[Experiment only] Collect cpp_wrapper perf numbers

.ci/aarch64_linux/aarch64_ci_build.sh

@@ -3,15 +3,22 @@ set -eux -o pipefail
 
 GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
 
-if [[ "$GPU_ARCH_VERSION" == *"12.6"* ]]; then
-    export TORCH_CUDA_ARCH_LIST="9.0"
-elif [[ "$GPU_ARCH_VERSION" == *"12.8"* ]]; then
-    export TORCH_CUDA_ARCH_LIST="9.0;10.0;12.0"
-fi
-
 SCRIPTPATH="$( cd -- "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P )"
 source $SCRIPTPATH/aarch64_ci_setup.sh
 
+tagged_version() {
+  GIT_DESCRIBE="git --git-dir /pytorch/.git describe --tags --match v[0-9]*.[0-9]*.[0-9]*"
+  if ${GIT_DESCRIBE} --exact >/dev/null; then
+    ${GIT_DESCRIBE}
+  else
+    return 1
+  fi
+}
+
+if tagged_version >/dev/null; then
+  export OVERRIDE_PACKAGE_VERSION="$(tagged_version | sed -e 's/^v//' -e 's/-.*$//')"
+fi
+
 ###############################################################################
 # Run aarch64 builder python
 ###############################################################################
@@ -20,7 +27,7 @@ cd /
 # on the mounted pytorch repo
 git config --global --add safe.directory /pytorch
 pip install -r /pytorch/requirements.txt
-pip install auditwheel==6.2.0
+pip install auditwheel
 if [ "$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_ci_setup.sh

@@ -5,14 +5,16 @@ set -eux -o pipefail
 # By creating symlinks from desired /opt/python to /usr/local/bin/
 
 NUMPY_VERSION=2.0.2
-if [[ "$DESIRED_PYTHON"  == "3.13" || "$DESIRED_PYTHON" == "3.13t" ]]; then
+PYGIT2_VERSION=1.15.1
+if [[ "$DESIRED_PYTHON"  == "3.13" ]]; then
     NUMPY_VERSION=2.1.2
+    PYGIT2_VERSION=1.16.0
 fi
 
 SCRIPTPATH="$( cd "$(dirname "$0")" ; pwd -P )"
 source $SCRIPTPATH/../manywheel/set_desired_python.sh
 
-pip install -q numpy==${NUMPY_VERSION} pyyaml==6.0.2 scons==4.7.0 ninja==1.11.1 patchelf==0.17.2
+pip install -q numpy==${NUMPY_VERSION} pyyaml==6.0.2 scons==4.7.0 ninja==1.11.1 patchelf==0.17.2 pygit2==${PYGIT2_VERSION}
 
 for tool in python python3 pip pip3 ninja scons patchelf; do
     ln -sf ${DESIRED_PYTHON_BIN_DIR}/${tool} /usr/local/bin;

.ci/aarch64_linux/aarch64_wheel_ci_build.py

@@ -4,9 +4,12 @@
 import os
 import shutil
 from subprocess import check_call, check_output
+from typing import List
+
+from pygit2 import Repository
 
 
-def list_dir(path: str) -> list[str]:
+def list_dir(path: str) -> List[str]:
     """'
     Helper for getting paths for Python
     """
@@ -31,47 +34,33 @@ def build_ArmComputeLibrary() -> None:
         "build=native",
     ]
     acl_install_dir = "/acl"
-    acl_checkout_dir = os.getenv("ACL_SOURCE_DIR", "ComputeLibrary")
-    if os.path.isdir(acl_install_dir):
-        shutil.rmtree(acl_install_dir)
-    if not os.path.isdir(acl_checkout_dir) or not len(os.listdir(acl_checkout_dir)):
-        check_call(
-            [
-                "git",
-                "clone",
-                "https://github.com/ARM-software/ComputeLibrary.git",
-                "-b",
-                "v25.02",
-                "--depth",
-                "1",
-                "--shallow-submodules",
-            ]
-        )
+    acl_checkout_dir = "ComputeLibrary"
+    os.makedirs(acl_install_dir)
+    check_call(
+        [
+            "git",
+            "clone",
+            "https://github.com/ARM-software/ComputeLibrary.git",
+            "-b",
+            "v24.09",
+            "--depth",
+            "1",
+            "--shallow-submodules",
+        ]
+    )
 
     check_call(
-        ["scons", "Werror=1", f"-j{os.cpu_count()}"] + acl_build_flags,
+        ["scons", "Werror=1", "-j8", f"build_dir=/{acl_install_dir}/build"]
+        + acl_build_flags,
         cwd=acl_checkout_dir,
     )
-    for d in ["arm_compute", "include", "utils", "support", "src", "build"]:
+    for d in ["arm_compute", "include", "utils", "support", "src"]:
         shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
 
