Enable graph deduplication

.ci/aarch64_linux/aarch64_ci_build.sh

@@ -20,7 +20,7 @@ cd /
 # on the mounted pytorch repo
 git config --global --add safe.directory /pytorch
 pip install -r /pytorch/requirements.txt
-pip install auditwheel==6.2.0
+pip install auditwheel
 if [ "$DESIRED_CUDA" = "cpu" ]; then
     echo "BASE_CUDA_VERSION is not set. Building cpu wheel."
     #USE_PRIORITIZED_TEXT_FOR_LD for enable linker script optimization https://github.com/pytorch/pytorch/pull/121975/files

.ci/aarch64_linux/aarch64_wheel_ci_build.py

@@ -99,14 +99,10 @@ def update_wheel(wheel_path, desired_cuda) -> None:
         if "126" in desired_cuda:
             libs_to_copy += [
                 "/usr/local/cuda/lib64/libnvrtc-builtins.so.12.6",
-                "/usr/local/cuda/lib64/libcufile.so.0",
-                "/usr/local/cuda/lib64/libcufile_rdma.so.1",
             ]
         elif "128" in desired_cuda:
             libs_to_copy += [
                 "/usr/local/cuda/lib64/libnvrtc-builtins.so.12.8",
-                "/usr/local/cuda/lib64/libcufile.so.0",
-                "/usr/local/cuda/lib64/libcufile_rdma.so.1",
             ]
     else:
         libs_to_copy += [
@@ -136,9 +132,6 @@ def complete_wheel(folder: str) -> str:
     """
     wheel_name = list_dir(f"/{folder}/dist")[0]
 
-    # Please note for cuda we don't run auditwheel since we use custom script to package
-    # the cuda dependencies to the wheel file using update_wheel() method.
-    # However we need to make sure filename reflects the correct Manylinux platform.
     if "pytorch" in folder and not enable_cuda:
         print("Repairing Wheel with AuditWheel")
         check_call(["auditwheel", "repair", f"dist/{wheel_name}"], cwd=folder)
@@ -150,14 +143,7 @@ def complete_wheel(folder: str) -> str:
             f"/{folder}/dist/{repaired_wheel_name}",
         )
     else:
-        repaired_wheel_name = wheel_name.replace(
-            "linux_aarch64", "manylinux_2_28_aarch64"
-        )
-        print(f"Renaming {wheel_name} wheel to {repaired_wheel_name}")
-        os.rename(
-            f"/{folder}/dist/{wheel_name}",
-            f"/{folder}/dist/{repaired_wheel_name}",
-        )
+        repaired_wheel_name = wheel_name
 
     print(f"Copying {repaired_wheel_name} to artifacts")
     shutil.copy2(
@@ -218,7 +204,7 @@ if __name__ == "__main__":
         else:
             build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version}.dev{build_date} PYTORCH_BUILD_NUMBER=1 "
     elif branch.startswith(("v1.", "v2.")):
-        build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1 : branch.find('-')]} PYTORCH_BUILD_NUMBER=1 "
+        build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1:branch.find('-')]} PYTORCH_BUILD_NUMBER=1 "
 
     if enable_mkldnn:
         build_ArmComputeLibrary()

.ci/aarch64_linux/build_aarch64_wheel.py

@@ -19,11 +19,13 @@ import boto3
 
 # AMI images for us-east-1, change the following based on your ~/.aws/config
 os_amis = {
+    "ubuntu18_04": "ami-078eece1d8119409f",  # login_name: ubuntu
     "ubuntu20_04": "ami-052eac90edaa9d08f",  # login_name: ubuntu
     "ubuntu22_04": "ami-0c6c29c5125214c77",  # login_name: ubuntu
     "redhat8": "ami-0698b90665a2ddcf1",  # login_name: ec2-user
 }
 
+ubuntu18_04_ami = os_amis["ubuntu18_04"]
 ubuntu20_04_ami = os_amis["ubuntu20_04"]
 
 
@@ -657,6 +659,18 @@ def configure_system(
             "sudo apt-get install -y python3-dev python3-yaml python3-setuptools python3-wheel python3-pip"
         )
     host.run_cmd("pip3 install dataclasses typing-extensions")
+    # Install and switch to gcc-8 on Ubuntu-18.04
+    if not host.using_docker() and host.ami == ubuntu18_04_ami and compiler == "gcc-8":
+        host.run_cmd("sudo apt-get install -y g++-8 gfortran-8")
+        host.run_cmd(
+            "sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-8 100"
+        )
+        host.run_cmd(
+            "sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-8 100"
+        )
+        host.run_cmd(
+            "sudo update-alternatives --install /usr/bin/gfortran gfortran /usr/bin/gfortran-8 100"
+        )
     if not use_conda:
         print("Installing Cython + numpy from PyPy")
         host.run_cmd("sudo pip3 install Cython")
@@ -747,7 +761,7 @@ def start_build(
         version = host.check_output("cat pytorch/version.txt").strip()[:-2]
         build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version}.dev{build_date} PYTORCH_BUILD_NUMBER=1"
     if branch.startswith(("v1.", "v2.")):
-        build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1 : branch.find('-')]} PYTORCH_BUILD_NUMBER=1"
+        build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1:branch.find('-')]} PYTORCH_BUILD_NUMBER=1"
     if host.using_docker():
         build_vars += " CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000"
     if enable_mkldnn:
@@ -1012,7 +1026,7 @@ if __name__ == "__main__":
         install_condaforge_python(host, args.python_version)
         sys.exit(0)
 
-    python_version = args.python_version if args.python_version is not None else "3.9"
+    python_version = args.python_version if args.python_version is not None else "3.8"
 
     if args.use_torch_from_pypi:
         configure_system(host, compiler=args.compiler, python_version=python_version)

.ci/docker/README.md

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

.ci/docker/almalinux/Dockerfile

@@ -44,9 +44,6 @@ FROM base as cuda
 ARG CUDA_VERSION=12.4
 RUN rm -rf /usr/local/cuda-*
 ADD ./common/install_cuda.sh install_cuda.sh
-COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
 ENV CUDA_HOME=/usr/local/cuda-${CUDA_VERSION}
 # Preserve CUDA_VERSION for the builds
 ENV CUDA_VERSION=${CUDA_VERSION}

.ci/docker/almalinux/build.sh

@@ -1,60 +1,82 @@
 #!/usr/bin/env bash
 # Script used only in CD pipeline
 
-set -exou pipefail
+set -eou pipefail
 
 image="$1"
 shift
 
 if [ -z "${image}" ]; then
-  echo "Usage: $0 IMAGENAME:ARCHTAG"
+  echo "Usage: $0 IMAGE"
   exit 1
 fi
 
-# Go from imagename:tag to tag
-DOCKER_TAG_PREFIX=$(echo "${image}" | awk -F':' '{print $2}')
+DOCKER_IMAGE_NAME="pytorch/${image}"
 
-CUDA_VERSION=""
-if [[ "${DOCKER_TAG_PREFIX}" == cuda* ]]; then
-    # extract cuda version from image name and tag.  e.g. manylinux2_28-builder:cuda12.8 returns 12.8
-    CUDA_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'cuda' '{print $2}')
-fi
-
-case ${DOCKER_TAG_PREFIX} in
-  cpu)
-    BASE_TARGET=base
-    ;;
-  cuda*)
-    BASE_TARGET=cuda${CUDA_VERSION}
-    ;;
-  *)
-    echo "ERROR: Unknown docker tag ${DOCKER_TAG_PREFIX}"
-    exit 1
-    ;;
-esac
-
-# TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
-# is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
-sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
-sudo systemctl daemon-reload
-sudo systemctl restart docker
 
 export DOCKER_BUILDKIT=1
 TOPDIR=$(git rev-parse --show-toplevel)
-tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
 
-docker build \
-  --target final \
-  --progress plain \
-  --build-arg "BASE_TARGET=${BASE_TARGET}" \
-  --build-arg "CUDA_VERSION=${CUDA_VERSION}" \
-  --build-arg "DEVTOOLSET_VERSION=11" \
-  -t ${tmp_tag} \
-  $@ \
-  -f "${TOPDIR}/.ci/docker/almalinux/Dockerfile" \
-  ${TOPDIR}/.ci/docker/
+CUDA_VERSION=${CUDA_VERSION:-12.1}
 
-if [ -n "${CUDA_VERSION}" ]; then
+case ${CUDA_VERSION} in
+  cpu)
+    BASE_TARGET=base
+    DOCKER_TAG=cpu
+    ;;
+  all)
+    BASE_TARGET=all_cuda
+    DOCKER_TAG=latest
+    ;;
+  *)
+    BASE_TARGET=cuda${CUDA_VERSION}
+    DOCKER_TAG=cuda${CUDA_VERSION}
+    ;;
+esac
+
+
+(
+  set -x
+  # TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
+  # is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
+  sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
+  sudo systemctl daemon-reload
+  sudo systemctl restart docker
+
+  docker build \
+    --target final \
+    --progress plain \
+    --build-arg "BASE_TARGET=${BASE_TARGET}" \
+    --build-arg "CUDA_VERSION=${CUDA_VERSION}" \
+    --build-arg "DEVTOOLSET_VERSION=11" \
+    -t ${DOCKER_IMAGE_NAME} \
+    $@ \
+    -f "${TOPDIR}/.ci/docker/almalinux/Dockerfile" \
+    ${TOPDIR}/.ci/docker/
+)
+
+if [[ "${DOCKER_TAG}" =~ ^cuda* ]]; then
   # Test that we're using the right CUDA compiler
-  docker run --rm "${tmp_tag}" nvcc --version | grep "cuda_${CUDA_VERSION}"
+  (
+    set -x
+    docker run --rm "${DOCKER_IMAGE_NAME}" nvcc --version | grep "cuda_${CUDA_VERSION}"
+  )
+fi
+
+GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
+GIT_BRANCH_NAME=${GITHUB_REF##*/}
+GIT_COMMIT_SHA=${GITHUB_SHA:-$(git rev-parse HEAD)}
+DOCKER_IMAGE_BRANCH_TAG=${DOCKER_IMAGE_NAME}-${GIT_BRANCH_NAME}
+DOCKER_IMAGE_SHA_TAG=${DOCKER_IMAGE_NAME}-${GIT_COMMIT_SHA}
+if [[ "${WITH_PUSH:-}" == true ]]; then
+  (
+    set -x
+    docker push "${DOCKER_IMAGE_NAME}"
+    if [[ -n ${GITHUB_REF} ]]; then
+        docker tag ${DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_BRANCH_TAG}
+        docker tag ${DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_SHA_TAG}
+        docker push "${DOCKER_IMAGE_BRANCH_TAG}"
+        docker push "${DOCKER_IMAGE_SHA_TAG}"
+    fi
+  )
 fi

.ci/docker/build.sh

@@ -1,8 +1,4 @@
 #!/bin/bash
-# The purpose of this script is to:
-# 1. Extract the set of parameters to be used for a docker build based on the provided image name.
-# 2. Run docker build with the parameters found in step 1.
-# 3. Run the built image and print out the expected and actual versions of packages installed.
 
 set -ex
 
@@ -99,11 +95,13 @@ fi
 # configuration, so we hardcode everything here rather than do it
 # from scratch
 case "$image" in
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc11)
-    CUDA_VERSION=12.6.3
+  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.4.1
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
@@ -116,6 +114,8 @@ case "$image" in
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
@@ -129,6 +129,8 @@ case "$image" in
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
@@ -142,57 +144,8 @@ case "$image" in
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.13
     GCC_VERSION=9
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.12
-    GCC_VERSION=9
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.13
-    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
@@ -206,6 +159,8 @@ case "$image" in
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
@@ -216,6 +171,8 @@ case "$image" in
   pytorch-linux-focal-py3-clang10-onnx)
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=10
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     ONNX=yes
@@ -223,20 +180,30 @@ case "$image" in
   pytorch-linux-focal-py3.9-clang10)
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=10
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
+    VULKAN_SDK_VERSION=1.2.162.1
+    SWIFTSHADER=yes
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
   pytorch-linux-focal-py3.11-clang10)
     ANACONDA_PYTHON_VERSION=3.11
     CLANG_VERSION=10
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
+    VULKAN_SDK_VERSION=1.2.162.1
+    SWIFTSHADER=yes
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
   pytorch-linux-focal-py3.9-gcc9)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     TRITON=yes
@@ -244,6 +211,8 @@ case "$image" in
   pytorch-linux-focal-rocm-n-1-py3)
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     ROCM_VERSION=6.2.4
     NINJA_VERSION=1.9.0
@@ -257,6 +226,8 @@ case "$image" in
   pytorch-linux-focal-rocm-n-py3)
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     ROCM_VERSION=6.3
     NINJA_VERSION=1.9.0
@@ -270,6 +241,8 @@ case "$image" in
   pytorch-linux-jammy-xpu-2024.0-py3)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     XPU_VERSION=0.5
     NINJA_VERSION=1.9.0
@@ -279,6 +252,8 @@ case "$image" in
   pytorch-linux-jammy-xpu-2025.0-py3)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     XPU_VERSION=2025.0
     NINJA_VERSION=1.9.0
@@ -288,6 +263,8 @@ case "$image" in
     pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     CONDA_CMAKE=yes
@@ -300,12 +277,16 @@ case "$image" in
     CUDA_VERSION=11.8
     CUDNN_VERSION=9
     CLANG_VERSION=12
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     TRITON=yes
     ;;
   pytorch-linux-jammy-py3-clang12-asan)
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=12
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     TRITON=yes
@@ -325,6 +306,8 @@ case "$image" in
   pytorch-linux-jammy-py3.9-gcc11)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     CONDA_CMAKE=yes
@@ -339,7 +322,7 @@ case "$image" in
     EXECUTORCH=yes
     ;;
   pytorch-linux-jammy-py3.12-halide)
-    CUDA_VERSION=12.6
+    CUDA_VERSION=12.4
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
     CONDA_CMAKE=yes
@@ -347,7 +330,7 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-jammy-py3.12-triton-cpu)
-    CUDA_VERSION=12.6
+    CUDA_VERSION=12.4
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
     CONDA_CMAKE=yes
@@ -357,18 +340,20 @@ case "$image" in
     # TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
     # We will need to update mypy version eventually, but that's for another day. The task
     # would be to upgrade mypy to 1.0.0 with Python 3.11
-    PYTHON_VERSION=3.9
-    PIP_CMAKE=yes
+    ANACONDA_PYTHON_VERSION=3.9
+    CONDA_CMAKE=yes
     ;;
   pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
-    PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.9
     CUDA_VERSION=11.8
-    PIP_CMAKE=yes
+    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 llvm src build install because the current version
@@ -379,6 +364,8 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=11
     ACL=yes
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     # snadampal: skipping llvm src build install because the current version
@@ -388,6 +375,8 @@ case "$image" in
     ;;
   *)
     # Catch-all for builds that are not hardcoded.
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     echo "image '$image' did not match an existing build configuration"
     if [[ "$image" == *py* ]]; then
@@ -436,20 +425,14 @@ if [[ "$image" == *cuda*  && ${OS} == "ubuntu" ]]; then
   fi
 fi
 
-no_cache_flag=""
-progress_flag=""
-# Do not use cache and progress=plain when in CI
-if [[ -n "${CI:-}" ]]; then
-  no_cache_flag="--no-cache"
-  progress_flag="--progress=plain"
-fi
-
 # Build image
 docker build \
-       ${no_cache_flag} \
-       ${progress_flag} \
+       --no-cache \
+       --progress=plain \
        --build-arg "BUILD_ENVIRONMENT=${image}" \
+       --build-arg "PROTOBUF=${PROTOBUF:-}" \
        --build-arg "LLVMDEV=${LLVMDEV:-}" \
+       --build-arg "DB=${DB:-}" \
        --build-arg "VISION=${VISION:-}" \
        --build-arg "UBUNTU_VERSION=${UBUNTU_VERSION}" \
        --build-arg "CENTOS_VERSION=${CENTOS_VERSION}" \
@@ -457,12 +440,13 @@ docker build \
        --build-arg "GLIBC_VERSION=${GLIBC_VERSION}" \
        --build-arg "CLANG_VERSION=${CLANG_VERSION}" \
        --build-arg "ANACONDA_PYTHON_VERSION=${ANACONDA_PYTHON_VERSION}" \
-       --build-arg "PYTHON_VERSION=${PYTHON_VERSION}" \
        --build-arg "GCC_VERSION=${GCC_VERSION}" \
        --build-arg "CUDA_VERSION=${CUDA_VERSION}" \
        --build-arg "CUDNN_VERSION=${CUDNN_VERSION}" \
        --build-arg "TENSORRT_VERSION=${TENSORRT_VERSION}" \
        --build-arg "GRADLE_VERSION=${GRADLE_VERSION}" \
+       --build-arg "VULKAN_SDK_VERSION=${VULKAN_SDK_VERSION}" \
+       --build-arg "SWIFTSHADER=${SWIFTSHADER}" \
        --build-arg "CMAKE_VERSION=${CMAKE_VERSION:-}" \
        --build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
        --build-arg "KATEX=${KATEX:-}" \
@@ -472,7 +456,6 @@ docker build \
        --build-arg "UCX_COMMIT=${UCX_COMMIT}" \
        --build-arg "UCC_COMMIT=${UCC_COMMIT}" \
        --build-arg "CONDA_CMAKE=${CONDA_CMAKE}" \
-       --build-arg "PIP_CMAKE=${PIP_CMAKE}" \
        --build-arg "TRITON=${TRITON}" \
        --build-arg "TRITON_CPU=${TRITON_CPU}" \
        --build-arg "ONNX=${ONNX}" \
@@ -498,7 +481,7 @@ docker build \
 UBUNTU_VERSION=$(echo ${UBUNTU_VERSION} | sed 's/-rc$//')
 
 function drun() {
-  docker run --rm "$tmp_tag" "$@"
+  docker run --rm "$tmp_tag" $*
 }
 
 if [[ "$OS" == "ubuntu" ]]; then
@@ -546,14 +529,3 @@ if [ -n "$KATEX" ]; then
     exit 1
   fi
 fi
-
-HAS_TRITON=$(drun python -c "import triton" > /dev/null 2>&1 && echo "yes" || echo "no")
-if [[ -n "$TRITON" || -n "$TRITON_CPU" ]]; then
-  if [ "$HAS_TRITON" = "no" ]; then
-    echo "expecting triton to be installed, but it is not"
-    exit 1
-  fi
-elif [ "$HAS_TRITON" = "yes" ]; then
-  echo "expecting triton to not be installed, but it is"
-  exit 1
-fi

.ci/docker/centos-rocm/Dockerfile

@@ -48,6 +48,20 @@ COPY ./common/install_conda.sh install_conda.sh
 COPY ./common/common_utils.sh common_utils.sh
 RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
 
