.xlarge.nonephemeral:
-    disk_size: 256
-    instance_type: g4dn.xlarge
-    is_ephemeral: false
-    max_available: 100
-    os: windows
   lf.c.windows.4xlarge:
     disk_size: 256
     instance_type: c5d.4xlarge
@@ -353,7 +138,7 @@ runner_types:
     disk_size: 256
     instance_type: p3.2xlarge
     is_ephemeral: true
-    max_available: 300
+    max_available: 150
     os: windows
   lf.c.windows.8xlarge.nvidia.gpu.nonephemeral:
     disk_size: 256

.github/lf-scale-config.yml

@@ -1,23 +1,13 @@
-
-# This file is generated by .github/scripts/validate_scale_config.py in test-infra
-# It defines runner types that will be provisioned by by LF Self-hosted runners
-
-# scale-config.yml:
-#   Powers what instance types are available for GHA auto-scaled
-#   runners. Runners listed here will be available as self hosted
-#   runners, configuration is directly pulled from the main branch.
+# Defines runner types that will be provisioned by by LF Self-hosted
+# runners for pytorch/pytorch and their labels.
 #
-# NOTE (Apr, 5, 2021): Linux runners are currently all an amazonlinux2
+# Runners listed here will be available as self hosted runners.
+# Configuration is directly pulled from the main branch.
 #
-# NOTE (Jan 5, 2021): Linux runners are all non-ephemeral to reduce the amount of CreateInstaces calls
-#                     to avoid RequestLimitExceeded issues
-#
-# TODO: Add some documentation on how the auto-scaling works
-#
-# NOTE: Default values,
+# Default values:
 #
 # runner_types:
-#   runner_label:
+#   runner_label: # label to specify in the Github Actions workflow
 #     instance_type: m4.large
 #     os: linux
 #     max_available: 20
@@ -31,312 +21,107 @@ runner_types:
     is_ephemeral: false
     max_available: 1000
     os: linux
-    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-2023.5.20240701.0-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
+    max_available: 30
     os: linux
-    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
+    max_available: 30
     os: linux
-    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-2023.5.20240701.0-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:
     disk_size: 200
     instance_type: c5.12xlarge
     is_ephemeral: true
     max_available: 300
     os: linux
-    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
+    max_available: 30
     os: linux
-    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
+    max_available: 250
     os: linux
-    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-2023.5.20240701.0-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-2023.5.20240701.0-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-2023.5.20240701.0-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
+    max_available: 520
     os: linux
-    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-2023.5.20240701.0-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
+    max_available: 50
     os: linux
-    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
+    max_available: 30
     os: linux
-    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
+    max_available: 20
     os: linux
-    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-2023.5.20240701.0-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-2023.5.20240701.0-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-2023.5.20240701.0-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
+    os: linux
+  lf.linux.large:
     disk_size: 15
     instance_type: c5.large
     is_ephemeral: false
     os: linux
-    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-2023.5.20240701.0-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:
+  lf.linux.arm64.m7g.2xlarge:
     disk_size: 256
-    instance_type: m7g.4xlarge
+    instance_type: m7g.2xlarge
     is_ephemeral: false
-    max_available: 200
+    max_available: 20
     os: linux
-    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-2023.5.20240701.0-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-2023.5.20240701.0-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-2023.5.20240701.0-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
-    is_ephemeral: true
-    max_available: 100
-    os: windows
-  lf.windows.g4dn.xlarge.nonephemeral:
-    disk_size: 256
-    instance_type: g4dn.xlarge
-    is_ephemeral: false
-    max_available: 100
-    os: windows
   lf.windows.4xlarge:
     disk_size: 256
     instance_type: c5d.4xlarge
@@ -353,7 +138,7 @@ runner_types:
     disk_size: 256
     instance_type: p3.2xlarge
     is_ephemeral: true
-    max_available: 300
+    max_available: 150
     os: windows
   lf.windows.8xlarge.nvidia.gpu.nonephemeral:
     disk_size: 256

.github/merge_rules.yaml

@@ -107,8 +107,8 @@
   mandatory_checks_name:
   - EasyCLA
   - Lint
-  - pull / linux-focal-py3_9-clang9-xla / build
-  - pull / linux-focal-py3_9-clang9-xla / test (xla, 1, 1, linux.12xlarge)
+  - pull / linux-focal-py3_8-clang9-xla / build
+  - pull / linux-focal-py3_8-clang9-xla / test (xla, 1, 1, linux.12xlarge)
 
