amend

.bazelignore

@@ -1,4 +1,3 @@
 # We do not use this library in our Bazel build. It contains an
 # infinitely recursing symlink that makes Bazel very unhappy.
 third_party/ittapi/
-third_party/opentelemetry-cpp

.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 +0,0 @@
-0.7b
-manylinux_2_17
-rocm6.2
-9be04068c3c0857a4cfd17d7e39e71d0423ebac2
-3e9e1959d23b93d78a08fcc5f868125dc3854dece32fd9458be9ef4467982291

.ci/docker/build.sh

@@ -84,30 +84,16 @@ fi
 # CMake 3.18 is needed to support CUDA17 language variant
 CMAKE_VERSION=3.18.5
 
-_UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
-_UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
+_UCX_COMMIT=00bcc6bb18fc282eb160623b4c0d300147f579af
+_UCC_COMMIT=7cb07a76ccedad7e56ceb136b865eb9319c258ea
 
 # It's annoying to rename jobs every time you want to rewrite a
 # configuration, so we hardcode everything here rather than do it
 # from scratch
 case "$image" in
-  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.4.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    ;;
-  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
+  pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9)
     CUDA_VERSION=12.1.1
-    CUDNN_VERSION=9
+    CUDNN_VERSION=8
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
     PROTOBUF=yes
@@ -119,24 +105,9 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.4.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks)
+  pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9-inductor-benchmarks)
     CUDA_VERSION=12.1.1
-    CUDNN_VERSION=9
+    CUDNN_VERSION=8
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
     PROTOBUF=yes
@@ -149,39 +120,9 @@ case "$image" in
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.1.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.12
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.4.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.12
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
+  pytorch-linux-focal-cuda11.8-cudnn8-py3-gcc9)
     CUDA_VERSION=11.8.0
-    CUDNN_VERSION=9
+    CUDNN_VERSION=8
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
     PROTOBUF=yes
@@ -193,37 +134,9 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.4.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    ;;
-  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
+  pytorch-linux-focal-cuda12.1-cudnn8-py3-gcc9)
     CUDA_VERSION=12.1.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    ;;
-  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.4.1
-    CUDNN_VERSION=9
+    CUDNN_VERSION=8
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
     PROTOBUF=yes
@@ -236,7 +149,7 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-focal-py3-clang10-onnx)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     CLANG_VERSION=10
     PROTOBUF=yes
     DB=yes
@@ -245,7 +158,7 @@ case "$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 +167,8 @@ case "$image" in
     GRADLE_VERSION=6.8.3
     NINJA_VERSION=1.9.0
     ;;
-  pytorch-linux-focal-py3.9-clang10)
-    ANACONDA_PYTHON_VERSION=3.9
+  pytorch-linux-focal-py3.8-clang10)
+    ANACONDA_PYTHON_VERSION=3.8
     CLANG_VERSION=10
     PROTOBUF=yes
     DB=yes
@@ -276,8 +189,8 @@ case "$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
@@ -286,40 +199,39 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-focal-rocm-n-1-py3)
-    ANACONDA_PYTHON_VERSION=3.10
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    ROCM_VERSION=6.1
+    ROCM_VERSION=5.6
     NINJA_VERSION=1.9.0
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
   pytorch-linux-focal-rocm-n-py3)
-    ANACONDA_PYTHON_VERSION=3.10
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    ROCM_VERSION=6.2
+    ROCM_VERSION=5.7
     NINJA_VERSION=1.9.0
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
   pytorch-linux-jammy-xpu-2024.0-py3)
-    ANACONDA_PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
     VISION=yes
-    XPU_VERSION=0.5
+    BASEKIT_VERSION=2024.0.0-49522
     NINJA_VERSION=1.9.0
     CONDA_CMAKE=yes
-    TRITON=yes
     ;;
-    pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
-    ANACONDA_PYTHON_VERSION=3.9
+    pytorch-linux-jammy-py3.8-gcc11-inductor-benchmarks)
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
@@ -330,10 +242,10 @@ case "$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-cudnn8-py3.8-clang12)
+    ANACONDA_PYTHON_VERSION=3.8
     CUDA_VERSION=11.8
-    CUDNN_VERSION=9
+    CUDNN_VERSION=8
     CLANG_VERSION=12
     PROTOBUF=yes
     DB=yes
@@ -355,8 +267,8 @@ case "$image" in
     CONDA_CMAKE=yes
     VISION=yes
     ;;
-  pytorch-linux-jammy-py3.9-gcc11)
-    ANACONDA_PYTHON_VERSION=3.9
+  pytorch-linux-jammy-py3.8-gcc11)
+    ANACONDA_PYTHON_VERSION=3.8
     GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
@@ -365,7 +277,6 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     DOCS=yes
-    UNINSTALL_DILL=yes
     ;;
   pytorch-linux-jammy-py3-clang12-executorch)
     ANACONDA_PYTHON_VERSION=3.10
@@ -373,14 +284,6 @@ case "$image" in
     CONDA_CMAKE=yes
     EXECUTORCH=yes
     ;;
-  pytorch-linux-jammy-py3.12-halide)
-    CUDA_VERSION=12.4
-    ANACONDA_PYTHON_VERSION=3.12
-    GCC_VERSION=11
-    CONDA_CMAKE=yes
-    HALIDE=yes
-    TRITON=yes
-    ;;
   pytorch-linux-focal-linter)
     # TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
     # We will need to update mypy version eventually, but that's for another day. The task
@@ -388,42 +291,11 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.9
     CONDA_CMAKE=yes
     ;;
-  pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
+  pytorch-linux-jammy-cuda11.8-cudnn8-py3.9-linter)
     ANACONDA_PYTHON_VERSION=3.9
     CUDA_VERSION=11.8
     CONDA_CMAKE=yes
     ;;
-  pytorch-linux-jammy-aarch64-py3.10-gcc11)
-    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
-    ;;
-  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
@@ -471,7 +343,7 @@ tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
 #when using cudnn version 8 install it separately from cuda
 if [[ "$image" == *cuda*  && ${OS} == "ubuntu" ]]; then
   IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
-  if [[ ${CUDNN_VERSION} == 9 ]]; then
+  if [[ ${CUDNN_VERSION} == 8 ]]; then
     IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
   fi
 fi
@@ -514,17 +386,13 @@ docker build \
        --build-arg "DOCS=${DOCS}" \
        --build-arg "INDUCTOR_BENCHMARKS=${INDUCTOR_BENCHMARKS}" \
        --build-arg "EXECUTORCH=${EXECUTORCH}" \
-       --build-arg "HALIDE=${HALIDE}" \
-       --build-arg "XPU_VERSION=${XPU_VERSION}" \
-       --build-arg "ACL=${ACL:-}" \
-       --build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
-       --build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
+       --build-arg "BASEKIT_VERSION=${BASEKIT_VERSION}" \
        -f $(dirname ${DOCKERFILE})/Dockerfile \
        -t "$tmp_tag" \
        "$@" \
        .
 
-# NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
+# NVIDIA dockers for RC releases use tag names like `11.0-cudnn8-devel-ubuntu18.04-rc`,
 # for this case we will set UBUNTU_VERSION to `18.04-rc` so that the Dockerfile could
 # find the correct image. As a result, here we have to replace the
 #   "$UBUNTU_VERSION" == "18.04-rc"

.ci/docker/centos-rocm/Dockerfile

@@ -62,7 +62,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
-# (optional) Install vision packages like OpenCV
+# (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@@ -77,9 +77,6 @@ RUN rm install_rocm.sh
 COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
 RUN bash ./install_rocm_magma.sh
 RUN rm install_rocm_magma.sh
-COPY ./common/install_amdsmi.sh install_amdsmi.sh
-RUN bash ./install_amdsmi.sh
-RUN rm install_amdsmi.sh
 ENV PATH /opt/rocm/bin:$PATH
 ENV PATH /opt/rocm/hcc/bin:$PATH
 ENV PATH /opt/rocm/hip/bin:$PATH
@@ -108,17 +105,10 @@ 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
-
-# Install AOTriton (Early fail)
-COPY ./aotriton_version.txt aotriton_version.txt
-COPY ./common/common_utils.sh common_utils.sh
-COPY ./common/install_aotriton.sh install_aotriton.sh
-RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
-ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
+RUN rm install_triton.sh common_utils.sh triton-rocm.txt triton_version.txt
 
 # Install ccache/sccache (do this last, so we get priority in PATH)
 COPY ./common/install_cache.sh install_cache.sh

.ci/docker/ci_commit_pins/executorch.txt

@@ -1 +1 @@
-cd1c833b079adb324871dcbbe75b43d42ffc0ade
+663882fe7dc518c04adf3d2ee5ccb7d99f41ade4

.ci/docker/ci_commit_pins/halide.txt

@@ -1 +0,0 @@
-461c12871f336fe6f57b55d6a297f13ef209161b

.ci/docker/ci_commit_pins/huggingface.txt

@@ -1 +1 @@
-243e186efbf7fb93328dd6b34927a4e8c8f24395
+6c26faa159b79a42d7fa46cb66e2d21523351987

.ci/docker/ci_commit_pins/timm.txt

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

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

@@ -0,0 +1 @@
+dafe1459823b9549417ed95e9720f1b594fab329

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

@@ -1 +0,0 @@
-91b14bf5593cf58a8541f3e6b9125600a867d4ef

.ci/docker/ci_commit_pins/triton.txt

@@ -1 +1 @@
-5fe38ffd73c2ac6ed6323b554205186696631c6f
+e28a256d71f3cf2bcc7b69d6bda73a9b855e385e

.ci/docker/common/install_acl.sh

@@ -1,16 +0,0 @@
-set -euo pipefail
-
-readonly version=v24.04
-readonly src_host=https://review.mlplatform.org/ml
-readonly src_repo=ComputeLibrary
-
-# Clone ACL
-[[ ! -d ${src_repo} ]] && git clone ${src_host}/${src_repo}.git
-cd ${src_repo}
-
-git checkout $version
-
-# Build with scons
-scons -j8  Werror=0 debug=0 neon=1 opencl=0 embed_kernels=0 \
-  os=linux arch=armv8a build=native multi_isa=1 \
-  fixed_format_kernels=1 openmp=1 cppthreads=0

.ci/docker/common/install_amdsmi.sh

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

.ci/docker/common/install_aotriton.sh

@@ -1,23 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
-
-TARBALL='aotriton.tar.gz'
-# 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"
-
-cd "${AOTRITON_INSTALL_PREFIX}"
-# Must use -L to follow redirects
-curl -L --retry 3 -o "${TARBALL}" "${AOTRITON_URL}"
-ACTUAL_SHA256=$(sha256sum "${TARBALL}" | cut -d " " -f 1)
-if [ "${SHA256}" != "${ACTUAL_SHA256}" ]; then
-  echo -n "Error: The SHA256 of downloaded tarball is ${ACTUAL_SHA256},"
-  echo " which does not match the expected value ${SHA256}."
-  exit
-fi
-tar xf "${TARBALL}" && rm -rf "${TARBALL}"

.ci/docker/common/install_base.sh

@@ -3,7 +3,7 @@
 set -ex
 
 install_ubuntu() {
-  # NVIDIA dockers for RC releases use tag names like `11.0-cudnn9-devel-ubuntu18.04-rc`,
+  # NVIDIA dockers for RC releases use tag names like `11.0-cudnn8-devel-ubuntu18.04-rc`,
   # for this case we will set UBUNTU_VERSION to `18.04-rc` so that the Dockerfile could
   # find the correct image. As a result, here we have to check for
   #   "$UBUNTU_VERSION" == "18.04"*
@@ -113,6 +113,7 @@ install_centos() {
     glibc-devel \
     glibc-headers \
     glog-devel \
+    hiredis-devel \
     libstdc++-devel \
     libsndfile-devel \
     make \
@@ -152,7 +153,7 @@ wget https://ossci-linux.s3.amazonaws.com/valgrind-${VALGRIND_VERSION}.tar.bz2
 tar -xjf valgrind-${VALGRIND_VERSION}.tar.bz2
 cd valgrind-${VALGRIND_VERSION}
 ./configure --prefix=/usr/local
-make -j$[$(nproc) - 2]
+make -j6
 sudo make install
 cd ../../
 rm -rf valgrind_build

.ci/docker/common/install_conda.sh

@@ -5,17 +5,17 @@ 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)
 
   case "$MAJOR_PYTHON_VERSION" in
-    3);;
+    2)
+      CONDA_FILE="Miniconda2-latest-Linux-x86_64.sh"
+    ;;
+    3)
+      CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
+    ;;
     *)
       echo "Unsupported ANACONDA_PYTHON_VERSION: $ANACONDA_PYTHON_VERSION"
       exit 1
@@ -47,41 +47,16 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   # Uncomment the below when resolved to track the latest conda update
   # as_jenkins conda update -y -n base conda
 
-  if [[ $(uname -m) == "aarch64" ]]; then
-    export SYSROOT_DEP="sysroot_linux-aarch64=2.17"
-  else
-    export SYSROOT_DEP="sysroot_linux-64=2.17"
-  fi
-
   # Install correct Python version
-  # Also ensure sysroot is using a modern GLIBC to match system compilers
-  as_jenkins conda create -n py_$ANACONDA_PYTHON_VERSION -y\
-             python="$ANACONDA_PYTHON_VERSION" \
-             ${SYSROOT_DEP}
-
-  # libstdcxx from conda default channels are too old, we need GLIBCXX_3.4.30
-  # which is provided in libstdcxx 12 and up.
-  conda_install libstdcxx-ng=12.3.0 -c conda-forge
+  as_jenkins conda create -n py_$ANACONDA_PYTHON_VERSION -y python="$ANACONDA_PYTHON_VERSION"
 
   # Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
-  if [[ $(uname -m) == "aarch64" ]]; then
-    CONDA_COMMON_DEPS="astunparse pyyaml setuptools openblas==0.3.25=*openmp* ninja==1.11.1 scons==4.5.2"
-
-    if [ "$ANACONDA_PYTHON_VERSION" = "3.8" ]; then
-      NUMPY_VERSION=1.24.4
-    else
-      NUMPY_VERSION=1.26.2
-    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" ] || [ "$ANACONDA_PYTHON_VERSION" = "3.13" ]; then
-      NUMPY_VERSION=1.26.0
+  if [ "$ANACONDA_PYTHON_VERSION" = "3.11" ]; then
+    conda_install numpy=1.23.5 ${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 +78,7 @@ 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 "$DOCS" ]; then
@@ -114,5 +89,14 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
     pip_install -r /opt/conda/requirements-docs.txt
   fi
 
+  # HACK HACK HACK
+  # gcc-9 for ubuntu-18.04 from http://ppa.launchpad.net/ubuntu-toolchain-r/test/ubuntu
+  # Pulls llibstdc++6 13.1.0-8ubuntu1~18.04 which is too new for conda
+  # So remove libstdc++6.so.3.29 installed by https://anaconda.org/anaconda/libstdcxx-ng/files?version=11.2.0
+  # Same is true for gcc-12 from Ubuntu-22.04
+  if grep -e [12][82].04.[623] /etc/issue >/dev/null; then
+    rm /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/lib/libstdc++.so.6
+  fi
+
   popd
 fi

.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

@@ -1,112 +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 3.13.0t"}
-
-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
-
-    local additional_flags=""
-    if [ "$py_ver" == "3.13.0t" ]; then
-        additional_flags=" --disable-gil"
-        mv cpython-3.13/ cpython-3.13t/
-    fi
-
-    pushd $py_folder
-
-    local prefix="/opt/_internal/cpython-${py_ver}"
-    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} ${additional_flags} > /dev/null
-
-    make -j40 > /dev/null
-    make install > /dev/null
-
-    if [[ "${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" = "3.13.0t" ]; then
-        PY_VER_SHORT="3.13"
-        PYT_VER_SHORT="3.13t"
-        check_var $PYTHON_DOWNLOAD_GITHUB_BRANCH
-        wget $PYTHON_DOWNLOAD_GITHUB_BRANCH/$PY_VER_SHORT.tar.gz -O Python-$py_ver.tgz
-        do_cpython_build $py_ver cpython-$PYT_VER_SHORT
-    elif [ "$py_ver" = "3.13.0" ]; then
-        PY_VER_SHORT="3.13"
-        check_var $PYTHON_DOWNLOAD_GITHUB_BRANCH
-        wget $PYTHON_DOWNLOAD_GITHUB_BRANCH/$PY_VER_SHORT.tar.gz -O Python-$py_ver.tgz
-        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_cudnn.sh

@@ -1,18 +1,20 @@
 #!/bin/bash
 
-if [[ -n "${CUDNN_VERSION}" ]]; then
+if [[ ${CUDNN_VERSION} == 8 ]]; then
     # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
     mkdir tmp_cudnn
     pushd tmp_cudnn
-    if [[ ${CUDA_VERSION:0:2} == "12" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda12-archive"
-    elif [[ ${CUDA_VERSION:0:2} == "11" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda11-archive"
+    if [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
+        CUDNN_NAME="cudnn-linux-x86_64-8.9.2.26_cuda12-archive"
+        curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${CUDNN_NAME}.tar.xz
+    elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
+        CUDNN_NAME="cudnn-linux-x86_64-8.7.0.84_cuda11-archive"
+        curl --retry 3 -OLs https://developer.download.nvidia.com/compute/redist/cudnn/v8.7.0/local_installers/11.8/${CUDNN_NAME}.tar.xz
     else
         print "Unsupported CUDA version ${CUDA_VERSION}"
         exit 1
     fi
-    curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/${CUDNN_NAME}.tar.xz
+
     tar xf ${CUDNN_NAME}.tar.xz
     cp -a ${CUDNN_NAME}/include/* /usr/local/cuda/include/
     cp -a ${CUDNN_NAME}/lib/* /usr/local/cuda/lib64/