+# (optional) Install protobuf for ONNX
+ARG PROTOBUF
+COPY ./common/install_protobuf.sh install_protobuf.sh
+RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
+RUN rm install_protobuf.sh
+ENV INSTALLED_PROTOBUF ${PROTOBUF}
+
+# (optional) Install database packages like LMDB and LevelDB
+ARG DB
+COPY ./common/install_db.sh install_db.sh
+RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
+RUN rm install_db.sh
+ENV INSTALLED_DB ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -61,7 +75,7 @@ COPY ./common/install_rocm.sh install_rocm.sh
 RUN bash ./install_rocm.sh
 RUN rm install_rocm.sh
 COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
-RUN bash ./install_rocm_magma.sh ${ROCM_VERSION}
+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

.ci/docker/ci_commit_pins/executorch.txt

@@ -1 +1 @@
-a325c56864c5b25630c1ebda03c8f16a96a02a19
+5e4d6b6380d575e48e37e9d987fded4ec588e7bc

.ci/docker/ci_commit_pins/nccl-cu12.txt

@@ -1 +1 @@
-v2.26.2-1
+v2.25.1-1

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

@@ -1 +1 @@
-0bcc8265e677e5321606a3311bf71470f14456a8
+e98b6fcb8df5b44eb0d0addb6767c573d37ba024

.ci/docker/ci_commit_pins/triton.txt

@@ -1 +1 @@
-96316ce50fade7e209553aba4898cd9b82aab83b
+4b3bb1f8da0ded6ccd572dd1358ef45af5a1befe

.ci/docker/common/install_base.sh

@@ -37,7 +37,7 @@ install_ubuntu() {
   if [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "11.8"* ]]; then
     maybe_libnccl_dev="libnccl2=2.15.5-1+cuda11.8 libnccl-dev=2.15.5-1+cuda11.8 --allow-downgrades --allow-change-held-packages"
   elif [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "12.4"* ]]; then
-    maybe_libnccl_dev="libnccl2=2.26.2-1+cuda12.4 libnccl-dev=2.26.2-1+cuda12.4 --allow-downgrades --allow-change-held-packages"
+    maybe_libnccl_dev="libnccl2=2.25.1-1+cuda12.4 libnccl-dev=2.25.1-1+cuda12.4 --allow-downgrades --allow-change-held-packages"
   else
     maybe_libnccl_dev=""
   fi
@@ -99,6 +99,9 @@ install_centos() {
 
   ccache_deps="asciidoc docbook-dtds docbook-style-xsl libxslt"
   numpy_deps="gcc-gfortran"
+  # Note: protobuf-c-{compiler,devel} on CentOS are too old to be used
+  # for Caffe2. That said, we still install them to make sure the build
+  # system opts to build/use protoc and libprotobuf from third-party.
   yum install -y \
     $ccache_deps \
     $numpy_deps \

.ci/docker/common/install_clang.sh

@@ -4,10 +4,16 @@ set -ex
 
 if [ -n "$CLANG_VERSION" ]; then
 
-  if [[ $UBUNTU_VERSION == 22.04 ]]; then
+  if [[ $CLANG_VERSION == 9 && $UBUNTU_VERSION == 18.04 ]]; then
+    sudo apt-get update
+    # gpg-agent is not available by default on 18.04
+    sudo apt-get install  -y --no-install-recommends gpg-agent
+    wget --no-check-certificate -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add  -
+    apt-add-repository "deb http://apt.llvm.org/bionic/ llvm-toolchain-bionic-${CLANG_VERSION} main"
+  elif [[ $UBUNTU_VERSION == 22.04 ]]; then
     # work around ubuntu apt-get conflicts
     sudo apt-get -y -f install
-    wget --no-check-certificate -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
+    wget --no-check-certificate -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add  -
     if [[ $CLANG_VERSION == 18 ]]; then
       apt-add-repository "deb http://apt.llvm.org/jammy/ llvm-toolchain-jammy-18 main"
     fi
@@ -35,7 +41,7 @@ if [ -n "$CLANG_VERSION" ]; then
   # clang's packaging is a little messed up (the runtime libs aren't
   # added into the linker path), so give it a little help
   clang_lib=("/usr/lib/llvm-$CLANG_VERSION/lib/clang/"*"/lib/linux")
-  echo "$clang_lib" >/etc/ld.so.conf.d/clang.conf
+  echo "$clang_lib" > /etc/ld.so.conf.d/clang.conf
   ldconfig
 
   # Cleanup package manager

.ci/docker/common/install_conda.sh

@@ -62,11 +62,11 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
 
   # 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 --update-deps -c conda-forge
+  conda_install libstdcxx-ng=12.3.0 -c conda-forge
 
   # Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
   if [[ $(uname -m) == "aarch64" ]]; then
-    conda_install "openblas==0.3.29=*openmp*"
+    conda_install "openblas==0.3.28=*openmp*"
   else
     conda_install "mkl=2021.4.0 mkl-include=2021.4.0"
   fi
@@ -87,7 +87,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   # I.e. magma-cuda102 package corresponds to CUDA_VERSION=10.2 and CUDA_VERSION=10.2.89
   # Magma is installed from a tarball in the ossci-linux bucket into the conda env
   if [ -n "$CUDA_VERSION" ]; then
-    conda_run ${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION})
+    ${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION}) ${ANACONDA_PYTHON_VERSION}
   fi
 
   # Install some other packages, including those needed for Python test reporting

.ci/docker/common/install_cpython.sh

@@ -7,7 +7,7 @@ PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/hea
 GET_PIP_URL=https://bootstrap.pypa.io/get-pip.py
 
 # Python versions to be installed in /opt/$VERSION_NO
-CPYTHON_VERSIONS=${CPYTHON_VERSIONS:-"3.9.0 3.10.1 3.11.0 3.12.0 3.13.0 3.13.0t"}
+CPYTHON_VERSIONS=${CPYTHON_VERSIONS:-"3.8.1 3.9.0 3.10.1 3.11.0 3.12.0 3.13.0 3.13.0t"}
 
 function check_var {
     if [ -z "$1" ]; then

.ci/docker/common/install_cuda.sh

@@ -2,11 +2,46 @@
 
 set -ex
 
+NCCL_VERSION=v2.25.1-1
 CUDNN_VERSION=9.5.1.17
 
+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_062 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
+    tar xf libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
+    cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
+
+function install_cusparselt_063 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.3.2-archive.tar.xz
+    tar xf libcusparse_lt-linux-x86_64-0.6.3.2-archive.tar.xz
+    cp -a libcusparse_lt-linux-x86_64-0.6.3.2-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-x86_64-0.6.3.2-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
+
 function install_118 {
     CUDNN_VERSION=9.1.0.70
-    echo "Installing CUDA 11.8 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.4.0"
+    NCCL_VERSION=v2.21.5-1
+    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
@@ -24,16 +59,23 @@ function install_118 {
     cd ..
     rm -rf tmp_cudnn
 
-    CUDA_VERSION=11.8 bash install_nccl.sh
+    # 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
 
-    CUDA_VERSION=11.8 bash install_cusparselt.sh
+    install_cusparselt_040
 
     ldconfig
 }
 
 function install_124 {
   CUDNN_VERSION=9.1.0.70
-  echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.2"
+  echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.2"
   rm -rf /usr/local/cuda-12.4 /usr/local/cuda
   # install CUDA 12.4.1 in the same container
   wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run
@@ -51,15 +93,22 @@ function install_124 {
   cd ..
   rm -rf tmp_cudnn
 
-  CUDA_VERSION=12.4 bash install_nccl.sh
+  # 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
 
-  CUDA_VERSION=12.4 bash install_cusparselt.sh
+  install_cusparselt_062
 
   ldconfig
 }
 
 function install_126 {
-  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
+  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
   rm -rf /usr/local/cuda-12.6 /usr/local/cuda
   # install CUDA 12.6.3 in the same container
   wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run
@@ -77,9 +126,16 @@ function install_126 {
   cd ..
   rm -rf tmp_cudnn
 
-  CUDA_VERSION=12.6 bash install_nccl.sh
+  # 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
 
-  CUDA_VERSION=12.6 bash install_cusparselt.sh
+  install_cusparselt_063
 
   ldconfig
 }
@@ -184,8 +240,8 @@ function prune_126 {
 }
 
 function install_128 {
-  CUDNN_VERSION=9.8.0.87
-  echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
+  CUDNN_VERSION=9.7.1.26
+  echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
   rm -rf /usr/local/cuda-12.8 /usr/local/cuda
   # install CUDA 12.8.0 in the same container
   wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux.run
@@ -203,9 +259,16 @@ function install_128 {
   cd ..
   rm -rf tmp_cudnn
 
-  CUDA_VERSION=12.8 bash install_nccl.sh
+  # 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
 
-  CUDA_VERSION=12.8 bash install_cusparselt.sh
+  install_cusparselt_063
 
   ldconfig
 }

.ci/docker/common/install_cuda_aarch64.sh

@@ -3,10 +3,166 @@
 
 set -ex
 
-CUDNN_VERSION=9.8.0.87
+NCCL_VERSION=v2.21.5-1
+CUDNN_VERSION=9.5.1.17
+
+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-sbsa/libcusparse_lt-linux-sbsa-0.6.2.3-archive.tar.xz
+    tar xf libcusparse_lt-linux-sbsa-0.6.2.3-archive.tar.xz
+    cp -a libcusparse_lt-linux-sbsa-0.6.2.3-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-sbsa-0.6.2.3-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
+
+function install_cusparselt_063 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-sbsa/libcusparse_lt-linux-sbsa-0.6.3.2-archive.tar.xz
+    tar xf libcusparse_lt-linux-sbsa-0.6.3.2-archive.tar.xz
+    cp -a libcusparse_lt-linux-sbsa-0.6.3.2-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-sbsa-0.6.3.2-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
+
+function install_124 {
+  CUDNN_VERSION=9.1.0.70
+  echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.2"
+  rm -rf /usr/local/cuda-12.4 /usr/local/cuda
+  # install CUDA 12.4.1 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux_sbsa.run
+  chmod +x cuda_12.4.1_550.54.15_linux_sbsa.run
+  ./cuda_12.4.1_550.54.15_linux_sbsa.run --toolkit --silent
+  rm -f cuda_12.4.1_550.54.15_linux_sbsa.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
+
+  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-sbsa/cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
+
+  # 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 ${NCCL_VERSION} --depth 1 https://github.com/NVIDIA/nccl.git
+  cd nccl && make -j src.build
+  cp -a build/include/* /usr/local/cuda/include/
+  cp -a build/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf nccl
+
+  install_cusparselt_063
+
+  ldconfig
+}
+
+function prune_124 {
+  echo "Pruning CUDA 12.4"
+  #####################################################################################
+  # CUDA 12.4 prune static libs
+  #####################################################################################
+  export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
+  export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
+
+  export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+  export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+
+  if [[ -n "$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 12.4 prune visual tools
+  #####################################################################################
+  export CUDA_BASE="/usr/local/cuda-12.4/"
+  rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.1.0 $CUDA_BASE/nsight-systems-2023.4.4/
+}
+
+function install_126 {
+  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
+  rm -rf /usr/local/cuda-12.6 /usr/local/cuda
+  # install CUDA 12.6.3 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux_sbsa.run
+  chmod +x cuda_12.6.3_560.35.05_linux_sbsa.run
+  ./cuda_12.6.3_560.35.05_linux_sbsa.run --toolkit --silent
+  rm -f cuda_12.6.3_560.35.05_linux_sbsa.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.6 /usr/local/cuda
+
+  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-sbsa/cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
+
+  # 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 ${NCCL_VERSION} --depth 1 https://github.com/NVIDIA/nccl.git
+  cd nccl && make -j src.build
+  cp -a build/include/* /usr/local/cuda/include/
+  cp -a build/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf nccl
+
+  install_cusparselt_063
+
+  ldconfig
+}
+
+function prune_126 {
+  echo "Pruning CUDA 12.6"
+  #####################################################################################
+  # CUDA 12.6 prune static libs
+  #####################################################################################
+  export NVPRUNE="/usr/local/cuda-12.6/bin/nvprune"
+  export CUDA_LIB_DIR="/usr/local/cuda-12.6/lib64"
+
+  export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+  export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+
+  if [[ -n "$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 12.6 prune visual tools
+  #####################################################################################
+  export CUDA_BASE="/usr/local/cuda-12.6/"
+  rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.3.2 $CUDA_BASE/nsight-systems-2024.5.1/
+}
 
 function install_128 {
-  echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
+  CUDNN_VERSION=9.7.1.26
+  echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
   rm -rf /usr/local/cuda-12.8 /usr/local/cuda
   # install CUDA 12.8.0 in the same container
   wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux_sbsa.run
@@ -24,9 +180,16 @@ function install_128 {
   cd ..
   rm -rf tmp_cudnn
 
-  CUDA_VERSION=12.8 bash install_nccl.sh
+  # 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
 
-  CUDA_VERSION=12.8 bash install_cusparselt.sh
+  install_cusparselt_063
 
   ldconfig
 }
@@ -35,6 +198,10 @@ function install_128 {
 while test $# -gt 0
 do
     case "$1" in
+    12.4) install_124; prune_124
+        ;;
+    12.6) install_126; prune_126
+        ;;
     12.8) install_128;
         ;;
     *) echo "bad argument $1"; exit 1

.ci/docker/common/install_cudnn.sh

@@ -5,7 +5,7 @@ if [[ -n "${CUDNN_VERSION}" ]]; then
     mkdir tmp_cudnn
     pushd tmp_cudnn
     if [[ ${CUDA_VERSION:0:4} == "12.8" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-9.8.0.87_cuda12-archive"
+        CUDNN_NAME="cudnn-linux-x86_64-9.7.1.26_cuda12-archive"
     elif [[ ${CUDA_VERSION:0:4} == "12.6" ]]; then
         CUDNN_NAME="cudnn-linux-x86_64-9.5.1.17_cuda12-archive"
     elif [[ ${CUDA_VERSION:0:2} == "12" ]]; then

.ci/docker/common/install_db.sh

@@ -0,0 +1,38 @@
+#!/bin/bash
+
+set -ex
+
+install_ubuntu() {
+  apt-get update
+
+  # Cleanup
+  apt-get autoclean && apt-get clean
+  rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
+}
+
+install_centos() {
+  # Need EPEL for many packages we depend on.
+  # See http://fedoraproject.org/wiki/EPEL
+  yum --enablerepo=extras install -y epel-release
+
+  # Cleanup
+  yum clean all
+  rm -rf /var/cache/yum
+  rm -rf /var/lib/yum/yumdb
+  rm -rf /var/lib/yum/history
+}
+
+# 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_executorch.sh

@@ -50,9 +50,10 @@ setup_executorch() {
   pushd executorch
 
   export PYTHON_EXECUTABLE=python
-  export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
+  export EXECUTORCH_BUILD_PYBIND=ON
+  export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
 
-  as_jenkins .ci/scripts/setup-linux.sh --build-tool cmake || true
+  as_jenkins .ci/scripts/setup-linux.sh cmake || true
   popd
 }
 

.ci/docker/common/install_halide.sh

@@ -35,9 +35,7 @@ git clone https://github.com/halide/Halide.git
 pushd Halide
 git checkout ${COMMIT} && git submodule update --init --recursive
 pip_install -r requirements.txt
-# NOTE: pybind has a requirement for cmake > 3.5 so set the minimum cmake version here with a flag
-#       Context: https://github.com/pytorch/pytorch/issues/150420
-cmake -G Ninja -DCMAKE_POLICY_VERSION_MINIMUM=3.5 -DCMAKE_BUILD_TYPE=Release -S . -B build
+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}

.ci/docker/common/install_linter.sh

@@ -2,6 +2,8 @@
 
 set -ex
 
+source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
+
 if [ -n "${UBUNTU_VERSION}" ]; then
   apt update
   apt-get install -y clang doxygen git graphviz nodejs npm libtinfo5
@@ -13,8 +15,8 @@ chown -R jenkins pytorch
 
 pushd pytorch
 # Install all linter dependencies
-pip install -r requirements.txt
-lintrunner init
+pip_install -r requirements.txt
+conda_run lintrunner init
 
 # Cache .lintbin directory as part of the Docker image
 cp -r .lintbin /tmp

.ci/docker/common/install_magma_conda.sh

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

.ci/docker/common/install_nccl.sh

@@ -1,26 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-NCCL_VERSION=""
-if [[ ${CUDA_VERSION:0:2} == "11" ]]; then
-  NCCL_VERSION=$(cat ci_commit_pins/nccl-cu11.txt)
-elif [[ ${CUDA_VERSION:0:2} == "12" ]]; then
-  NCCL_VERSION=$(cat ci_commit_pins/nccl-cu12.txt)
-else
-  echo "Unexpected CUDA_VERSION ${CUDA_VERSION}"
-  exit 1
-fi
-
-if [[ -n "${NCCL_VERSION}" ]]; then
-  # 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
-  pushd nccl
-  make -j src.build
-  cp -a build/include/* /usr/local/cuda/include/
-  cp -a build/lib/* /usr/local/cuda/lib64/
-  popd
-  rm -rf nccl
-  ldconfig
-fi

.ci/docker/common/install_ninja.sh

@@ -4,15 +4,10 @@ set -ex
 
 [ -n "$NINJA_VERSION" ]
 
-arch=$(uname -m)
-if [ "$arch" == "aarch64" ]; then
-    url="https://github.com/ninja-build/ninja/releases/download/v${NINJA_VERSION}/ninja-linux-aarch64.zip"
-else
-    url="https://github.com/ninja-build/ninja/releases/download/v${NINJA_VERSION}/ninja-linux.zip"
-fi
+url="https://github.com/ninja-build/ninja/releases/download/v${NINJA_VERSION}/ninja-linux.zip"
 
 pushd /tmp
 wget --no-verbose --output-document=ninja-linux.zip "$url"
 unzip ninja-linux.zip -d /usr/local/bin
 rm -f ninja-linux.zip
-popd
+popd

.ci/docker/common/install_onnx.sh

@@ -32,7 +32,7 @@ pip_install coloredlogs packaging
 
 pip_install onnxruntime==1.18.1
 pip_install onnx==1.17.0
-pip_install onnxscript==0.2.2 --no-deps
+pip_install onnxscript==0.1.0 --no-deps
 # required by onnxscript
 pip_install ml_dtypes
 

.ci/docker/common/install_openblas.sh

@@ -4,7 +4,7 @@
 set -ex
 
 cd /
-git clone https://github.com/OpenMathLib/OpenBLAS.git -b v0.3.29 --depth 1 --shallow-submodules
+git clone https://github.com/OpenMathLib/OpenBLAS.git -b v0.3.28 --depth 1 --shallow-submodules
 
 
 OPENBLAS_BUILD_FLAGS="