 - name: Documentation
   patterns:
@@ -282,11 +282,9 @@
   - torch/_C/_distributed*
   - torch/csrc/distributed/**
   - torch/testing/_internal/distributed/**
-  - torch/multiprocessing/**
   - test/distributed/**
   - test/cpp/dist_autograd/**
   - test/cpp/rpc/**
-  - test/*multiprocessing*
   approved_by:
   - wconstab
   - mrshenli
@@ -525,13 +523,6 @@
   - Skylion007
   - ngimel
   - peterbell10
-  - eqy
-  - jansel
-  - jeffdaily
-  - eellison
-  - anijain2305
-  - bdhirsh
-  - zou3519
   mandatory_checks_name:
   - EasyCLA
   - Lint
@@ -546,8 +537,6 @@
   - ezyang
   - dzhulgakov
   - malfet
-  - albanD
-  - ptrblck
   mandatory_checks_name:
   - EasyCLA
   - Lint

.github/nitpicks.yml

@@ -1,5 +0,0 @@
-- markdown: |
-    ## Attention! native_functions.yaml was changed
-    If you are adding a new function or defaulted argument to native_functions.yaml, you cannot use it from pre-existing Python frontend code until our FC window passes (two weeks).  Split your PR into two PRs, one which adds the new C++ functionality, and one that makes use of it from Python, and land them two weeks apart.  See https://github.com/pytorch/pytorch/wiki/PyTorch's-Python-Frontend-Backward-and-Forward-Compatibility-Policy#forwards-compatibility-fc for more info.
-  pathFilter:
-    - 'aten/src/ATen/native/native_functions.yaml'

.github/pytorch-probot.yml

@@ -6,10 +6,8 @@ ciflow_push_tags:
 - ciflow/binaries_libtorch
 - ciflow/binaries_wheel
 - ciflow/inductor
-- 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/conda-env-iOS.txt

@@ -4,4 +4,4 @@ ninja=1.10.2
 numpy=1.23.3
 pyyaml=6.0
 setuptools=68.2.2
-typing-extensions=4.11.0
+typing-extensions=4.9.0

.github/requirements/pip-requirements-iOS.txt

@@ -1,4 +1,4 @@
 # iOS simulator requirements
 coremltools==5.0b5
 protobuf==3.20.2
-optree==0.12.1
+optree==0.11.0

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

@@ -1,7 +1,6 @@
 boto3==1.19.12
 hypothesis==6.56.4
-expecttest==0.2.1
-fbscribelogger==0.1.6
+expecttest==0.1.6
 librosa>=0.6.2
 mpmath==1.3.0
 networkx==2.8.7
@@ -18,16 +17,16 @@ pytest-xdist==3.3.1
 pytest-rerunfailures==10.3
 pytest-flakefinder==1.1.0
 scipy==1.10.1
-sympy==1.12.1 ; python_version == "3.8"
-sympy==1.13.1 ; python_version >= "3.9"
+sympy==1.11.1
 unittest-xml-reporting<=3.2.0,>=2.0.0
 xdoctest==1.1.0
 filelock==3.6.0
+sympy==1.11.1
 pytest-cpp==2.3.0
 rockset==1.0.3
 z3-solver==4.12.2.0
 tensorboard==2.13.0
-optree==0.12.1
+optree==0.11.0
 # 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

.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()
@@ -48,25 +50,6 @@ def patch_init_py(
         f.write(orig)
 
 
-# TODO: remove patch_setup_py() once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
-def patch_setup_py(path: Path) -> None:
-    with open(path) as f:
-        orig = f.read()
-    try:
-        orig = check_and_replace(
-            orig,
-            "https://tritonlang.blob.core.windows.net/llvm-builds/",
-            "https://oaitriton.blob.core.windows.net/public/llvm-builds/",
-        )
-        with open(path, "w") as f:
-            f.write(orig)
-    except RuntimeError as e:
-        print(
-            f"Applying patch_setup_py() for llvm-build package failed: {e}.",
-            "If you are trying to build a newer version of Triton, you can ignore this.",
-        )
-
-
 def build_triton(
     *,
     version: str,
@@ -108,9 +91,6 @@ def build_triton(
         else:
             check_call(["git", "checkout", commit_hash], cwd=triton_basedir)
 
-        # TODO: remove this and patch_setup_py() once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
-        patch_setup_py(triton_pythondir / "setup.py")
-
         if build_conda:
             with open(triton_basedir / "meta.yaml", "w") as meta:
                 print(