.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

@@ -5,22 +5,9 @@ set -ex
 # cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
 mkdir tmp_cusparselt && cd tmp_cusparselt
 
-if [[ ${CUDA_VERSION:0:4} =~ ^12\.[2-6]$ ]]; 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 [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
-    arch_path='sbsa'
-    export TARGETARCH=${TARGETARCH:-$(uname -m)}
-    if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
-        arch_path='x86_64'
-    fi
-    CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.5.2.1-archive"
-    curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
+if [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
+    CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.5.2.1-archive"
+    curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/${CUSPARSELT_NAME}.tar.xz
 elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
     CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.4.0.7-archive"
     curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/${CUSPARSELT_NAME}.tar.xz

.ci/docker/common/install_db.sh

@@ -4,6 +4,11 @@ set -ex
 
 install_ubuntu() {
   apt-get update
+  apt-get install -y --no-install-recommends \
+          libhiredis-dev \
+          libleveldb-dev \
+          liblmdb-dev \
+          libsnappy-dev
 
   # Cleanup
   apt-get autoclean && apt-get clean
@@ -15,6 +20,12 @@ install_centos() {
   # See http://fedoraproject.org/wiki/EPEL
   yum --enablerepo=extras install -y epel-release
 
+  yum install -y \
+      hiredis-devel \
+      leveldb-devel \
+      lmdb-devel \
+      snappy-devel
+
   # Cleanup
   yum clean all
   rm -rf /var/cache/yum

.ci/docker/common/install_executorch.sh

@@ -37,9 +37,6 @@ install_conda_dependencies() {
 
 install_pip_dependencies() {
   pushd executorch/.ci/docker
-  # Install PyTorch CPU build beforehand to avoid installing the much bigger CUDA
-  # binaries later, ExecuTorch only needs CPU
-  pip_install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
   # Install all Python dependencies
   pip_install -r requirements-ci.txt
   popd
@@ -47,14 +44,14 @@ install_pip_dependencies() {
 
 setup_executorch() {
   pushd executorch
-  # Setup swiftshader and Vulkan SDK which are required to build the Vulkan delegate
-  as_jenkins bash .ci/scripts/setup-vulkan-linux-deps.sh
+  source .ci/scripts/utils.sh
 
-  export PYTHON_EXECUTABLE=python
-  export EXECUTORCH_BUILD_PYBIND=ON
-  export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
+  install_flatc_from_source
+  pip_install .
+  build_executorch_runner "cmake"
 
-  as_jenkins .ci/scripts/setup-linux.sh cmake
+  # Make sure that all the newly generate files are owned by Jenkins
+  chown -R jenkins .
   popd
 }
 

.ci/docker/common/install_halide.sh

@@ -1,46 +0,0 @@
-#!/bin/bash
-set -ex
-
-source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
-
-COMMIT=$(get_pinned_commit halide)
-test -n "$COMMIT"
-
-# activate conda to populate CONDA_PREFIX
-test -n "$ANACONDA_PYTHON_VERSION"
-eval "$(conda shell.bash hook)"
-conda activate py_$ANACONDA_PYTHON_VERSION
-
-if [ -n "${UBUNTU_VERSION}" ];then
-    apt update
-    apt-get install -y lld liblld-15-dev libpng-dev libjpeg-dev libgl-dev \
-                  libopenblas-dev libeigen3-dev libatlas-base-dev libzstd-dev
-fi
-
-conda_install numpy scipy imageio cmake ninja
-
-git clone --depth 1 --branch release/16.x --recursive https://github.com/llvm/llvm-project.git
-cmake -DCMAKE_BUILD_TYPE=Release \
-        -DLLVM_ENABLE_PROJECTS="clang" \
-        -DLLVM_TARGETS_TO_BUILD="X86;NVPTX" \
-        -DLLVM_ENABLE_TERMINFO=OFF -DLLVM_ENABLE_ASSERTIONS=ON \
-        -DLLVM_ENABLE_EH=ON -DLLVM_ENABLE_RTTI=ON -DLLVM_BUILD_32_BITS=OFF \
-        -S llvm-project/llvm -B llvm-build -G Ninja
-cmake --build llvm-build
-cmake --install llvm-build --prefix llvm-install
-export LLVM_ROOT=`pwd`/llvm-install
-export LLVM_CONFIG=$LLVM_ROOT/bin/llvm-config
-
-git clone https://github.com/halide/Halide.git
-pushd Halide
-git checkout ${COMMIT} && git submodule update --init --recursive
-pip_install -r requirements.txt
-cmake -G Ninja -DCMAKE_BUILD_TYPE=Release -S . -B build
-cmake --build build
-test -e ${CONDA_PREFIX}/lib/python3 || ln -s python${ANACONDA_PYTHON_VERSION} ${CONDA_PREFIX}/lib/python3
-cmake --install build --prefix ${CONDA_PREFIX}
-chown -R jenkins ${CONDA_PREFIX}
-popd
-rm -rf Halide llvm-build llvm-project llvm-install
-
-python -c "import halide"  # check for errors

.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

@@ -1,172 +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 60300 ]]; then
-    echo "ROCm 6.3+ MIOpen does not need any patches, do not build from source"
-    exit 0
-elif [[ $ROCM_INT -ge 60200 ]] && [[ $ROCM_INT -lt 60300 ]]; then
-    MIOPEN_BRANCH="release/rocm-rel-6.2-staging"
-elif [[ $ROCM_INT -ge 60100 ]] && [[ $ROCM_INT -lt 60200 ]]; then
-    echo "ROCm 6.1 MIOpen does not need any patches, do not build from source"
-    exit 0
-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
@@ -26,20 +26,18 @@ pip_install \
   pytest-cov==4.0.0 \
   pytest-subtests==0.10.0 \
   tabulate==0.9.0 \
-  transformers==4.36.2
+  transformers==4.32.1
 
 pip_install coloredlogs packaging
+retry pip_install -i https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/ --no-cache-dir --no-input ort-nightly==1.17.0.dev20231005006
 
-pip_install onnxruntime==1.18.1
-pip_install onnx==1.16.2
-pip_install onnxscript==0.1.0.dev20240831 --no-deps
-# required by onnxscript
-pip_install ml_dtypes
+pip_install -i https://test.pypi.org/simple/ onnx==1.15.0rc2
+pip_install onnxscript==0.1.0.dev20231128 --no-deps
 
 # Cache the transformers model to be used later by ONNX tests. We need to run the transformers
 # package to download the model. By default, the model is cached at ~/.cache/huggingface/hub/
 IMPORT_SCRIPT_FILENAME="/tmp/onnx_import_script.py"
-as_jenkins echo 'import transformers; transformers.AutoModel.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3");' > "${IMPORT_SCRIPT_FILENAME}"
+as_jenkins echo 'import transformers; transformers.AutoModel.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2");' > "${IMPORT_SCRIPT_FILENAME}"
 
 # Need a PyTorch version for transformers to work
 pip_install --pre torch --index-url https://download.pytorch.org/whl/nightly/cpu

.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_openssl.sh

@@ -9,8 +9,7 @@ tar xf "${OPENSSL}.tar.gz"
 cd "${OPENSSL}"
 ./config --prefix=/opt/openssl -d '-Wl,--enable-new-dtags,-rpath,$(LIBRPATH)'
 # NOTE: openssl install errors out when built with the -j option
-NPROC=$[$(nproc) - 2]
-make -j${NPROC}; make install_sw
+make -j6; make install_sw
 # Link the ssl libraries to the /usr/lib folder.
 sudo ln -s /opt/openssl/lib/lib* /usr/lib
 cd ..

.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_protobuf.sh

@@ -2,6 +2,8 @@
 
 set -ex
 
+# This function installs protobuf 3.17
+install_protobuf_317() {
   pb_dir="/usr/temp_pb_install_dir"
   mkdir -p $pb_dir
 
@@ -11,9 +13,44 @@ mkdir -p $pb_dir
   ln -s /usr/lib64 "$pb_dir/lib64"
 
   curl -LO "https://github.com/protocolbuffers/protobuf/releases/download/v3.17.3/protobuf-all-3.17.3.tar.gz" --retry 3
-
-tar -xvz --no-same-owner -C "$pb_dir" --strip-components 1 -f protobuf-all-3.17.3.tar.gz
-NPROC=$[$(nproc) - 2]
-pushd "$pb_dir" && ./configure && make -j${NPROC} && make -j${NPROC} check && sudo make -j${NRPOC} install && sudo ldconfig
+  tar -xvz -C "$pb_dir" --strip-components 1 -f protobuf-all-3.17.3.tar.gz
+  # -j6 to balance memory usage and speed.
+  # naked `-j` seems to use too much memory.
+  pushd "$pb_dir" && ./configure && make -j6 && make -j6 check && sudo make -j6 install && sudo ldconfig
   popd
   rm -rf $pb_dir
+}
+
+install_ubuntu() {
+  # Ubuntu 14.04 has cmake 2.8.12 as the default option, so we will
+  # install cmake3 here and use cmake3.
+  apt-get update
+  if [[ "$UBUNTU_VERSION" == 14.04 ]]; then
+    apt-get install -y --no-install-recommends cmake3
+  fi
+
+  # Cleanup
+  apt-get autoclean && apt-get clean
+  rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
+
+  install_protobuf_317
+}
+
+install_centos() {
+  install_protobuf_317
+}
+
+# Install base packages depending on the base OS
+ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
+case "$ID" in
+  ubuntu)
+    install_ubuntu
+    ;;
+  centos)
+    install_centos
+    ;;
+  *)
+    echo "Unable to determine OS..."
+    exit 1
+    ;;
+esac

.ci/docker/common/install_rocm.sh

@@ -6,6 +6,9 @@ ver() {
     printf "%3d%03d%03d%03d" $(echo "$1" | tr '.' ' ');
 }
 
+# Map ROCm version to AMDGPU version
+declare -A AMDGPU_VERSIONS=( ["5.0"]="21.50" ["5.1.1"]="22.10.1" ["5.2"]="22.20" )
+
 install_ubuntu() {
     apt-get update
     if [[ $UBUNTU_VERSION == 18.04 ]]; then
@@ -23,14 +26,31 @@ install_ubuntu() {
     apt-get install -y libc++1
     apt-get install -y libc++abi1
 
+    if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
         # Add amdgpu repository
         UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
-    echo "deb [arch=amd64] https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
+        local amdgpu_baseurl
+        if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
+          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu"
+        else
+          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/ubuntu"
+        fi
+        echo "deb [arch=amd64] ${amdgpu_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
+    fi
+
+    ROCM_REPO="ubuntu"
+    if [[ $(ver $ROCM_VERSION) -lt $(ver 4.2) ]]; then
+        ROCM_REPO="xenial"
+    fi
+
+    if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
+        ROCM_REPO="${UBUNTU_VERSION_NAME}"
+    fi
 
     # Add rocm repository
     wget -qO - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add -
     local rocm_baseurl="http://repo.radeon.com/rocm/apt/${ROCM_VERSION}"
-    echo "deb [arch=amd64] ${rocm_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/rocm.list
+    echo "deb [arch=amd64] ${rocm_baseurl} ${ROCM_REPO} main" > /etc/apt/sources.list.d/rocm.list
     apt-get update --allow-insecure-repositories
 
     DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \
@@ -39,28 +59,26 @@ install_ubuntu() {
                    rocm-libs \
                    rccl \
                    rocprofiler-dev \
-                   roctracer-dev \
-                   amd-smi-lib
-
-    if [[ $(ver $ROCM_VERSION) -ge $(ver 6.1) ]]; then
-        DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated rocm-llvm-dev
-    fi
+                   roctracer-dev
 
     # precompiled miopen kernels added in ROCm 3.5, renamed in ROCm 5.5
     # search for all unversioned packages
     # if search fails it will abort this script; use true to avoid case where search fails
+    if [[ $(ver $ROCM_VERSION) -ge $(ver 5.5) ]]; then
         MIOPENHIPGFX=$(apt-cache search --names-only miopen-hip-gfx | awk '{print $1}' | grep -F -v . || true)
         if [[ "x${MIOPENHIPGFX}" = x ]]; then
           echo "miopen-hip-gfx package not available" && exit 1
         else
           DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENHIPGFX}
         fi
-
-    # ROCm 6.0 had a regression where journal_mode was enabled on the kdb files resulting in permission errors at runtime
-    for kdb in /opt/rocm/share/miopen/db/*.kdb
-    do
-        sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
-    done
+    else
+        MIOPENKERNELS=$(apt-cache search --names-only miopenkernels | awk '{print $1}' | grep -F -v . || true)
+        if [[ "x${MIOPENKERNELS}" = x ]]; then
+          echo "miopenkernels package not available" && exit 1
+        else
+          DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated ${MIOPENKERNELS}
+        fi
+    fi
 
     # Cleanup
     apt-get autoclean && apt-get clean
@@ -77,12 +95,17 @@ install_centos() {
   yum install -y epel-release
   yum install -y dkms kernel-headers-`uname -r` kernel-devel-`uname -r`
 
+  if [[ $(ver $ROCM_VERSION) -ge $(ver 4.5) ]]; then
       # Add amdgpu repository
       local amdgpu_baseurl
       if [[ $OS_VERSION == 9 ]]; then
-      amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/9.0/main/x86_64"
+          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/9.0/main/x86_64"
       else
+        if [[ $(ver $ROCM_VERSION) -ge $(ver 5.3) ]]; then
           amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/rhel/7.9/main/x86_64"
+        else
+          amdgpu_baseurl="https://repo.radeon.com/amdgpu/${AMDGPU_VERSIONS[$ROCM_VERSION]}/rhel/7.9/main/x86_64"
+        fi
       fi
       echo "[AMDGPU]" > /etc/yum.repos.d/amdgpu.repo
       echo "name=AMDGPU" >> /etc/yum.repos.d/amdgpu.repo
@@ -90,6 +113,7 @@ install_centos() {
       echo "enabled=1" >> /etc/yum.repos.d/amdgpu.repo
       echo "gpgcheck=1" >> /etc/yum.repos.d/amdgpu.repo
       echo "gpgkey=http://repo.radeon.com/rocm/rocm.gpg.key" >> /etc/yum.repos.d/amdgpu.repo
+  fi
 
   local rocm_baseurl="http://repo.radeon.com/rocm/yum/${ROCM_VERSION}"
   echo "[ROCm]" > /etc/yum.repos.d/rocm.repo
@@ -107,23 +131,25 @@ install_centos() {
                    rocm-libs \
                    rccl \
                    rocprofiler-dev \
-                   roctracer-dev \
-                   amd-smi-lib
+                   roctracer-dev
 
   # precompiled miopen kernels; search for all unversioned packages
   # if search fails it will abort this script; use true to avoid case where search fails
+  if [[ $(ver $ROCM_VERSION) -ge $(ver 5.5) ]]; then
       MIOPENHIPGFX=$(yum -q search miopen-hip-gfx | grep miopen-hip-gfx | awk '{print $1}'| grep -F kdb. || true)
       if [[ "x${MIOPENHIPGFX}" = x ]]; then
         echo "miopen-hip-gfx package not available" && exit 1
       else
         yum install -y ${MIOPENHIPGFX}
       fi
-
-  # ROCm 6.0 had a regression where journal_mode was enabled on the kdb files resulting in permission errors at runtime
-  for kdb in /opt/rocm/share/miopen/db/*.kdb
-  do
-      sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
-  done
+  else
+      MIOPENKERNELS=$(yum -q search miopenkernels | grep miopenkernels- | awk '{print $1}'| grep -F kdb. || true)
+      if [[ "x${MIOPENKERNELS}" = x ]]; then
+        echo "miopenkernels package not available" && exit 1
+      else
+        yum install -y ${MIOPENKERNELS}
+      fi
+  fi
 
   # Cleanup
   yum clean all

.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

@@ -1,24 +1,17 @@
 #!/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
 
 # Version 2.7.2 + ROCm related updates
-git checkout a1625ff4d9bc362906bd01f805dbbe12612953f6
+git checkout 823531632140d0edcb7e77c3edc0e837421471c5
 
 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

@@ -12,9 +12,9 @@ conda_reinstall() {
   as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y --force-reinstall $*
 }
 
-if [ -n "${XPU_VERSION}" ]; then
-  TRITON_REPO="https://github.com/intel/intel-xpu-backend-for-triton"
-  TRITON_TEXT_FILE="triton-xpu"
+if [ -n "${ROCM_VERSION}" ]; then
+  TRITON_REPO="https://github.com/ROCmSoftwarePlatform/triton"
+  TRITON_TEXT_FILE="triton-rocm"
 else
   TRITON_REPO="https://github.com/openai/triton"
   TRITON_TEXT_FILE="triton"
@@ -38,33 +38,19 @@ 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 "${CONDA_CMAKE}" ]; then
@@ -78,6 +64,5 @@ if [ -n "${CONDA_CMAKE}" ]; then
   # latest numpy version, which fails ASAN tests with the following import error: Numba
   # needs NumPy 1.20 or less.
   conda_reinstall cmake="${CMAKE_VERSION}"
-  # Note that we install numpy with pip as conda might not have the version we want
-  pip_install --force-reinstall numpy=="${NUMPY_VERSION}"
+  conda_reinstall numpy="${NUMPY_VERSION}"
 fi