.ci/docker/common/install_protobuf.sh

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

.ci/docker/common/install_python.sh

@@ -1,18 +0,0 @@
-#!/bin/bash
-set -ex
-
-apt-get update
-# Use deadsnakes in case we need an older python version
-sudo add-apt-repository ppa:deadsnakes/ppa
-apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python3-pip python${PYTHON_VERSION}-venv
-
-# Use a venv because uv and some other package managers don't support --user install
-ln -s /usr/bin/python${PYTHON_VERSION} /usr/bin/python
-python -m venv /var/lib/jenkins/ci_env
-source /var/lib/jenkins/ci_env/bin/activate
-
-python -mpip install --upgrade pip
-python -mpip install -r /opt/requirements-ci.txt
-if [ -n "${PIP_CMAKE}" ]; then
-  python -mpip install cmake==3.31.6
-fi

.ci/docker/common/install_rocm.sh

@@ -8,6 +8,10 @@ ver() {
 
 install_ubuntu() {
     apt-get update
+    if [[ $UBUNTU_VERSION == 18.04 ]]; then
+      # gpg-agent is not available by default on 18.04
+      apt-get install -y --no-install-recommends gpg-agent
+    fi
     if [[ $UBUNTU_VERSION == 20.04 ]]; then
       # gpg-agent is not available by default on 20.04
       apt-get install -y --no-install-recommends gpg-agent
@@ -19,13 +23,6 @@ install_ubuntu() {
     apt-get install -y libc++1
     apt-get install -y libc++abi1
 
-    # Make sure rocm packages from repo.radeon.com have highest priority
-    cat << EOF > /etc/apt/preferences.d/rocm-pin-600
-Package: *
-Pin: release o=repo.radeon.com
-Pin-Priority: 600
-EOF
-
     # Add amdgpu repository
     UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
     echo "deb [arch=amd64] https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list

.ci/docker/common/install_rocm_drm.sh

@@ -115,7 +115,7 @@ index a5007ffc..13fa07fc 100644
  	if (!fp) {
 -		fprintf(stderr, "%s: %s\n", AMDGPU_ASIC_ID_TABLE,
 -			strerror(errno));
-+		//fprintf(stderr, "amdgpu.ids: No such file or directory\n");
++		fprintf(stderr, "amdgpu.ids: No such file or directory\n");
  		return;
  	}
 

.ci/docker/common/install_rocm_magma.sh

@@ -1,32 +1,50 @@
-#!/usr/bin/env bash
-# Script used only in CD pipeline
+#!/bin/bash
+# Script used in CI and CD pipeline
 
-set -eou pipefail
+set -ex
 
-function do_install() {
-    rocm_version=$1
-    rocm_version_nodot=${1//./}
+# Magma build scripts need `python`
+ln -sf /usr/bin/python3 /usr/bin/python
 
-    # Version 2.7.2 + ROCm related updates
-    MAGMA_VERSION=a1625ff4d9bc362906bd01f805dbbe12612953f6
-    magma_archive="magma-rocm${rocm_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
+ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
+case "$ID" in
+  almalinux)
+    yum install -y gcc-gfortran
+    ;;
+  *)
+    echo "No preinstalls to build magma..."
+    ;;
+esac
 
-    rocm_dir="/opt/rocm"
-    (
-        set -x
-        tmp_dir=$(mktemp -d)
-        pushd ${tmp_dir}
-        curl -OLs https://ossci-linux.s3.us-east-1.amazonaws.com/${magma_archive}
-        if tar -xvf "${magma_archive}"
-        then
-            mkdir -p "${rocm_dir}/magma"
-            mv include "${rocm_dir}/magma/include"
-            mv lib "${rocm_dir}/magma/lib"
-        else
-            echo "${magma_archive} not found, skipping magma install"
-        fi
-        popd
-    )
-}
+MKLROOT=${MKLROOT:-/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION}
 
-do_install $1
+# "install" hipMAGMA into /opt/rocm/magma by copying after build
+git clone https://bitbucket.org/icl/magma.git
+pushd magma
+
+# Version 2.7.2 + ROCm related updates
+git checkout a1625ff4d9bc362906bd01f805dbbe12612953f6
+
+cp make.inc-examples/make.inc.hip-gcc-mkl make.inc
+echo 'LIBDIR += -L$(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 'DEVCCFLAGS += --gpu-max-threads-per-block=256' >> make.inc
+export PATH="${PATH}:/opt/rocm/bin"
+if [[ -n "$PYTORCH_ROCM_ARCH" ]]; then
+  amdgpu_targets=`echo $PYTORCH_ROCM_ARCH | sed 's/;/ /g'`
+else
+  amdgpu_targets=`rocm_agent_enumerator | grep -v gfx000 | sort -u | xargs`
+fi
+for arch in $amdgpu_targets; do
+  echo "DEVCCFLAGS += --offload-arch=$arch" >> make.inc
+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}"
+popd
+mv magma /opt/rocm

.ci/docker/common/install_swiftshader.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+
+set -ex
+
+[ -n "${SWIFTSHADER}" ]
+
+retry () {
+    $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
+}
+
+_https_amazon_aws=https://ossci-android.s3.amazonaws.com
+
+# SwiftShader
+_swiftshader_dir=/var/lib/jenkins/swiftshader
+_swiftshader_file_targz=swiftshader-abe07b943-prebuilt.tar.gz
+mkdir -p $_swiftshader_dir
+_tmp_swiftshader_targz="/tmp/${_swiftshader_file_targz}"
+
+curl --silent --show-error --location --fail --retry 3 \
+  --output "${_tmp_swiftshader_targz}" "$_https_amazon_aws/${_swiftshader_file_targz}"
+
+tar -C "${_swiftshader_dir}" -xzf "${_tmp_swiftshader_targz}"
+
+export VK_ICD_FILENAMES="${_swiftshader_dir}/build/Linux/vk_swiftshader_icd.json"

.ci/docker/common/install_triton.sh

@@ -2,12 +2,6 @@
 
 set -ex
 
-mkdir -p /opt/triton
-if [ -z "${TRITON}" ] && [ -z "${TRITON_CPU}" ]; then
-  echo "TRITON and TRITON_CPU are not set. Exiting..."
-  exit 0
-fi
-
 source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
 
 get_conda_version() {
@@ -58,7 +52,6 @@ cd triton
 as_jenkins git checkout ${TRITON_PINNED_COMMIT}
 as_jenkins git submodule update --init --recursive
 cd python
-pip_install pybind11==2.13.6
 
 # TODO: remove patch setup.py once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
 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
@@ -67,22 +60,17 @@ if [ -n "${UBUNTU_VERSION}" ] && [ -n "${GCC_VERSION}" ] && [[ "${GCC_VERSION}"
   # Triton needs at least gcc-9 to build
   apt-get install -y g++-9
 
-  CXX=g++-9 conda_run python setup.py bdist_wheel
+  CXX=g++-9 pip_install -e .
 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 conda_run python setup.py bdist_wheel
+  CXX=g++-9 pip_install -e .
 else
-  conda_run python setup.py bdist_wheel
+  pip_install -e .
 fi
 
-# Copy the wheel to /opt for multi stage docker builds
-cp dist/*.whl /opt/triton
-# Install the wheel for docker builds that don't use multi stage
-pip_install dist/*.whl
-
 if [ -n "${CONDA_CMAKE}" ]; then
   # TODO: This is to make sure that the same cmake and numpy version from install conda
   # script is used. Without this step, the newer cmake version (3.25.2) downloaded by

.ci/docker/common/install_vulkan_sdk.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+
+set -ex
+
+[ -n "${VULKAN_SDK_VERSION}" ]
+
+retry () {
+    $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
+}
+
+_vulkansdk_dir=/var/lib/jenkins/vulkansdk
+_tmp_vulkansdk_targz=/tmp/vulkansdk.tar.gz
+
+curl \
+  --silent \
+  --show-error \
+  --location \
+  --fail \
+  --retry 3 \
+  --output "${_tmp_vulkansdk_targz}" "https://ossci-android.s3.amazonaws.com/vulkansdk-linux-x86_64-${VULKAN_SDK_VERSION}.tar.gz"
+
+mkdir -p "${_vulkansdk_dir}"
+tar -C "${_vulkansdk_dir}" -xzf "${_tmp_vulkansdk_targz}" --strip-components 1
+rm -rf "${_tmp_vulkansdk_targz}"

.ci/docker/libtorch/Dockerfile

@@ -49,9 +49,6 @@ 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
-COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
 ENV CUDA_HOME /usr/local/cuda
 
 FROM cuda as cuda11.8
@@ -75,7 +72,6 @@ RUN bash ./install_magma.sh 12.8
 RUN ln -sf /usr/local/cuda-12.8 /usr/local/cuda
 
 FROM cpu as rocm
-ARG ROCM_VERSION
 ARG PYTORCH_ROCM_ARCH
 ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
 ENV MKLROOT /opt/intel
@@ -90,11 +86,11 @@ ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
 # gfortran and python needed for building magma from source for ROCm
 RUN apt-get update -y && \
     apt-get install gfortran -y && \
-    apt-get install python3 python-is-python3 -y && \
+    apt-get install python -y && \
     apt-get clean
 
 RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
-RUN bash ./install_rocm_magma.sh ${ROCM_VERSION} && rm install_rocm_magma.sh
+RUN bash ./install_rocm_magma.sh && rm install_rocm_magma.sh
 
 FROM ${BASE_TARGET} as final
 COPY --from=openssl            /opt/openssl           /opt/openssl

.ci/docker/libtorch/build.sh

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

.ci/docker/linter-cuda/Dockerfile

@@ -18,31 +18,28 @@ COPY ./common/install_user.sh install_user.sh
 RUN bash ./install_user.sh && rm install_user.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
-ARG PYTHON_VERSION
-ARG PIP_CMAKE
-# Put venv into the env vars so users don't need to activate it
-ENV PATH /var/lib/jenkins/ci_env/bin:$PATH
-ENV VIRTUAL_ENV /var/lib/jenkins/ci_env
-COPY requirements-ci.txt /opt/requirements-ci.txt
-COPY ./common/install_python.sh install_python.sh
-RUN bash ./install_python.sh && rm install_python.sh /opt/requirements-ci.txt
+ARG ANACONDA_PYTHON_VERSION
+ARG CONDA_CMAKE
+ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
+ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
+COPY requirements-ci.txt /opt/conda/requirements-ci.txt
+COPY ./common/install_conda.sh install_conda.sh
+COPY ./common/common_utils.sh common_utils.sh
+COPY ./common/install_magma_conda.sh install_magma_conda.sh
+RUN bash ./install_conda.sh && rm install_conda.sh install_magma_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
 
 # Install cuda and cudnn
 ARG CUDA_VERSION
 COPY ./common/install_cuda.sh install_cuda.sh
-COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
-RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh
 ENV DESIRED_CUDA ${CUDA_VERSION}
 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH
 
 # Note that Docker build forbids copying file outside the build context
 COPY ./common/install_linter.sh install_linter.sh
+COPY ./common/common_utils.sh common_utils.sh
 RUN bash ./install_linter.sh
-RUN rm install_linter.sh
-
-RUN chown -R jenkins:jenkins /var/lib/jenkins/ci_env
+RUN rm install_linter.sh common_utils.sh
 
 USER jenkins
 CMD ["bash"]

.ci/docker/linter/Dockerfile

@@ -15,18 +15,20 @@ COPY ./common/install_user.sh install_user.sh
 RUN bash ./install_user.sh && rm install_user.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
-ARG PYTHON_VERSION
-ARG PIP_CMAKE
-ENV PATH /var/lib/jenkins/ci_env/bin:$PATH
-ENV VIRTUAL_ENV /var/lib/jenkins/ci_env
-COPY requirements-ci.txt /opt/requirements-ci.txt
-COPY ./common/install_python.sh install_python.sh
-RUN bash ./install_python.sh && rm install_python.sh /opt/requirements-ci.txt
+ARG ANACONDA_PYTHON_VERSION
+ARG CONDA_CMAKE
+ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
+ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
+COPY requirements-ci.txt /opt/conda/requirements-ci.txt
+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
 
 # Note that Docker build forbids copying file outside the build context
 COPY ./common/install_linter.sh install_linter.sh
+COPY ./common/common_utils.sh common_utils.sh
 RUN bash ./install_linter.sh
-RUN rm install_linter.sh
+RUN rm install_linter.sh common_utils.sh
 
 USER jenkins
 CMD ["bash"]

.ci/docker/manywheel/Dockerfile

@@ -64,10 +64,7 @@ FROM base as cuda
 ARG BASE_CUDA_VERSION=10.2
 # Install CUDA
 ADD ./common/install_cuda.sh install_cuda.sh
-COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
-RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
 
 FROM base as intel
 # MKL
@@ -198,6 +195,6 @@ RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
 # cmake3 is needed for the MIOpen build
 RUN ln -sf /usr/local/bin/cmake /usr/bin/cmake3
 ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
-RUN bash ./install_rocm_magma.sh ${ROCM_VERSION} && rm install_rocm_magma.sh
+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

.ci/docker/manywheel/Dockerfile_2014

@@ -0,0 +1,153 @@
+# 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

@@ -36,10 +36,7 @@ FROM base as cuda
 ARG BASE_CUDA_VERSION=11.8
 # Install CUDA
 ADD ./common/install_cuda.sh install_cuda.sh
-COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
-RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
 
 FROM base as intel
 # MKL
@@ -161,7 +158,7 @@ ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
 RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
 ENV MKLROOT /opt/intel
 ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
-RUN bash ./install_rocm_magma.sh ${ROCM_VERSION} && rm install_rocm_magma.sh
+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
 

.ci/docker/manywheel/Dockerfile_2_28_aarch64

@@ -38,12 +38,6 @@ RUN yum install -y \
   sudo \
   gcc-toolset-${GCCTOOLSET_VERSION}-toolchain
 
-# (optional) Install non-default Ninja version
-ARG NINJA_VERSION
-COPY ./common/install_ninja.sh install_ninja.sh
-RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
-RUN rm install_ninja.sh
-
 # Ensure the expected devtoolset is used
 ENV PATH=/opt/rh/gcc-toolset-${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

.ci/docker/manywheel/Dockerfile_cuda_aarch64

@@ -67,10 +67,7 @@ FROM base as cuda
 ARG BASE_CUDA_VERSION
 # Install CUDA
 ADD ./common/install_cuda_aarch64.sh install_cuda_aarch64.sh
-COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
-COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-RUN bash ./install_cuda_aarch64.sh ${BASE_CUDA_VERSION} && rm install_cuda_aarch64.sh install_nccl.sh ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda_aarch64.sh ${BASE_CUDA_VERSION} && rm install_cuda_aarch64.sh
 
 FROM base as magma
 ARG BASE_CUDA_VERSION

.ci/docker/manywheel/Dockerfile_s390x

@@ -42,7 +42,6 @@ RUN yum install -y \
   llvm-devel \
   libzstd-devel \
   python3.12-devel \
-  python3.12-test \
   python3.12-setuptools \
   python3.12-pip \
   python3-virtualenv \
@@ -102,33 +101,24 @@ CMD ["/bin/bash"]
 
 # install test dependencies:
 # - grpcio requires system openssl, bundled crypto fails to build
+# - ml_dtypes 0.4.0 requires some fixes provided in later commits to build
 RUN dnf install -y \
   protobuf-devel \
   protobuf-c-devel \
   protobuf-lite-devel \
-  hdf5-devel \
-  python3-h5py \
-  git
+  wget \
+  patch
 
-RUN env GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=True pip3 install grpcio
-
-# cmake-3.28.0 from pip for onnxruntime
-RUN python3 -mpip install cmake==3.28.0
-
-# build onnxruntime 1.21.0 from sources.
-# it is not possible to build it from sources using pip,
-# so just build it from upstream repository.
-# h5py is dependency of onnxruntime_training.
-# h5py==3.11.0 builds with hdf5-devel 1.10.5 from repository.
-# install newest flatbuffers version first:
-# for some reason old version is getting pulled in otherwise.
-# packaging package is required for onnxruntime wheel build.
-RUN pip3 install flatbuffers && \
-  pip3 install h5py==3.11.0 && \
-  pip3 install packaging && \
-  git clone https://github.com/microsoft/onnxruntime && \
-  cd onnxruntime && git checkout v1.21.0 && \
+RUN env GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=True pip3 install grpcio==1.65.4
+RUN cd ~ && \
+  git clone https://github.com/jax-ml/ml_dtypes && \
+  cd ml_dtypes && \
+  git checkout v0.4.0 && \
   git submodule update --init --recursive && \
-  ./build.sh --config Release --parallel 0 --enable_pybind --build_wheel --enable_training --enable_training_apis --enable_training_ops --skip_tests --allow_running_as_root && \
-  pip3 install ./build/Linux/Release/dist/onnxruntime_training-*.whl && \
-  cd .. && /bin/rm -rf ./onnxruntime
+  wget https://github.com/jax-ml/ml_dtypes/commit/b969f76914d6b30676721bc92bf0f6021a0d1321.patch && \
+  wget https://github.com/jax-ml/ml_dtypes/commit/d4e6d035ecda073eab8bcf60f4eef572ee7087e6.patch && \
+  patch -p1 < b969f76914d6b30676721bc92bf0f6021a0d1321.patch && \
+  patch -p1 < d4e6d035ecda073eab8bcf60f4eef572ee7087e6.patch && \
+  python3 setup.py bdist_wheel && \
+  pip3 install dist/*.whl && \
+  rm -rf ml_dtypes

.ci/docker/manywheel/build.sh

@@ -1,7 +1,7 @@
 #!/usr/bin/env bash
 # Script used only in CD pipeline
 
-set -exou pipefail
+set -eou pipefail
 
 TOPDIR=$(git rev-parse --show-toplevel)
 
@@ -9,110 +9,151 @@ image="$1"
 shift
 
 if [ -z "${image}" ]; then
-  echo "Usage: $0 IMAGE:ARCHTAG"
+  echo "Usage: $0 IMAGE"
   exit 1
 fi
 
-# Go from imagename:tag to tag
-DOCKER_TAG_PREFIX=$(echo "${image}" | awk -F':' '{print $2}')
+DOCKER_IMAGE="pytorch/${image}"
 
-GPU_ARCH_VERSION=""
-if [[ "${DOCKER_TAG_PREFIX}" == cuda* ]]; then
-    # extract cuda version from image name.  e.g. manylinux2_28-builder:cuda12.8 returns 12.8
-    GPU_ARCH_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'cuda' '{print $2}')
-elif [[ "${DOCKER_TAG_PREFIX}" == rocm* ]]; then
-    # extract rocm version from image name.  e.g. manylinux2_28-builder:rocm6.2.4 returns 6.2.4
-    GPU_ARCH_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'rocm' '{print $2}')
-fi
+DOCKER_REGISTRY="${DOCKER_REGISTRY:-docker.io}"
 
+GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
+GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
 MANY_LINUX_VERSION=${MANY_LINUX_VERSION:-}
 DOCKERFILE_SUFFIX=${DOCKERFILE_SUFFIX:-}
+WITH_PUSH=${WITH_PUSH:-}
 