.github/scripts/check_labels.py

@@ -27,12 +27,6 @@ def parse_args() -> Any:
 
     parser = ArgumentParser("Check PR labels")
     parser.add_argument("pr_num", type=int)
-    # add a flag to return a non-zero exit code if the PR does not have the required labels
-    parser.add_argument(
-        "--exit-non-zero",
-        action="store_true",
-        help="Return a non-zero exit code if the PR does not have the required labels",
-    )
 
     return parser.parse_args()
 
@@ -47,13 +41,10 @@ def main() -> None:
         if not has_required_labels(pr):
             print(LABEL_ERR_MSG)
             add_label_err_comment(pr)
-            if args.exit_non_zero:
-                sys.exit(1)
         else:
             delete_all_label_err_comments(pr)
     except Exception as e:
-        if args.exit_non_zero:
-            sys.exit(1)
+        pass
 
     sys.exit(0)
 

.github/scripts/cherry_pick.py

@@ -169,8 +169,7 @@ def create_cherry_pick_branch(
     repo.create_branch_and_checkout(branch=cherry_pick_branch)
 
     # We might want to support ghstack later
-    # We don't want to resolve conflicts here.
-    repo._run_git("cherry-pick", "-x", commit_sha)
+    repo._run_git("cherry-pick", "-x", "-X", "theirs", commit_sha)
     repo.push(branch=cherry_pick_branch, dry_run=False)
 
     return cherry_pick_branch

.github/scripts/filter_test_configs.py

@@ -39,9 +39,9 @@ SUPPORTED_PERIODICAL_MODES: Dict[str, Callable[[Optional[str]], bool]] = {
 }
 
 # The link to the published list of disabled jobs
-DISABLED_JOBS_URL = "https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json?versionId=sxzMTP57qj.Vwz8dN1glkTK560Txq9W3"
+DISABLED_JOBS_URL = "https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json"
 # and unstable jobs
-UNSTABLE_JOBS_URL = "https://ossci-metrics.s3.amazonaws.com/unstable-jobs.json?versionId=8f1.4S3MupuHXH8t0waxyGnPsGHJYdv9"
+UNSTABLE_JOBS_URL = "https://ossci-metrics.s3.amazonaws.com/unstable-jobs.json"
 
 # Some constants used to handle disabled and unstable jobs
 JOB_NAME_SEP = "/"
@@ -505,9 +505,6 @@ def perform_misc_tasks(
         "ci-verbose-test-logs",
         check_for_setting(labels, pr_body, "ci-verbose-test-logs"),
     )
-    set_output(
-        "ci-test-showlocals", check_for_setting(labels, pr_body, "ci-test-showlocals")
-    )
     set_output(
         "ci-no-test-timeout", check_for_setting(labels, pr_body, "ci-no-test-timeout")
     )

.github/scripts/generate_binary_build_matrix.py

@@ -18,13 +18,13 @@ from typing import Dict, List, Optional, Tuple
 CUDA_ARCHES = ["11.8", "12.1", "12.4"]
 
 
-CUDA_ARCHES_FULL_VERSION = {"11.8": "11.8.0", "12.1": "12.1.1", "12.4": "12.4.1"}
+CUDA_ARCHES_FULL_VERSION = {"11.8": "11.8.0", "12.1": "12.1.1", "12.4": "12.4.0"}
 
 
 CUDA_ARCHES_CUDNN_VERSION = {"11.8": "9", "12.1": "9", "12.4": "9"}
 
 
-ROCM_ARCHES = ["6.1", "6.2"]
+ROCM_ARCHES = ["6.0", "6.1"]
 
 XPU_ARCHES = ["xpu"]
 