.ci/docker/common/install_ucc.sh

@@ -36,12 +36,7 @@ function install_ucc() {
   git submodule update --init --recursive
 
   ./autogen.sh
-  # We only run distributed tests on Tesla M60 and A10G
-  NVCC_GENCODE="-gencode=arch=compute_52,code=sm_52 -gencode=arch=compute_86,code=compute_86"
-  ./configure --prefix=$UCC_HOME          \
-    --with-ucx=$UCX_HOME                  \
-    --with-cuda=$with_cuda                \
-    --with-nvcc-gencode="${NVCC_GENCODE}"
+  ./configure --prefix=$UCC_HOME --with-ucx=$UCX_HOME --with-cuda=$with_cuda
   time make -j
   sudo make install
 

.ci/docker/common/install_vision.sh

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

.ci/docker/common/install_xpu.sh

@@ -1,33 +1,30 @@
 #!/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
+# Refer to https://dgpu-docs.intel.com/releases/stable_647_21_20230714.html
+
+# Intel® oneAPI Base Toolkit (version 2024.0.0) has been updated to include functional and security updates.
+# Refer to https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html
 
 # Users should update to the latest version as it becomes available
 
 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
-    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
+        | gpg --dearmor --output /usr/share/keyrings/intel-graphics.gpg
     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
-    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
+        | gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
+
+    # Add the signed entry to APT sources and configure the APT client to use the Intel repository
+    echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/production/2328 unified" \
+        | tee /etc/apt/sources.list.d/intel-gpu-jammy.list
+    echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" \
+        | tee /etc/apt/sources.list.d/oneAPI.list
 
     # Update the packages list and repository index
     apt-get update
@@ -43,11 +40,11 @@ function install_ubuntu() {
         mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo
     # Development Packages
     apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev level-zero-dev
-    # Install Intel Support Packages
-    if [ -n "$XPU_VERSION" ]; then
-        apt-get install -y intel-for-pytorch-gpu-dev-${XPU_VERSION} intel-pti-dev
+    # Install Intel® oneAPI Base Toolkit
+    if [ -n "$BASEKIT_VERSION" ]; then
+        apt-get install intel-basekit=$BASEKIT_VERSION -y
     else
-        apt-get install -y intel-for-pytorch-gpu-dev intel-pti-dev
+        apt-get install intel-basekit -y
     fi
 
     # Cleanup
@@ -55,49 +52,44 @@ 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 +98,6 @@ 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=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
@@ -148,11 +105,8 @@ case "$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

@@ -1,82 +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${CUDA_VERSION}
-    ;;
-esac
-
-
-(
-  set -x
-  # TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
-  # is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
-  sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
-  sudo systemctl daemon-reload
-  sudo systemctl restart docker
-
-  docker build \
-    --target final \
-    --progress plain \
-    --build-arg "BASE_TARGET=${BASE_TARGET}" \
-    --build-arg "CUDA_VERSION=${CUDA_VERSION}" \
-    --build-arg "DEVTOOLSET_VERSION=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

@@ -1,203 +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

@@ -1,161 +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
-
-    # TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
-    # is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
-    sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
-    sudo systemctl daemon-reload
-    sudo systemctl restart docker
-
-    DOCKER_BUILDKIT=1 docker build  \
-        ${DOCKER_GPU_BUILD_ARG} \
-        --build-arg "GPU_IMAGE=${GPU_IMAGE}" \
-        --target "${TARGET}" \
-        -t "${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=${GITHUB_REF##*/}
-GIT_COMMIT_SHA=${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/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

@@ -15,7 +15,7 @@ click
 #Pinned versions:
 #test that import:
 
-coremltools==5.0b5 ; python_version < "3.12"
+coremltools==5.0b5
 #Description: Apple framework for ML integration
 #Pinned versions: 5.0b5
 #test that import:
@@ -25,19 +25,9 @@ coremltools==5.0b5 ; python_version < "3.12"
 #Pinned versions:
 #test that import:
 
-dill==0.3.7
-#Description: dill extends pickle with serializing and de-serializing for most built-ins
-#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:
 
@@ -57,11 +47,6 @@ junitparser==2.1.1
 #Pinned versions: 2.1.1
 #test that import:
 
-lark==0.12.0
-#Description: parser
-#Pinned versions: 0.12.0
-#test that import:
-
 librosa>=0.6.2 ; python_version < "3.11"
 #Description: A python package for music and audio analysis
 #Pinned versions: >=0.6.2
@@ -81,7 +66,7 @@ librosa>=0.6.2 ; python_version < "3.11"
 #Description: A testing library that allows you to replace parts of your
 #system under test with mock objects
 #Pinned versions:
-#test that import: test_modules.py, test_nn.py,
+#test that import: test_module_init.py, test_modules.py, test_nn.py,
 #test_testing.py
 
 #MonkeyType # breaks pytorch-xla-linux-bionic-py3.7-clang8
@@ -90,10 +75,10 @@ librosa>=0.6.2 ; python_version < "3.11"
 #Pinned versions:
 #test that import:
 
-mypy==1.11.2
+mypy==1.7.0
 # Pin MyPy version because new errors are likely to appear with each release
 #Description: linter
-#Pinned versions: 1.10.0
+#Pinned versions: 1.7.0
 #test that import: test_typing.py, test_type_hints.py
 
 networkx==2.8.8
@@ -109,7 +94,7 @@ 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 +124,9 @@ opt-einsum==3.3
 #Pinned versions: 3.3
 #test that import: test_linalg.py
 
-optree==0.12.1
+optree==0.9.1
 #Description: A library for tree manipulation
-#Pinned versions: 0.12.1
+#Pinned versions: 0.9.1
 #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,
@@ -152,9 +137,9 @@ optree==0.12.1
 #test_pointwise_ops.py, test_dtensor_ops.py, test_torchinductor.py, test_fx.py,
 #test_fake_tensor.py, test_mps.py
 
-pillow==10.3.0
+pillow==10.0.1
 #Description:  Python Imaging Library fork
-#Pinned versions: 10.3.0
+#Pinned versions: 10.0.1
 #test that import:
 
 protobuf==3.20.2
@@ -177,6 +162,11 @@ pytest-xdist==3.3.1
 #Pinned versions:
 #test that import:
 
+pytest-shard==0.1.2
+#Description: plugin spliting up tests in pytest
+#Pinned versions:
+#test that import:
+
 pytest-flakefinder==1.1.0
 #Description: plugin for rerunning tests a fixed number of times in pytest
 #Pinned versions: 1.1.0
@@ -223,7 +213,7 @@ 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
@@ -233,11 +223,12 @@ scikit-image==0.22.0 ; python_version >= "3.10"
 #Pinned versions: 0.20.3
 #test that import:
 
-scipy==1.10.1 ; python_version <= "3.11"
-scipy==1.12.0 ; python_version == "3.12"
+scipy==1.6.3 ; python_version < "3.10"
+scipy==1.8.1 ; python_version == "3.10"
+scipy==1.10.1 ; python_version == "3.11"
 # Pin SciPy because of failing distribution tests (see #60347)
 #Description: scientific python
-#Pinned versions: 1.10.1
+#Pinned versions: 1.6.3
 #test that import: test_unary_ufuncs.py, test_torch.py,test_tensor_creation_ops.py
 #test_spectral_ops.py, test_sparse_csr.py, test_reductions.py,test_nn.py
 #test_linalg.py, test_binary_ufuncs.py
@@ -252,8 +243,7 @@ tb-nightly==2.13.0a20230426
 #Pinned versions:
 #test that import:
 
-# needed by torchgen utils
-typing-extensions
+#typing-extensions
 #Description: type hints for python
 #Pinned versions:
 #test that import:
@@ -268,29 +258,24 @@ unittest-xml-reporting<=3.2.0,>=2.0.0
 #Pinned versions:
 #test that import:
 
-#lintrunner is supported on aarch64-linux only from 0.12.4 version
-lintrunner==0.12.5
+lintrunner==0.10.7
 #Description: all about linters!
-#Pinned versions: 0.12.5
+#Pinned versions: 0.10.7
 #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
 #test that import:
 
-ghstack==0.8.0
+ghstack==0.7.1
 #Description: ghstack tool
-#Pinned versions: 0.8.0
+#Pinned versions: 0.7.1
 #test that import:
 
-jinja2==3.1.4
+jinja2==3.1.2
 #Description: jinja2 template engine
-#Pinned versions: 3.1.4
+#Pinned versions: 3.1.2
 #test that import:
 
 pytest-cpp==2.3.0
@@ -308,37 +293,13 @@ tensorboard==2.13.0
 #Pinned versions:
 #test that import: test_tensorboard
 
-pywavelets==1.4.1 ; python_version < "3.12"
-pywavelets==1.5.0 ; python_version >= "3.12"
+pywavelets==1.4.1
 #Description: This is a requirement of scikit-image, we need to pin
 # it here because 1.5.0 conflicts with numpy 1.21.2 used in CI
 #Pinned versions: 1.4.1
 #test that import:
 
-lxml==5.0.0
+lxml==5.0.0.
 #Description: This is a requirement of unittest-xml-reporting
 
 # 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:
-
-parameterized==0.8.1
-#Description: Parameterizes unittests, both the tests themselves and the entire testing class
-#Pinned versions:
-#test that import:

.ci/docker/triton_version.txt

@@ -1 +1 @@
-3.1.0
+2.2.0

.ci/docker/ubuntu-cuda/Dockerfile

@@ -56,7 +56,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
-# (optional) Install vision packages like OpenCV
+# (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@@ -103,14 +103,6 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
 RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
 
-ARG HALIDE
-# Build and install halide
-COPY ./common/install_halide.sh install_halide.sh
-COPY ./common/common_utils.sh common_utils.sh
-COPY ci_commit_pins/halide.txt halide.txt
-RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
-RUN rm install_halide.sh common_utils.sh halide.txt
-
 # Install ccache/sccache (do this last, so we get priority in PATH)
 COPY ./common/install_cache.sh install_cache.sh
 ENV PATH /opt/cache/bin:$PATH
@@ -147,7 +139,7 @@ COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
 ARG CUDNN_VERSION
 ARG CUDA_VERSION
 COPY ./common/install_cudnn.sh install_cudnn.sh
-RUN if [ -n "${CUDNN_VERSION}" ]; then bash install_cudnn.sh; fi
+RUN if [ "${CUDNN_VERSION}" -eq 8 ]; then bash install_cudnn.sh; fi
 RUN rm install_cudnn.sh
 
 # Install CUSPARSELT
@@ -156,17 +148,10 @@ 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
 RUN if [ -h /usr/local/cuda-12.1/cuda-12.1 ]; then rm /usr/local/cuda-12.1/cuda-12.1; fi
-RUN if [ -h /usr/local/cuda-12.4/cuda-12.4 ]; then rm /usr/local/cuda-12.4/cuda-12.4; fi
 
 USER jenkins
 CMD ["bash"]

.ci/docker/ubuntu-rocm/Dockerfile

@@ -53,7 +53,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
-# (optional) Install vision packages like OpenCV
+# (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@@ -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
@@ -80,11 +78,6 @@ ENV MAGMA_HOME /opt/rocm/magma
 ENV LANG C.UTF-8
 ENV LC_ALL C.UTF-8
 
-# Install amdsmi
-COPY ./common/install_amdsmi.sh install_amdsmi.sh
-RUN bash ./install_amdsmi.sh
-RUN rm install_amdsmi.sh
-
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
 COPY ./common/install_cmake.sh install_cmake.sh
@@ -102,17 +95,10 @@ 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
-
-# Install AOTriton
-COPY ./aotriton_version.txt aotriton_version.txt
-COPY ./common/common_utils.sh common_utils.sh
-COPY ./common/install_aotriton.sh install_aotriton.sh
-RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
-ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
+RUN rm install_triton.sh common_utils.sh triton-rocm.txt triton_version.txt
 
 # Install ccache/sccache (do this last, so we get priority in PATH)
 COPY ./common/install_cache.sh install_cache.sh
@@ -123,8 +109,5 @@ 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
@@ -62,20 +61,15 @@ COPY ci_commit_pins/timm.txt timm.txt
 RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
 RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
 
-# Install XPU Dependencies
-ARG XPU_VERSION
-COPY ./common/install_xpu.sh install_xpu.sh
-RUN bash ./install_xpu.sh && rm install_xpu.sh
-
 ARG TRITON
 # Install triton, this needs to be done before sccache because the latter will
 # try to reach out to S3, which docker build runners don't have access
 COPY ./common/install_triton.sh install_triton.sh
 COPY ./common/common_utils.sh common_utils.sh
-COPY ci_commit_pins/triton-xpu.txt triton-xpu.txt
-COPY triton_version.txt triton_version.txt
+# TODO: will add triton xpu commit
+COPY ci_commit_pins/triton.txt triton.txt
 RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
-RUN rm install_triton.sh common_utils.sh triton-xpu.txt triton_version.txt
+RUN rm install_triton.sh common_utils.sh triton.txt
 
 # (optional) Install database packages like LMDB and LevelDB
 ARG DB
@@ -84,13 +78,18 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
-# (optional) Install vision packages like OpenCV
+# (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
 RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
 ENV INSTALLED_VISION ${VISION}
 
+# Install XPU Dependencies
+ARG BASEKIT_VERSION
+COPY ./common/install_xpu.sh install_xpu.sh
+RUN bash ./install_xpu.sh && rm install_xpu.sh
+
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
 COPY ./common/install_cmake.sh install_cmake.sh

.ci/docker/ubuntu/Dockerfile

@@ -37,7 +37,6 @@ COPY requirements-ci.txt requirements-docs.txt /opt/conda/
 COPY ./common/install_conda.sh install_conda.sh
 COPY ./common/common_utils.sh common_utils.sh
 RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt /opt/conda/requirements-docs.txt
-RUN if [ -n "${UNINSTALL_DILL}" ]; then pip uninstall -y dill; fi
 
 # Install gcc
 ARG GCC_VERSION
@@ -50,7 +49,7 @@ 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
@@ -80,7 +79,7 @@ RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
 RUN rm install_db.sh
 ENV INSTALLED_DB ${DB}
 
-# (optional) Install vision packages like OpenCV
+# (optional) Install vision packages like OpenCV and ffmpeg
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
 RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
@@ -155,33 +154,16 @@ COPY ci_commit_pins/executorch.txt executorch.txt
 RUN if [ -n "${EXECUTORCH}" ]; then bash ./install_executorch.sh; fi
 RUN rm install_executorch.sh common_utils.sh executorch.txt
 
-ARG HALIDE
-# Build and install halide
-COPY ./common/install_halide.sh install_halide.sh
-COPY ./common/common_utils.sh common_utils.sh
-COPY ci_commit_pins/halide.txt halide.txt
-RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
-RUN rm install_halide.sh common_utils.sh halide.txt
-
 ARG ONNX
 # Install ONNX dependencies
 COPY ./common/install_onnx.sh ./common/common_utils.sh ./
 RUN if [ -n "${ONNX}" ]; then bash ./install_onnx.sh; fi
 RUN rm install_onnx.sh common_utils.sh
 
-# (optional) Build ACL
-ARG ACL
-COPY ./common/install_acl.sh install_acl.sh
-RUN if [ -n "${ACL}" ]; then bash ./install_acl.sh; fi
-RUN rm install_acl.sh
-ENV INSTALLED_ACL ${ACL}
-
 # Install ccache/sccache (do this last, so we get priority in PATH)
-ARG SKIP_SCCACHE_INSTALL
 COPY ./common/install_cache.sh install_cache.sh
 ENV PATH /opt/cache/bin:$PATH
-RUN if [ -z "${SKIP_SCCACHE_INSTALL}" ]; then bash ./install_cache.sh; fi
-RUN rm install_cache.sh
+RUN bash ./install_cache.sh && rm install_cache.sh
 
 # Add jni.h for java host build
 COPY ./common/install_jni.sh install_jni.sh
@@ -198,9 +180,7 @@ ARG BUILD_ENVIRONMENT
 ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
 
 # Install LLVM dev version (Defined in the pytorch/builder github repository)
-ARG SKIP_LLVM_SRC_BUILD_INSTALL
 COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
-RUN if [ -n "${SKIP_LLVM_SRC_BUILD_INSTALL}" ]; then set -eu; rm -rf /opt/llvm; fi
 
 # AWS specific CUDA build guidance
 ENV TORCH_CUDA_ARCH_LIST Maxwell

.ci/onnx/common.sh

@@ -1,9 +1,5 @@
-#!/bin/bash
-
 set -ex
 
-source "$(dirname "${BASH_SOURCE[0]}")/../pytorch/common_utils.sh"
-
 LOCAL_DIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)
 ROOT_DIR=$(cd "$LOCAL_DIR"/../.. && pwd)
 TEST_DIR="$ROOT_DIR/test"

.ci/onnx/test.sh

@@ -3,20 +3,6 @@
 # shellcheck source=./common.sh
 source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
 
-# Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
-WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
-cleanup_workspace() {
-  echo "sudo may print the following warning message that can be ignored. The chown command will still run."
-  echo "    sudo: setrlimit(RLIMIT_STACK): Operation not permitted"
-  echo "For more details refer to https://github.com/sudo-project/sudo/issues/42"
-  sudo chown -R "$WORKSPACE_ORIGINAL_OWNER_ID" /var/lib/jenkins/workspace
-}
-# Disable shellcheck SC2064 as we want to parse the original owner immediately.
-# shellcheck disable=SC2064
-trap_add cleanup_workspace EXIT
-sudo chown -R jenkins /var/lib/jenkins/workspace
-git config --global --add safe.directory /var/lib/jenkins/workspace
-
 if [[ "$BUILD_ENVIRONMENT" == *onnx* ]]; then
   # TODO: This can be removed later once vision is also part of the Docker image
   pip install -q --user --no-use-pep517 "git+https://github.com/pytorch/vision.git@$(cat .github/ci_commit_pins/vision.txt)"