-case ${image} in
-    manylinux2_28-builder:cpu)
+case ${GPU_ARCH_TYPE} in
+    cpu)
         TARGET=cpu_final
+        DOCKER_TAG=cpu
+        GPU_IMAGE=centos:7
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
+        ;;
+    cpu-manylinux_2_28)
+        TARGET=cpu_final
+        DOCKER_TAG=cpu
         GPU_IMAGE=amd64/almalinux:8
         DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28"
         ;;
-    manylinuxaarch64-builder:cpu-aarch64)
+    cpu-aarch64)
         TARGET=final
+        DOCKER_TAG=cpu-aarch64
         GPU_IMAGE=arm64v8/centos:7
         DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=10"
         MANY_LINUX_VERSION="aarch64"
         ;;
-    manylinux2_28_aarch64-builder:cpu-aarch64)
+    cpu-aarch64-2_28)
         TARGET=final
+        DOCKER_TAG=cpu-aarch64
         GPU_IMAGE=arm64v8/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11 --build-arg NINJA_VERSION=1.12.1"
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28_aarch64"
         ;;
-    manylinuxcxx11-abi-builder:cpu-cxx11-abi)
+    cpu-cxx11-abi)
         TARGET=final
+        DOCKER_TAG=cpu-cxx11-abi
         GPU_IMAGE=""
         DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
         MANY_LINUX_VERSION="cxx11-abi"
         ;;
-    manylinuxs390x-builder:cpu-s390x)
+    cpu-s390x)
         TARGET=final
+        DOCKER_TAG=cpu-s390x
         GPU_IMAGE=s390x/almalinux:8
         DOCKER_GPU_BUILD_ARG=""
         MANY_LINUX_VERSION="s390x"
         ;;
-    manylinux2_28-builder:cuda*)
+    cuda)
         TARGET=cuda_final
+        DOCKER_TAG=cuda${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=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28"
         ;;
-    manylinuxaarch64-builder:cuda*)
+    cuda-aarch64)
         TARGET=cuda_final
+        DOCKER_TAG=cuda${GPU_ARCH_VERSION}
         GPU_IMAGE=arm64v8/centos:7
         DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="aarch64"
         DOCKERFILE_SUFFIX="_cuda_aarch64"
         ;;
-    manylinux2_28-builder:rocm*)
+    rocm|rocm-manylinux_2_28)
         TARGET=rocm_final
+        DOCKER_TAG=rocm${GPU_ARCH_VERSION}
         GPU_IMAGE=rocm/dev-centos-7:${GPU_ARCH_VERSION}-complete
         DEVTOOLSET_VERSION="9"
-        MANY_LINUX_VERSION="2_28"
-        DEVTOOLSET_VERSION="11"
-        GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
+        if [ ${GPU_ARCH_TYPE} == "rocm-manylinux_2_28" ]; then
+            MANY_LINUX_VERSION="2_28"
+            DEVTOOLSET_VERSION="11"
+            GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
+        fi
+        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101"
         DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
         ;;
-    manylinux2_28-builder:xpu)
+    xpu)
         TARGET=xpu_final
+        DOCKER_TAG=xpu
         GPU_IMAGE=amd64/almalinux:8
         DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28"
         ;;
     *)
-        echo "ERROR: Unrecognized image name: ${image}"
+        echo "ERROR: Unrecognized GPU_ARCH_TYPE: ${GPU_ARCH_TYPE}"
         exit 1
         ;;
 esac
 
+IMAGES=''
+
 if [[ -n ${MANY_LINUX_VERSION} && -z ${DOCKERFILE_SUFFIX} ]]; then
     DOCKERFILE_SUFFIX=_${MANY_LINUX_VERSION}
 fi
-# Only activate this if in CI
-if [ "$(uname -m)" != "s390x" ] && [ -v CI ]; then
-    # TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
-    # is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
-    sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
-    sudo systemctl daemon-reload
-    sudo systemctl restart docker
+(
+    set -x
+
+    if [ "$(uname -m)" != "s390x" ]; then
+        # TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
+        # is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
+        sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
+        sudo systemctl daemon-reload
+        sudo systemctl restart docker
+    fi
+
+    DOCKER_BUILDKIT=1 docker build  \
+        ${DOCKER_GPU_BUILD_ARG} \
+        --build-arg "GPU_IMAGE=${GPU_IMAGE}" \
+        --target "${TARGET}" \
+        -t "${DOCKER_IMAGE}" \
+        $@ \
+        -f "${TOPDIR}/.ci/docker/manywheel/Dockerfile${DOCKERFILE_SUFFIX}" \
+        "${TOPDIR}/.ci/docker/"
+)
+
+GITHUB_REF=${GITHUB_REF:-$(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 "${DOCKER_IMAGE_SHA_TAG}"
+        fi
+    )
 fi
-
-tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
-
-DOCKER_BUILDKIT=1 docker build  \
-    ${DOCKER_GPU_BUILD_ARG} \
-    --build-arg "GPU_IMAGE=${GPU_IMAGE}" \
-    --target "${TARGET}" \
-    -t "${tmp_tag}" \
-    $@ \
-    -f "${TOPDIR}/.ci/docker/manywheel/Dockerfile${DOCKERFILE_SUFFIX}" \
-    "${TOPDIR}/.ci/docker/"

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

@@ -3,7 +3,7 @@
 # Script used only in CD pipeline
 
 OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/
-CURL_DOWNLOAD_URL=https://curl.se/download
+CURL_DOWNLOAD_URL=https://curl.askapache.com/download
 
 AUTOCONF_DOWNLOAD_URL=https://ftp.gnu.org/gnu/autoconf
 

.ci/docker/requirements-ci.txt

@@ -41,14 +41,11 @@ fbscribelogger==0.1.7
 #Pinned versions: 0.1.6
 #test that import:
 
-flatbuffers==2.0 ; platform_machine != "s390x"
+flatbuffers==2.0
 #Description: cross platform serialization library
 #Pinned versions: 2.0
 #test that import:
 
-flatbuffers ; platform_machine == "s390x"
-#Description: cross platform serialization library; Newer version is required on s390x for new python version
-
 hypothesis==5.35.1
 # Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
 #Description: advanced library for generating parametrized tests
@@ -93,10 +90,10 @@ librosa>=0.6.2 ; python_version < "3.11"
 #Pinned versions:
 #test that import:
 
-mypy==1.14.0
+mypy==1.13.0
 # Pin MyPy version because new errors are likely to appear with each release
 #Description: linter
-#Pinned versions: 1.14.0
+#Pinned versions: 1.10.0
 #test that import: test_typing.py, test_type_hints.py
 
 networkx==2.8.8
@@ -105,10 +102,10 @@ networkx==2.8.8
 #Pinned versions: 2.8.8
 #test that import: functorch
 
-ninja==1.11.1.3
-#Description: build system. Used in some tests. Used in build to generate build
-#time tracing information
-#Pinned versions: 1.11.1.3
+#ninja
+#Description: build system.  Note that it install from
+#here breaks things so it is commented out
+#Pinned versions: 1.10.0.post1
 #test that import: run_test.py, test_cpp_extensions_aot.py,test_determination.py
 
 numba==0.49.0 ; python_version < "3.9"
@@ -297,7 +294,7 @@ ghstack==0.8.0
 #Pinned versions: 0.8.0
 #test that import:
 
-jinja2==3.1.6
+jinja2==3.1.5
 #Description: jinja2 template engine
 #Pinned versions: 3.1.4
 #test that import:
@@ -342,7 +339,7 @@ onnx==1.17.0
 #Pinned versions:
 #test that import:
 
-onnxscript==0.2.2
+onnxscript==0.1.0
 #Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
@@ -356,7 +353,7 @@ parameterized==0.8.1
 #Pinned versions: 1.24.0
 #test that import: test_sac_estimator.py
 
-pwlf==2.2.1
+pwlf==2.2.1 ; python_version >= "3.8"
 #Description: required for testing torch/distributed/_tools/sac_estimator.py
 #Pinned versions: 2.2.1
 #test that import: test_sac_estimator.py
@@ -368,9 +365,10 @@ PyYAML
 pyzstd
 setuptools
 
+ninja==1.11.1 ; platform_machine == "aarch64"
 scons==4.5.2 ; platform_machine == "aarch64"
 
-pulp==2.9.0
+pulp==2.9.0 ; python_version >= "3.8"
 #Description: required for testing ilp formulaiton under torch/distributed/_tools
 #Pinned versions: 2.9.0
 #test that import: test_sac_ilp.py

.ci/docker/requirements-docs.txt

@@ -1,20 +1,15 @@
 sphinx==5.3.0
 #Description: This is used to generate PyTorch docs
 #Pinned versions: 5.3.0
--e git+https://github.com/pytorch/pytorch_sphinx_theme.git@pytorch_sphinx_theme2#egg=pytorch_sphinx_theme2
+-e git+https://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
 
 # TODO: sphinxcontrib.katex 0.9.0 adds a local KaTeX server to speed up pre-rendering
 # but it doesn't seem to work and hangs around idly. The initial thought is probably
 # something related to Docker setup. We can investigate this later
-
 sphinxcontrib.katex==0.8.6
 #Description: This is used to generate PyTorch docs
 #Pinned versions: 0.8.6
 
-sphinxext-opengraph==0.9.1
-#Description: This is used to generate PyTorch docs
-#Pinned versions: 0.9.1
-
 matplotlib==3.5.3
 #Description: This is used to generate PyTorch docs
 #Pinned versions: 3.5.3
@@ -51,6 +46,5 @@ myst-nb==0.17.2
 # The following are required to build torch.distributed.elastic.rendezvous.etcd* docs
 python-etcd==0.4.5
 sphinx-copybutton==0.5.0
-sphinx-design==0.4.0
-sphinxcontrib-mermaid==1.0.0
+sphinx-panels==0.4.1
 myst-parser==0.18.1

.ci/docker/triton_version.txt

@@ -1 +1 @@
-3.3.0
+3.2.0

.ci/docker/ubuntu-cuda/Dockerfile

@@ -2,7 +2,7 @@ ARG UBUNTU_VERSION
 ARG CUDA_VERSION
 ARG IMAGE_NAME
 
-FROM ${IMAGE_NAME} as base
+FROM ${IMAGE_NAME}
 
 ARG UBUNTU_VERSION
 ARG CUDA_VERSION
@@ -43,6 +43,20 @@ ARG CLANG_VERSION
 COPY ./common/install_clang.sh install_clang.sh
 RUN bash ./install_clang.sh && rm install_clang.sh
 
+# (optional) Install protobuf for ONNX
+ARG PROTOBUF
+COPY ./common/install_protobuf.sh install_protobuf.sh
+RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
+RUN rm install_protobuf.sh
+ENV INSTALLED_PROTOBUF ${PROTOBUF}
+
+# (optional) Install database packages like LMDB and LevelDB
+ARG DB
+COPY ./common/install_db.sh install_db.sh
+RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
+RUN rm install_db.sh
+ENV INSTALLED_DB ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -83,20 +97,14 @@ RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
 RUN rm install_cmake.sh
 
 ARG TRITON
-
-FROM base as triton-builder
 # Install triton, this needs to be done before sccache because the latter will
 # try to reach out to S3, which docker build runners don't have access
 COPY ./common/install_triton.sh install_triton.sh
 COPY ./common/common_utils.sh common_utils.sh
 COPY ci_commit_pins/triton.txt triton.txt
 COPY triton_version.txt triton_version.txt
-RUN bash ./install_triton.sh
-
-FROM base as final
-COPY --from=triton-builder /opt/triton /opt/triton
-RUN if [ -n "${TRITON}" ]; then pip install /opt/triton/*.whl; chown -R jenkins:jenkins /opt/conda; fi
-RUN rm -rf /opt/triton
+RUN if [ -n "${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
@@ -151,16 +159,6 @@ COPY ./common/install_cusparselt.sh install_cusparselt.sh
 RUN bash install_cusparselt.sh
 RUN rm install_cusparselt.sh
 
-# Install NCCL
-ARG CUDA_VERSION
-COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-RUN bash install_nccl.sh
-RUN rm install_nccl.sh /ci_commit_pins/nccl-cu*
-ENV USE_SYSTEM_NCCL=1
-ENV NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
-ENV NCCL_LIB_DIR="/usr/local/cuda/lib64/"
-
 # Install CUDSS
 ARG CUDA_VERSION
 COPY ./common/install_cudss.sh install_cudss.sh

.ci/docker/ubuntu-rocm/Dockerfile

@@ -43,6 +43,20 @@ ARG CLANG_VERSION
 COPY ./common/install_clang.sh install_clang.sh
 RUN bash ./install_clang.sh && rm install_clang.sh
 
+# (optional) Install protobuf for ONNX
+ARG PROTOBUF
+COPY ./common/install_protobuf.sh install_protobuf.sh
+RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
+RUN rm install_protobuf.sh
+ENV INSTALLED_PROTOBUF ${PROTOBUF}
+
+# (optional) Install database packages like LMDB and LevelDB
+ARG DB
+COPY ./common/install_db.sh install_db.sh
+RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
+RUN rm install_db.sh
+ENV INSTALLED_DB ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -56,7 +70,7 @@ COPY ./common/install_rocm.sh install_rocm.sh
 RUN bash ./install_rocm.sh
 RUN rm install_rocm.sh
 COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
-RUN bash ./install_rocm_magma.sh ${ROCM_VERSION}
+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

.ci/docker/ubuntu-xpu/Dockerfile

@@ -77,6 +77,13 @@ 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-xpu.txt triton_version.txt
 
+# (optional) Install database packages like LMDB and LevelDB
+ARG DB
+COPY ./common/install_db.sh install_db.sh
+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
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./

.ci/docker/ubuntu/Dockerfile

@@ -1,6 +1,6 @@
 ARG UBUNTU_VERSION
 
-FROM ubuntu:${UBUNTU_VERSION} as base
+FROM ubuntu:${UBUNTU_VERSION}
 
 ARG UBUNTU_VERSION
 
@@ -52,17 +52,9 @@ RUN  bash ./install_lcov.sh && rm install_lcov.sh
 # Install cuda and cudnn
 ARG CUDA_VERSION
 COPY ./common/install_cuda.sh install_cuda.sh
-COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
-RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh
 ENV DESIRED_CUDA ${CUDA_VERSION}
 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH
-# No effect if cuda not installed
-ENV USE_SYSTEM_NCCL=1
-ENV NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
-ENV NCCL_LIB_DIR="/usr/local/cuda/lib64/"
-
 
 # (optional) Install UCC
 ARG UCX_COMMIT
@@ -75,6 +67,20 @@ ADD ./common/install_ucc.sh install_ucc.sh
 RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
 RUN rm install_ucc.sh
 
+# (optional) Install protobuf for ONNX
+ARG PROTOBUF
+COPY ./common/install_protobuf.sh install_protobuf.sh
+RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
+RUN rm install_protobuf.sh
+ENV INSTALLED_PROTOBUF ${PROTOBUF}
+
+# (optional) Install database packages like LMDB and LevelDB
+ARG DB
+COPY ./common/install_db.sh install_db.sh
+RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
+RUN rm install_db.sh
+ENV INSTALLED_DB ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -82,6 +88,18 @@ RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
 RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
 ENV INSTALLED_VISION ${VISION}
 
+# (optional) Install Vulkan SDK
+ARG VULKAN_SDK_VERSION
+COPY ./common/install_vulkan_sdk.sh install_vulkan_sdk.sh
+RUN if [ -n "${VULKAN_SDK_VERSION}" ]; then bash ./install_vulkan_sdk.sh; fi
+RUN rm install_vulkan_sdk.sh
+
+# (optional) Install swiftshader
+ARG SWIFTSHADER
+COPY ./common/install_swiftshader.sh install_swiftshader.sh
+RUN if [ -n "${SWIFTSHADER}" ]; then bash ./install_swiftshader.sh; fi
+RUN rm install_swiftshader.sh
+
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
 COPY ./common/install_cmake.sh install_cmake.sh
@@ -109,21 +127,20 @@ RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_d
 RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
 
 ARG TRITON
-ARG TRITON_CPU
-
-# Create a separate stage for building Triton and Triton-CPU.  install_triton
-# will check for the presence of env vars
-FROM base as triton-builder
+# Install triton, this needs to be done before sccache because the latter will
+# try to reach out to S3, which docker build runners don't have access
 COPY ./common/install_triton.sh install_triton.sh
 COPY ./common/common_utils.sh common_utils.sh
 COPY ci_commit_pins/triton.txt triton.txt
-COPY ci_commit_pins/triton-cpu.txt triton-cpu.txt
-RUN bash ./install_triton.sh
+RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
+RUN rm install_triton.sh common_utils.sh triton.txt
 
-FROM base as final
-COPY --from=triton-builder /opt/triton /opt/triton
-RUN if [ -n "${TRITON}" ] || [ -n "${TRITON_CPU}" ]; then pip install /opt/triton/*.whl; chown -R jenkins:jenkins /opt/conda; fi
-RUN rm -rf /opt/triton
+ARG TRITON_CPU
+COPY ./common/install_triton.sh install_triton.sh
+COPY ./common/common_utils.sh common_utils.sh
+COPY ci_commit_pins/triton-cpu.txt triton-cpu.txt
+RUN if [ -n "${TRITON_CPU}" ]; then bash ./install_triton.sh; fi
+RUN rm install_triton.sh common_utils.sh triton-cpu.txt
 
 ARG EXECUTORCH
 # Build and install executorch

.ci/magma-rocm/.gitignore

@@ -1,2 +0,0 @@
-output/
-magma-rocm*/

.ci/magma-rocm/Makefile

@@ -1,41 +0,0 @@
-SHELL=/usr/bin/env bash
-
-DOCKER_CMD ?= docker
-DESIRED_ROCM ?= 6.4
-DESIRED_ROCM_SHORT = $(subst .,,$(DESIRED_ROCM))
-PACKAGE_NAME = magma-rocm
-# inherit this from underlying docker image, do not pass this env var to docker
-#PYTORCH_ROCM_ARCH ?= gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201
-
-DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
-	-v $(shell git rev-parse --show-toplevel)/.ci:/builder \
-	-w /builder \
-	-e PACKAGE_NAME=${PACKAGE_NAME}${DESIRED_ROCM_SHORT} \
-	-e DESIRED_ROCM=${DESIRED_ROCM} \
-	"pytorch/manylinux2_28-builder:rocm${DESIRED_ROCM}-main" \
-	magma-rocm/build_magma.sh
-
-.PHONY: all
-all: magma-rocm64
-all: magma-rocm63
-all: magma-rocm624
-
-.PHONY:
-clean:
-	$(RM) -r magma-*
-	$(RM) -r output
-
-.PHONY: magma-rocm64
-magma-rocm64: DESIRED_ROCM := 6.4
-magma-rocm64:
-	$(DOCKER_RUN)
-
-.PHONY: magma-rocm63
-magma-rocm63: DESIRED_ROCM := 6.3
-magma-rocm63:
-	$(DOCKER_RUN)
-
-.PHONY: magma-rocm624
-magma-rocm624: DESIRED_ROCM := 6.2.4
-magma-rocm624:
-	$(DOCKER_RUN)

.ci/magma-rocm/README.md

@@ -1,48 +0,0 @@
-# Magma ROCm
-
-This folder contains the scripts and configurations to build libmagma.so, linked for various versions of ROCm.
-
-## Building
-
-Look in the `Makefile` for available targets to build. To build any target, for example `magma-rocm63`, run
-
-```
-# Using `docker`
-make magma-rocm63
-
-# Using `podman`
-DOCKER_CMD=podman make magma-rocm63
-```
-
-This spawns a `pytorch/manylinux-rocm<version>` docker image, which has the required `devtoolset` and ROCm versions installed.
-Within the docker image, it runs `build_magma.sh` with the correct environment variables set, which package the necessary files
-into a tarball, with the following structure:
-
-```
-.
-├── include       # header files
-├── lib           # libmagma.so
-├── info
-│   ├── licenses  # license file
-│   └── recipe    # build script
-```
-
-More specifically, `build_magma.sh` copies over the relevant files from the `package_files` directory depending on the ROCm version.
-Outputted binaries should be in the `output` folder.
-
-
-## Pushing
-
-Packages can be uploaded to an S3 bucket using:
-
-```
-aws s3 cp output/*/magma-cuda*.bz2 <bucket-with-path>
-```
-
-If you do not have upload permissions, please ping @seemethere or @soumith to gain access
-
-## New versions
-
-New ROCm versions can be added by creating a new make target with the next desired version. For ROCm version N.n, the target should be named `magma-rocmNn`.
-
-Make sure to edit the appropriate environment variables (e.g., DESIRED_ROCM) in the `Makefile` accordingly. Remember also to check `build_magma.sh` to ensure the logic for copying over the files remains correct.