 
-def replace_tag(filename) -> None:
-    with open(filename) as f:
-        lines = f.readlines()
-    for i, line in enumerate(lines):
-        if line.startswith("Tag:"):
-            lines[i] = line.replace("-linux_", "-manylinux_2_28_")
-            print(f"Updated tag from {line} to {lines[i]}")
-            break
-
-    with open(filename, "w") as f:
-        f.writelines(lines)
-
-
-def package_cuda_wheel(wheel_path, desired_cuda) -> None:
+def update_wheel(wheel_path) -> None:
     """
-    Package the cuda wheel libraries
+    Update the cuda wheel libraries
     """
     folder = os.path.dirname(wheel_path)
     wheelname = os.path.basename(wheel_path)
@@ -91,6 +80,7 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
         "/usr/local/cuda/lib64/libnvToolsExt.so.1",
         "/usr/local/cuda/lib64/libnvJitLink.so.12",
         "/usr/local/cuda/lib64/libnvrtc.so.12",
+        "/usr/local/cuda/lib64/libnvrtc-builtins.so.12.4",
         "/usr/local/cuda/lib64/libcudnn_adv.so.9",
         "/usr/local/cuda/lib64/libcudnn_cnn.so.9",
         "/usr/local/cuda/lib64/libcudnn_graph.so.9",
@@ -102,19 +92,18 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
         "/usr/lib64/libgfortran.so.5",
         "/acl/build/libarm_compute.so",
         "/acl/build/libarm_compute_graph.so",
-        "/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
-        "/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
-        "/usr/local/lib/libnvpl_lapack_core.so.0",
-        "/usr/local/lib/libnvpl_blas_core.so.0",
     ]
-
-    if "128" in desired_cuda:
+    if enable_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",
+            "/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
+            "/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
+            "/usr/local/lib/libnvpl_lapack_core.so.0",
+            "/usr/local/lib/libnvpl_blas_core.so.0",
+        ]
+    else:
+        libs_to_copy += [
+            "/opt/OpenBLAS/lib/libopenblas.so.0",
         ]
-
     # Copy libraries to unzipped_folder/a/lib
     for lib_path in libs_to_copy:
         lib_name = os.path.basename(lib_path)
@@ -123,13 +112,6 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
             f"cd {folder}/tmp/torch/lib/; "
             f"patchelf --set-rpath '$ORIGIN' --force-rpath {folder}/tmp/torch/lib/{lib_name}"
         )
-
-    # Make sure the wheel is tagged with manylinux_2_28
-    for f in os.scandir(f"{folder}/tmp/"):
-        if f.is_dir() and f.name.endswith(".dist-info"):
-            replace_tag(f"{f.path}/WHEEL")
-            break
-
     os.mkdir(f"{folder}/cuda_wheel")
     os.system(f"cd {folder}/tmp/; zip -r {folder}/cuda_wheel/{wheelname} *")
     shutil.move(
@@ -146,9 +128,6 @@ 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)
@@ -160,14 +139,7 @@ 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(
@@ -199,24 +171,22 @@ if __name__ == "__main__":
     args = parse_arguments()
     enable_mkldnn = args.enable_mkldnn
     enable_cuda = args.enable_cuda
-    branch = check_output(
-        ["git", "rev-parse", "--abbrev-ref", "HEAD"], cwd="/pytorch"
-    ).decode()
+    repo = Repository("/pytorch")
+    branch = repo.head.name
+    if branch == "HEAD":
+        branch = "master"
 
     print("Building PyTorch wheel")
-    build_vars = "CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000 "
-    # MAX_JOB=5 is not required for CPU backend (see commit 465d98b)
-    if enable_cuda:
-        build_vars = "MAX_JOBS=5 " + build_vars
+    build_vars = "MAX_JOBS=5 CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000 "
+    os.system("cd /pytorch; python setup.py clean")
 
     override_package_version = os.getenv("OVERRIDE_PACKAGE_VERSION")
-    desired_cuda = os.getenv("DESIRED_CUDA")
     if override_package_version is not None:
         version = override_package_version
         build_vars += (
             f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version} PYTORCH_BUILD_NUMBER=1 "
         )
-    elif branch in ["nightly", "main"]:
+    elif branch in ["nightly", "master"]:
         build_date = (
             check_output(["git", "log", "--pretty=format:%cs", "-1"], cwd="/pytorch")
             .decode()
@@ -226,11 +196,12 @@ if __name__ == "__main__":
             check_output(["cat", "version.txt"], cwd="/pytorch").decode().strip()[:-2]
         )
         if enable_cuda:
+            desired_cuda = os.getenv("DESIRED_CUDA")
             build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version}.dev{build_date}+{desired_cuda} PYTORCH_BUILD_NUMBER=1 "
         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()
@@ -254,6 +225,6 @@ if __name__ == "__main__":
         print("Updating Cuda Dependency")
         filename = os.listdir("/pytorch/dist/")
         wheel_path = f"/pytorch/dist/{filename[0]}"
-        package_cuda_wheel(wheel_path, desired_cuda)
+        update_wheel(wheel_path)
     pytorch_wheel_name = complete_wheel("/pytorch/")
     print(f"Build Complete. Created {pytorch_wheel_name}..")

.ci/aarch64_linux/build_aarch64_wheel.py

@@ -12,22 +12,22 @@ import os
 import subprocess
 import sys
 import time
-from typing import Optional, Union
+from typing import Dict, List, Optional, Tuple, Union
 
 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
 }
-
-ubuntu20_04_ami = os_amis["ubuntu20_04"]
+ubuntu18_04_ami = os_amis["ubuntu18_04"]
 
 
-def compute_keyfile_path(key_name: Optional[str] = None) -> tuple[str, str]:
+def compute_keyfile_path(key_name: Optional[str] = None) -> Tuple[str, str]:
     if key_name is None:
         key_name = os.getenv("AWS_KEY_NAME")
         if key_name is None:
@@ -57,7 +57,7 @@ def ec2_instances_by_id(instance_id):
 
 
 def start_instance(
-    key_name, ami=ubuntu20_04_ami, instance_type="t4g.2xlarge", ebs_size: int = 50
+    key_name, ami=ubuntu18_04_ami, instance_type="t4g.2xlarge", ebs_size: int = 50
 ):
     inst = ec2.create_instances(
         ImageId=ami,
@@ -96,7 +96,7 @@ class RemoteHost:
         self.keyfile_path = keyfile_path
         self.login_name = login_name
 