.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

@@ -44,13 +44,26 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda11* ]]; then
   fi
 fi
 
-if [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
+if [[ ${BUILD_ENVIRONMENT} == *"caffe2"* ]]; then
+  echo "Caffe2 build is ON"
+  export BUILD_CAFFE2=ON
+fi
+
+if [[ ${BUILD_ENVIRONMENT} == *"paralleltbb"* ]]; then
+  export ATEN_THREADING=TBB
+  export USE_TBB=1
+elif [[ ${BUILD_ENVIRONMENT} == *"parallelnative"* ]]; then
   export ATEN_THREADING=NATIVE
 fi
 
 # Enable LLVM dependency for TensorExpr testing
+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
@@ -68,35 +81,7 @@ if ! which conda; then
     export USE_MKLDNN=0
   fi
 else
-  # CMAKE_PREFIX_PATH precedences
-  # 1. $CONDA_PREFIX, if defined. This follows the pytorch official build instructions.
-  # 2. /opt/conda/envs/py_${ANACONDA_PYTHON_VERSION}, if ANACONDA_PYTHON_VERSION defined.
-  #    This is for CI, which defines ANACONDA_PYTHON_VERSION but not CONDA_PREFIX.
-  # 3. $(conda info --base). The fallback value of pytorch official build
-  #    instructions actually refers to this.
-  #    Commonly this is /opt/conda/
-  if [[ -v CONDA_PREFIX ]]; then
-    export CMAKE_PREFIX_PATH=${CONDA_PREFIX}
-  elif [[ -v ANACONDA_PYTHON_VERSION ]]; then
-    export CMAKE_PREFIX_PATH="/opt/conda/envs/py_${ANACONDA_PYTHON_VERSION}"
-  else
-    # already checked by `! which conda`
-    CMAKE_PREFIX_PATH="$(conda info --base)"
-    export CMAKE_PREFIX_PATH
-  fi
-
-  # Workaround required for MKL library linkage
-  # https://github.com/pytorch/pytorch/issues/119557
-  if [ "$ANACONDA_PYTHON_VERSION" = "3.12" ]; then
-    export CMAKE_LIBRARY_PATH="/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/lib/"
-    export CMAKE_INCLUDE_PATH="/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/include/"
-  fi
-fi
-
-if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
-  export USE_MKLDNN=1
-  export USE_MKLDNN_ACL=1
-  export ACL_ROOT_DIR=/ComputeLibrary
+  export CMAKE_PREFIX_PATH=/opt/conda
 fi
 
 if [[ "$BUILD_ENVIRONMENT" == *libtorch* ]]; then
@@ -171,8 +156,7 @@ fi
 if [[ "$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
@@ -226,28 +210,6 @@ if [[ "${BUILD_ENVIRONMENT}" != *android* && "${BUILD_ENVIRONMENT}" != *cuda* ]]
   export BUILD_STATIC_RUNTIME_BENCHMARK=ON
 fi
 
-if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
-  export CMAKE_BUILD_TYPE=RelWithAssert
-fi
-
-# Do not change workspace permissions for ROCm CI jobs
-# as it can leave workspace with bad permissions for cancelled jobs
-if [[ "$BUILD_ENVIRONMENT" != *rocm* && "$BUILD_ENVIRONMENT" != *s390x* ]]; then
-  # Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
-  WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
-  cleanup_workspace() {
-    echo "sudo may print the following warning message that can be ignored. The chown command will still run."
-    echo "    sudo: setrlimit(RLIMIT_STACK): Operation not permitted"
-    echo "For more details refer to https://github.com/sudo-project/sudo/issues/42"
-    sudo chown -R "$WORKSPACE_ORIGINAL_OWNER_ID" /var/lib/jenkins/workspace
-  }
-  # Disable shellcheck SC2064 as we want to parse the original owner immediately.
-  # shellcheck disable=SC2064
-  trap_add cleanup_workspace EXIT
-  sudo chown -R jenkins /var/lib/jenkins/workspace
-  git config --global --add safe.directory /var/lib/jenkins/workspace
-fi
-
 if [[ "$BUILD_ENVIRONMENT" == *-bazel-* ]]; then
   set -e
 
@@ -273,38 +235,17 @@ else
   ( ! get_exit_code python setup.py clean bad_argument )
 
   if [[ "$BUILD_ENVIRONMENT" != *libtorch* ]]; then
+
     # rocm builds fail when WERROR=1
     # XLA test build fails when WERROR=1
     # set only when building other architectures
     # or building non-XLA tests.
     if [[ "$BUILD_ENVIRONMENT" != *rocm*  &&
-          "$BUILD_ENVIRONMENT" != *s390x*   &&
           "$BUILD_ENVIRONMENT" != *xla* ]]; then
-      if [[ "$BUILD_ENVIRONMENT" != *py3.8* ]]; then
-        # Install numpy-2.0.2 for builds which are backward compatible with 1.X
-        python -mpip install --pre numpy==2.0.2
-      fi
-
-      WERROR=1 python setup.py clean
-
-      if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
-        BUILD_LIBTORCH_WHL=1 BUILD_PYTHON_ONLY=0 python setup.py bdist_wheel
-        BUILD_LIBTORCH_WHL=0 BUILD_PYTHON_ONLY=1 python setup.py bdist_wheel --cmake
-      else
       WERROR=1 python setup.py bdist_wheel
-      fi
-    else
-      python setup.py clean
-      if [[ "$BUILD_ENVIRONMENT" == *xla* ]]; then
-        source .ci/pytorch/install_cache_xla.sh
-      fi
-      if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
-        echo "USE_SPLIT_BUILD cannot be used with xla or rocm"
-        exit 1
     else
       python setup.py bdist_wheel
     fi
-    fi
     pip_install_whl "$(echo dist/*.whl)"
 
     # TODO: I'm not sure why, but somehow we lose verbose commands
@@ -341,11 +282,10 @@ else
     CUSTOM_OP_BUILD="${CUSTOM_TEST_ARTIFACT_BUILD_DIR}/custom-op-build"
     CUSTOM_OP_TEST="$PWD/test/custom_operator"
     python --version
-    SITE_PACKAGES="$(python -c 'import site; print(";".join([x for x in site.getsitepackages()] + [x + "/torch" for x in site.getsitepackages()]))')"
-
+    SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
     mkdir -p "$CUSTOM_OP_BUILD"
     pushd "$CUSTOM_OP_BUILD"
-    cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
+    cmake "$CUSTOM_OP_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
           -DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
     make VERBOSE=1
     popd
@@ -355,10 +295,10 @@ else
     JIT_HOOK_BUILD="${CUSTOM_TEST_ARTIFACT_BUILD_DIR}/jit-hook-build"
     JIT_HOOK_TEST="$PWD/test/jit_hooks"
     python --version
-    SITE_PACKAGES="$(python -c 'import site; print(";".join([x for x in site.getsitepackages()] + [x + "/torch" for x in site.getsitepackages()]))')"
+    SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
     mkdir -p "$JIT_HOOK_BUILD"
     pushd "$JIT_HOOK_BUILD"
-    cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
+    cmake "$JIT_HOOK_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
           -DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
     make VERBOSE=1
     popd
@@ -370,7 +310,7 @@ else
     python --version
     mkdir -p "$CUSTOM_BACKEND_BUILD"
     pushd "$CUSTOM_BACKEND_BUILD"
-    cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES" -DPython_EXECUTABLE="$(which python)" \
+    cmake "$CUSTOM_BACKEND_TEST" -DCMAKE_PREFIX_PATH="$SITE_PACKAGES/torch" -DPYTHON_EXECUTABLE="$(which python)" \
           -DCMAKE_MODULE_PATH="$CUSTOM_TEST_MODULE_PATH" -DUSE_ROCM="$CUSTOM_TEST_USE_ROCM"
     make VERBOSE=1
     popd
@@ -401,8 +341,4 @@ if [[ "$BUILD_ENVIRONMENT" != *libtorch* && "$BUILD_ENVIRONMENT" != *bazel* ]];
   python tools/stats/export_test_times.py
 fi
 
-# snadampal: skipping it till sccache support added for aarch64
-# https://github.com/pytorch/pytorch/issues/121559
-if [[ "$BUILD_ENVIRONMENT" != *aarch64* &&  "$BUILD_ENVIRONMENT" != *s390x* ]]; then
 print_sccache_stats
-fi

.ci/pytorch/common_utils.sh

@@ -56,29 +56,9 @@ function assert_git_not_dirty() {
 function pip_install_whl() {
   # This is used to install PyTorch and other build artifacts wheel locally
   # without using any network connection
-
-  # Convert the input arguments into an array
-  local args=("$@")
-
-  # Check if the first argument contains multiple paths separated by spaces
-  if [[ "${args[0]}" == *" "* ]]; then
-    # Split the string by spaces into an array
-    IFS=' ' read -r -a paths <<< "${args[0]}"
-    # Loop through each path and install individually
-    for path in "${paths[@]}"; do
-      echo "Installing $path"
-      python3 -mpip install --no-index --no-deps "$path"
-    done
-  else
-    # Loop through each argument and install individually
-    for path in "${args[@]}"; do
-      echo "Installing $path"
-      python3 -mpip install --no-index --no-deps "$path"
-    done
-  fi
+  python3 -mpip install --no-index --no-deps "$@"
 }
 
-
 function pip_install() {
   # retry 3 times
   # old versions of pip don't have the "--progress-bar" flag
@@ -178,11 +158,6 @@ function install_torchvision() {
   fi
 }
 
-function install_tlparse() {
-  pip_install --user "tlparse==0.3.25"
-  PATH="$(python -m site --user-base)/bin:$PATH"
-}
-
 function install_torchrec_and_fbgemm() {
   local torchrec_commit
   torchrec_commit=$(get_pinned_commit torchrec)
@@ -208,6 +183,28 @@ function clone_pytorch_xla() {
   fi
 }
 
+function checkout_install_torchdeploy() {
+  local commit
+  commit=$(get_pinned_commit multipy)
+  pushd ..
+  git clone --recurse-submodules https://github.com/pytorch/multipy.git
+  pushd multipy
+  git checkout "${commit}"
+  python multipy/runtime/example/generate_examples.py
+  BUILD_CUDA_TESTS=1 pip install -e .
+  popd
+  popd
+}
+
+function test_torch_deploy(){
+ pushd ..
+ pushd multipy
+ ./multipy/runtime/build/test_deploy
+ ./multipy/runtime/build/test_deploy_gpu
+ popd
+ popd
+}
+
 function checkout_install_torchbench() {
   local commit
   commit=$(get_pinned_commit torchbench)
@@ -222,8 +219,6 @@ function checkout_install_torchbench() {
     # to install and test other models
     python install.py --continue_on_fail
   fi
-  echo "Print all dependencies after TorchBench is installed"
-  python -mpip freeze
   popd
 }
 

.ci/pytorch/create_test_cert.py

@@ -1,4 +1,4 @@
-from datetime import datetime, timedelta, timezone
+from datetime import datetime, timedelta
 from tempfile import mkdtemp
 
 from cryptography import x509
@@ -6,7 +6,6 @@ from cryptography.hazmat.primitives import hashes, serialization
 from cryptography.hazmat.primitives.asymmetric import rsa
 from cryptography.x509.oid import NameOID
 
-
 temp_dir = mkdtemp()
 print(temp_dir)
 
@@ -42,10 +41,10 @@ def create_cert(path, C, ST, L, O, key):
         .issuer_name(issuer)
         .public_key(key.public_key())
         .serial_number(x509.random_serial_number())
-        .not_valid_before(datetime.now(timezone.utc))
+        .not_valid_before(datetime.utcnow())
         .not_valid_after(
             # Our certificate will be valid for 10 days
-            datetime.now(timezone.utc)
+            datetime.utcnow()
             + timedelta(days=10)
         )
         .add_extension(
@@ -88,10 +87,10 @@ def sign_certificate_request(path, csr_cert, ca_cert, private_ca_key):
         .issuer_name(ca_cert.subject)
         .public_key(csr_cert.public_key())
         .serial_number(x509.random_serial_number())
-        .not_valid_before(datetime.now(timezone.utc))
+        .not_valid_before(datetime.utcnow())
         .not_valid_after(
             # Our certificate will be valid for 10 days
-            datetime.now(timezone.utc)
+            datetime.utcnow()
             + timedelta(days=10)
             # Sign our certificate with our private key
         )

.ci/pytorch/docs-test.sh

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

.ci/pytorch/install_cache_xla.sh

@@ -1,37 +0,0 @@
-#!/bin/bash
-
-# Script for installing sccache on the xla build job, which uses xla's docker
-# image and doesn't have sccache installed on it.  This is mostly copied from
-# .ci/docker/install_cache.sh.  Changes are: removing checks that will always
-# return the same thing, ex checks for for rocm, CUDA, and changing the path
-# where sccache is installed, and not changing /etc/environment.
-
-set -ex
-
-install_binary() {
-  echo "Downloading sccache binary from S3 repo"
-  curl --retry 3 https://s3.amazonaws.com/ossci-linux/sccache -o /tmp/cache/bin/sccache
-}
-
-mkdir -p /tmp/cache/bin
-mkdir -p /tmp/cache/lib
-export PATH="/tmp/cache/bin:$PATH"
-
-install_binary
-chmod a+x /tmp/cache/bin/sccache
-
-function write_sccache_stub() {
-  # Unset LD_PRELOAD for ps because of asan + ps issues
-  # https://gcc.gnu.org/bugzilla/show_bug.cgi?id=90589
-  # shellcheck disable=SC2086
-  # shellcheck disable=SC2059
-  printf "#!/bin/sh\nif [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then\n  exec sccache $(which $1) \"\$@\"\nelse\n  exec $(which $1) \"\$@\"\nfi" > "/tmp/cache/bin/$1"
-  chmod a+x "/tmp/cache/bin/$1"
-}
-
-write_sccache_stub cc
-write_sccache_stub c++
-write_sccache_stub gcc
-write_sccache_stub g++
-write_sccache_stub clang
-write_sccache_stub clang++

.ci/pytorch/macos-common.sh

@@ -9,7 +9,7 @@ sysctl -a | grep machdep.cpu
 
 # These are required for both the build job and the test job.
 # In the latter to test cpp extensions.
-export MACOSX_DEPLOYMENT_TARGET=11.1
+export MACOSX_DEPLOYMENT_TARGET=11.0
 export CXX=clang++
 export CC=clang
 

.ci/pytorch/macos-test.sh

@@ -9,13 +9,15 @@ if [[ -n "$CONDA_ENV" ]]; then
   export PATH="$CONDA_ENV/bin":$PATH
 fi
 
-# Test that OpenMP is enabled
+# Test that OpenMP is enabled for non-arm64 build
+if [[ ${BUILD_ENVIRONMENT} != *arm64* ]]; then
   pushd test
   if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available()))") == "1" ]]; then
     echo "Build should have OpenMP enabled, but torch.backends.openmp.is_available() is False"
     exit 1
   fi
   popd
+fi
 
 setup_test_python() {
   # The CircleCI worker hostname doesn't resolve to an address.
@@ -25,9 +27,8 @@ setup_test_python() {
   echo "Ninja version: $(ninja --version)"
   echo "Python version: $(which python) ($(python --version))"
 
-  # Set the limit on open file handles to 16384
-  # might help with intermittent compiler test failures
-  ulimit -n 16384
+  # Increase default limit on open file handles from 256 to 1024
+  ulimit -n 1024
 }
 
 test_python_all() {
@@ -148,8 +149,6 @@ test_jit_hooks() {
   assert_git_not_dirty
 }
 
-install_tlparse
-
 if [[ $NUM_TEST_SHARDS -gt 1 ]]; then
   test_python_shard "${SHARD_NUMBER}"
   if [[ "${SHARD_NUMBER}" == 1 ]]; then

.ci/pytorch/multigpu-test.sh

@@ -18,9 +18,7 @@ time python test/run_test.py --verbose -i distributed/test_c10d_gloo
 time python test/run_test.py --verbose -i distributed/test_c10d_nccl
 time python test/run_test.py --verbose -i distributed/test_c10d_spawn_gloo
 time python test/run_test.py --verbose -i distributed/test_c10d_spawn_nccl
-time python test/run_test.py --verbose -i distributed/test_compute_comm_reordering
 time python test/run_test.py --verbose -i distributed/test_store
-time python test/run_test.py --verbose -i distributed/test_symmetric_memory
 time python test/run_test.py --verbose -i distributed/test_pg_wrapper
 time python test/run_test.py --verbose -i distributed/rpc/cuda/test_tensorpipe_agent
 # FSDP tests
@@ -36,6 +34,7 @@ time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test
 # functional collective tests
 time python test/run_test.py --verbose -i distributed/test_functional_api
 
+
 # DTensor tests
 time python test/run_test.py --verbose -i distributed/_tensor/test_random_ops
 time python test/run_test.py --verbose -i distributed/_tensor/test_dtensor_compile
@@ -44,19 +43,12 @@ 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
 