.ci/magma-rocm/build_magma.sh

@@ -1,42 +0,0 @@
-#!/usr/bin/env bash
-
-set -eou pipefail
-
-# Environment variables
-# The script expects DESIRED_CUDA and PACKAGE_NAME to be set
-ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
-
-# Version 2.7.2 + ROCm related updates
-MAGMA_VERSION=a1625ff4d9bc362906bd01f805dbbe12612953f6
-
-# Folders for the build
-PACKAGE_FILES=${ROOT_DIR}/magma-rocm/package_files # metadata
-PACKAGE_DIR=${ROOT_DIR}/magma-rocm/${PACKAGE_NAME} # build workspace
-PACKAGE_OUTPUT=${ROOT_DIR}/magma-rocm/output # where tarballs are stored
-PACKAGE_BUILD=${PACKAGE_DIR} # where the content of the tarball is prepared
-PACKAGE_RECIPE=${PACKAGE_BUILD}/info/recipe
-PACKAGE_LICENSE=${PACKAGE_BUILD}/info/licenses
-mkdir -p ${PACKAGE_DIR} ${PACKAGE_OUTPUT}/linux-64 ${PACKAGE_BUILD} ${PACKAGE_RECIPE} ${PACKAGE_LICENSE}
-
-# Fetch magma sources and verify checksum
-pushd ${PACKAGE_DIR}
-git clone https://bitbucket.org/icl/magma.git
-pushd magma
-git checkout ${MAGMA_VERSION}
-popd
-popd
-
-# build
-pushd ${PACKAGE_DIR}/magma
-# The build.sh script expects to be executed from the sources root folder
-INSTALL_DIR=${PACKAGE_BUILD} ${PACKAGE_FILES}/build.sh
-popd
-
-# Package recipe, license and tarball
-# Folder and package name are backward compatible for the build workflow
-cp ${PACKAGE_FILES}/build.sh ${PACKAGE_RECIPE}/build.sh
-cp ${PACKAGE_DIR}/magma/COPYRIGHT ${PACKAGE_LICENSE}/COPYRIGHT
-pushd ${PACKAGE_BUILD}
-tar cjf ${PACKAGE_OUTPUT}/linux-64/${PACKAGE_NAME}-${MAGMA_VERSION}-1.tar.bz2 include lib info
-echo Built in ${PACKAGE_OUTPUT}/linux-64/${PACKAGE_NAME}-${MAGMA_VERSION}-1.tar.bz2
-popd

.ci/magma-rocm/package_files/build.sh

@@ -1,38 +0,0 @@
-# Magma build scripts need `python`
-ln -sf /usr/bin/python3 /usr/bin/python
-
-ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
-case "$ID" in
-  almalinux)
-    yum install -y gcc-gfortran
-    ;;
-  *)
-    echo "No preinstalls to build magma..."
-    ;;
-esac
-
-MKLROOT=${MKLROOT:-/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION}
-
-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,$(MKLROOT)/lib -Wl,--rpath,/opt/rocm/magma/lib -ldl' >> make.inc
-echo 'DEVCCFLAGS += --gpu-max-threads-per-block=256' >> make.inc
-export PATH="${PATH}:/opt/rocm/bin"
-if [[ -n "$PYTORCH_ROCM_ARCH" ]]; then
-  amdgpu_targets=`echo $PYTORCH_ROCM_ARCH | sed 's/;/ /g'`
-else
-  amdgpu_targets=`rocm_agent_enumerator | grep -v gfx000 | sort -u | xargs`
-fi
-for arch in $amdgpu_targets; do
-  echo "DEVCCFLAGS += --offload-arch=$arch" >> make.inc
-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}"
-cp -R lib ${INSTALL_DIR}
-cp -R include ${INSTALL_DIR}

.ci/magma/Makefile

@@ -12,7 +12,7 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
 	-e PACKAGE_NAME=${PACKAGE_NAME}${DESIRED_CUDA_SHORT} \
 	-e DESIRED_CUDA=${DESIRED_CUDA} \
 	-e CUDA_ARCH_LIST="${CUDA_ARCH_LIST}" \
-	"pytorch/manylinux2_28-builder:cuda${DESIRED_CUDA}-main" \
+	"pytorch/manylinux-builder:cuda${DESIRED_CUDA}-main" \
 	magma/build_magma.sh
 
 .PHONY: all

.ci/manywheel/build_common.sh

@@ -111,6 +111,12 @@ case ${DESIRED_PYTHON} in
     ;;
 esac
 
+if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
+    export _GLIBCXX_USE_CXX11_ABI=1
+else
+    export _GLIBCXX_USE_CXX11_ABI=0
+fi
+
 if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
     echo "Calling build_amd.py at $(date)"
     python tools/amd_build/build_amd.py
@@ -203,6 +209,12 @@ if [[ -n "$BUILD_PYTHONLESS" ]]; then
 
     mkdir -p /tmp/$LIBTORCH_HOUSE_DIR
 
+    if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
+        LIBTORCH_ABI="cxx11-abi-"
+    else
+        LIBTORCH_ABI=
+    fi
+
     zip -rq /tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-$PYTORCH_BUILD_VERSION.zip libtorch
     cp /tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-$PYTORCH_BUILD_VERSION.zip \
        /tmp/$LIBTORCH_HOUSE_DIR/libtorch-$LIBTORCH_ABI$LIBTORCH_VARIANT-latest.zip

.ci/manywheel/build_cuda.sh

@@ -54,11 +54,11 @@ cuda_version_nodot=$(echo $CUDA_VERSION | tr -d '.')
 TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;7.5;8.0;8.6"
 case ${CUDA_VERSION} in
     12.8)
-        TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;12.0+PTX" #removing sm_50-sm_70 as these architectures are deprecated in CUDA 12.8 and will be removed in future releases
+        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0;10.0;12.0+PTX" #Ripping out 5.0 and 6.0 due to ld error
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
     12.6)
-        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
+        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0+PTX"
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
     12.4)

.ci/manywheel/build_libtorch.sh

@@ -95,6 +95,12 @@ python setup.py clean
 retry pip install -qr requirements.txt
 retry pip install -q numpy==2.0.1
 
+if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
+    export _GLIBCXX_USE_CXX11_ABI=1
+else
+    export _GLIBCXX_USE_CXX11_ABI=0
+fi
+
 if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
     echo "Calling build_amd.py at $(date)"
     python tools/amd_build/build_amd.py
@@ -163,6 +169,12 @@ fi
 
 )
 
+if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
+    LIBTORCH_ABI="cxx11-abi-"
+else
+    LIBTORCH_ABI=
+fi
+
 (
     set -x
 

.ci/pytorch/build.sh

@@ -35,7 +35,7 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
 fi
 
 if [[ "$BUILD_ENVIRONMENT" == *cuda11* ]]; then
-  if [[ "$BUILD_ENVIRONMENT" != *clang* ]]; then
+  if [[ "$BUILD_ENVIRONMENT" != *cuda11.3* && "$BUILD_ENVIRONMENT" != *clang* ]]; then
     # TODO: there is a linking issue when building with UCC using clang,
     # disable it for now and to be fix later.
     # TODO: disable UCC temporarily to enable CUDA 12.1 in CI
@@ -173,7 +173,6 @@ if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   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 TORCH_XPU_ARCH_LIST=pvc
 fi
 
 # sccache will fail for CUDA builds if all cores are used for compiling
@@ -192,7 +191,7 @@ fi
 
 # We only build FlashAttention files for CUDA 8.0+, and they require large amounts of
 # memory to build and will OOM
-if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ 1 -eq $(echo "${TORCH_CUDA_ARCH_LIST} >= 8.0" | bc) ]] && [ -z "$MAX_JOBS_OVERRIDE" ]; then
+if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ 1 -eq $(echo "${TORCH_CUDA_ARCH_LIST} >= 8.0" | bc) ]]; then
   echo "WARNING: FlashAttention files require large amounts of memory to build and will OOM"
   echo "Setting MAX_JOBS=(nproc-2)/3 to reduce memory usage"
   export MAX_JOBS="$(( $(nproc --ignore=2) / 3 ))"
@@ -277,8 +276,10 @@ else
     # or building non-XLA tests.
     if [[ "$BUILD_ENVIRONMENT" != *rocm*  &&
           "$BUILD_ENVIRONMENT" != *xla* ]]; then
-      # Install numpy-2.0.2 for builds which are backward compatible with 1.X
-      python -mpip install numpy==2.0.2
+      if [[ "$BUILD_ENVIRONMENT" != *py3.8* ]]; then
+        # Install numpy-2.0.2 for builds which are backward compatible with 1.X
+        python -mpip install numpy==2.0.2
+      fi
 
       WERROR=1 python setup.py clean
 
@@ -301,18 +302,6 @@ else
     fi
     pip_install_whl "$(echo dist/*.whl)"
 
-    if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
-      echo "Checking that xpu is compiled"
-      pushd dist/
-      if python -c 'import torch; exit(0 if torch.xpu._is_compiled() else 1)'; then
-        echo "XPU support is compiled in."
-      else
-        echo "XPU support is NOT compiled in."
-        exit 1
-      fi
-      popd
-    fi
-
     # TODO: I'm not sure why, but somehow we lose verbose commands
     set -x
 
@@ -388,10 +377,8 @@ else
     # This is an attempt to mitigate flaky libtorch build OOM error. By default, the build parallelization
     # is set to be the number of CPU minus 2. So, let's try a more conservative value here. A 4xlarge has
     # 16 CPUs
-    if [ -z "$MAX_JOBS_OVERRIDE" ]; then
-      MAX_JOBS=$(nproc --ignore=4)
-      export MAX_JOBS
-    fi
+    MAX_JOBS=$(nproc --ignore=4)
+    export MAX_JOBS
 
     # NB: Install outside of source directory (at the same level as the root
     # pytorch folder) so that it doesn't get cleaned away prior to docker push.

.ci/pytorch/check_binary.sh

@@ -59,16 +59,78 @@ else
   export install_root="$(dirname $(which python))/../lib/python${py_dot}/site-packages/torch/"
 fi
 
+###############################################################################
+# Setup XPU ENV
+###############################################################################
+if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
+  set +u
+  # Refer https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html
+  source /opt/intel/oneapi/compiler/latest/env/vars.sh
+  source /opt/intel/oneapi/pti/latest/env/vars.sh
+fi
+
 ###############################################################################
 # Check GCC ABI
 ###############################################################################
 
-# NOTE: As of https://github.com/pytorch/pytorch/issues/126551 we only produce
-#       wheels with cxx11-abi
+# NOTE [ Building libtorch with old vs. new gcc ABI ]
+#
+# Packages built with one version of ABI could not be linked against by client
+# C++ libraries that were compiled using the other version of ABI. Since both
+# gcc ABIs are still common in the wild, we need to support both ABIs. Currently:
+#
+# - All the nightlies built on CentOS 7 + devtoolset7 use the old gcc ABI.
+# - All the nightlies built on Ubuntu 16.04 + gcc 5.4 use the new gcc ABI.
 
 echo "Checking that the gcc ABI is what we expect"
 if [[ "$(uname)" != 'Darwin' ]]; then
-  # We also check that there are cxx11 symbols in libtorch
+  function is_expected() {
+    if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* || "$DESIRED_CUDA" == *"rocm"* ]]; then
+      if [[ "$1" -gt 0 || "$1" == "ON " ]]; then
+        echo 1
+      fi
+    else
+      if [[ -z "$1" || "$1" == 0 || "$1" == "OFF" ]]; then
+        echo 1
+      fi
+    fi
+  }
+
+  # First we check that the env var in TorchConfig.cmake is correct
+
+  # We search for D_GLIBCXX_USE_CXX11_ABI=1 in torch/TorchConfig.cmake
+  torch_config="${install_root}/share/cmake/Torch/TorchConfig.cmake"
+  if [[ ! -f "$torch_config" ]]; then
+    echo "No TorchConfig.cmake found!"
+    ls -lah "$install_root/share/cmake/Torch"
+    exit 1
+  fi
+  echo "Checking the TorchConfig.cmake"
+  cat "$torch_config"
+
+  # The sed call below is
+  #   don't print lines by default (only print the line we want)
+  # -n
+  #   execute the following expression
+  # e
+  #   replace lines that match with the first capture group and print
+  # s/.*D_GLIBCXX_USE_CXX11_ABI=\(.\)".*/\1/p
+  #   any characters, D_GLIBCXX_USE_CXX11_ABI=, exactly one any character, a
+  #   quote, any characters
+  #   Note the exactly one single character after the '='. In the case that the
+  #     variable is not set the '=' will be followed by a '"' immediately and the
+  #     line will fail the match and nothing will be printed; this is what we
+  #     want.  Otherwise it will capture the 0 or 1 after the '='.
+  # /.*D_GLIBCXX_USE_CXX11_ABI=\(.\)".*/
+  #   replace the matched line with the capture group and print
+  # /\1/p
+  actual_gcc_abi="$(sed -ne 's/.*D_GLIBCXX_USE_CXX11_ABI=\(.\)".*/\1/p' < "$torch_config")"
+  if [[ "$(is_expected "$actual_gcc_abi")" != 1 ]]; then
+    echo "gcc ABI $actual_gcc_abi not as expected."
+    exit 1
+  fi
+
+  # We also check that there are [not] cxx11 symbols in libtorch
   #
   echo "Checking that symbols in libtorch.so have the right gcc abi"
   python3 "$(dirname ${BASH_SOURCE[0]})/smoke_test/check_binary_symbols.py"
@@ -146,11 +208,35 @@ setup_link_flags () {
 
 TEST_CODE_DIR="$(dirname $(realpath ${BASH_SOURCE[0]}))/test_example_code"
 build_and_run_example_cpp () {
+  if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
+    GLIBCXX_USE_CXX11_ABI=1
+  else
+    GLIBCXX_USE_CXX11_ABI=0
+  fi
   setup_link_flags
-  g++ ${TEST_CODE_DIR}/$1.cpp -I${install_root}/include -I${install_root}/include/torch/csrc/api/include -std=gnu++17 -L${install_root}/lib ${REF_LIB} ${ADDITIONAL_LINKER_FLAGS} -ltorch $TORCH_CPU_LINK_FLAGS $TORCH_CUDA_LINK_FLAGS $C10_LINK_FLAGS -o $1
+  g++ ${TEST_CODE_DIR}/$1.cpp -I${install_root}/include -I${install_root}/include/torch/csrc/api/include -D_GLIBCXX_USE_CXX11_ABI=$GLIBCXX_USE_CXX11_ABI -std=gnu++17 -L${install_root}/lib ${REF_LIB} ${ADDITIONAL_LINKER_FLAGS} -ltorch $TORCH_CPU_LINK_FLAGS $TORCH_CUDA_LINK_FLAGS $C10_LINK_FLAGS -o $1
   ./$1
 }
 
+build_example_cpp_with_incorrect_abi () {
+  if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
+    GLIBCXX_USE_CXX11_ABI=0
+  else
+    GLIBCXX_USE_CXX11_ABI=1
+  fi
+  set +e
+  setup_link_flags
+  g++ ${TEST_CODE_DIR}/$1.cpp -I${install_root}/include -I${install_root}/include/torch/csrc/api/include -D_GLIBCXX_USE_CXX11_ABI=$GLIBCXX_USE_CXX11_ABI -std=gnu++17 -L${install_root}/lib ${REF_LIB} ${ADDITIONAL_LINKER_FLAGS} -ltorch $TORCH_CPU_LINK_FLAGS $TORCH_CUDA_LINK_FLAGS $C10_LINK_FLAGS -o $1
+  ERRCODE=$?
+  set -e
+  if [ "$ERRCODE" -eq "0" ]; then
+    echo "Building example with incorrect ABI didn't throw error. Aborting."
+    exit 1
+  else
+    echo "Building example with incorrect ABI throws expected error. Proceeding."
+  fi
+}
+
 ###############################################################################
 # Check simple Python/C++ calls
 ###############################################################################
@@ -160,6 +246,11 @@ if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
     export LD_LIBRARY_PATH=/usr/local/cuda/lib64
   fi
   build_and_run_example_cpp simple-torch-test
+  # `_GLIBCXX_USE_CXX11_ABI` is always ignored by gcc in devtoolset7, so we test
+  # the expected failure case for Ubuntu 16.04 + gcc 5.4 only.
+  if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
+    build_example_cpp_with_incorrect_abi simple-torch-test
+  fi
 else
   pushd /tmp
   python -c 'import torch'
@@ -216,14 +307,6 @@ else
   fi
 fi
 
-###############################################################################
-# Check XPU configured correctly
-###############################################################################
-if [[ "$DESIRED_CUDA" == 'xpu' && "$PACKAGE_TYPE" != 'libtorch' ]]; then
-  echo "Checking that xpu is compiled"
-  python -c 'import torch; exit(0 if torch.xpu._is_compiled() else 1)'
-fi
-
 ###############################################################################
 # Check CUDA configured correctly
 ###############################################################################
@@ -302,19 +385,10 @@ except RuntimeError as e:
 fi
 