-    def _gen_ssh_prefix(self) -> list[str]:
+    def _gen_ssh_prefix(self) -> List[str]:
         return [
             "ssh",
             "-o",
@@ -108,13 +108,13 @@ class RemoteHost:
         ]
 
     @staticmethod
-    def _split_cmd(args: Union[str, list[str]]) -> list[str]:
+    def _split_cmd(args: Union[str, List[str]]) -> List[str]:
         return args.split() if isinstance(args, str) else args
 
-    def run_ssh_cmd(self, args: Union[str, list[str]]) -> None:
+    def run_ssh_cmd(self, args: Union[str, List[str]]) -> None:
         subprocess.check_call(self._gen_ssh_prefix() + self._split_cmd(args))
 
-    def check_ssh_output(self, args: Union[str, list[str]]) -> str:
+    def check_ssh_output(self, args: Union[str, List[str]]) -> str:
         return subprocess.check_output(
             self._gen_ssh_prefix() + self._split_cmd(args)
         ).decode("utf-8")
@@ -157,7 +157,7 @@ class RemoteHost:
     def using_docker(self) -> bool:
         return self.container_id is not None
 
-    def run_cmd(self, args: Union[str, list[str]]) -> None:
+    def run_cmd(self, args: Union[str, List[str]]) -> None:
         if not self.using_docker():
             return self.run_ssh_cmd(args)
         assert self.container_id is not None
@@ -178,7 +178,7 @@ class RemoteHost:
         if rc != 0:
             raise subprocess.CalledProcessError(rc, docker_cmd)
 
-    def check_output(self, args: Union[str, list[str]]) -> str:
+    def check_output(self, args: Union[str, List[str]]) -> str:
         if not self.using_docker():
             return self.check_ssh_output(args)
         assert self.container_id is not None
@@ -230,7 +230,7 @@ class RemoteHost:
             )
         self.download_file(remote_file, local_file)
 
-    def list_dir(self, path: str) -> list[str]:
+    def list_dir(self, path: str) -> List[str]:
         return self.check_output(["ls", "-1", path]).split("\n")
 
 
@@ -327,7 +327,7 @@ def build_ArmComputeLibrary(host: RemoteHost, git_clone_flags: str = "") -> None
         ]
     )
     host.run_cmd(
-        f"git clone https://github.com/ARM-software/ComputeLibrary.git -b v25.02 {git_clone_flags}"
+        f"git clone https://github.com/ARM-software/ComputeLibrary.git -b v24.09 {git_clone_flags}"
     )
 
     host.run_cmd(f"cd ComputeLibrary && scons Werror=1 -j8 {acl_build_flags}")
@@ -358,7 +358,7 @@ def checkout_repo(
     branch: str = "main",
     url: str,
     git_clone_flags: str,
-    mapping: dict[str, tuple[str, str]],
+    mapping: Dict[str, Tuple[str, str]],
 ) -> Optional[str]:
     for prefix in mapping:
         if not branch.startswith(prefix):
@@ -619,11 +619,9 @@ def build_torchaudio(
     if host.using_docker():
         build_vars += " CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000"
 
-    host.run_cmd(
-        f"cd audio && export FFMPEG_ROOT=$(pwd)/third_party/ffmpeg && export USE_FFMPEG=1 \
+    host.run_cmd(f"cd audio && export FFMPEG_ROOT=$(pwd)/third_party/ffmpeg && export USE_FFMPEG=1 \
         && ./packaging/ffmpeg/build.sh \
-        && {build_vars} python3 setup.py bdist_wheel"
-    )
+        && {build_vars} python3 setup.py bdist_wheel")
 
     wheel_name = host.list_dir("audio/dist")[0]
     embed_libgomp(host, use_conda, os.path.join("audio", "dist", wheel_name))
@@ -657,6 +655,18 @@ 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")
@@ -669,7 +679,7 @@ def build_domains(
     branch: str = "main",
     use_conda: bool = True,
     git_clone_flags: str = "",
-) -> tuple[str, str, str, str]:
+) -> Tuple[str, str, str, str]:
     vision_wheel_name = build_torchvision(
         host, branch=branch, use_conda=use_conda, git_clone_flags=git_clone_flags
     )
@@ -696,7 +706,7 @@ def start_build(
     pytorch_build_number: Optional[str] = None,
     shallow_clone: bool = True,
     enable_mkldnn: bool = False,
-) -> tuple[str, str, str, str, str]:
+) -> Tuple[str, str, str, str, str]:
     git_clone_flags = " --depth 1 --shallow-submodules" if shallow_clone else ""
     if host.using_docker() and not use_conda:
         print("Auto-selecting conda option for docker images")
@@ -747,7 +757,7 @@ 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:
@@ -920,9 +930,9 @@ def parse_arguments():
     parser.add_argument("--debug", action="store_true")
     parser.add_argument("--build-only", action="store_true")
     parser.add_argument("--test-only", type=str)
-    group = parser.add_mutually_exclusive_group()
-    group.add_argument("--os", type=str, choices=list(os_amis.keys()))
-    group.add_argument("--ami", type=str)
+    parser.add_argument(
+        "--os", type=str, choices=list(os_amis.keys()), default="ubuntu20_04"
+    )
     parser.add_argument(
         "--python-version",
         type=str,
@@ -952,13 +962,7 @@ def parse_arguments():
 
 if __name__ == "__main__":
     args = parse_arguments()
-    ami = (
-        args.ami
-        if args.ami is not None
-        else os_amis[args.os]
-        if args.os is not None
-        else ubuntu20_04_ami
-    )
+    ami = os_amis[args.os]
     keyfile_path, key_name = compute_keyfile_path(args.key_name)
 
     if args.list_instances:
@@ -1012,7 +1016,7 @@ 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/caffe2/README.md