 # Other tests
 time python test/run_test.py --verbose -i test_cuda_primary_ctx
-time python test/run_test.py --verbose -i test_optim -- -k test_forloop_goes_right_direction_multigpu
-time python test/run_test.py --verbose -i test_optim -- -k test_mixed_device_dtype
+time python test/run_test.py --verbose -i test_optim -- -k optimizers_with_varying_tensors
 time python test/run_test.py --verbose -i test_foreach -- -k test_tensors_grouping
 assert_git_not_dirty

.ci/pytorch/perf_test/compare_with_baseline.py

@@ -3,7 +3,6 @@ import json
 import math
 import sys
 
-
 parser = argparse.ArgumentParser()
 parser.add_argument(
     "--test-name", dest="test_name", action="store", required=True, help="test name"
@@ -60,16 +59,16 @@ print("sample mean: ", sample_mean)
 print("sample sigma: ", sample_sigma)
 
 if math.isnan(sample_mean):
-    raise Exception("""Error: sample mean is NaN""")  # noqa: TRY002
+    raise Exception("""Error: sample mean is NaN""")
 elif math.isnan(sample_sigma):
-    raise Exception("""Error: sample sigma is NaN""")  # noqa: TRY002
+    raise Exception("""Error: sample sigma is NaN""")
 
 z_value = (sample_mean - mean) / sigma
 
 print("z-value: ", z_value)
 
 if z_value >= 3:
-    raise Exception(  # noqa: TRY002
+    raise Exception(
         f"""\n
 z-value >= 3, there is high chance of perf regression.\n
 To reproduce this regression, run

.ci/pytorch/perf_test/get_stats.py

@@ -3,7 +3,6 @@ import sys
 
 import numpy
 
-
 sample_data_list = sys.argv[1:]
 sample_data_list = [float(v.strip()) for v in sample_data_list]
 

.ci/pytorch/perf_test/update_commit_hash.py

@@ -1,7 +1,6 @@
 import json
 import sys
 
-
 data_file_path = sys.argv[1]
 commit_hash = sys.argv[2]
 

.ci/pytorch/print_sccache_log.py

@@ -1,6 +1,5 @@
 import sys
 
-
 log_file_path = sys.argv[1]
 
 with open(log_file_path) as f:

.ci/pytorch/python_doc_push_script.sh

@@ -26,8 +26,8 @@ echo "error: python_doc_push_script.sh: version (arg2) not specified"
 fi
 
 # Argument 1: Where to copy the built documentation to
-# (pytorch_docs/$install_path)
-install_path="${1:-${DOCS_INSTALL_PATH:-${DOCS_VERSION}}}"
+# (pytorch.github.io/$install_path)
+install_path="${1:-${DOCS_INSTALL_PATH:-docs/${DOCS_VERSION}}}"
 if [ -z "$install_path" ]; then
 echo "error: python_doc_push_script.sh: install_path (arg1) not specified"
   exit 1
@@ -68,8 +68,8 @@ build_docs () {
 }
 
 
-git clone https://github.com/pytorch/docs pytorch_docs -b "$branch" --depth 1
-pushd pytorch_docs
+git clone https://github.com/pytorch/pytorch.github.io -b "$branch" --depth 1
+pushd pytorch.github.io
 
 export LC_ALL=C
 export PATH=/opt/conda/bin:$PATH
@@ -105,7 +105,6 @@ if [ "$is_main_doc" = true ]; then
     echo undocumented objects found:
     cat build/coverage/python.txt
     echo "Make sure you've updated relevant .rsts in docs/source!"
-    echo "You can reproduce locally by running 'cd docs && make coverage && cat build/coverage/python.txt'"
     exit 1
   fi
 else

.ci/pytorch/test.sh

@@ -6,30 +6,6 @@
 
 set -ex
 
-# Suppress ANSI color escape sequences
-export TERM=vt100
-
-# shellcheck source=./common.sh
-source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
-
-# Do not change workspace permissions for ROCm CI jobs
-# as it can leave workspace with bad permissions for cancelled jobs
-if [[ "$BUILD_ENVIRONMENT" != *rocm* ]]; then
-  # Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
-  WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
-  cleanup_workspace() {
-    echo "sudo may print the following warning message that can be ignored. The chown command will still run."
-    echo "    sudo: setrlimit(RLIMIT_STACK): Operation not permitted"
-    echo "For more details refer to https://github.com/sudo-project/sudo/issues/42"
-    sudo chown -R "$WORKSPACE_ORIGINAL_OWNER_ID" /var/lib/jenkins/workspace
-  }
-  # Disable shellcheck SC2064 as we want to parse the original owner immediately.
-  # shellcheck disable=SC2064
-  trap_add cleanup_workspace EXIT
-  sudo chown -R jenkins /var/lib/jenkins/workspace
-  git config --global --add safe.directory /var/lib/jenkins/workspace
-fi
-
 echo "Environment variables:"
 env
 
@@ -114,6 +90,9 @@ if [[ -n $TESTS_TO_INCLUDE ]]; then
   INCLUDE_CLAUSE="--include $TESTS_TO_INCLUDE"
 fi
 
+# shellcheck source=./common.sh
+source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
+
 echo "Environment variables"
 env
 
@@ -151,8 +130,6 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* || "$BUILD_ENVIRONMENT" == *rocm* ]]; then
   export PYTORCH_TESTING_DEVICE_ONLY_FOR="cuda"
 elif [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   export PYTORCH_TESTING_DEVICE_ONLY_FOR="xpu"
-  # setting PYTHON_TEST_EXTRA_OPTION
-  export PYTHON_TEST_EXTRA_OPTION="--xpu"
 fi
 
 if [[ "$TEST_CONFIG" == *crossref* ]]; then
@@ -160,8 +137,6 @@ if [[ "$TEST_CONFIG" == *crossref* ]]; then
 fi
 
 if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
-  # regression in ROCm 6.0 on MI50 CI runners due to hipblaslt; remove in 6.1
-  export VALGRIND=OFF
   # Print GPU info
   rocminfo
   rocminfo | grep -E 'Name:.*\sgfx|Marketing'
@@ -169,7 +144,7 @@ fi
 
 if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   # Source Intel oneAPI envrioment script to enable xpu runtime related libraries
-  # refer to https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-5.html
+  # refer to https://www.intel.com/content/www/us/en/docs/oneapi/programming-guide/2024-0/use-the-setvars-and-oneapi-vars-scripts-with-linux.html
   # shellcheck disable=SC1091
   source /opt/intel/oneapi/compiler/latest/env/vars.sh
   # Check XPU status before testing
@@ -184,13 +159,6 @@ if [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]] ; then
   export PATH="$HOME/.local/bin:$PATH"
 fi
 
-if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
-  # TODO: revisit this once the CI is stabilized on aarch64 linux
-  export VALGRIND=OFF
-fi
-
-install_tlparse
-
 # DANGER WILL ROBINSON.  The LD_PRELOAD here could cause you problems
 # if you're not careful.  Check this if you made some changes and the
 # ASAN test is not working
@@ -237,6 +205,8 @@ if [[ "$BUILD_ENVIRONMENT" == *asan* ]]; then
     export LD_PRELOAD=/usr/lib/llvm-15/lib/clang/15.0.7/lib/linux/libclang_rt.asan-x86_64.so
     # Disable valgrind for asan
     export VALGRIND=OFF
+    # Increase stack size, because ASAN red zones use more stack
+    ulimit -s 81920
 
     (cd test && python -c "import torch; print(torch.__version__, torch.version.git_version)")
     echo "The next four invocations are expected to crash; if they don't that means ASAN/UBSAN is misconfigured"
@@ -252,7 +222,9 @@ fi
 # This tests that the debug asserts are working correctly.
 if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
     echo "We are in debug mode: $BUILD_ENVIRONMENT. Expect the python assertion to fail"
-    (cd test && ! get_exit_code python -c "import torch; torch._C._crash_if_debug_asserts_fail(424242)")
+    # TODO: Enable the check after we setup the build to run debug asserts without having
+    #       to do a full (and slow) debug build
+    # (cd test && ! get_exit_code python -c "import torch; torch._C._crash_if_debug_asserts_fail(424242)")
 elif [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]]; then
     # Noop when debug is disabled. Skip bazel jobs because torch isn't available there yet.
     echo "We are not in debug mode: $BUILD_ENVIRONMENT. Expect the assertion to pass"
@@ -278,17 +250,14 @@ test_python_shard() {
 
   # Bare --include flag is not supported and quoting for lint ends up with flag not being interpreted correctly
   # shellcheck disable=SC2086
-
-  # modify LD_LIBRARY_PATH to ensure it has the conda env.
-  # This set of tests has been shown to be buggy without it for the split-build
-  time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose $PYTHON_TEST_EXTRA_OPTION
+  time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose
 
   assert_git_not_dirty
 }
 
 test_python() {
   # shellcheck disable=SC2086
-  time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --verbose $PYTHON_TEST_EXTRA_OPTION
+  time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --verbose
   assert_git_not_dirty
 }
 
@@ -299,13 +268,34 @@ test_dynamo_shard() {
     exit 1
   fi
   python tools/dynamo/verify_dynamo.py
-  # PLEASE DO NOT ADD ADDITIONAL EXCLUDES HERE.
-  # Instead, use @skipIfTorchDynamo on your tests.
+  # Temporarily disable test_fx for dynamo pending the investigation on TTS
+  # regression in https://github.com/pytorch/torchdynamo/issues/784
   time python test/run_test.py --dynamo \
-    --exclude-inductor-tests \
     --exclude-jit-executor \
     --exclude-distributed-tests \
-    --exclude-torch-export-tests \
+    --exclude \
+      test_ao_sparsity \
+      test_autograd \
+      test_jit \
+      test_proxy_tensor \
+      test_quantization \
+      test_public_bindings \
+      test_dataloader \
+      test_reductions \
+      test_namedtensor \
+      test_namedtuple_return_api \
+      profiler/test_profiler \
+      profiler/test_profiler_tree \
+      test_overrides \
+      test_python_dispatch \
+      test_fx \
+      test_package \
+      test_legacy_vmap \
+      test_custom_ops \
+      test_content_store \
+      export/test_db \
+      functorch/test_dims \
+      functorch/test_aotdispatch \
     --shard "$1" "$NUM_TEST_SHARDS" \
     --verbose
   assert_git_not_dirty
@@ -314,24 +304,11 @@ test_dynamo_shard() {
 test_inductor_distributed() {
   # Smuggle a few multi-gpu tests here so that we don't have to request another large node
   echo "Testing multi_gpu tests in test_torchinductor"
-  python test/run_test.py -i inductor/test_torchinductor.py -k test_multi_gpu --verbose
-  python test/run_test.py -i inductor/test_aot_inductor.py -k test_non_default_cuda_device --verbose
-  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/_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_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
-  python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_clip_grad_norm_.py -k test_clip_grad_norm_2d --verbose
-  python test/run_test.py -i distributed/fsdp/test_fsdp_tp_integration.py -k test_fsdp_tp_integration --verbose
+  pytest test/inductor/test_torchinductor.py -k test_multi_gpu
+  pytest test/inductor/test_aot_inductor.py -k test_non_default_cuda_device
+  pytest test/inductor/test_aot_inductor.py -k test_replicate_on_devices
+  pytest test/distributed/_tensor/test_dtensor_compile.py
+  pytest test/distributed/tensor/parallel/test_fsdp_2d_parallel.py
 
   # this runs on both single-gpu and multi-gpu instance. It should be smart about skipping tests that aren't supported
   # with if required # gpus aren't available
@@ -339,51 +316,18 @@ test_inductor_distributed() {
   assert_git_not_dirty
 }
 
-test_inductor_shard() {
-  if [[ -z "$NUM_TEST_SHARDS" ]]; then
-    echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
-    exit 1
-  fi
-
+test_inductor() {
   python tools/dynamo/verify_dynamo.py
-  python test/run_test.py --inductor \
-    --include test_modules test_ops test_ops_gradients test_torch \
-    --shard "$1" "$NUM_TEST_SHARDS" \
-    --verbose
-
+  python test/run_test.py --inductor --include test_modules test_ops test_ops_gradients test_torch --verbose
   # Do not add --inductor for the following inductor unit tests, otherwise we will fail because of nested dynamo state
-  python test/run_test.py \
-    --include inductor/test_torchinductor inductor/test_torchinductor_opinfo inductor/test_aot_inductor \
-    --shard "$1" "$NUM_TEST_SHARDS" \
-    --verbose
-}
+  python test/run_test.py --include inductor/test_torchinductor inductor/test_torchinductor_opinfo --verbose
 
-test_inductor_aoti() {
   # docker build uses bdist_wheel which does not work with test_aot_inductor
   # TODO: need a faster way to build
-  if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
-    # We need to hipify before building again
-    python3 tools/amd_build/build_amd.py
-  fi
+  if [[ "$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
-}
-
-test_inductor_cpp_wrapper_abi_compatible() {
-  export TORCHINDUCTOR_ABI_COMPATIBLE=1
-  TEST_REPORTS_DIR=$(pwd)/test/test-reports
-  mkdir -p "$TEST_REPORTS_DIR"
-
-  echo "Testing Inductor cpp wrapper mode with TORCHINDUCTOR_ABI_COMPATIBLE=1"
-  PYTORCH_TESTING_DEVICE_ONLY_FOR="" python test/run_test.py --include inductor/test_cpu_cpp_wrapper
-  python test/run_test.py --include inductor/test_cuda_cpp_wrapper inductor/test_cpu_repro
-
-  TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/timm_models.py --device cuda --accuracy --amp \
-    --training --inductor --disable-cudagraphs --only vit_base_patch16_224 \
-    --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv"
-  python benchmarks/dynamo/check_accuracy.py \
-    --actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv" \
-    --expected "benchmarks/dynamo/ci_expected_accuracy/inductor_timm_training.csv"
+      CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aot_inductor
+  fi
 }
 
 # "Global" flags for inductor benchmarking controlled by TEST_CONFIG
@@ -394,22 +338,7 @@ 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_results.csv" "benchmarks/dynamo/pr_time_benchmarks/benchmarks"
-  echo "benchmark results on current PR: "
-  cat  "$TEST_REPORTS_DIR/pr_time_benchmarks_results.csv"
-
-}
-
-if [[ "${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 [[ "${TEST_CONFIG}" == *aot_eager* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--backend aot_eager)
@@ -423,7 +352,7 @@ if [[ "${TEST_CONFIG}" == *dynamic* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--dynamic-shapes --dynamic-batch-only)
 fi
 
-if [[ "${TEST_CONFIG}" == *cpu* ]]; then
+if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--device cpu)
 else
   DYNAMO_BENCHMARK_FLAGS+=(--device cuda)
@@ -447,18 +376,6 @@ 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
@@ -474,62 +391,45 @@ 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" \
+        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}_${target}.csv"
-      fi
-      if [[ "$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" \
-          "${target_flag[@]}" --"$mode" --quant --backend "$backend" "$@" \
-          --output "$TEST_REPORTS_DIR/${backend}_cudagraphs_low_precision_${suite}_quant_${mode}_${device}_${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}_${target}.csv"
+            --output "$TEST_REPORTS_DIR/${backend}_max_autotune_${suite}_${dtype}_${mode}_cuda_${target}.csv"
       fi
     done
   done
@@ -566,19 +466,6 @@ test_single_dynamo_benchmark() {
     test_perf_for_dashboard "$suite" \
       "${DYNAMO_BENCHMARK_FLAGS[@]}" "$@" "${partition_flags[@]}"
   else
-    if [[ "${TEST_CONFIG}" == *aot_inductor* && "${TEST_CONFIG}" != *cpu_aot_inductor* ]]; then
-      # Test AOTInductor with the ABI-compatible mode on CI
-      # This can be removed once the ABI-compatible mode becomes default.
-      # For CPU device, we perfer non ABI-compatible mode on CI when testing AOTInductor.
-      export TORCHINDUCTOR_ABI_COMPATIBLE=1
-    fi
-
-    if [[ "${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[@]}" \
@@ -593,19 +480,6 @@ test_single_dynamo_benchmark() {
   fi
 }
 
-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 "${TEST_REPORTS_DIR}/gpt_fast_benchmark.csv"
-}
-
-test_inductor_halide() {
-  python test/run_test.py --include inductor/test_halide.py --verbose
-  assert_git_not_dirty
-}
-
 test_dynamo_benchmark() {
   # Usage: test_dynamo_benchmark huggingface 0
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
@@ -620,16 +494,8 @@ test_dynamo_benchmark() {
   elif [[ "${TEST_CONFIG}" == *perf* ]]; then
     test_single_dynamo_benchmark "dashboard" "$suite" "$shard_id" "$@"
   else
-    if [[ "${TEST_CONFIG}" == *cpu* ]]; then
-      local dt="float32"
-      if [[ "${TEST_CONFIG}" == *amp* ]]; then
-        dt="amp"
-      fi
-      if [[ "${TEST_CONFIG}" == *freezing* ]]; then
-        test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --"$dt" --freezing "$@"
-      else
-        test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --"$dt" "$@"
-      fi
+    if [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
+      test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --float32 "$@"
     elif [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
       test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
     else
@@ -643,15 +509,11 @@ test_inductor_torchbench_smoketest_perf() {
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
 