 ###############################################################################
-# Check for C++ ABI compatibility to GCC-11
+# Check for C++ ABI compatibility between gcc7 and gcc9 compiled binaries
 ###############################################################################
 if [[ "$(uname)" == 'Linux' &&  "$PACKAGE_TYPE" == 'manywheel' ]]; then
   pushd /tmp
-  # Per https://gcc.gnu.org/onlinedocs/gcc/C_002b_002b-Dialect-Options.html gcc-11 is ABI16
-  # Though manylinux_2.28 should have been build with gcc-14, per
-  # https://github.com/pypa/manylinux?tab=readme-ov-file#manylinux_2_28-almalinux-8-based
-  # On s390x gcc 14 is used because it contains fix for interaction
-  # between precompiled headers and vectorization builtins.
-  # This fix is not available in earlier gcc versions.
-  # gcc-14 uses ABI19.
-  if [[ "$(uname -m)" != "s390x" ]]; then
-    python -c "import torch; exit(0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi1016' else 1)"
-  fi
+  python -c "import torch; exit(0 if torch.compiled_with_cxx11_abi() else (0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi1011' else 1))"
   popd
 fi

.ci/pytorch/macos-build.sh

@@ -33,15 +33,56 @@ if which sccache > /dev/null; then
   export PATH="${tmp_dir}:$PATH"
 fi
 
-print_cmake_info
-if [[ ${BUILD_ENVIRONMENT} == *"distributed"* ]]; then
-  # Needed for inductor benchmarks, as lots of HF networks make `torch.distribtued` calls
-  USE_DISTRIBUTED=1 USE_OPENMP=1 WERROR=1 python setup.py bdist_wheel
-else
+cross_compile_arm64() {
+  # Cross compilation for arm64
   # Explicitly set USE_DISTRIBUTED=0 to align with the default build config on mac. This also serves as the sole CI config that tests
   # that building with USE_DISTRIBUTED=0 works at all. See https://github.com/pytorch/pytorch/issues/86448
+  USE_DISTRIBUTED=0 CMAKE_OSX_ARCHITECTURES=arm64 MACOSX_DEPLOYMENT_TARGET=11.0 USE_MKLDNN=OFF USE_QNNPACK=OFF WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel
+}
+
+compile_arm64() {
+  # Compilation for arm64
+  # TODO: Compile with OpenMP support (but this causes CI regressions as cross-compilation were done with OpenMP disabled)
   USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel
+}
+
+compile_x86_64() {
+  USE_DISTRIBUTED=0 WERROR=1 python setup.py bdist_wheel --plat-name=macosx_10_9_x86_64
+}
+
+build_lite_interpreter() {
+    echo "Testing libtorch (lite interpreter)."
+
+    CPP_BUILD="$(pwd)/../cpp_build"
+    # Ensure the removal of the tmp directory
+    trap 'rm -rfv ${CPP_BUILD}' EXIT
+    rm -rf "${CPP_BUILD}"
+    mkdir -p "${CPP_BUILD}/caffe2"
+
+    # It looks libtorch need to be built in "${CPP_BUILD}/caffe2 folder.
+    BUILD_LIBTORCH_PY=$PWD/tools/build_libtorch.py
+    pushd "${CPP_BUILD}/caffe2" || exit
+    VERBOSE=1 DEBUG=1 python "${BUILD_LIBTORCH_PY}"
+    popd || exit
+
+    "${CPP_BUILD}/caffe2/build/bin/test_lite_interpreter_runtime"
+}
+
+print_cmake_info
+
+if [[ ${BUILD_ENVIRONMENT} = *arm64* ]]; then
+  if [[ $(uname -m) == "arm64" ]]; then
+    compile_arm64
+  else
+    cross_compile_arm64
+  fi
+elif [[ ${BUILD_ENVIRONMENT} = *lite-interpreter* ]]; then
+  export BUILD_LITE_INTERPRETER=1
+  build_lite_interpreter
+else
+  compile_x86_64
 fi
+
 if which sccache > /dev/null; then
   print_sccache_stats
 fi

.ci/pytorch/macos-test.sh

@@ -221,39 +221,25 @@ test_torchbench_smoketest() {
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
 
+  local backend=eager
+  local dtype=notset
   local device=mps
-  local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam pytorch_unet stable_diffusion_text_encoder moco speech_transformer)
 
-  for backend in eager inductor; do
+  touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
+  touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
 
-    for dtype in notset float16 bfloat16; do
-      echo "Launching torchbench inference performance run for backend ${backend} and dtype ${dtype}"
-      local dtype_arg="--${dtype}"
-      if [ "$dtype" == notset ]; then
-          dtype_arg="--float32"
-      fi
-      touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
-      for model in "${models[@]}"; do
-        PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-          --performance --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
-          --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv" || true
-      done
-    done
-
-    for dtype in notset amp; do
-      echo "Launching torchbench training performance run for backend ${backend} and dtype ${dtype}"
-      touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
-      local dtype_arg="--${dtype}"
-      if [ "$dtype" == notset ]; then
-          dtype_arg="--float32"
-      fi
-      for model in "${models[@]}"; do
-        PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-          --performance --only "$model" --backend "$backend" --training --devices "$device" "$dtype_arg" \
-          --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv" || true
-      done
-    done
+  echo "Setup complete, launching torchbench training performance run"
+  for model in hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152; do
+    PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
+      --performance --only "$model" --backend "$backend" --training --devices "$device" \
+      --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
+  done
 
+  echo "Launching torchbench inference performance run"
+  for model in hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152; do
+    PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
+      --performance --only "$model" --backend "$backend" --inference --devices "$device" \
+      --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
   done
 
   echo "Pytorch benchmark on mps device completed"

.ci/pytorch/python_doc_push_script.sh

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

.ci/pytorch/smoke_test/check_binary_symbols.py

@@ -80,7 +80,7 @@ def grep_symbols(lib: str, patterns: list[Any]) -> list[str]:
         return functools.reduce(list.__add__, (x.result() for x in tasks), [])
 
 
-def check_lib_symbols_for_abi_correctness(lib: str) -> None:
+def check_lib_symbols_for_abi_correctness(lib: str, pre_cxx11_abi: bool = True) -> None:
     print(f"lib: {lib}")
     cxx11_symbols = grep_symbols(lib, LIBTORCH_CXX11_PATTERNS)
     pre_cxx11_symbols = grep_symbols(lib, LIBTORCH_PRE_CXX11_PATTERNS)
@@ -88,12 +88,28 @@ def check_lib_symbols_for_abi_correctness(lib: str) -> None:
     num_pre_cxx11_symbols = len(pre_cxx11_symbols)
     print(f"num_cxx11_symbols: {num_cxx11_symbols}")
     print(f"num_pre_cxx11_symbols: {num_pre_cxx11_symbols}")
-    if num_pre_cxx11_symbols > 0:
-        raise RuntimeError(
-            f"Found pre-cxx11 symbols, but there shouldn't be any, see: {pre_cxx11_symbols[:100]}"
+    if pre_cxx11_abi:
+        if num_cxx11_symbols > 0:
+            raise RuntimeError(
+                f"Found cxx11 symbols, but there shouldn't be any, see: {cxx11_symbols[:100]}"
+            )
+        if num_pre_cxx11_symbols < 1000:
+            raise RuntimeError("Didn't find enough pre-cxx11 symbols.")
+        # Check for no recursive iterators, regression test for https://github.com/pytorch/pytorch/issues/133437
+        rec_iter_symbols = grep_symbols(
+            lib, [re.compile("std::filesystem::recursive_directory_iterator.*")]
         )
-    if num_cxx11_symbols < 100:
-        raise RuntimeError("Didn't find enought cxx11 symbols")
+        if len(rec_iter_symbols) > 0:
+            raise RuntimeError(
+                f"recursive_directory_iterator in used pre-CXX11 binaries, see; {rec_iter_symbols}"
+            )
+    else:
+        if num_pre_cxx11_symbols > 0:
+            raise RuntimeError(
+                f"Found pre-cxx11 symbols, but there shouldn't be any, see: {pre_cxx11_symbols[:100]}"
+            )
+        if num_cxx11_symbols < 100:
+            raise RuntimeError("Didn't find enought cxx11 symbols")
 
 
 def main() -> None:
@@ -105,8 +121,9 @@ def main() -> None:
         else:
             install_root = Path(distutils.sysconfig.get_python_lib()) / "torch"
 
-    libtorch_cpu_path = str(install_root / "lib" / "libtorch_cpu.so")
-    check_lib_symbols_for_abi_correctness(libtorch_cpu_path)
+    libtorch_cpu_path = install_root / "lib" / "libtorch_cpu.so"
+    pre_cxx11_abi = "cxx11-abi" not in os.getenv("DESIRED_DEVTOOLSET", "")
+    check_lib_symbols_for_abi_correctness(libtorch_cpu_path, pre_cxx11_abi)
 
 
 if __name__ == "__main__":

.ci/pytorch/smoke_test/max_autotune.py

@@ -46,9 +46,7 @@ def train(args, model, device, train_loader, optimizer, epoch):
         optimizer.step()
         if batch_idx % args.log_interval == 0:
             print(
-                f"Train Epoch: {epoch} "
-                f"[{batch_idx * len(data)}/{len(train_loader.dataset)} "
-                f"({100.0 * batch_idx / len(train_loader):.0f}%)]\tLoss: {loss.item():.6f}"
+                f"Train Epoch: {epoch} [{batch_idx * len(data)}/{len(train_loader.dataset)} ({100. * batch_idx / len(train_loader):.0f}%)]\tLoss: {loss.item():.6f}"  # noqa: B950
             )
             if args.dry_run:
                 break
@@ -73,9 +71,7 @@ def test(model, device, test_loader):
     test_loss /= len(test_loader.dataset)
 
     print(
-        f"\nTest set: Average loss: {test_loss:.4f}, "
-        f"Accuracy: {correct}/{len(test_loader.dataset)} "
-        f"({100.0 * correct / len(test_loader.dataset):.0f}%)\n"
+        f"\nTest set: Average loss: {test_loss:.4f}, Accuracy: {correct}/{len(test_loader.dataset)} ({100. * correct / len(test_loader.dataset):.0f}%)\n"  # noqa: B950
     )
 
 

.ci/pytorch/smoke_test/smoke_test.py

@@ -7,7 +7,6 @@ import subprocess
 import sys
 from pathlib import Path
 from tempfile import NamedTemporaryFile
-from typing import Optional
 
 import torch
 import torch._dynamo
@@ -77,13 +76,10 @@ def read_release_matrix():
 
 
 def test_numpy():
-    try:
-        import numpy as np
+    import numpy as np
 
-        x = np.arange(5)
-        torch.tensor(x)
-    except ImportError:
-        print("Numpy check skipped. Numpy is not installed.")
+    x = np.arange(5)
+    torch.tensor(x)
 
 
 def check_version(package: str) -> None:
@@ -170,10 +166,6 @@ def test_cuda_gds_errors_captured() -> None:
     major_version = int(torch.version.cuda.split(".")[0])
     minor_version = int(torch.version.cuda.split(".")[1])
 
-    if target_os == "windows":
-        print(f"{target_os} is not supported for GDS smoke test")
-        return
-
     if major_version < 12 or (major_version == 12 and minor_version < 6):
         print("CUDA version is not supported for GDS smoke test")
         return
@@ -196,41 +188,8 @@ def test_cuda_gds_errors_captured() -> None:
         )
 
 
-def find_pypi_package_version(package: str) -> Optional[str]:
-    from importlib import metadata
-
-    dists = metadata.distributions()
-    for dist in dists:
-        if dist.metadata["Name"].startswith(package):
-            return dist.version
-    return None
-
-
-def cudnn_to_version_str(cudnn_version: int) -> str:
-    patch = int(cudnn_version % 10)
-    minor = int((cudnn_version / 100) % 100)
-    major = int((cudnn_version / 10000) % 10000)
-    return f"{major}.{minor}.{patch}"
-
-
-def compare_pypi_to_torch_versions(
-    package: str, pypi_version: str, torch_version: str
-) -> None:
-    if pypi_version is None:
-        raise RuntimeError(f"Can't find {package} in PyPI for Torch: {torch_version}")
-    if pypi_version.startswith(torch_version):
-        print(f"Found matching {package}. Torch: {torch_version} PyPI {pypi_version}")
-    else:
-        raise RuntimeError(
-            f"Wrong {package} version. Torch: {torch_version} PyPI: {pypi_version}"
-        )
-
-
 def smoke_test_cuda(
-    package: str,
-    runtime_error_check: str,
-    torch_compile_check: str,
-    pypi_pkg_check: str,
+    package: str, runtime_error_check: str, torch_compile_check: str
 ) -> None:
     if not torch.cuda.is_available() and is_cuda_system:
         raise RuntimeError(f"Expected CUDA {gpu_arch_ver}. However CUDA is not loaded.")
@@ -260,30 +219,20 @@ def smoke_test_cuda(
             raise RuntimeError(
                 f"Wrong CUDA version. Loaded: {torch.version.cuda} Expected: {gpu_arch_ver}"
             )
-
         print(f"torch cuda: {torch.version.cuda}")
+        # todo add cudnn version validation
+        print(f"torch cudnn: {torch.backends.cudnn.version()}")
+        print(f"cuDNN enabled? {torch.backends.cudnn.enabled}")
+
         torch.cuda.init()
         print("CUDA initialized successfully")
         print(f"Number of CUDA devices: {torch.cuda.device_count()}")
         for i in range(torch.cuda.device_count()):
             print(f"Device {i}: {torch.cuda.get_device_name(i)}")
 
-        print(f"cuDNN enabled? {torch.backends.cudnn.enabled}")
-        torch_cudnn_version = cudnn_to_version_str(torch.backends.cudnn.version())
-        print(f"Torch cuDNN version: {torch_cudnn_version}")
-
+        # nccl is availbale only on Linux
         if sys.platform in ["linux", "linux2"]:
-            torch_nccl_version = ".".join(str(v) for v in torch.cuda.nccl.version())
-            print(f"Torch nccl; version: {torch_nccl_version}")
-
-        # Pypi dependencies are installed on linux ony and nccl is availbale only on Linux.
-        if pypi_pkg_check == "enabled" and sys.platform in ["linux", "linux2"]:
-            compare_pypi_to_torch_versions(
-                "cudnn", find_pypi_package_version("nvidia-cudnn"), torch_cudnn_version
-            )
-            compare_pypi_to_torch_versions(
-                "nccl", find_pypi_package_version("nvidia-nccl"), torch_nccl_version
-            )
+            print(f"torch nccl version: {torch.cuda.nccl.version()}")
 
         if runtime_error_check == "enabled":
             test_cuda_runtime_errors_captured()
@@ -442,13 +391,6 @@ def parse_args():
         choices=["enabled", "disabled"],
         default="enabled",
     )
-    parser.add_argument(
-        "--pypi-pkg-check",
-        help="Check pypi package versions cudnn and nccl",
-        type=str,
-        choices=["enabled", "disabled"],
-        default="enabled",
-    )
     return parser.parse_args()
 
 
@@ -464,7 +406,6 @@ def main() -> None:
     smoke_test_conv2d()
     test_linalg()
     test_numpy()
-
     if is_cuda_system:
         test_linalg("cuda")
         test_cuda_gds_errors_captured()
@@ -473,10 +414,7 @@ def main() -> None:
         smoke_test_modules()
 
     smoke_test_cuda(
-        options.package,
-        options.runtime_error_check,
-        options.torch_compile_check,
-        options.pypi_pkg_check,
+        options.package, options.runtime_error_check, options.torch_compile_check
     )
 
 

.ci/pytorch/test.sh

@@ -314,13 +314,6 @@ test_python() {
   assert_git_not_dirty
 }
 
-test_lazy_tensor_meta_reference_disabled() {
-  export TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1
-  echo "Testing lazy tensor operations without meta reference"
-  time python test/run_test.py --include lazy/test_ts_opinfo.py --verbose
-  export -n TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE
-}
-
 
 test_dynamo_wrapped_shard() {
   if [[ -z "$NUM_TEST_SHARDS" ]]; then
@@ -483,8 +476,6 @@ elif [[ "${TEST_CONFIG}" == *aot_eager* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--backend aot_eager)
 elif [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--export-aot-inductor)
-elif [[ "${TEST_CONFIG}" == *max_autotune_inductor* ]]; then
-  DYNAMO_BENCHMARK_FLAGS+=(--inductor --inductor-compile-mode max-autotune)
 elif [[ "${TEST_CONFIG}" == *inductor* && "${TEST_CONFIG}" != *perf* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--inductor)
 fi
@@ -499,59 +490,6 @@ else
   DYNAMO_BENCHMARK_FLAGS+=(--device cuda)
 fi
 
-test_cachebench() {
-  TEST_REPORTS_DIR=$(pwd)/test/test-reports
-  mkdir -p "$TEST_REPORTS_DIR"
-
-  local BENCHMARK
-  if [[ "${SHARD_NUMBER}" == 1 ]]; then
-    local BENCHMARK=torchbench
-  elif [[ "${SHARD_NUMBER}" == 2 ]]; then
-    local BENCHMARK=huggingface
-  else
-    echo "invalid SHARD_NUMBER: ${SHARD_NUMBER}"
-    exit 1
-  fi
-
-  local mode_options=("training" "inference")
-
-  for mode in "${mode_options[@]}"; do
-    $TASKSET python "benchmarks/dynamo/cachebench.py" \
-        --mode "$mode" \
-        --device cuda \
-        --benchmark "$BENCHMARK" \
-        --repeat 3 \
-        --output "$TEST_REPORTS_DIR/cachebench_${BENCHMARK}_${mode}.json"
-
-    $TASKSET python "benchmarks/dynamo/cachebench.py" \
-        --mode "$mode" \
-        --dynamic \
-        --device cuda \
-        --benchmark "$BENCHMARK" \
-        --repeat 3 \
-        --output "$TEST_REPORTS_DIR/cachebench_${BENCHMARK}_${mode}_dynamic.json"
-  done
-}
-
-test_verify_cachebench() {
-  TMP_TEST_REPORTS_DIR=$(mktemp -d)
-  TEST_OUTPUT="$TMP_TEST_REPORTS_DIR/test.json"
-
-  $TASKSET python "benchmarks/dynamo/cachebench.py" \
-      --mode training \
-      --device cpu \
-      --model nanogpt \
-      --benchmark torchbench \
-      --output "$TEST_OUTPUT"
-
-  # -s checks file exists and is non empty
-  if [[ ! -s "$TEST_OUTPUT" ]]; then
-    echo "Cachebench failed to produce an output."
-    echo "Run 'python benchmarks/dynamo/cachebench.py' to make sure it works"
-    exit 1
-  fi
-}
-
 test_perf_for_dashboard() {
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
@@ -580,8 +518,6 @@ test_perf_for_dashboard() {
     test_inductor_set_cpu_affinity
   elif [[ "${TEST_CONFIG}" == *cuda_a10g* ]]; then
     device=cuda_a10g
-  elif [[ "${TEST_CONFIG}" == *h100* ]]; then
-    device=cuda_h100
   elif [[ "${TEST_CONFIG}" == *rocm* ]]; then
     device=rocm
   fi
@@ -762,8 +698,6 @@ test_dynamo_benchmark() {
       fi
     elif [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
       test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
-    elif [[ "${TEST_CONFIG}" == *max_autotune_inductor* ]]; then
-      test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
     else
       test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
       test_single_dynamo_benchmark "training" "$suite" "$shard_id" --training --amp "$@"
@@ -1173,7 +1107,7 @@ build_xla() {
   apply_patches
   SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
   # These functions are defined in .circleci/common.sh in pytorch/xla repo
-  retry install_pre_deps_pytorch_xla $XLA_DIR $USE_CACHE
+  retry install_deps_pytorch_xla $XLA_DIR $USE_CACHE
   CMAKE_PREFIX_PATH="${SITE_PACKAGES}/torch:${CMAKE_PREFIX_PATH}" XLA_SANDBOX_BUILD=1 build_torch_xla $XLA_DIR
   assert_git_not_dirty
 }
@@ -1474,13 +1408,14 @@ test_executorch() {
   pushd /executorch
 
   export PYTHON_EXECUTABLE=python
-  export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
+  export EXECUTORCH_BUILD_PYBIND=ON
+  export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
 