@@ -10,3 +10,5 @@ example: `py2-cuda9.0-cudnn7-ubuntu16.04`. The Docker images that are
 built on Jenkins and are used in triggered builds already have this
 environment variable set in their manifest. Also see
 `./docker/jenkins/*/Dockerfile` and search for `BUILD_ENVIRONMENT`.
+
+Our Jenkins installation is located at https://ci.pytorch.org/jenkins/.

.ci/caffe2/test.sh

@@ -13,6 +13,10 @@ if [[ "${BUILD_ENVIRONMENT}" == *-android* ]]; then
   echo 'Skipping tests'
   exit 0
 fi
+if [[ "${BUILD_ENVIRONMENT}" == *-rocm* ]]; then
+  # temporary to locate some kernel issues on the CI nodes
+  export HSAKMT_DEBUG_LEVEL=4
+fi
 # These additional packages are needed for circleci ROCm builds.
 if [[ $BUILD_ENVIRONMENT == *rocm* ]]; then
     # Need networkx 2.0 because bellmand_ford was moved in 2.1 . Scikit-image by

.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

@@ -1,7 +1,6 @@
 ARG CUDA_VERSION=12.4
 ARG BASE_TARGET=cuda${CUDA_VERSION}
-ARG ROCM_IMAGE=rocm/dev-almalinux-8:6.3-complete
-FROM amd64/almalinux:8.10-20250519 as base
+FROM amd64/almalinux:8 as base
 
 ENV LC_ALL en_US.UTF-8
 ENV LANG en_US.UTF-8
@@ -9,10 +8,12 @@ ENV LANGUAGE en_US.UTF-8
 
 ARG DEVTOOLSET_VERSION=11
 
+ENV LC_ALL en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US.UTF-8
+
 RUN yum -y update
 RUN yum -y install epel-release
-# install glibc-langpack-en make sure en_US.UTF-8 locale is available
-RUN yum -y install glibc-langpack-en
 RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel openssl-devel yum-utils autoconf automake make gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
 # Just add everything as a safe.directory for git since these will be used in multiple places with git
 RUN git config --global --add safe.directory '*'
@@ -40,12 +41,9 @@ RUN bash ./install_conda.sh && rm install_conda.sh
 
 # Install CUDA
 FROM base as cuda
-ARG CUDA_VERSION=12.6
+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}
@@ -56,20 +54,18 @@ FROM cuda as cuda11.8
 RUN bash ./install_cuda.sh 11.8
 ENV DESIRED_CUDA=11.8
 
+FROM cuda as cuda12.1
+RUN bash ./install_cuda.sh 12.1
+ENV DESIRED_CUDA=12.1
+
+FROM cuda as cuda12.4
+RUN bash ./install_cuda.sh 12.4
+ENV DESIRED_CUDA=12.4
+
 FROM cuda as cuda12.6
 RUN bash ./install_cuda.sh 12.6
 ENV DESIRED_CUDA=12.6
 
-FROM cuda as cuda12.8
-RUN bash ./install_cuda.sh 12.8
-ENV DESIRED_CUDA=12.8
-
-FROM ${ROCM_IMAGE} as rocm
-ENV PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
-ADD ./common/install_mkl.sh install_mkl.sh
-RUN bash ./install_mkl.sh && rm install_mkl.sh
-ENV MKLROOT /opt/intel
-
 # Install MNIST test data
 FROM base as mnist
 ADD ./common/install_mnist.sh install_mnist.sh
@@ -77,8 +73,9 @@ RUN bash ./install_mnist.sh
 
 FROM base as all_cuda
 COPY --from=cuda11.8  /usr/local/cuda-11.8 /usr/local/cuda-11.8
+COPY --from=cuda12.1  /usr/local/cuda-12.1 /usr/local/cuda-12.1
+COPY --from=cuda12.4  /usr/local/cuda-12.4 /usr/local/cuda-12.4
 COPY --from=cuda12.6  /usr/local/cuda-12.6 /usr/local/cuda-12.6
-COPY --from=cuda12.4  /usr/local/cuda-12.8 /usr/local/cuda-12.8
 
 # Final step
 FROM ${BASE_TARGET} as final

.ci/docker/almalinux/build.sh

@@ -1,70 +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=""
-ROCM_VERSION=""
-EXTRA_BUILD_ARGS=""
-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 $2}')
-    EXTRA_BUILD_ARGS="--build-arg CUDA_VERSION=${CUDA_VERSION}"
-elif [[ "${DOCKER_TAG_PREFIX}" == rocm* ]]; then
-    # extract rocm version from image name and tag.  e.g. manylinux2_28-builder:rocm6.2.4 returns 6.2.4
-    ROCM_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'rocm' '{print $2}')
-    EXTRA_BUILD_ARGS="--build-arg ROCM_IMAGE=rocm/dev-almalinux-8:${ROCM_VERSION}-complete"
-fi
-
-case ${DOCKER_TAG_PREFIX} in
-  cpu)
-    BASE_TARGET=base
-    ;;
-  cuda*)
-    BASE_TARGET=cuda${CUDA_VERSION}
-    ;;
-  rocm*)
-    BASE_TARGET=rocm
-    ;;
-  *)
-    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 "DEVTOOLSET_VERSION=11" \
-  ${EXTRA_BUILD_ARGS} \
-  -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/aotriton_version.txt