-  # Test some models in the cpp wrapper mode
-  TORCHINDUCTOR_ABI_COMPATIBLE=1 TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
-    --bfloat16 --inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
-  TORCHINDUCTOR_ABI_COMPATIBLE=1 TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
-    --bfloat16 --inference --inductor --only llama --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
-  TORCHINDUCTOR_ABI_COMPATIBLE=1 TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
-    --bfloat16 --inference --inductor --only moco --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
+  # smoke test the cpp_wrapper mode
+  TORCHINDUCTOR_CPP_WRAPPER=1 python benchmarks/dynamo/torchbench.py --device cuda --accuracy --bfloat16 \
+    --inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_smoketest.csv"
   python benchmarks/dynamo/check_accuracy.py \
-    --actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv" \
+      --actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_smoketest.csv" \
       --expected "benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_inference.csv"
 
   python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --float16 --training \
@@ -660,7 +522,7 @@ test_inductor_torchbench_smoketest_perf() {
   # The threshold value needs to be actively maintained to make this check useful
   python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_training_smoketest.csv" -t 1.4
 
-  TORCHINDUCTOR_ABI_COMPATIBLE=1 python benchmarks/dynamo/torchbench.py --device cuda --performance --bfloat16 --inference \
+  python benchmarks/dynamo/torchbench.py --device cuda --performance --bfloat16 --inference \
     --export-aot-inductor --only nanogpt --output "$TEST_REPORTS_DIR/inductor_inference_smoketest.csv"
   # The threshold value needs to be actively maintained to make this check useful
   # The perf number of nanogpt seems not very stable, e.g.
@@ -679,94 +541,6 @@ test_inductor_torchbench_smoketest_perf() {
       "$TEST_REPORTS_DIR/inductor_training_smoketest_$test.csv" \
       --expected benchmarks/dynamo/expected_ci_perf_inductor_torchbench.csv
   done
-
-  # Perform some "warm-start" runs for a few huggingface models.
-  for test in AlbertForQuestionAnswering AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
-    python benchmarks/dynamo/huggingface.py --accuracy --training --amp --inductor --device cuda --warm-start-latency \
-      --only $test --output "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv"
-    python benchmarks/dynamo/check_accuracy.py \
-      --actual "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/inductor_huggingface_training.csv"
-  done
-}
-
-test_inductor_get_core_number() {
-  if [[ "${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 "$TEST_REPORTS_DIR"
-
-  test_inductor_set_cpu_affinity
-  MODELS_SPEEDUP_TARGET=benchmarks/dynamo/expected_ci_speedup_inductor_torchbench_cpu.csv
-
-  grep -v '^ *#' < "$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 [[ ${model_cfg[4]} == "cpp" ]]; then
-      export TORCHINDUCTOR_CPP_WRAPPER=1
-    else
-      unset TORCHINDUCTOR_CPP_WRAPPER
-    fi
-    local output_name="$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
-      $TASKSET python benchmarks/dynamo/torchbench.py \
-        --inference --performance --"$data_type" -dcpu -n50 --only "$model_name" --dynamic-shapes \
-        --dynamic-batch-only --freezing --timeout 9000 --"$backend" --output "$output_name"
-    else
-      $TASKSET python benchmarks/dynamo/torchbench.py \
-        --inference --performance --"$data_type" -dcpu -n50 --only "$model_name" \
-        --freezing --timeout 9000 --"$backend" --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 "$TEST_REPORTS_DIR/aot_inductor_smoke_test.csv" \
-    --expected "benchmarks/dynamo/ci_expected_accuracy/aot_inductor_timm_inference.csv"
-}
-
-test_torchbench_gcp_smoketest(){
-  pushd "${TORCHBENCHPATH}"
-  python test.py -v
-  popd
 }
 
 test_python_gloo_with_tls() {
@@ -800,6 +574,7 @@ test_aten() {
   ${SUDO} ln -sf "$TORCH_LIB_DIR"/libmkldnn* "$TEST_BASE_DIR"
   ${SUDO} ln -sf "$TORCH_LIB_DIR"/libnccl* "$TEST_BASE_DIR"
   ${SUDO} ln -sf "$TORCH_LIB_DIR"/libtorch* "$TEST_BASE_DIR"
+  ${SUDO} ln -sf "$TORCH_LIB_DIR"/libtbb* "$TEST_BASE_DIR"
 
   ls "$TEST_BASE_DIR"
   aten/tools/run_tests.sh "$TEST_BASE_DIR"
@@ -824,6 +599,21 @@ test_without_numpy() {
   popd
 }
 
+# pytorch extensions require including torch/extension.h which includes all.h
+# which includes utils.h which includes Parallel.h.
+# So you can call for instance parallel_for() from your extension,
+# but the compilation will fail because of Parallel.h has only declarations
+# and definitions are conditionally included Parallel.h(see last lines of Parallel.h).
+# I tried to solve it #39612 and #39881 by including Config.h into Parallel.h
+# But if Pytorch is built with TBB it provides Config.h
+# that has AT_PARALLEL_NATIVE_TBB=1(see #3961 or #39881) and it means that if you include
+# torch/extension.h which transitively includes Parallel.h
+# which transitively includes tbb.h which is not available!
+if [[ "${BUILD_ENVIRONMENT}" == *tbb* ]]; then
+  sudo mkdir -p /usr/include/tbb
+  sudo cp -r "$PWD"/third_party/tbb/include/tbb/* /usr/include/tbb
+fi
+
 test_libtorch() {
   local SHARD="$1"
 
@@ -837,6 +627,7 @@ test_libtorch() {
     ln -sf "$TORCH_LIB_DIR"/libc10* "$TORCH_BIN_DIR"
     ln -sf "$TORCH_LIB_DIR"/libshm* "$TORCH_BIN_DIR"
     ln -sf "$TORCH_LIB_DIR"/libtorch* "$TORCH_BIN_DIR"
+    ln -sf "$TORCH_LIB_DIR"/libtbb* "$TORCH_BIN_DIR"
     ln -sf "$TORCH_LIB_DIR"/libnvfuser* "$TORCH_BIN_DIR"
 
     export CPP_TESTS_DIR="${TORCH_BIN_DIR}"
@@ -902,8 +693,9 @@ test_xpu_bin(){
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
 
-  for xpu_case in "${BUILD_BIN_DIR}"/*{xpu,sycl}*; do
-    if [[ "$xpu_case" != *"*"* && "$xpu_case" != *.so && "$xpu_case" != *.a ]]; then
+  for xpu_case in "${BUILD_BIN_DIR}"/*{xpu,sycl}*
+  do
+    if [[ "$xpu_case" != *"*"* ]]; then
       case_name=$(basename "$xpu_case")
       echo "Testing ${case_name} ..."
       "$xpu_case" --gtest_output=xml:"$TEST_REPORTS_DIR"/"$case_name".xml
@@ -973,6 +765,7 @@ test_rpc() {
   # test reporting process to function as expected.
   ln -sf "$TORCH_LIB_DIR"/libtorch* "$TORCH_BIN_DIR"
   ln -sf "$TORCH_LIB_DIR"/libc10* "$TORCH_BIN_DIR"
+  ln -sf "$TORCH_LIB_DIR"/libtbb* "$TORCH_BIN_DIR"
 
   CPP_TESTS_DIR="${TORCH_BIN_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_cpp_rpc
 }
@@ -1074,113 +867,11 @@ 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"
@@ -1252,8 +943,7 @@ test_bazel() {
 
     tools/bazel test --config=cpu-only --test_timeout=480 --test_output=all --test_tag_filters=-gpu-required --test_filter=-*CUDA :all_tests
   else
-    # Increase the test timeout to 480 like CPU tests because modules_test frequently timeout
-    tools/bazel test --test_timeout=480 --test_output=errors \
+    tools/bazel test --test_output=errors \
       //:any_test \
       //:autograd_test \
       //:dataloader_test \
@@ -1348,27 +1038,18 @@ test_docs_test() {
 }
 
 test_executorch() {
-  echo "Install torchvision and torchaudio"
-  install_torchvision
-  install_torchaudio
-
   pushd /executorch
 
-  export PYTHON_EXECUTABLE=python
-  export EXECUTORCH_BUILD_PYBIND=ON
-  export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
-
-  # NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
-  # from the PR
-  # shellcheck disable=SC1091
-  source .ci/scripts/setup-linux.sh cmake
-
-  echo "Run ExecuTorch unit tests"
-  pytest -v -n auto
-  # shellcheck disable=SC1091
-  LLVM_PROFDATA=llvm-profdata-12 LLVM_COV=llvm-cov-12 bash test/run_oss_cpp_tests.sh
+  echo "Install torchvision and torchaudio"
+  # TODO(huydhn): Switch this to the pinned commits on ExecuTorch once they are
+  # there.  These libraries need to be built here, and not part of the Docker
+  # image because they require the target version of torch to be installed first
+  pip_install --no-use-pep517 --user "git+https://github.com/pytorch/audio.git"
+  pip_install --no-use-pep517 --user "git+https://github.com/pytorch/vision.git"
 
   echo "Run ExecuTorch regression tests for some models"
+  # NB: This is a sample model, more can be added here
+  export PYTHON_EXECUTABLE=python
   # TODO(huydhn): Add more coverage here using ExecuTorch's gather models script
   # shellcheck disable=SC1091
   source .ci/scripts/test.sh mv3 cmake xnnpack-quantization-delegation ''
@@ -1382,36 +1063,11 @@ test_executorch() {
   assert_git_not_dirty
 }
 
-test_linux_aarch64() {
-  python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
-        test_transformers test_multiprocessing test_numpy_interop \
-        --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
-
-  # Dynamo tests
-  python test/run_test.py --include dynamo/test_compile dynamo/test_backends dynamo/test_comptime dynamo/test_config \
-       dynamo/test_functions dynamo/test_fx_passes_pre_grad dynamo/test_interop dynamo/test_model_output dynamo/test_modules \
-       dynamo/test_optimizers dynamo/test_recompile_ux dynamo/test_recompiles \
-       --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
-
-  # Inductor tests
-  python test/run_test.py --include inductor/test_torchinductor inductor/test_benchmark_fusion inductor/test_codecache \
-       inductor/test_config inductor/test_control_flow inductor/test_coordinate_descent_tuner inductor/test_fx_fusion \
-       inductor/test_group_batch_fusion inductor/test_inductor_freezing inductor/test_inductor_utils \
-       inductor/test_inplacing_pass inductor/test_kernel_benchmark inductor/test_layout_optim \
-       inductor/test_max_autotune inductor/test_memory_planning inductor/test_metrics inductor/test_multi_kernel inductor/test_pad_mm \
-       inductor/test_pattern_matcher inductor/test_perf inductor/test_profiler inductor/test_select_algorithm inductor/test_smoke \
-       inductor/test_split_cat_fx_passes inductor/test_standalone_compile inductor/test_torchinductor \
-       inductor/test_torchinductor_codegen_dynamic_shapes inductor/test_torchinductor_dynamic_shapes inductor/test_memory \
-       --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
-}
-
 if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-bazel-* ]]; then
   (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
-  test_linux_aarch64
-elif [[ "${TEST_CONFIG}" == *backward* ]]; then
+if [[ "${TEST_CONFIG}" == *backward* ]]; then
   test_forward_backward_compatibility
   # Do NOT add tests after bc check tests, see its comment.
 elif [[ "${TEST_CONFIG}" == *xla* ]]; then
@@ -1431,12 +1087,11 @@ elif [[ "$TEST_CONFIG" == distributed ]]; then
   if [[ "${SHARD_NUMBER}" == 1 ]]; then
     test_rpc
   fi
+elif [[ "$TEST_CONFIG" == deploy ]]; then
+  checkout_install_torchdeploy
+  test_torch_deploy
 elif [[ "${TEST_CONFIG}" == *inductor_distributed* ]]; then
   test_inductor_distributed
-elif [[ "${TEST_CONFIG}" == *inductor-halide* ]]; then
-  test_inductor_halide
-elif [[ "${TEST_CONFIG}" == *inductor-micro-benchmark* ]]; then
-  test_inductor_micro_benchmark
 elif [[ "${TEST_CONFIG}" == *huggingface* ]]; then
   install_torchvision
   id=$((SHARD_NUMBER-1))
@@ -1446,58 +1101,39 @@ elif [[ "${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 [[ "${TEST_CONFIG}" == *cpu_inductor* ]]; then
     install_torchaudio cpu
   else
     install_torchaudio cuda
   fi
   install_torchtext
   install_torchvision
-  TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install git+https://github.com/pytorch/ao.git
   id=$((SHARD_NUMBER-1))
   # https://github.com/opencv/opencv-python/issues/885
   pip_install opencv-python==4.8.0.74
   if [[ "${TEST_CONFIG}" == *inductor_torchbench_smoketest_perf* ]]; then
     checkout_install_torchbench hf_Bert hf_Albert nanogpt timm_vision_transformer
     PYTHONPATH=$(pwd)/torchbench test_inductor_torchbench_smoketest_perf
-  elif [[ "${TEST_CONFIG}" == *inductor_torchbench_cpu_smoketest_perf* ]]; then
-    checkout_install_torchbench timm_vision_transformer phlippe_densenet basic_gnn_edgecnn \
-      llama_v2_7b_16h resnet50 timm_efficientnet mobilenet_v3_large timm_resnest \
-      functorch_maml_omniglot yolov3 mobilenet_v2 resnext50_32x4d densenet121 mnasnet1_0
-    PYTHONPATH=$(pwd)/torchbench test_inductor_torchbench_cpu_smoketest_perf
-  elif [[ "${TEST_CONFIG}" == *torchbench_gcp_smoketest* ]]; then
-    checkout_install_torchbench
-    TORCHBENCHPATH=$(pwd)/torchbench test_torchbench_gcp_smoketest
   else
     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* ]]; then
       install_torchrec_and_fbgemm
     fi
     PYTHONPATH=$(pwd)/torchbench test_dynamo_benchmark torchbench "$id"
   fi
-elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper_abi_compatible* ]]; then
+elif [[ "${TEST_CONFIG}" == *inductor* && "${SHARD_NUMBER}" == 1 ]]; then
   install_torchvision
-  test_inductor_cpp_wrapper_abi_compatible
-elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
-  install_torchvision
-  test_inductor_shard "${SHARD_NUMBER}"
-  if [[ "${SHARD_NUMBER}" == 1 ]]; then
-    if [[ "${BUILD_ENVIRONMENT}" != linux-jammy-py3.9-gcc11-build ]]; then
+  test_inductor
   test_inductor_distributed
-    fi
-  fi
-elif [[ "${TEST_CONFIG}" == *dynamo* ]]; then
+elif [[ "${TEST_CONFIG}" == *dynamo* && "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
+  install_torchvision
+  test_dynamo_shard 1
+  test_aten
+elif [[ "${TEST_CONFIG}" == *dynamo* && $SHARD_NUMBER -gt 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
   install_torchvision
   test_dynamo_shard "${SHARD_NUMBER}"
-  if [[ "${SHARD_NUMBER}" == 1 ]]; then
-    test_aten
-  fi
-elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
-  install_torchvision
-  test_python_shard "$SHARD_NUMBER"
-  test_aten
 elif [[ "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
   test_without_numpy
   install_torchvision
@@ -1527,6 +1163,10 @@ elif [[ "${BUILD_ENVIRONMENT}" == *-mobile-lightweight-dispatch* ]]; then
   test_libtorch
 elif [[ "${TEST_CONFIG}" = docs_test ]]; then
   test_docs_test
+elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
+  install_torchvision
+  test_python
+  test_aten
 elif [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
   install_torchvision
   test_python

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

@@ -16,29 +16,24 @@ set PATH=C:\Program Files\CMake\bin;C:\Program Files\7-Zip;C:\ProgramData\chocol
 
 set INSTALLER_DIR=%SCRIPT_HELPERS_DIR%\installation-helpers
 
+
+call %INSTALLER_DIR%\install_mkl.bat
+if errorlevel 1 exit /b
+if not errorlevel 0 exit /b
+
 call %INSTALLER_DIR%\install_magma.bat
-if errorlevel 1 goto fail
-if not errorlevel 0 goto fail
+if errorlevel 1 exit /b
+if not errorlevel 0 exit /b
 
 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
-)
+if errorlevel 1 exit /b
+if not errorlevel 0 exit /b
 
 :: 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
-if errorlevel 1 goto fail
-if not errorlevel 0 goto fail
-
-call pip install mkl-include==2021.4.0 mkl-devel==2021.4.0
-if errorlevel 1 goto fail
-if not errorlevel 0 goto fail
+if errorlevel 1 exit /b
+if not errorlevel 0 exit /b
 
 :: Override VS env here
 pushd .
@@ -47,18 +42,8 @@ if "%VC_VERSION%" == "" (
 ) else (
     call "C:\Program Files (x86)\Microsoft Visual Studio\%VC_YEAR%\%VC_PRODUCT%\VC\Auxiliary\Build\vcvarsall.bat" x64 -vcvars_ver=%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
-)
-
+if errorlevel 1 exit /b
+if not errorlevel 0 exit /b
 @echo on
 popd
 