   # For llama3
   bash examples/models/llama3_2_vision/install_requirements.sh
   # NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
   # from the PR
-  bash .ci/scripts/setup-linux.sh --build-tool cmake
+  bash .ci/scripts/setup-linux.sh cmake
 
   echo "Run ExecuTorch unit tests"
   pytest -v -n auto
@@ -1504,7 +1439,7 @@ test_executorch() {
 test_linux_aarch64() {
   python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
         test_transformers test_multiprocessing test_numpy_interop test_autograd test_binary_ufuncs test_complex test_spectral_ops \
-        test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
+        test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops \
         --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 
   # Dynamo tests
@@ -1526,27 +1461,6 @@ test_linux_aarch64() {
        --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 }
 
-test_operator_benchmark() {
-  TEST_REPORTS_DIR=$(pwd)/test/test-reports
-  mkdir -p "$TEST_REPORTS_DIR"
-  TEST_DIR=$(pwd)
-
-  test_inductor_set_cpu_affinity
-
-  cd benchmarks/operator_benchmark/pt_extension
-  python setup.py install
-
-  cd "${TEST_DIR}"/benchmarks/operator_benchmark
-  $TASKSET python -m benchmark_all_test --device "$1" --tag-filter "$2" \
-      --output-dir "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.csv"
-
-  pip_install pandas
-  python check_perf_csv.py \
-      --actual "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.csv" \
-      --expected "expected_ci_operator_benchmark_eager_float32_cpu.csv"
-}
-
-
 if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-bazel-* ]]; then
   (cd test && python -c "import torch; print(torch.__config__.show())")
   (cd test && python -c "import torch; print(torch.__config__.parallel_info())")
@@ -1577,19 +1491,6 @@ elif [[ "$TEST_CONFIG" == distributed ]]; then
   if [[ "${SHARD_NUMBER}" == 1 ]]; then
     test_rpc
   fi
-elif [[ "${TEST_CONFIG}" == *operator_benchmark* ]]; then
-  TEST_MODE="short"
-
-  if [[ "${TEST_CONFIG}" == *cpu* ]]; then
-    if [[ "${TEST_CONFIG}" == *long* ]]; then
-      TEST_MODE="long"
-    elif [[ "${TEST_CONFIG}" == *all* ]]; then
-      TEST_MODE="all"
-    fi
-
-    test_operator_benchmark cpu ${TEST_MODE}
-
-  fi
 elif [[ "${TEST_CONFIG}" == *inductor_distributed* ]]; then
   test_inductor_distributed
 elif [[ "${TEST_CONFIG}" == *inductor-halide* ]]; then
@@ -1606,16 +1507,6 @@ elif [[ "${TEST_CONFIG}" == *timm* ]]; then
   install_torchvision
   id=$((SHARD_NUMBER-1))
   test_dynamo_benchmark timm_models "$id"
-elif [[ "${TEST_CONFIG}" == cachebench ]]; then
-  install_torchaudio cuda
-  install_torchvision
-  checkout_install_torchbench nanogpt BERT_pytorch resnet50 hf_T5 llama moco
-  PYTHONPATH=$(pwd)/torchbench test_cachebench
-elif [[ "${TEST_CONFIG}" == verify_cachebench ]]; then
-  install_torchaudio cpu
-  install_torchvision
-  checkout_install_torchbench nanogpt
-  PYTHONPATH=$(pwd)/torchbench test_verify_cachebench
 elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
   if [[ "${TEST_CONFIG}" == *cpu* ]]; then
     install_torchaudio cpu
@@ -1652,7 +1543,6 @@ elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper* ]]; then
   install_torchvision
   checkout_install_torchbench hf_T5 llama moco
   PYTHONPATH=$(pwd)/torchbench test_inductor_cpp_wrapper_shard "$SHARD_NUMBER"
-  test_inductor_aoti
 elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
   install_torchvision
   test_inductor_shard "${SHARD_NUMBER}"
@@ -1672,7 +1562,6 @@ elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
   test_python_shard "$SHARD_NUMBER"
   test_aten
 elif [[ "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
-  test_lazy_tensor_meta_reference_disabled
   test_without_numpy
   install_torchvision
   test_python_shard 1

.ci/pytorch/windows/arm64/bootstrap_buildtools.bat

@@ -17,24 +17,32 @@ curl -L -o "%INSTALLER_FILE%" %DOWNLOAD_URL%
 :: Install the Visual Studio Build Tools with C++ components
 echo Installing Visual Studio Build Tools with C++ components...
 echo Installing MSVC %MSVC_VERSION%
-"%INSTALLER_FILE%" --norestart --quiet --wait --installPath "%DEPENDENCIES_DIR%\VSBuildTools" ^
-    --add Microsoft.VisualStudio.Workload.VCTools ^
-    --add Microsoft.VisualStudio.Component.Windows10SDK ^
-    --add Microsoft.VisualStudio.Component.Windows11SDK.22621 ^
-    --add Microsoft.VisualStudio.Component.VC.ASAN ^
-    --add Microsoft.VisualStudio.Component.VC.CMake.Project ^
-    --add Microsoft.VisualStudio.Component.VC.CoreBuildTools ^
-    --add Microsoft.VisualStudio.Component.VC.CoreIde ^
-    --add Microsoft.VisualStudio.Component.VC.Redist.14.Latest ^
-    --add Microsoft.VisualStudio.Component.VC.Tools.ARM64EC ^
-    --add Microsoft.VisualStudio.Component.VC.Tools.ARM64 ^
-    --add Microsoft.VisualStudio.Component.VC.Tools.x86.x64
-
-echo exitcode = %errorlevel%
+if "%MSVC_VERSION%" == "latest" (
+    "%INSTALLER_FILE%" --norestart --nocache --quiet --wait --installPath "%DEPENDENCIES_DIR%\VSBuildTools" ^
+        --add Microsoft.VisualStudio.Component.Windows11SDK.22621 ^
+        --add Microsoft.VisualStudio.Component.VC.ASAN ^
+        --add Microsoft.VisualStudio.Component.VC.CMake.Project ^
+        --add Microsoft.VisualStudio.Component.VC.Tools.ARM64 ^
+        --add Microsoft.VisualStudio.Component.VC.Tools.x86.x64
+) else if "%MSVC_VERSION%" == "14.40" (
+    "%INSTALLER_FILE%" --norestart --nocache --quiet --wait --installPath "%DEPENDENCIES_DIR%\VSBuildTools" ^
+        --add Microsoft.VisualStudio.Component.Windows11SDK.22621 ^
+        --add Microsoft.VisualStudio.Component.VC.ASAN ^
+        --add Microsoft.VisualStudio.Component.VC.CMake.Project ^
+        --add Microsoft.VisualStudio.Component.VC.14.40.17.10.ARM64 ^
+        --add Microsoft.VisualStudio.Component.VC.14.40.17.10.x86.x64
+) else if "%MSVC_VERSION%" == "14.36" (
+    "%INSTALLER_FILE%" --norestart --nocache --quiet --wait --installPath "%DEPENDENCIES_DIR%\VSBuildTools" ^
+        --add Microsoft.VisualStudio.Component.Windows11SDK.22621 ^
+        --add Microsoft.VisualStudio.Component.VC.ASAN ^
+        --add Microsoft.VisualStudio.Component.VC.CMake.Project ^
+        --add Microsoft.VisualStudio.Component.VC.14.36.17.6.ARM64 ^
+        --add Microsoft.VisualStudio.Component.VC.14.36.17.6.x86.x64
+)
 
 :: Check if installation was successful
 if %errorlevel% neq 0 (
-    echo Failed to install Visual Studio Build Tools with C++ components.
+    echo "Failed to install Visual Studio Build Tools with C++ components. (exitcode = %errorlevel%)"
     exit /b 1
 )
 

.ci/pytorch/windows/arm64/bootstrap_python.bat

@@ -6,25 +6,22 @@ echo Dependency Python installation started.
 if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
 if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
 
-if "%DESIRED_PYTHON%" == "3.13" (
-    echo Python version is set to 3.13
-    set DOWNLOAD_URL=https://www.python.org/ftp/python/3.13.2/python-3.13.2-arm64.exe
-) else if "%DESIRED_PYTHON%" == "3.12" (
-    echo Python version is set to 3.12
-    set DOWNLOAD_URL=https://www.python.org/ftp/python/3.12.7/python-3.12.7-arm64.exe
-) else if "%DESIRED_PYTHON%" == "3.11" (
-    echo Python version is set to 3.11
-    set DOWNLOAD_URL=https://www.python.org/ftp/python/3.11.9/python-3.11.9-arm64.exe
+if "%PYTHON_VERSION%"=="Python312" (
+    echo Python version is set to Python312
+    set DOWNLOAD_URL="https://www.python.org/ftp/python/3.12.7/python-3.12.7-arm64.exe"
+) else if "%PYTHON_VERSION%"=="Python311" (
+    echo Python version is set to Python311
+    set DOWNLOAD_URL="https://www.python.org/ftp/python/3.11.9/python-3.11.9-arm64.exe"
 ) else (
-    echo DESIRED_PYTHON not defined, Python version is set to 3.12
-    set DOWNLOAD_URL=https://www.python.org/ftp/python/3.12.7/python-3.12.7-arm64.exe
+    echo PYTHON_VERSION not defined, Python version is set to Python312
+    set DOWNLOAD_URL="https://www.python.org/ftp/python/3.12.7/python-3.12.7-arm64.exe"
 )
 
 set INSTALLER_FILE=%DOWNLOADS_DIR%\python-installer.exe
 
 :: Download installer
 echo Downloading Python...
-curl -L -o "%INSTALLER_FILE%" "%DOWNLOAD_URL%"
+curl -L -o "%INSTALLER_FILE%" %DOWNLOAD_URL%
 
 :: Install Python
 echo Installing Python...

.ci/pytorch/windows/arm64/bootstrap_tests.bat

@@ -14,7 +14,7 @@ where python
 :: install dependencies
 python -m pip install --upgrade pip
 pip install -r requirements.txt
-pip install pytest numpy protobuf expecttest hypothesis
+pip install pytest numpy
 
 :: find file name for pytorch wheel
 for /f "delims=" %%f in ('dir /b "%PYTORCH_FINAL_PACKAGE_DIR%" ^| findstr "torch-"') do set "TORCH_WHEEL_FILENAME=%PYTORCH_FINAL_PACKAGE_DIR%\%%f"

.ci/pytorch/windows/arm64/smoke_test.bat

@@ -1,6 +1,8 @@
 @echo off
 setlocal
 
+set "ORIG_PATH=%PATH%"
+
 if "%PACKAGE_TYPE%" == "wheel" goto wheel
 if "%PACKAGE_TYPE%" == "libtorch" goto libtorch
 
@@ -8,7 +10,21 @@ echo "unknown package type"
 exit /b 1
 
 :wheel
-call %PYTORCH_ROOT%\.ci\pytorch\windows\arm64\bootstrap_tests.bat
+echo "install wheel package"
+
+echo Running pip install...
+pip install -q --pre numpy protobuf
+echo Error level after pip install: %ERRORLEVEL%
+if errorlevel 1 exit /b 1
+
+for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *.whl') do pip install "%%i"
+if errorlevel 1 exit /b 1
+
+goto smoke_test
+
+:smoke_test
+python -c "import torch"
+if ERRORLEVEL 1 exit /b 1
 
 echo Running python rnn_smoke.py...
 python %PYTORCH_ROOT%\.ci\pytorch\test_example_code\rnn_smoke_win_arm64.py
@@ -23,12 +39,10 @@ goto end
 :libtorch
 echo "install and test libtorch"
 
-if not exist tmp mkdir tmp
-
-for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *-latest.zip') do C:\Windows\System32\tar.exe -xf "%%i" -C tmp
+for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *-latest.zip') do tar -xf "%%i" -C tmp
 if ERRORLEVEL 1 exit /b 1
 
-pushd tmp
+pushd tmp\libtorch
 
 set VC_VERSION_LOWER=14
 set VC_VERSION_UPPER=36
@@ -46,4 +60,6 @@ if ERRORLEVEL 1 exit /b 1
 .\simple-torch-test.exe
 if ERRORLEVEL 1 exit /b 1
 
-:end
+:end
+set "PATH=%ORIG_PATH%"
+popd

.ci/pytorch/windows/cuda124.bat

@@ -37,7 +37,7 @@ IF "%CUDA_PATH_V124%"=="" (
 )
 
 IF "%BUILD_VISION%" == "" (
-    set TORCH_CUDA_ARCH_LIST=6.1;7.0;7.5;8.0;8.6;9.0
+    set TORCH_CUDA_ARCH_LIST=5.0;6.0;6.1;7.0;7.5;8.0;8.6;9.0
     set TORCH_NVCC_FLAGS=-Xfatbin -compress-all
 ) ELSE (
     set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -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=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90

.ci/pytorch/windows/cuda126.bat

@@ -37,7 +37,7 @@ IF "%CUDA_PATH_V126%"=="" (
 )
 
 IF "%BUILD_VISION%" == "" (
-    set TORCH_CUDA_ARCH_LIST=6.1;7.0;7.5;8.0;8.6;9.0
+    set TORCH_CUDA_ARCH_LIST=5.0;6.0;6.1;7.0;7.5;8.0;8.6;9.0
     set TORCH_NVCC_FLAGS=-Xfatbin -compress-all
 ) ELSE (
     set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -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=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90

.ci/pytorch/windows/cuda128.bat

@@ -37,7 +37,7 @@ IF "%CUDA_PATH_V128%"=="" (
 )
 
 IF "%BUILD_VISION%" == "" (
-    set TORCH_CUDA_ARCH_LIST=6.1;7.0;7.5;8.0;8.6;9.0;10.0;12.0
+    set TORCH_CUDA_ARCH_LIST=5.0;6.0;6.1;7.0;7.5;8.0;8.6;9.0;10.0;12.0
     set TORCH_NVCC_FLAGS=-Xfatbin -compress-all
 ) ELSE (
     set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -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=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_100,code=compute_100 -gencode=arch=compute_120,code=compute_120

.ci/pytorch/windows/internal/smoke_test.bat

@@ -42,6 +42,7 @@ if "%DESIRED_PYTHON%" == "3.12" set "PYTHON_INSTALLER_URL=https://www.python.org
 if "%DESIRED_PYTHON%" == "3.11" set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.11.0/python-3.11.0-amd64.exe"
 if "%DESIRED_PYTHON%" == "3.10" set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.10.0/python-3.10.0-amd64.exe"
 if "%DESIRED_PYTHON%" == "3.9" set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.9.0/python-3.9.0-amd64.exe"
+if "%DESIRED_PYTHON%" == "3.8" set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.8.2/python-3.8.2-amd64.exe"
 if "%PYTHON_INSTALLER_URL%" == "" (
     echo Python %DESIRED_PYTHON% not supported yet
 )
@@ -70,20 +71,11 @@ if "%DESIRED_PYTHON%" == "3.13" %PYTHON_EXEC% -m pip install --pre numpy==2.1.2
 if "%DESIRED_PYTHON%" == "3.12" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf
 if "%DESIRED_PYTHON%" == "3.11" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf
 if "%DESIRED_PYTHON%" == "3.10" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf
-if "%DESIRED_PYTHON%" == "3.9" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf networkx
+if "%DESIRED_PYTHON%" == "3.9" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf
 
 if errorlevel 1 exit /b 1
 
-if "%PYTORCH_BUILD_VERSION:dev=%" NEQ "%PYTORCH_BUILD_VERSION%" (
-    set "CHANNEL=nightly"
-) else (
-    set "CHANNEL=test"
-)
-
-set "EXTRA_INDEX= "
-if "%CUDA_VERSION%" == "xpu" set "EXTRA_INDEX=--index-url https://download.pytorch.org/whl/%CHANNEL%/xpu"
-
-for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *.whl') do %PYTHON_EXEC% -m pip install "%%i" %EXTRA_INDEX%
+for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *.whl') do %PYTHON_EXEC% -m pip install "%%i"
 if errorlevel 1 exit /b 1
 
 goto smoke_test

.ci/pytorch/windows/internal/xpu_install.bat

@@ -47,9 +47,9 @@ set XPU_EXTRA_INSTALLED=0
 set XPU_EXTRA_UNINSTALL=0
 
 if not [%XPU_VERSION%]==[] if [%XPU_VERSION%]==[2025.0] (
-    set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/9d6d6c17-ca2d-4735-9331-99447e4a1280/intel-deep-learning-essentials-2025.0.1.28_offline.exe
+    set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/efc86abd-cb77-452e-a03f-a741895b8ece/intel-deep-learning-essentials-2025.0.0.336_offline.exe
     set XPU_BUNDLE_PRODUCT_NAME=intel.oneapi.win.deep-learning-essentials.product
-    set XPU_BUNDLE_VERSION=2025.0.1+20
+    set XPU_BUNDLE_VERSION=2025.0.0+335
     set XPU_BUNDLE_INSTALLED=0
     set XPU_BUNDLE_UNINSTALL=0
     set XPU_EXTRA_URL=NULL