@@ -0,0 +1,5 @@
+0.7b
+manylinux_2_17
+rocm6.2
+9be04068c3c0857a4cfd17d7e39e71d0423ebac2
+3e9e1959d23b93d78a08fcc5f868125dc3854dece32fd9458be9ef4467982291

.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
 
@@ -85,86 +81,101 @@ elif [[ "$image" == *linter* ]]; then
   DOCKERFILE="linter/Dockerfile"
 fi
 
+# CMake 3.18 is needed to support CUDA17 language variant
+CMAKE_VERSION=3.18.5
+
 _UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
 _UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
-if [[ "$image" == *rocm* ]]; then
-  _UCX_COMMIT=cc312eaa4655c0cc5c2bcd796db938f90563bcf6
-  _UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d
-fi
-
-tag=$(echo $image | awk -F':' '{print $2}')
 
 # It's annoying to rename jobs every time you want to rewrite a
 # configuration, so we hardcode everything here rather than do it
 # from scratch
-case "$tag" in
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc11)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    TRITON=yes
-    ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.8
+case "$image" in
+  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.4.1
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.1.1
+    CUDNN_VERSION=9
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.4.1
+    CUDNN_VERSION=9
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-focal-cuda12.6-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}
-    TRITON=yes
-    ;;
-  pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6
+  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.1.1
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6
+  pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.1.1
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6
+  pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.4.1
     CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.13
+    ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
@@ -173,81 +184,149 @@ case "$tag" in
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.4.1
+    CUDNN_VERSION=9
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.1.1
+    CUDNN_VERSION=9
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.4.1
+    CUDNN_VERSION=9
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
   pytorch-linux-focal-py3-clang10-onnx)
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=10
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
+    CONDA_CMAKE=yes
     ONNX=yes
     ;;
   pytorch-linux-focal-py3.9-clang10)
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=10
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
+    VULKAN_SDK_VERSION=1.2.162.1
+    SWIFTSHADER=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
   pytorch-linux-focal-py3.11-clang10)
     ANACONDA_PYTHON_VERSION=3.11
     CLANG_VERSION=10
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
+    VULKAN_SDK_VERSION=1.2.162.1
+    SWIFTSHADER=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
   pytorch-linux-focal-py3.9-gcc9)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-rocm-n-1-py3)
+  pytorch-linux-focal-rocm-n-1-py3)
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
-    ROCM_VERSION=6.3
+    ROCM_VERSION=6.1
     NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
     TRITON=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-rocm-n-py3)
+  pytorch-linux-focal-rocm-n-py3)
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
-    ROCM_VERSION=6.4
+    ROCM_VERSION=6.2.4
     NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-jammy-xpu-2024.0-py3)
+    ANACONDA_PYTHON_VERSION=3.9
+    GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    XPU_VERSION=0.5
+    NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
     TRITON=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    INDUCTOR_BENCHMARKS=yes
     ;;
   pytorch-linux-jammy-xpu-2025.0-py3)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     XPU_VERSION=2025.0
     NINJA_VERSION=1.9.0
-    TRITON=yes
-    ;;
-  pytorch-linux-jammy-xpu-2025.1-py3)
-    ANACONDA_PYTHON_VERSION=3.9
-    GCC_VERSION=11
-    VISION=yes
-    XPU_VERSION=2025.1
-    NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
     pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     DOCS=yes
     INDUCTOR_BENCHMARKS=yes
@@ -257,30 +336,40 @@ case "$tag" 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
     ;;
   pytorch-linux-jammy-py3-clang15-asan)
     ANACONDA_PYTHON_VERSION=3.10
     CLANG_VERSION=15
+    CONDA_CMAKE=yes
     VISION=yes
     ;;
   pytorch-linux-jammy-py3-clang18-asan)
     ANACONDA_PYTHON_VERSION=3.10
     CLANG_VERSION=18
+    CONDA_CMAKE=yes
     VISION=yes
     ;;
   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
     TRITON=yes
     DOCS=yes
     UNINSTALL_DILL=yes
@@ -288,36 +377,44 @@ case "$tag" in
   pytorch-linux-jammy-py3-clang12-executorch)
     ANACONDA_PYTHON_VERSION=3.10
     CLANG_VERSION=12
+    CONDA_CMAKE=yes
     EXECUTORCH=yes
     ;;
   pytorch-linux-jammy-py3.12-halide)
-    CUDA_VERSION=12.6
+    CUDA_VERSION=12.4
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
+    CONDA_CMAKE=yes
     HALIDE=yes
     TRITON=yes
     ;;
   pytorch-linux-jammy-py3.12-triton-cpu)
-    CUDA_VERSION=12.6
+    CUDA_VERSION=12.4
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
+    CONDA_CMAKE=yes
     TRITON_CPU=yes
     ;;
   pytorch-linux-focal-linter)
     # TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
     # We will need to update mypy version eventually, but that's for another day. The task
     # would be to upgrade mypy to 1.0.0 with Python 3.11
-    PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.9
+    CONDA_CMAKE=yes
     ;;
   pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
-    PYTHON_VERSION=3.9
+    ANACONDA_PYTHON_VERSION=3.9
     CUDA_VERSION=11.8
+    CONDA_CMAKE=yes
     ;;
   pytorch-linux-jammy-aarch64-py3.10-gcc11)
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=11
     ACL=yes
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
+    CONDA_CMAKE=yes
     # snadampal: skipping llvm src build install because the current version
     # from pytorch/llvm:9.0.1 is x86 specific
     SKIP_LLVM_SRC_BUILD_INSTALL=yes
@@ -326,7 +423,10 @@ case "$tag" 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
     # from pytorch/llvm:9.0.1 is x86 specific
     SKIP_LLVM_SRC_BUILD_INSTALL=yes
@@ -334,6 +434,8 @@ case "$tag" in
     ;;
   *)
     # Catch-all for builds that are not hardcoded.
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     echo "image '$image' did not match an existing build configuration"
     if [[ "$image" == *py* ]]; then
@@ -349,7 +451,8 @@ case "$tag" in
       TRITON=yes
       # To ensure that any ROCm config will build using conda cmake
       # and thus have LAPACK/MKL enabled
-      fi
+      CONDA_CMAKE=yes
+    fi
     if [[ "$image" == *centos7* ]]; then
       NINJA_VERSION=1.10.2
     fi
@@ -365,6 +468,9 @@ case "$tag" in
     if [[ "$image" == *glibc* ]]; then
       extract_version_from_image_name glibc GLIBC_VERSION
     fi
+    if [[ "$image" == *cmake* ]]; then
+      extract_version_from_image_name cmake CMAKE_VERSION
+    fi
   ;;
 esac
 