@@ -68,12 +53,12 @@ set CUDA_PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v%CUDA_VERSION%
 
 if x%CUDA_VERSION:.=%==x%CUDA_VERSION% (
     echo CUDA version %CUDA_VERSION% format isn't correct, which doesn't contain '.'
-    goto fail
+    exit /b 1
 )
 rem version transformer, for example 10.1 to 10_1.
 if x%CUDA_VERSION:.=%==x%CUDA_VERSION% (
     echo CUDA version %CUDA_VERSION% format isn't correct, which doesn't contain '.'
-    goto fail
+    exit /b 1
 )
 set VERSION_SUFFIX=%CUDA_VERSION:.=_%
 set CUDA_PATH_V%VERSION_SUFFIX%=%CUDA_PATH%
@@ -81,6 +66,13 @@ 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
@@ -97,8 +89,8 @@ set SCCACHE_IGNORE_SERVER_IO_ERROR=1
 sccache --stop-server
 sccache --start-server
 sccache --zero-stats
-set CMAKE_C_COMPILER_LAUNCHER=sccache
-set CMAKE_CXX_COMPILER_LAUNCHER=sccache
+set CC=sccache-cl
+set CXX=sccache-cl
 
 set CMAKE_GENERATOR=Ninja
 
@@ -110,8 +102,8 @@ if "%USE_CUDA%"=="1" (
   :: CMake requires a single command as CUDA_NVCC_EXECUTABLE, so we push the wrappers
   :: randomtemp.exe and sccache.exe into a batch file which CMake invokes.
   curl -kL https://github.com/peterjc123/randomtemp-rust/releases/download/v0.4/randomtemp.exe --output %TMP_DIR_WIN%\bin\randomtemp.exe
-  if errorlevel 1 goto fail
-  if not errorlevel 0 goto fail
+  if errorlevel 1 exit /b
+  if not errorlevel 0 exit /b
   echo @"%TMP_DIR_WIN%\bin\randomtemp.exe" "%TMP_DIR_WIN%\bin\sccache.exe" "%CUDA_PATH%\bin\nvcc.exe" %%* > "%TMP_DIR%/bin/nvcc.bat"
   cat %TMP_DIR%/bin/nvcc.bat
   set CUDA_NVCC_EXECUTABLE=%TMP_DIR%/bin/nvcc.bat
@@ -123,8 +115,8 @@ if "%USE_CUDA%"=="1" (
 set
 
 python setup.py bdist_wheel
-if errorlevel 1 goto fail
-if not errorlevel 0 goto fail
+if errorlevel 1 exit /b
+if not errorlevel 0 exit /b
 sccache --show-stats
 python -c "import os, glob; os.system('python -mpip install --no-index --no-deps ' + glob.glob('dist/*.whl')[0])"
 (
@@ -144,8 +136,3 @@ python -c "import os, glob; os.system('python -mpip install --no-index --no-deps
 
 sccache --show-stats --stats-format json | jq .stats > sccache-stats-%BUILD_ENVIRONMENT%-%OUR_GITHUB_JOB_ID%.json
 sccache --stop-server
-
-exit /b 0
-
-:fail
-exit /b 1

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

@@ -0,0 +1,14 @@
+if "%REBUILD%"=="" (
+  if "%BUILD_ENVIRONMENT%"=="" (
+    curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/mkl_2020.2.254.7z --output %TMP_DIR_WIN%\mkl.7z
+  ) else (
+    aws s3 cp s3://ossci-windows/mkl_2020.2.254.7z %TMP_DIR_WIN%\mkl.7z --quiet
+  )
+  if errorlevel 1 exit /b
+  if not errorlevel 0 exit /b
+  7z x -aoa %TMP_DIR_WIN%\mkl.7z -o%TMP_DIR_WIN%\mkl
+  if errorlevel 1 exit /b
+  if not errorlevel 0 exit /b
+)
+set CMAKE_INCLUDE_PATH=%TMP_DIR_WIN%\mkl\include
+set LIB=%TMP_DIR_WIN%\mkl\lib;%LIB%

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

@@ -1,13 +1,18 @@
 mkdir %TMP_DIR_WIN%\bin
 
 if "%REBUILD%"=="" (
-  IF EXIST %TMP_DIR_WIN%\bin\sccache.exe (
+  :check_sccache
+  %TMP_DIR_WIN%\bin\sccache.exe --show-stats || (
     taskkill /im sccache.exe /f /t || ver > nul
     del %TMP_DIR_WIN%\bin\sccache.exe || ver > nul
-  )
+    del %TMP_DIR_WIN%\bin\sccache-cl.exe || ver > nul
     if "%BUILD_ENVIRONMENT%"=="" (
-    curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/sccache-v0.7.4.exe --output %TMP_DIR_WIN%\bin\sccache.exe
+      curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/sccache.exe --output %TMP_DIR_WIN%\bin\sccache.exe
+      curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/sccache-cl.exe --output %TMP_DIR_WIN%\bin\sccache-cl.exe
     ) else (
-    aws s3 cp s3://ossci-windows/sccache-v0.7.4.exe %TMP_DIR_WIN%\bin\sccache.exe
+      aws s3 cp s3://ossci-windows/sccache.exe %TMP_DIR_WIN%\bin\sccache.exe
+      aws s3 cp s3://ossci-windows/sccache-cl.exe %TMP_DIR_WIN%\bin\sccache-cl.exe
+    )
+    goto :check_sccache
   )
 )

.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/run_python_nn_smoketests.py

@@ -4,7 +4,6 @@ import os
 import subprocess
 import sys
 
-
 COMMON_TESTS = [
     (
         "Checking that torch is available",

.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

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

.circleci/README.md

@@ -1,4 +1,468 @@
 Warning
 =======
 
-PyTorch migration from CircleCI to github actions has been completed. All continuous integration & deployment workflows are defined in  `.github/workflows` folder
+Contents may be out of date. Our CircleCI workflows are gradually being migrated to Github actions.
+
+Structure of CI
+===============
+
+setup job:
+1. Does a git checkout
+2. Persists CircleCI scripts (everything in `.circleci`) into a workspace.  Why?
+   We don't always do a Git checkout on all subjobs, but we usually
+   still want to be able to call scripts one way or another in a subjob.
+   Persisting files this way lets us have access to them without doing a
+   checkout.  This workspace is conventionally mounted on `~/workspace`
+   (this is distinguished from `~/project`, which is the conventional
+   working directory that CircleCI will default to starting your jobs
+   in.)
+3. Write out the commit message to `.circleci/COMMIT_MSG`.  This is so
+   we can determine in subjobs if we should actually run the jobs or
+   not, even if there isn't a Git checkout.
+
+
+CircleCI configuration generator
+================================
+
+One may no longer make changes to the `.circleci/config.yml` file directly.
+Instead, one must edit these Python scripts or files in the `verbatim-sources/` directory.
+
+
+Usage
+----------
+
+1. Make changes to these scripts.
+2. Run the `regenerate.sh` script in this directory and commit the script changes and the resulting change to `config.yml`.
+
+You'll see a build failure on GitHub if the scripts don't agree with the checked-in version.
+
+
+Motivation
+----------
+
+These scripts establish a single, authoritative source of documentation for the CircleCI configuration matrix.
+The documentation, in the form of diagrams, is automatically generated and cannot drift out of sync with the YAML content.
+
+Furthermore, consistency is enforced within the YAML config itself, by using a single source of data to generate
+multiple parts of the file.
+
+* Facilitates one-off culling/enabling of CI configs for testing PRs on special targets
+
+Also see https://github.com/pytorch/pytorch/issues/17038
+
+
+Future direction
+----------------
+
+### Declaring sparse config subsets
+See comment [here](https://github.com/pytorch/pytorch/pull/17323#pullrequestreview-206945747):
+
+In contrast with a full recursive tree traversal of configuration dimensions,
+> in the future I think we actually want to decrease our matrix somewhat and have only a few mostly-orthogonal builds that taste as many different features as possible on PRs, plus a more complete suite on every PR and maybe an almost full suite nightly/weekly (we don't have this yet). Specifying PR jobs in the future might be easier to read with an explicit list when we come to this.
+----------------
+----------------
+
+# How do the binaries / nightlies / releases work?
+
+### What is a binary?
+
+A binary or package (used interchangeably) is a pre-built collection of c++ libraries, header files, python bits, and other files. We build these and distribute them so that users do not need to install from source.
+
+A **binary configuration** is a collection of
+
+* release or nightly
+    * releases are stable, nightlies are beta and built every night
+* python version
+    * linux: 3.7m (mu is wide unicode or something like that. It usually doesn't matter but you should know that it exists)
+    * macos: 3.7, 3.8
+    * windows: 3.7, 3.8
+* cpu version
+    * cpu, cuda 9.0, cuda 10.0
+    * The supported cuda versions occasionally change
+* operating system
+    * Linux - these are all built on CentOS. There haven't been any problems in the past building on CentOS and using on Ubuntu
+    * MacOS
+    * Windows - these are built on Azure pipelines
+* devtoolset version (gcc compiler version)
+    * This only matters on Linux cause only Linux uses gcc. tldr is gcc made a backwards incompatible change from gcc 4.8 to gcc 5, because it had to change how it implemented std::vector and std::string
+
+### Where are the binaries?
+
+The binaries are built in CircleCI. There are nightly binaries built every night at 9pm PST (midnight EST) and release binaries corresponding to Pytorch releases, usually every few months.
+
+We have 3 types of binary packages
+
+* pip packages - nightlies are stored on s3 (pip install -f \<a s3 url\>). releases are stored in a pip repo (pip install torch) (ask Soumith about this)
+* conda packages - nightlies and releases are both stored in a conda repo. Nighty packages have a '_nightly' suffix
+* libtorch packages - these are zips of all the c++ libraries, header files, and sometimes dependencies. These are c++ only
+    * shared with dependencies (the only supported option for Windows)
+    * static with dependencies
+    * shared without dependencies
+    * static without dependencies
+
+All binaries are built in CircleCI workflows except Windows. There are checked-in workflows (committed into the .circleci/config.yml) to build the nightlies every night. Releases are built by manually pushing a PR that builds the suite of release binaries (overwrite the config.yml to build the release)
+
+# CircleCI structure of the binaries
+
+Some quick vocab:
+
+* A \**workflow** is a CircleCI concept; it is a DAG of '**jobs**'. ctrl-f 'workflows' on https://github.com/pytorch/pytorch/blob/main/.circleci/config.yml to see the workflows.
+* **jobs** are a sequence of '**steps**'
+* **steps** are usually just a bash script or a builtin CircleCI command. *All steps run in new environments, environment variables declared in one script DO NOT persist to following steps*
+* CircleCI has a **workspace**, which is essentially a cache between steps of the *same job* in which you can store artifacts between steps.
+
+## How are the workflows structured?
+
+The nightly binaries have 3 workflows. We have one job (actually 3 jobs:  build, test, and upload) per binary configuration
+
+1. binary_builds
+    1. every day midnight EST
+    2. linux: https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/linux-binary-build-defaults.yml
+    3. macos: https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/macos-binary-build-defaults.yml
+    4. For each binary configuration, e.g. linux_conda_3.7_cpu there is a
+        1. binary_linux_conda_3.7_cpu_build
+            1. Builds the build. On linux jobs this uses the 'docker executor'.
+            2. Persists the package to the workspace
+        2. binary_linux_conda_3.7_cpu_test
+            1. Loads the package to the workspace
+            2. Spins up a docker image (on Linux), mapping the package and code repos into the docker
+            3. Runs some smoke tests in the docker
+            4. (Actually, for macos this is a step rather than a separate job)
+        3. binary_linux_conda_3.7_cpu_upload
+            1. Logs in to aws/conda
+            2. Uploads the package
+2. update_s3_htmls
+    1. every day 5am EST
+    2. https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/binary_update_htmls.yml
+    3. See below for what these are for and why they're needed
+    4. Three jobs that each examine the current contents of aws and the conda repo and update some html files in s3
+3. binarysmoketests
+    1. every day
+    2. https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/nightly-build-smoke-tests-defaults.yml
+    3. For each binary configuration, e.g. linux_conda_3.7_cpu there is a
+        1. smoke_linux_conda_3.7_cpu
+            1. Downloads the package from the cloud, e.g. using the official pip or conda instructions
+            2. Runs the smoke tests
+
+## How are the jobs structured?
+
+The jobs are in https://github.com/pytorch/pytorch/tree/main/.circleci/verbatim-sources. Jobs are made of multiple steps. There are some shared steps used by all the binaries/smokes. Steps of these jobs are all delegated to scripts in https://github.com/pytorch/pytorch/tree/main/.circleci/scripts .
+
+* Linux jobs: https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/linux-binary-build-defaults.yml
+    * binary_linux_build.sh
+    * binary_linux_test.sh
+    * binary_linux_upload.sh
+* MacOS jobs: https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/macos-binary-build-defaults.yml
+    * binary_macos_build.sh
+    * binary_macos_test.sh
+    * binary_macos_upload.sh
+* Update html jobs: https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/binary_update_htmls.yml
+    * These delegate from the pytorch/builder repo
+    * https://github.com/pytorch/builder/blob/main/cron/update_s3_htmls.sh
+    * https://github.com/pytorch/builder/blob/main/cron/upload_binary_sizes.sh
+* Smoke jobs (both linux and macos): https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/nightly-build-smoke-tests-defaults.yml
+    * These delegate from the pytorch/builder repo
+    * https://github.com/pytorch/builder/blob/main/run_tests.sh
+    * https://github.com/pytorch/builder/blob/main/smoke_test.sh
+    * https://github.com/pytorch/builder/blob/main/check_binary.sh
+* Common shared code (shared across linux and macos): https://github.com/pytorch/pytorch/blob/main/.circleci/verbatim-sources/nightly-binary-build-defaults.yml
+    * binary_checkout.sh - checks out pytorch/builder repo. Right now this also checks out pytorch/pytorch, but it shouldn't. pytorch/pytorch should just be shared through the workspace. This can handle being run before binary_populate_env.sh
+    * binary_populate_env.sh - parses BUILD_ENVIRONMENT into the separate env variables that make up a binary configuration. Also sets lots of default values, the date, the version strings, the location of folders in s3, all sorts of things. This generally has to be run before other steps.
+    * binary_install_miniconda.sh - Installs miniconda, cross platform. Also hacks this for the update_binary_sizes job that doesn't have the right env variables
+    * binary_run_in_docker.sh - Takes a bash script file (the actual test code) from a hardcoded location, spins up a docker image, and runs the script inside the docker image
+
+### **Why do the steps all refer to scripts?**
+
+CircleCI creates a  final yaml file by inlining every <<* segment, so if we were to keep all the code in the config.yml itself then the config size would go over 4 MB and cause infra problems.
+
+### **What is binary_run_in_docker for?**
+
+So, CircleCI has several executor types: macos, machine, and docker are the ones we use. The 'machine' executor gives you two cores on some linux vm. The 'docker' executor gives you considerably more cores (nproc was 32 instead of 2 back when I tried in February). Since the dockers are faster, we try to run everything that we can in dockers. Thus
+
+* linux build jobs use the docker executor. Running them on the docker executor was at least 2x faster than running them on the machine executor
+* linux test jobs use the machine executor in order for them to properly interface with GPUs since docker executors cannot execute with attached GPUs
+* linux upload jobs use the machine executor. The upload jobs are so short that it doesn't really matter what they use
+* linux smoke test jobs use the machine executor for the same reason as the linux test jobs
+
+binary_run_in_docker.sh is a way to share the docker start-up code between the binary test jobs and the binary smoke test jobs
+
+### **Why does binary_checkout also checkout pytorch? Why shouldn't it?**
+
+We want all the nightly binary jobs to run on the exact same git commit, so we wrote our own checkout logic to ensure that the same commit was always picked. Later circleci changed that to use a single pytorch checkout and persist it through the workspace (they did this because our config file was too big, so they wanted to take a lot of the setup code into scripts, but the scripts needed the code repo to exist to be called, so they added a prereq step called 'setup' to checkout the code and persist the needed scripts to the workspace). The changes to the binary jobs were not properly tested, so they all broke from missing pytorch code no longer existing. We hotfixed the problem by adding the pytorch checkout back to binary_checkout, so now there's two checkouts of pytorch on the binary jobs. This problem still needs to be fixed, but it takes careful tracing of which code is being called where.
+
+# Code structure of the binaries (circleci agnostic)
+
+## Overview
+
+The code that runs the binaries lives in two places, in the normal [github.com/pytorch/pytorch](http://github.com/pytorch/pytorch), but also in [github.com/pytorch/builder](http://github.com/pytorch/builder), which is a repo that defines how all the binaries are built. The relevant code is
+
+
+```
+# All code needed to set-up environments for build code to run in,
+# but only code that is specific to the current CI system
+pytorch/pytorch
+- .circleci/                # Folder that holds all circleci related stuff
+  - config.yml              # GENERATED file that actually controls all circleci behavior
+  - verbatim-sources        # Used to generate job/workflow sections in ^
+  - scripts/                # Code needed to prepare circleci environments for binary build scripts
+- setup.py                  # Builds pytorch. This is wrapped in pytorch/builder
+- cmake files               # used in normal building of pytorch
+# All code needed to prepare a binary build, given an environment
+# with all the right variables/packages/paths.
+pytorch/builder
+# Given an installed binary and a proper python env, runs some checks
+# to make sure the binary was built the proper way. Checks things like
+# the library dependencies, symbols present, etc.
+- check_binary.sh
+# Given an installed binary, runs python tests to make sure everything
+# is in order. These should be de-duped. Right now they both run smoke
+# tests, but are called from different places. Usually just call some
+# import statements, but also has overlap with check_binary.sh above
+- run_tests.sh
+- smoke_test.sh
+# Folders that govern how packages are built. See paragraphs below
+- conda/
+  - build_pytorch.sh          # Entrypoint. Delegates to proper conda build folder
+  - switch_cuda_version.sh    # Switches activate CUDA installation in Docker
+  - pytorch-nightly/          # Build-folder
+- manywheel/
+  - build_cpu.sh              # Entrypoint for cpu builds
+  - build.sh                  # Entrypoint for CUDA builds
+  - build_common.sh           # Actual build script that ^^ call into
+- wheel/
+  - build_wheel.sh            # Entrypoint for wheel builds
+- windows/
+  - build_pytorch.bat         # Entrypoint for wheel builds on Windows
+```
+
+Every type of package has an entrypoint build script that handles the all the important logic.
+
+## Conda
+
+Linux, MacOS and Windows use the same code flow for the conda builds.
+
+Conda packages are built with conda-build, see https://conda.io/projects/conda-build/en/latest/resources/commands/conda-build.html
+
+Basically, you pass `conda build` a build folder (pytorch-nightly/ above) that contains a build script and a meta.yaml. The meta.yaml specifies in what python environment to build the package in, and what dependencies the resulting package should have, and the build script gets called in the env to build the thing.
+tl;dr on conda-build is
+
+1. Creates a brand new conda environment, based off of deps in the meta.yaml
+    1. Note that environment variables do not get passed into this build env unless they are specified in the meta.yaml
+    2. If the build fails this environment will stick around. You can activate it for much easier debugging. The “General Python” section below explains what exactly a python “environment” is.
+2. Calls build.sh in the environment
+3. Copies the finished package to a new conda env, also specified by the meta.yaml
+4. Runs some simple import tests (if specified in the meta.yaml)
+5. Saves the finished package as a tarball
+
+The build.sh we use is essentially a wrapper around `python setup.py build`, but it also manually copies in some of our dependent libraries into the resulting tarball and messes with some rpaths.
+
+The entrypoint file `builder/conda/build_conda.sh` is complicated because
+
+* It works for Linux, MacOS and Windows
+    * The mac builds used to create their own environments, since they all used to be on the same machine. There’s now a lot of extra logic to handle conda envs. This extra machinery could be removed
+* It used to handle testing too, which adds more logic messing with python environments too. This extra machinery could be removed.
+
+## Manywheels (linux pip and libtorch packages)
+
+Manywheels are pip packages for linux distros. Note that these manywheels are not actually manylinux compliant.
+
+`builder/manywheel/build_cpu.sh` and `builder/manywheel/build.sh` (for CUDA builds) just set different env vars and then call into `builder/manywheel/build_common.sh`
+
+The entrypoint file `builder/manywheel/build_common.sh` is really really complicated because
+
+* This used to handle building for several different python versions at the same time. The loops have been removed, but there's still unnecessary folders and movements here and there.
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This used to handle testing the pip packages too. This is why there’s testing code at the end that messes with python installations and stuff
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This also builds libtorch packages
+    * This should really be separate. libtorch packages are c++ only and have no python. They should not share infra with all the python specific stuff in this file.
+* There is a lot of messing with rpaths. This is necessary, but could be made much much simpler if the above issues were fixed.
+
+## Wheels (MacOS pip and libtorch packages)
+
+The entrypoint file `builder/wheel/build_wheel.sh` is complicated because
+
+* The mac builds used to all run on one machine (we didn’t have autoscaling mac machines till circleci). So this script handled siloing itself by setting-up and tearing-down its build env and siloing itself into its own build directory.
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This also builds libtorch packages
+    * Ditto the comment above. This should definitely be separated out.
+
+Note that the MacOS Python wheels are still built in conda environments. Some of the dependencies present during build also come from conda.
+
+## Windows Wheels (Windows pip and libtorch packages)
+
+The entrypoint file `builder/windows/build_pytorch.bat` is complicated because
+
+* This used to handle building for several different python versions at the same time. This is why there are loops everywhere
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This used to handle testing the pip packages too. This is why there’s testing code at the end that messes with python installations and stuff
+    * The script is never used this way anymore. This extra machinery could be removed.
+* This also builds libtorch packages
+    * This should really be separate. libtorch packages are c++ only and have no python. They should not share infra with all the python specific stuff in this file.
+
+Note that the Windows Python wheels are still built in conda environments. Some of the dependencies present during build also come from conda.
+
+## General notes
+
+### Note on run_tests.sh, smoke_test.sh, and check_binary.sh
+
+* These should all be consolidated
+* These must run on all OS types: MacOS, Linux, and Windows
+* These all run smoke tests at the moment. They inspect the packages some, maybe run a few import statements. They DO NOT run the python tests nor the cpp tests. The idea is that python tests on main and PR merges will catch all breakages. All these tests have to do is make sure the special binary machinery didn’t mess anything up.
+* There are separate run_tests.sh and smoke_test.sh because one used to be called by the smoke jobs and one used to be called by the binary test jobs (see circleci structure section above). This is still true actually, but these could be united into a single script that runs these checks, given an installed pytorch package.
+
+### Note on libtorch
+
+Libtorch packages are built in the wheel build scripts: manywheel/build_*.sh for linux and build_wheel.sh for mac. There are several things wrong with this
+
+* It’s confusing. Most of those scripts deal with python specifics.
+* The extra conditionals everywhere severely complicate the wheel build scripts
+* The process for building libtorch is different from the official instructions (a plain call to cmake, or a call to a script)
+
+### Note on docker images / Dockerfiles
+
+All linux builds occur in docker images. The docker images are
+
+* pytorch/conda-cuda
+    * Has ALL CUDA versions installed. The script pytorch/builder/conda/switch_cuda_version.sh sets /usr/local/cuda to a symlink to e.g. /usr/local/cuda-10.0 to enable different CUDA builds
+    * Also used for cpu builds
+* pytorch/manylinux-cuda90
+* pytorch/manylinux-cuda100
+    * Also used for cpu builds
+
+The Dockerfiles are available in pytorch/builder, but there is no circleci job or script to build these docker images, and they cannot be run locally (unless you have the correct local packages/paths). Only Soumith can build them right now.
+
+### General Python
+
+* This is still a good explanation of python installations https://caffe2.ai/docs/faq.html#why-do-i-get-import-errors-in-python-when-i-try-to-use-caffe2
+
+# How to manually rebuild the binaries
+
+tl;dr make a PR that looks like https://github.com/pytorch/pytorch/pull/21159
+
+Sometimes we want to push a change to mainand then rebuild all of today's binaries after that change. As of May 30, 2019 there isn't a way to manually run a workflow in the UI. You can manually re-run a workflow, but it will use the exact same git commits as the first run and will not include any changes. So we have to make a PR and then force circleci to run the binary workflow instead of the normal tests. The above PR is an example of how to do this; essentially you copy-paste the binarybuilds workflow steps into the default workflow steps. If you need to point the builder repo to a different commit then you'd need to change https://github.com/pytorch/pytorch/blob/main/.circleci/scripts/binary_checkout.sh#L42-L45 to checkout what you want.
+
+## How to test changes to the binaries via .circleci
+
+Writing PRs that test the binaries is annoying, since the default circleci jobs that run on PRs are not the jobs that you want to run. Likely, changes to the binaries will touch something under .circleci/ and require that .circleci/config.yml be regenerated (.circleci/config.yml controls all .circleci behavior, and is generated using `.circleci/regenerate.sh` in python 3.7). But you also need to manually hardcode the binary jobs that you want to test into the .circleci/config.yml workflow, so you should actually make at least two commits, one for your changes and one to temporarily hardcode jobs. See https://github.com/pytorch/pytorch/pull/22928 as an example of how to do this.
+
+```sh
+# Make your changes
+touch .circleci/verbatim-sources/nightly-binary-build-defaults.yml
+# Regenerate the yaml, has to be in python 3.7
+.circleci/regenerate.sh
+# Make a commit
+git add .circleci *
+git commit -m "My real changes"
+git push origin my_branch
+# Now hardcode the jobs that you want in the .circleci/config.yml workflows section
+# Also eliminate ensure-consistency and should_run_job checks
+# e.g. https://github.com/pytorch/pytorch/commit/2b3344bfed8772fe86e5210cc4ee915dee42b32d
+# Make a commit you won't keep
+git add .circleci
+git commit -m "[DO NOT LAND] testing binaries for above changes"
+git push origin my_branch
+# Now you need to make some changes to the first commit.
+git rebase -i HEAD~2 # mark the first commit as 'edit'
+# Make the changes
+touch .circleci/verbatim-sources/nightly-binary-build-defaults.yml
+.circleci/regenerate.sh
+# Ammend the commit and recontinue
+git add .circleci
+git commit --amend
+git rebase --continue
+# Update the PR, need to force since the commits are different now
+git push origin my_branch --force
+```
+
+The advantage of this flow is that you can make new changes to the base commit and regenerate the .circleci without having to re-write which binary jobs you want to test on. The downside is that all updates will be force pushes.
+
+## How to build a binary locally
+
+### Linux
+
+You can build Linux binaries locally easily using docker.
+
+```sh
+# Run the docker
+# Use the correct docker image, pytorch/conda-cuda used here as an example
+#
+# -v path/to/foo:path/to/bar makes path/to/foo on your local machine (the
+#    machine that you're running the command on) accessible to the docker
+#    container at path/to/bar. So if you then run `touch path/to/bar/baz`
+#    in the docker container then you will see path/to/foo/baz on your local
+#    machine. You could also clone the pytorch and builder repos in the docker.
+#
+# If you know how, add ccache as a volume too and speed up everything
+docker run \
+    -v your/pytorch/repo:/pytorch \
+    -v your/builder/repo:/builder \
+    -v where/you/want/packages/to/appear:/final_pkgs \
+    -it pytorch/conda-cuda /bin/bash
+# Export whatever variables are important to you. All variables that you'd
+# possibly need are in .circleci/scripts/binary_populate_env.sh
+# You should probably always export at least these 3 variables
+export PACKAGE_TYPE=conda
+export DESIRED_PYTHON=3.7
+export DESIRED_CUDA=cpu
+# Call the entrypoint
+# `|& tee foo.log` just copies all stdout and stderr output to foo.log
+# The builds generate lots of output so you probably need this when
+# building locally.
+/builder/conda/build_pytorch.sh |& tee build_output.log
+```
+
+**Building CUDA binaries on docker**
+
+You can build CUDA binaries on CPU only machines, but you can only run CUDA binaries on CUDA machines. This means that you can build a CUDA binary on a docker on your laptop if you so choose (though it’s gonna take a long time).
+
+For Facebook employees, ask about beefy machines that have docker support and use those instead of your laptop; it will be 5x as fast.
+
+### MacOS
+
+There’s no easy way to generate reproducible hermetic MacOS environments. If you have a Mac laptop then you can try emulating the .circleci environments as much as possible, but you probably have packages in /usr/local/, possibly installed by brew, that will probably interfere with the build. If you’re trying to repro an error on a Mac build in .circleci and you can’t seem to repro locally, then my best advice is actually to iterate on .circleci    :/
+
+But if you want to try, then I’d recommend
+
+```sh
+# Create a new terminal
+# Clear your LD_LIBRARY_PATH and trim as much out of your PATH as you
+# know how to do
+# Install a new miniconda
+# First remove any other python or conda installation from your PATH
+# Always install miniconda 3, even if building for Python <3
+new_conda="~/my_new_conda"
+conda_sh="$new_conda/install_miniconda.sh"
+curl -o "$conda_sh" https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
+chmod +x "$conda_sh"
+"$conda_sh" -b -p "$MINICONDA_ROOT"
+rm -f "$conda_sh"
+export PATH="~/my_new_conda/bin:$PATH"
+# Create a clean python env
+# All MacOS builds use conda to manage the python env and dependencies
+# that are built with, even the pip packages
+conda create -yn binary python=2.7
+conda activate binary
+# Export whatever variables are important to you. All variables that you'd
+# possibly need are in .circleci/scripts/binary_populate_env.sh
+# You should probably always export at least these 3 variables
+export PACKAGE_TYPE=conda
+export DESIRED_PYTHON=3.7
+export DESIRED_CUDA=cpu
+# Call the entrypoint you want
+path/to/builder/wheel/build_wheel.sh
+```
+
+N.B. installing a brand new miniconda is important. This has to do with how conda installations work. See the “General Python” section above, but tldr; is that
+
+1. You make the ‘conda’ command accessible by prepending `path/to/conda_root/bin` to your PATH.
+2. You make a new env and activate it, which then also gets prepended to your PATH. Now you have `path/to/conda_root/envs/new_env/bin:path/to/conda_root/bin:$PATH`
+3. Now say you (or some code that you ran) call python executable `foo`
+    1. if you installed `foo` in `new_env`, then `path/to/conda_root/envs/new_env/bin/foo` will get called, as expected.
+    2. But if you forgot to installed `foo` in `new_env` but happened to previously install it in your root conda env (called ‘base’), then unix/linux will still find `path/to/conda_root/bin/foo` . This is dangerous, since `foo` can be a different version than you want; `foo` can even be for an incompatible python version!
+
+Newer conda versions and proper python hygiene can prevent this, but just install a new miniconda to be safe.
+
+### Windows
+
+TODO: fill in