.circleci/scripts/binary_linux_test.sh

@@ -90,17 +90,8 @@ fi
 /pytorch/.ci/pytorch/check_binary.sh
 
 if [[ "\$GPU_ARCH_TYPE" != *s390x* && "\$GPU_ARCH_TYPE" != *xpu* && "\$GPU_ARCH_TYPE" != *rocm*  && "$PACKAGE_TYPE" != libtorch ]]; then
-
-  torch_pkg_size="$(ls -1 /final_pkgs/torch-* | sort |tail -1 |xargs wc -c |cut -d ' ' -f1)"
-  # todo: implement check for large binaries
-  # if the package is larger than 1.5GB, we disable the pypi check.
-  # this package contains all libraries packaged in torch libs folder
-  # example of such package is https://download.pytorch.org/whl/cu126_full/torch
-  if [[ "\$torch_pkg_size" -gt  1500000000 ]]; then
-    python /pytorch/.ci/pytorch/smoke_test/smoke_test.py --package=torchonly --torch-compile-check disabled --pypi-pkg-check disabled
-  else
-    python /pytorch/.ci/pytorch/smoke_test/smoke_test.py --package=torchonly --torch-compile-check disabled $extra_parameters
-  fi
+  # Exclude s390, xpu, rocm and libtorch builds from smoke testing
+  python /pytorch/.ci/pytorch/smoke_test/smoke_test.py --package=torchonly --torch-compile-check disabled
 fi
 
 # Clean temp files

.circleci/scripts/binary_populate_env.sh

@@ -31,9 +31,9 @@ fi
 export DOCKER_IMAGE=${DOCKER_IMAGE:-}
 if [[ -z "$DOCKER_IMAGE" ]]; then
   if [[ "$DESIRED_CUDA" == cpu ]]; then
-    export DOCKER_IMAGE="pytorch/manylinux2_28:cpu"
+    export DOCKER_IMAGE="pytorch/manylinux:cpu"
   else
-    export DOCKER_IMAGE="pytorch/manylinux2_28-builder:${DESIRED_CUDA:2}"
+    export DOCKER_IMAGE="pytorch/manylinux-builder:${DESIRED_CUDA:2}"
   fi
 fi
 
@@ -74,12 +74,6 @@ TRITON_VERSION=$(cat $PYTORCH_ROOT/.ci/docker/triton_version.txt)
 
 # Here PYTORCH_EXTRA_INSTALL_REQUIREMENTS is already set for the all the wheel builds hence append TRITON_CONSTRAINT
 TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64'"
-
-# CUDA 12.8 builds have triton for Linux and Linux aarch64 binaries.
-if [[ "$DESIRED_CUDA" == cu128 ]]; then
-  TRITON_CONSTRAINT="platform_system == 'Linux'"
-fi
-
 if [[ "$PACKAGE_TYPE" =~ .*wheel.* &&  -n "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" && ! "$PYTORCH_BUILD_VERSION" =~ .*xpu.* ]]; then
   TRITON_REQUIREMENT="triton==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
   if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
@@ -104,11 +98,11 @@ if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_B
 fi
 
 # Set triton via PYTORCH_EXTRA_INSTALL_REQUIREMENTS for triton xpu package
-if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*xpu.* ]]; then
-    TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}"
+if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*xpu.* && $(uname) == "Linux" ]]; then
+    TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
     if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
         TRITON_SHORTHASH=$(cut -c1-8 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton-xpu.txt)
-        TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}+git${TRITON_SHORTHASH}"
+        TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}+git${TRITON_SHORTHASH}; ${TRITON_CONSTRAINT}"
     fi
     if [[ -z "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
         export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${TRITON_REQUIREMENT}"

.circleci/scripts/binary_upload.sh

@@ -55,16 +55,12 @@ s3_upload() {
     s3_upload_dir="${s3_root_dir}/${UPLOAD_SUBFOLDER}/"
   fi
   (
-    cache_control_flag=""
-    if [[ "${UPLOAD_CHANNEL}" = "test" ]]; then
-      cache_control_flag="--cache-control='no-cache,no-store,must-revalidate'"
-    fi
     for pkg in ${PKG_DIR}/*.${extension}; do
       (
         set -x
         shm_id=$(sha256sum "${pkg}" | awk '{print $1}')
         ${AWS_S3_CP} --no-progress --acl public-read "${pkg}" "${s3_upload_dir}" \
-          --metadata "checksum-sha256=${shm_id}" ${cache_control_flag}
+          --metadata "checksum-sha256=${shm_id}"
       )
     done
   )

.circleci/scripts/binary_windows_build.sh

@@ -4,18 +4,15 @@ set -eux -o pipefail
 source "${BINARY_ENV_FILE:-/c/w/env}"
 mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR"
 
-if [[ "$OS" != "windows-arm64" ]]; then
-    export CUDA_VERSION="${DESIRED_CUDA/cu/}"
-    export USE_SCCACHE=1
-    export SCCACHE_BUCKET=ossci-compiler-cache
-    export SCCACHE_IGNORE_SERVER_IO_ERROR=1
-    export VC_YEAR=2022
-fi
+export CUDA_VERSION="${DESIRED_CUDA/cu/}"
+export USE_SCCACHE=1
+export SCCACHE_BUCKET=ossci-compiler-cache
+export SCCACHE_IGNORE_SERVER_IO_ERROR=1
+export VC_YEAR=2022
 
 if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
     export USE_SCCACHE=0
     export XPU_VERSION=2025.0
-    export XPU_ENABLE_KINETO=1
 fi
 
 echo "Free space on filesystem before build:"
@@ -23,16 +20,7 @@ df -h
 
 pushd "$PYTORCH_ROOT/.ci/pytorch/"
 export NIGHTLIES_PYTORCH_ROOT="$PYTORCH_ROOT"
-
-if [[ "$OS" == "windows-arm64" ]]; then
-    if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
-        ./windows/arm64/build_libtorch.bat
-    elif [[ "$PACKAGE_TYPE" == 'wheel' ]]; then
-        ./windows/arm64/build_pytorch.bat
-    fi
-else
-    ./windows/internal/build_wheels.bat
-fi
+./windows/internal/build_wheels.bat
 
 echo "Free space on filesystem after build:"
 df -h

.circleci/scripts/binary_windows_test.sh

@@ -11,11 +11,6 @@ if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
 fi
 
 pushd "$PYTORCH_ROOT/.ci/pytorch/"
-
-if [[ "$OS" == "windows-arm64" ]]; then
-    ./windows/arm64/smoke_test.bat
-else
-    ./windows/internal/smoke_test.bat
-fi
+./windows/internal/smoke_test.bat
 
 popd

.clang-tidy

@@ -12,7 +12,6 @@ bugprone-*,
 -bugprone-macro-parentheses,
 -bugprone-lambda-function-name,
 -bugprone-reserved-identifier,
--bugprone-return-const-ref-from-parameter,
 -bugprone-swapped-arguments,
 clang-analyzer-core.*,
 clang-analyzer-cplusplus.*,
@@ -25,7 +24,6 @@ cppcoreguidelines-*,
 -cppcoreguidelines-avoid-non-const-global-variables,
 -cppcoreguidelines-interfaces-global-init,
 -cppcoreguidelines-macro-usage,
--cppcoreguidelines-macro-to-enum,
 -cppcoreguidelines-owning-memory,
 -cppcoreguidelines-pro-bounds-array-to-pointer-decay,
 -cppcoreguidelines-pro-bounds-constant-array-index,
@@ -52,11 +50,11 @@ modernize-*,
 -modernize-macro-to-enum,
 -modernize-return-braced-init-list,
 -modernize-use-auto,
+-modernize-use-default-member-init,
 -modernize-use-using,
 -modernize-use-trailing-return-type,
 -modernize-use-nodiscard,
 performance-*,
--performance-enum-size,
 readability-container-size-empty,
 readability-delete-null-pointer,
 readability-duplicate-include

.editorconfig

@@ -1,14 +0,0 @@
-root = true
-
-[*]
-end_of_line = lf
-insert_final_newline = true
-
-# Python
-[*.py]
-indent_style = space
-indent_size = 4
-
-# Make
-[Makefile]
-indent_style = tab

.flake8

@@ -38,7 +38,6 @@ per-file-ignores =
     torchgen/api/types/__init__.py: F401,F403
     torchgen/executorch/api/types/__init__.py: F401,F403
     test/dynamo/test_higher_order_ops.py: B950
-    test/dynamo/test_error_messages.py: B950
     torch/testing/_internal/dynamo_test_failures.py: B950
     # TOR901 is only for test, we want to ignore it for everything else.
     # It's not easy to configure this without affecting other per-file-ignores,

.github/ISSUE_TEMPLATE/pt2-bug-report.yml

@@ -20,7 +20,7 @@ body:
 
         - Don't compare indices of max/min etc, because that avoids the above requirement
 
-        - When comparing eager and torch.compile, use a higher precision result as a baseline. `torch._dynamo.utils.same` with fp64_ref will handle this comparison.
+        - If comparing eager and torch.compile at fp16/bf16, you should use fp32 as baseline
 
         - Ensure rng state used to compare results is equivalent. Use `torch._inductor.config.fallback_random=True` and reset the torch rng seed between comparisons
 

.github/actionlint.yaml

@@ -1,10 +1,8 @@
 self-hosted-runner:
   labels:
-    # GitHub hosted runner that actionlint doesn't recognize because actionlint version (1.6.21) is too old
-    - ubuntu-24.04
     # GitHub hosted x86 Linux runners
-    - linux.24_04.4x
-    - linux.24_04.16x
+    - linux.20_04.4x
+    - linux.20_04.16x
     # Organization-wide AWS Linux Runners
     - linux.large
     - linux.2xlarge
@@ -12,6 +10,7 @@ self-hosted-runner:
     - linux.9xlarge.ephemeral
     - am2.linux.9xlarge.ephemeral
     - linux.12xlarge
+    - linux.12xlarge.ephemeral
     - linux.24xlarge
     - linux.24xlarge.ephemeral
     - linux.arm64.2xlarge
@@ -43,17 +42,10 @@ self-hosted-runner:
     - windows.8xlarge.nvidia.gpu
     - windows.8xlarge.nvidia.gpu.nonephemeral
     - windows.g5.4xlarge.nvidia.gpu
-    # Windows ARM64 runners
-    - windows-11-arm64
-    # Organization-wide AMD-hosted runners
-    # MI2xx runners
+    # Organization-wide AMD hosted runners
     - linux.rocm.gpu
     - linux.rocm.gpu.2
     - linux.rocm.gpu.4
-    # MI300 runners
-    - linux.rocm.gpu.mi300.2
-    - linux.rocm.gpu.mi300.4
-    - rocm-docker
     # Repo-specific Apple hosted  runners
     - macos-m1-ultra
     - macos-m2-14

.github/actions/binary-docker-build/action.yml

@@ -1,70 +0,0 @@
-name: Binary docker build
-
-description: Build docker image for binary builds
-
-inputs:
-  docker-image-name:
-    description: Docker image name for PR builds
-    required: true
-  docker-build-dir:
-    description: Location of the build.sh relative to .ci/docker
-    required: true
-  custom-tag-prefix:
-    description: Custom tag prefix for the docker image
-    required: false
-  DOCKER_TOKEN:
-    description: Docker token for authentication
-    required: true
-  DOCKER_ID:
-    description: Docker ID for authentication
-    required: true
-
-runs:
-  using: composite
-  steps:
-    - name: Checkout PyTorch
-      uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
-
-    - name: Calculate docker image
-      id: calculate-docker-image
-      uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
-      with:
-        docker-image-name: ${{ inputs.docker-image-name }}
-        docker-build-dir: .ci/docker
-        custom-tag-prefix: ${{ inputs.custom-tag-prefix }}
-        docker-build-script: ${{ inputs.docker-build-dir }}/build.sh
-        always-rebuild: true
-        push: true
-
-    - name: Tag and (if WITH_PUSH) push docker image to docker.io
-      env:
-        DOCKER_TOKEN: ${{ inputs.DOCKER_TOKEN }}
-        DOCKER_ID: ${{ inputs.DOCKER_ID }}
-        DOCKER_IMAGE_NAME: ${{ inputs.docker-image-name }}
-        DOCKER_IMAGE_PREFIX: ${{ inputs.custom-tag-prefix }}
-        CREATED_FULL_DOCKER_IMAGE_NAME: ${{ steps.calculate-docker-image.outputs.docker-image }}
-      shell: bash
-      run: |
-        set -euox pipefail
-        GITHUB_REF=${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)}
-        CI_FOLDER_SHA=$(git rev-parse HEAD:.ci/docker)
-
-        DOCKER_IMAGE_NAME_PREFIX=docker.io/pytorch/${DOCKER_IMAGE_NAME}:${DOCKER_IMAGE_PREFIX}
-
-        docker tag ${CREATED_FULL_DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_NAME_PREFIX}
-        docker tag ${CREATED_FULL_DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_NAME_PREFIX}-${GIT_BRANCH_NAME}
-        docker tag ${CREATED_FULL_DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_NAME_PREFIX}-${GIT_COMMIT_SHA}
-        docker tag ${CREATED_FULL_DOCKER_IMAGE_NAME} ${DOCKER_IMAGE_NAME_PREFIX}-${CI_FOLDER_SHA}
-
-        # Pretty sure Github will mask tokens and I'm not sure if it will even be
-        # printed due to pipe, but just in case
-        set +x
-        if [[ ${WITH_PUSH:-false} == "true" ]]; then
-          echo "${DOCKER_TOKEN}" | docker login -u "${DOCKER_ID}" --password-stdin
-          docker push ${DOCKER_IMAGE_NAME_PREFIX}
-          docker push ${DOCKER_IMAGE_NAME_PREFIX}-${GIT_BRANCH_NAME}
-          docker push ${DOCKER_IMAGE_NAME_PREFIX}-${GIT_COMMIT_SHA}
-          docker push ${DOCKER_IMAGE_NAME_PREFIX}-${CI_FOLDER_SHA}
-        fi

.github/actions/checkout-pytorch/action.yml

@@ -23,44 +23,9 @@ runs:
       id: check_container_runner
       run: echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
 
-    - name: Set up parallel fetch and clean workspace
-      id: first-clean
-      continue-on-error: true
+    - name: Clean workspace
       shell: bash
       if: ${{ steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' }}
-      env:
-        NO_SUDO: ${{ inputs.no-sudo }}
-      run: |
-        # Use all available CPUs for fetching
-        cd "${GITHUB_WORKSPACE}"
-        git config --global fetch.parallel 0
-        git config --global submodule.fetchJobs 0
-
-        # Clean workspace. The default checkout action should also do this, but
-        # do it here as well just in case
-        if [[ -d .git ]]; then
-          if [ -z "${NO_SUDO}" ]; then
-            sudo git clean -ffdx
-          else
-            git clean -ffdx
-          fi
-        fi
-
-    - name: Checkout PyTorch
-      id: first-checkout-attempt
-      continue-on-error: true
-      uses: actions/checkout@v4
-      with:
-        ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
-        # --depth=1 for speed, manually fetch history and other refs as necessary
-        fetch-depth: ${{ inputs.fetch-depth }}
-        submodules: ${{ inputs.submodules }}
-        show-progress: false
-
-    - name: Clean workspace (try again)
-      if: ${{ steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' &&
-        (steps.first-clean.outcome != 'success' || steps.first-checkout-attempt.outcome != 'success') }}
-      shell: bash
       env:
         NO_SUDO: ${{ inputs.no-sudo }}
       run: |
@@ -75,11 +40,11 @@ runs:
         fi
         mkdir "${GITHUB_WORKSPACE}"
 
-    - name: Checkout PyTorch (try again)
+    - name: Checkout PyTorch
       uses: actions/checkout@v4
-      if: ${{ steps.first-clean.outcome != 'success' || steps.first-checkout-attempt.outcome != 'success' }}
       with:
         ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
+        # --depth=1 for speed, manually fetch history and other refs as necessary
         fetch-depth: ${{ inputs.fetch-depth }}
         submodules: ${{ inputs.submodules }}
         show-progress: false

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

@@ -66,7 +66,7 @@ runs:
 
     - name: configure aws credentials
       if : ${{ inputs.aws-role-to-assume != '' }}
-      uses: aws-actions/configure-aws-credentials@v4
+      uses: aws-actions/configure-aws-credentials@v3
       with:
         role-to-assume: ${{ inputs.aws-role-to-assume }}
         role-session-name: gha-linux-test

.github/actions/test-pytorch-binary/action.yml

@@ -15,6 +15,7 @@ runs:
           -e BINARY_ENV_FILE \
           -e BUILD_ENVIRONMENT \
           -e DESIRED_CUDA \
+          -e DESIRED_DEVTOOLSET \
           -e DESIRED_PYTHON \
           -e GITHUB_ACTIONS \
           -e GPU_ARCH_TYPE \

.github/actions/upload-test-artifacts/action.yml

@@ -48,8 +48,14 @@ runs:
       run: |
         # Remove any previous usage logs if they exist
         rm -f logs-*.zip
-        zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt' || true
-        zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log' || true
+        # this workflow is also run in bazel build test, but we dont generate usage reports for it
+        # so check to see if the file exists first
+        if [ -f 'usage_log.txt' ]; then
+            zip "logs-${FILE_SUFFIX}.zip" 'usage_log.txt'
+        fi
+        if find "test/test-reports" -name "*.log" 2>/dev/null | grep -q .; then
+            zip -r "logs-${FILE_SUFFIX}.zip" test/test-reports -i '*.log'
+        fi
 
     - name: Zip debugging artifacts for upload
       if: runner.os != 'Windows' && !inputs.use-gha

.github/ci_commit_pins/audio.txt

@@ -1 +1 @@
-d60ce09e2c532d5bf2e05619e700ab520543465e
+f084f34bbb743fada85f66b0ed8041387565e69c

.github/ci_commit_pins/xla.txt

@@ -1 +1 @@
-ac9a39f4b768cef09b9d2be8e074be496d7783b6
+b2b890e962f5fb6f481e5da2eb4a43bb990d0f1b

.github/labeler.yml

@@ -98,7 +98,7 @@
 - test/distributed/**
 - torch/testing/_internal/distributed/**
 
-"release notes: distributed (checkpoint)":
+"module: distributed_checkpoint":
 - torch/distributed/checkpoint/**
 - test/distributed/checkpoint/**
 
@@ -112,22 +112,3 @@
 - torch/csrc/inductor/aoti_include/xpu.h
 - torch/csrc/inductor/cpp_wrapper/device_internal/xpu.h
 - torch/csrc/inductor/cpp_wrapper/xpu.h
-
-"release notes: inductor (aoti)":
-- torch/_C/_aoti.pyi
-- torch/_dynamo/repro/aoti.py
-- torch/_export/serde/aoti_schema.py
-- torch/_higher_order_ops/aoti_call_delegate.py
-- torch/_inductor/codegen/aoti_runtime/**
-- torch/_inductor/codegen/aoti_hipify_utils.py
-- torch/_inductor/codegen/cpp_wrapper_cpu.py
-- torch/_inductor/codegen/cpp_wrapper_gpu.py
-- torch/_inductor/aoti_eager.py
-- torch/csrc/inductor/aoti_runtime/**
-- torch/csrc/inductor/aoti_torch/**
-- torch/csrc/inductor/aoti_runner/**
-- torch/csrc/inductor/aoti_eager/**
-- torch/csrc/inductor/aoti_package/**
-- torch/csrc/inductor/aoti_include/**
-- torchgen/aoti/**
-- torchgen/gen_aoti_c_shim.py