@@ -378,20 +484,14 @@ 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}" \
@@ -399,19 +499,22 @@ 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:-}" \
        --build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
-       --build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx90a;gfx942}" \
+       --build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx90a}" \
        --build-arg "IMAGE_NAME=${IMAGE_NAME}" \
        --build-arg "UCX_COMMIT=${UCX_COMMIT}" \
        --build-arg "UCC_COMMIT=${UCC_COMMIT}" \
+       --build-arg "CONDA_CMAKE=${CONDA_CMAKE}" \
        --build-arg "TRITON=${TRITON}" \
        --build-arg "TRITON_CPU=${TRITON_CPU}" \
        --build-arg "ONNX=${ONNX}" \
@@ -420,7 +523,6 @@ docker build \
        --build-arg "EXECUTORCH=${EXECUTORCH}" \
        --build-arg "HALIDE=${HALIDE}" \
        --build-arg "XPU_VERSION=${XPU_VERSION}" \
-       --build-arg "UNINSTALL_DILL=${UNINSTALL_DILL}" \
        --build-arg "ACL=${ACL:-}" \
        --build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
        --build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
@@ -438,7 +540,7 @@ docker build \
 UBUNTU_VERSION=$(echo ${UBUNTU_VERSION} | sed 's/-rc$//')
 
 function drun() {
-  docker run --rm "$tmp_tag" "$@"
+  docker run --rm "$tmp_tag" $*
 }
 
 if [[ "$OS" == "ubuntu" ]]; then
@@ -486,23 +588,3 @@ if [ -n "$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 [ "$HAS_TRITON" = "yes" ]; then
-  echo "expecting triton to not be installed, but it is"
-  exit 1
-fi
-
-# Sanity check cmake version.  Executorch reinstalls cmake and I'm not sure if
-# they support 4.0.0 yet, so exclude them from this check.
-CMAKE_VERSION=$(drun cmake --version)
-if [[ "$EXECUTORCH" != *yes* && "$CMAKE_VERSION" != *4.* ]]; then
-  echo "CMake version is not 4.0.0:"
-  drun cmake --version
-  exit 1
-fi

.ci/docker/centos-rocm/Dockerfile

@@ -17,8 +17,9 @@ RUN bash ./install_base.sh && rm install_base.sh
 # Update CentOS git version
 RUN yum -y remove git
 RUN yum -y remove git-*
-RUN yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
-    sed -i 's/packages.endpoint/packages.endpointdev/' /etc/yum.repos.d/endpoint.repo
+RUN yum -y install https://packages.endpoint.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm || \
+    (yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
+    sed -i "s/packages.endpoint/packages.endpointdev/" /etc/yum.repos.d/endpoint.repo)
 RUN yum install -y git
 
 # Install devtoolset
@@ -39,6 +40,7 @@ RUN bash ./install_user.sh && rm install_user.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
 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
@@ -46,6 +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 ./
@@ -59,7 +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
@@ -73,6 +89,12 @@ ENV MAGMA_HOME /opt/rocm/magma
 ENV LANG en_US.utf8
 ENV LC_ALL en_US.utf8
 
+# (optional) Install non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
+
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
 COPY ./common/install_ninja.sh install_ninja.sh
@@ -91,6 +113,13 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
 RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
 
+# Install AOTriton (Early fail)
+COPY ./aotriton_version.txt aotriton_version.txt
+COPY ./common/common_utils.sh common_utils.sh
+COPY ./common/install_aotriton.sh install_aotriton.sh
+RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
+ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
+
 # Install ccache/sccache (do this last, so we get priority in PATH)
 COPY ./common/install_cache.sh install_cache.sh
 ENV PATH /opt/cache/bin:$PATH