.circleci/codegen_validation/normalize_yaml_fragment.py

@@ -5,7 +5,6 @@ import sys
 
 import yaml
 
-
 # Need to import modules that lie on an upward-relative path
 sys.path.append(os.path.join(sys.path[0], ".."))
 

.circleci/scripts/binary_checkout.sh

@@ -0,0 +1,69 @@
+#!/bin/bash
+set -eux -o pipefail
+
+retry () {
+    $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
+}
+
+
+# This step runs on multiple executors with different envfile locations
+if [[ "$(uname)" == Darwin ]]; then
+  # macos executor (builds and tests)
+  workdir="/Users/distiller/project"
+elif [[ "$OSTYPE" == "msys" ]]; then
+  # windows executor (builds and tests)
+  rm -rf /c/w
+  ln -s "/c/Users/circleci/project" /c/w
+  workdir="/c/w"
+elif [[ -d "/home/circleci/project" ]]; then
+  # machine executor (binary tests)
+  workdir="/home/circleci/project"
+else
+  # docker executor (binary builds)
+  workdir="/"
+fi
+
+# It is very important that this stays in sync with binary_populate_env.sh
+if [[ "$OSTYPE" == "msys" ]]; then
+  # We need to make the paths as short as possible on Windows
+  export PYTORCH_ROOT="$workdir/p"
+  export BUILDER_ROOT="$workdir/b"
+else
+  export PYTORCH_ROOT="$workdir/pytorch"
+  export BUILDER_ROOT="$workdir/builder"
+fi
+
+# Try to extract PR number from branch if not already set
+if [[ -z "${CIRCLE_PR_NUMBER:-}" ]]; then
+  CIRCLE_PR_NUMBER="$(echo ${CIRCLE_BRANCH} | sed -E -n 's/pull\/([0-9]*).*/\1/p')"
+fi
+
+# Clone the Pytorch branch
+retry git clone https://github.com/pytorch/pytorch.git "$PYTORCH_ROOT"
+pushd "$PYTORCH_ROOT"
+if [[ -n "${CIRCLE_PR_NUMBER:-}" ]]; then
+  # "smoke" binary build on PRs
+  git fetch --force origin "pull/${CIRCLE_PR_NUMBER}/head:remotes/origin/pull/${CIRCLE_PR_NUMBER}"
+  git reset --hard "$CIRCLE_SHA1"
+  git checkout -q -B "$CIRCLE_BRANCH"
+  git reset --hard "$CIRCLE_SHA1"
+elif [[ -n "${CIRCLE_SHA1:-}" ]]; then
+  # Scheduled workflows & "smoke" binary build on trunk on PR merges
+  DEFAULT_BRANCH="$(git remote show $CIRCLE_REPOSITORY_URL | awk '/HEAD branch/ {print $NF}')"
+  git reset --hard "$CIRCLE_SHA1"
+  git checkout -q -B $DEFAULT_BRANCH
+else
+  echo "Can't tell what to checkout"
+  exit 1
+fi
+retry git submodule update --init --recursive
+echo "Using Pytorch from "
+git --no-pager log --max-count 1
+popd
+
+# Clone the Builder main repo
+retry git clone -q https://github.com/pytorch/builder.git "$BUILDER_ROOT"
+pushd "$BUILDER_ROOT"
+echo "Using builder from "
+git --no-pager log --max-count 1
+popd

.circleci/scripts/binary_install_miniconda.sh

@@ -0,0 +1,44 @@
+#!/bin/bash
+
+set -eux -o pipefail
+
+# This step runs on multiple executors with different envfile locations
+if [[ "$(uname)" == Darwin ]]; then
+  envfile="/Users/distiller/project/env"
+elif [[ -d "/home/circleci/project" ]]; then
+  # machine executor (binary tests)
+  envfile="/home/circleci/project/env"
+else
+  # docker executor (binary builds)
+  envfile="/env"
+fi
+
+# TODO this is super hacky and ugly. Basically, the binary_update_html job does
+# not have an env file, since it does not call binary_populate_env.sh, since it
+# does not have a BUILD_ENVIRONMENT. So for this one case, which we detect by a
+# lack of an env file, we manually export the environment variables that we
+# need to install miniconda
+if [[ ! -f "$envfile" ]]; then
+  MINICONDA_ROOT="/home/circleci/project/miniconda"
+  workdir="/home/circleci/project"
+  retry () {
+      $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
+  }
+  export -f retry
+else
+  source "$envfile"
+fi
+
+conda_sh="$workdir/install_miniconda.sh"
+if [[ "$(uname)" == Darwin ]]; then
+  curl --retry 3 --retry-all-errors -o "$conda_sh" https://repo.anaconda.com/miniconda/Miniconda3-py39_4.12.0-MacOSX-x86_64.sh
+else
+  curl --retry 3 --retry-all-errors -o "$conda_sh" https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
+fi
+chmod +x "$conda_sh"
+"$conda_sh" -b -p "$MINICONDA_ROOT"
+rm -f "$conda_sh"
+
+# We can't actually add miniconda to the PATH in the envfile, because that
+# breaks 'unbuffer' in Mac jobs. This is probably because conda comes with
+# a tclsh, which then gets inserted before the tclsh needed in /usr/bin