@@ -68,18 +68,18 @@ PYTORCH_EXTRA_INSTALL_REQUIREMENTS = {
         "nvidia-nvtx-cu12==12.1.105; platform_system == 'Linux' and platform_machine == 'x86_64'"
     ),
     "12.4": (
-        "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-cuda-nvrtc-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
+        "nvidia-cuda-runtime-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
+        "nvidia-cuda-cupti-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
         "nvidia-cudnn-cu12==9.1.0.70; platform_system == 'Linux' and platform_machine == 'x86_64' | "
-        "nvidia-cublas-cu12==12.4.5.8; 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-cublas-cu12==12.4.2.65; platform_system == 'Linux' and platform_machine == 'x86_64' | "
+        "nvidia-cufft-cu12==11.2.0.44; platform_system == 'Linux' and platform_machine == 'x86_64' | "
+        "nvidia-curand-cu12==10.3.5.119; platform_system == 'Linux' and platform_machine == 'x86_64' | "
+        "nvidia-cusolver-cu12==11.6.0.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
+        "nvidia-cusparse-cu12==12.3.0.142; platform_system == 'Linux' and platform_machine == 'x86_64' | "
         "nvidia-nccl-cu12==2.21.5; 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'"
+        "nvidia-nvtx-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64' | "
+        "nvidia-nvjitlink-cu12==12.4.99; platform_system == 'Linux' and platform_machine == 'x86_64'"
     ),
 }
 
@@ -215,7 +215,7 @@ LIBTORCH_CONTAINER_IMAGES: Dict[Tuple[str, str], str] = {
     ("cpu", CXX11_ABI): f"pytorch/libtorch-cxx11-builder:cpu-{DEFAULT_TAG}",
 }
 
-FULL_PYTHON_VERSIONS = ["3.9", "3.10", "3.11", "3.12"]
+FULL_PYTHON_VERSIONS = ["3.8", "3.9", "3.10", "3.11", "3.12"]
 
 
 def translate_desired_cuda(gpu_arch_type: str, gpu_arch_version: str) -> str:
@@ -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
@@ -366,23 +365,13 @@ def generate_wheels_matrix(
                 else arch_version
             )
 
-            # TODO: Enable python 3.13 on rocm, aarch64, windows
+            # TODO: Enable python 3.13 on rocm, xpu, aarch64, windows
             if (
-                gpu_arch_type == "rocm" or (os != "linux" and os != "linux-s390x")
+                gpu_arch_type in ["rocm", "xpu"] or os != "linux"
             ) 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 3.10 for 12.1 CUDA
-                if python_version == "3.10" and arch_version == "12.1":
+                if arch_version != "cuda-aarch64":
                     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": "",
-                            "build_name": f"{package_type}-py{python_version}-{gpu_arch_type}{gpu_arch_version}-full".replace(  # noqa: B950
+                            "pytorch_extra_install_requirements": (
+                                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(
                     {
@@ -441,9 +452,10 @@ 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 ""
+                            "cxx11-abi"
+                            if arch_version in ["cpu-cxx11-abi", "xpu"]
+                            else ""
                         ),
                         "container_image": WHEEL_CONTAINER_IMAGES[arch_version],
                         "package_type": package_type,
@@ -451,13 +463,12 @@ def generate_wheels_matrix(
                             ".", "_"
                         ),
                         "pytorch_extra_install_requirements": (
-                            PYTORCH_EXTRA_INSTALL_REQUIREMENTS["12.4"]  # fmt: skip
-                            if os != "linux" and gpu_arch_type != "xpu"
+                            PYTORCH_EXTRA_INSTALL_REQUIREMENTS["12.1"]  # fmt: skip
+                            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:
@@ -70,20 +69,12 @@ 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 = (
             GITHUB_DIR
             / f"workflows/generated-{self.build_environment}-{self.branches}.yml"
         )
-        if self.use_split_build:
-            output_file_path = (
-                GITHUB_DIR
-                / f"workflows/generated-{self.build_environment}-{self.branches}"
-            )
         with open(output_file_path, "w") as output_file:
             GENERATED = "generated"  # Note that please keep the variable GENERATED otherwise phabricator will hide the whole file
             output_file.writelines([f"# @{GENERATED} DO NOT EDIT MANUALLY\n"])
@@ -119,20 +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",
@@ -181,25 +158,10 @@ LINUX_BINARY_SMOKE_WORKFLOWS = [
         build_configs=generate_binary_build_matrix.generate_wheels_matrix(
             OperatingSystem.LINUX,
             arches=["11.8", "12.1", "12.4"],
-            python_versions=["3.9"],
+            python_versions=["3.8"],
         ),
         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 (
-            err.code == 403
-            and all(
-                key in err.headers
-                for key in ["X-RateLimit-Limit", "X-RateLimit-Remaining"]
-            )
-            and int(err.headers["X-RateLimit-Remaining"]) == 0
+        if err.code == 403 and all(
+            key in err.headers for key in ["X-RateLimit-Limit", "X-RateLimit-Used"]
         ):
             print(
-                f"""{url}
-                Rate limit exceeded:
+                f"""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