.ci/docker/ci_commit_pins/executorch.txt

@@ -1 +1 @@
-b173722085b3f555d6ba4533d6bbaddfd7c71144
+6f638937d64e3396793956d75ee3e14802022745

.ci/docker/ci_commit_pins/nccl-cu11.txt

@@ -1 +0,0 @@
-v2.21.5-1

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

@@ -1 +0,0 @@
-v2.26.5-1

.ci/docker/ci_commit_pins/timm.txt

@@ -1 +1 @@
-5d535d7a2d4b435b1b5c1177fd8f04a12b942b9a
+ac3470188b914c5d7a5058a7e28b9eb685a62427

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

@@ -1 +1 @@
-b0e26b7359c147b8aa0af686c20510fb9b15990a
+e98b6fcb8df5b44eb0d0addb6767c573d37ba024

.ci/docker/ci_commit_pins/triton.txt

@@ -1 +1 @@
-c8757738a7418249896224430ce84888e8ecdd79
+35c6c7c6284582b3f41c71c150e11b517acf074a

.ci/docker/common/install_acl.sh

@@ -1,7 +1,7 @@
 set -euo pipefail
 
-readonly version=v25.02
-readonly src_host=https://github.com/ARM-software
+readonly version=v24.04
+readonly src_host=https://review.mlplatform.org/ml
 readonly src_repo=ComputeLibrary
 
 # Clone ACL

.ci/docker/common/install_aotriton.sh

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

.ci/docker/common/install_base.sh

@@ -32,12 +32,8 @@ install_ubuntu() {
 
   # HACK: UCC testing relies on libnccl library from NVIDIA repo, and version 2.16 crashes
   # See https://github.com/pytorch/pytorch/pull/105260#issuecomment-1673399729
-  # TODO: Eliminate this hack, we should not relay on apt-get installation
-  # See https://github.com/pytorch/pytorch/issues/144768
   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"
   else
     maybe_libnccl_dev=""
   fi
@@ -80,8 +76,7 @@ install_ubuntu() {
     vim \
     unzip \
     gpg-agent \
-    gdb \
-    bc
+    gdb
 
   # Should resolve issues related to various apt package repository cert issues
   # see: https://github.com/pytorch/pytorch/issues/65931
@@ -99,6 +94,9 @@ 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_cache.sh

@@ -9,7 +9,12 @@ install_ubuntu() {
   # Instead use lib and headers from OpenSSL1.1 installed in `install_openssl.sh``
   apt-get install -y cargo
   echo "Checking out sccache repo"
-  git clone https://github.com/mozilla/sccache -b v0.10.0
+  if [ -n "$CUDA_VERSION" ]; then
+      # TODO: Remove this
+      git clone https://github.com/pytorch/sccache
+  else
+      git clone https://github.com/mozilla/sccache -b v0.8.2
+  fi
   cd sccache
   echo "Building sccache"
   cargo build --release
@@ -36,33 +41,41 @@ sed -e 's|PATH="\(.*\)"|PATH="/opt/cache/bin:\1"|g' -i /etc/environment
 export PATH="/opt/cache/bin:$PATH"
 
 # Setup compiler cache
-install_ubuntu
+if [ -n "$ROCM_VERSION" ]; then
+  curl --retry 3 http://repo.radeon.com/misc/.sccache_amd/sccache -o /opt/cache/bin/sccache
+else
+  ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
+  if [ -n "$CUDA_VERSION" ]; then
+    # TODO: Install the pre-built binary from S3 as building from source
+    # https://github.com/pytorch/sccache has started failing mysteriously
+    # in which sccache server couldn't start with the following error:
+    #   sccache: error: Invalid argument (os error 22)
+    install_binary
+  else
+    install_ubuntu
+  fi
+fi
 chmod a+x /opt/cache/bin/sccache
 
 function write_sccache_stub() {
   # Unset LD_PRELOAD for ps because of asan + ps issues
   # https://gcc.gnu.org/bugzilla/show_bug.cgi?id=90589
   if [ $1 == "gcc" ]; then
-    # Do not call sccache recursively when dumping preprocessor argument
-    # For some reason it's very important for the first cached nvcc invocation
-    cat >"/opt/cache/bin/$1" <<EOF
+  # Do not call sccache recursively when dumping preprocessor argument
+  # For some reason it's very important for the first cached nvcc invocation
+    cat > "/opt/cache/bin/$1" <<EOF
 #!/bin/sh
 
-# sccache does not support -E flag, so we need to call the original compiler directly in order to avoid calling this wrapper recursively
-for arg in "\$@"; do
-  if [ "\$arg" = "-E" ]; then
-    exec $(which $1) "\$@"
-  fi
-done
-
-if [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
+if [ "\$1" = "-E" ] || [ "\$2" = "-E" ]; then
+  exec $(which $1) "\$@"
+elif [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
   exec sccache $(which $1) "\$@"
 else
   exec $(which $1) "\$@"
 fi
 EOF
   else
-    cat >"/opt/cache/bin/$1" <<EOF
+    cat > "/opt/cache/bin/$1" <<EOF
 #!/bin/sh
 
 if [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
@@ -112,7 +125,7 @@ if [ -n "$ROCM_VERSION" ]; then
     TOPDIR=$(dirname $OLDCOMP)
     WRAPPED="$TOPDIR/original/$COMPNAME"
     mv "$OLDCOMP" "$WRAPPED"
-    printf "#!/bin/sh\nexec sccache $WRAPPED \"\$@\"" >"$OLDCOMP"
+    printf "#!/bin/sh\nexec sccache $WRAPPED \"\$@\"" > "$OLDCOMP"
     chmod a+x "$OLDCOMP"
   }
 

.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_cmake.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+
+set -ex
+
+[ -n "$CMAKE_VERSION" ]
+
+# Remove system cmake install so it won't get used instead
+ID=$(grep -oP '(?<=^ID=).+' /etc/os-release | tr -d '"')
+case "$ID" in
+  ubuntu)
+    apt-get remove cmake -y
+    ;;
+  centos)
+    yum remove cmake -y
+    ;;
+  *)
+    echo "Unable to determine OS..."
+    exit 1
+    ;;
+esac
+
+# Turn 3.6.3 into v3.6
+path=$(echo "${CMAKE_VERSION}" | sed -e 's/\([0-9].[0-9]\+\).*/v\1/')
+file="cmake-${CMAKE_VERSION}-Linux-x86_64.tar.gz"
+
+# Download and install specific CMake version in /usr/local
+pushd /tmp
+curl -Os --retry 3 "https://cmake.org/files/${path}/${file}"
+tar -C /usr/local --strip-components 1 --no-same-owner -zxf cmake-*.tar.gz
+rm -f cmake-*.tar.gz
+popd

.ci/docker/common/install_conda.sh

@@ -7,7 +7,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   BASE_URL="https://repo.anaconda.com/miniconda"
   CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
   if [[ $(uname -m) == "aarch64" ]] || [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
-    BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"  # @lint-ignore
+    BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"
     CONDA_FILE="Miniforge3-Linux-$(uname -m).sh"
   fi
 
@@ -25,8 +25,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   mkdir -p /opt/conda
   chown jenkins:jenkins /opt/conda
 
-  SCRIPT_FOLDER="$( cd "$(dirname "$0")" ; pwd -P )"
-  source "${SCRIPT_FOLDER}/common_utils.sh"
+  source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
 
   pushd /tmp
   wget -q "${BASE_URL}/${CONDA_FILE}"
@@ -62,11 +61,11 @@ 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 [[ $(uname -m) == "aarch64" ]]; then
-    conda_install "openblas==0.3.29=*openmp*"
+    conda_install "openblas==0.3.25=*openmp*"
   else
     conda_install "mkl=2021.4.0 mkl-include=2021.4.0"
   fi
@@ -75,11 +74,18 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   # and libpython-static for torch deploy
   conda_install llvmdev=8.0.0 "libpython-static=${ANACONDA_PYTHON_VERSION}"
 
+  # Use conda cmake in some cases. Conda cmake will be newer than our supported
+  # min version (3.5 for xenial and 3.10 for bionic), so we only do it in those
+  # following builds that we know should use conda. Specifically, Ubuntu bionic
+  # and focal cannot find conda mkl with stock cmake, so we need a cmake from conda
+  if [ -n "${CONDA_CMAKE}" ]; then
+    conda_install cmake
+  fi
+
   # Magma package names are concatenation of CUDA major and minor ignoring revision
   # I.e. magma-cuda102 package corresponds to CUDA_VERSION=10.2 and CUDA_VERSION=10.2.89
-  # Magma is installed from a tarball in the ossci-linux bucket into the conda env
   if [ -n "$CUDA_VERSION" ]; then
-    conda_run ${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION})
+    conda_install magma-cuda$(TMP=${CUDA_VERSION/./};echo ${TMP%.*[0-9]}) -c pytorch
   fi
 
   # Install some other packages, including those needed for Python test reporting

.ci/docker/common/install_cpython.sh

@@ -3,11 +3,11 @@
 set -uex -o pipefail
 
 PYTHON_DOWNLOAD_URL=https://www.python.org/ftp/python
-PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads  # @lint-ignore
+PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads
 GET_PIP_URL=https://bootstrap.pypa.io/get-pip.py
 
 # Python versions to be installed in /opt/$VERSION_NO
-CPYTHON_VERSIONS=${CPYTHON_VERSIONS:-"3.9.0 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
@@ -70,7 +70,7 @@ function do_cpython_build {
     # install setuptools since python 3.12 is required to use distutils
     ${prefix}/bin/pip install wheel==0.34.2 setuptools==68.2.2
     local abi_tag=$(${prefix}/bin/python -c "from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag; print('{0}{1}-{2}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag()))")
-    ln -sf ${prefix} /opt/python/${abi_tag}
+    ln -s ${prefix} /opt/python/${abi_tag}
 }
 
 function build_cpython {

.ci/docker/common/install_cuda.sh

@@ -2,82 +2,183 @@
 
 set -ex
 
-arch_path=''
-targetarch=${TARGETARCH:-$(uname -m)}
-if [ ${targetarch} = 'amd64' ] || [ "${targetarch}" = 'x86_64' ]; then
-  arch_path='x86_64'
-else
-  arch_path='sbsa'
-fi
+NCCL_VERSION=v2.21.5-1
+CUDNN_VERSION=9.5.1.17
 
-function install_cuda {
-  version=$1
-  runfile=$2
-  major_minor=${version%.*}
-  rm -rf /usr/local/cuda-${major_minor} /usr/local/cuda
-  if [[ ${arch_path} == 'sbsa' ]]; then
-      runfile="${runfile}_sbsa"
-  fi
-  runfile="${runfile}.run"
-  wget -q https://developer.download.nvidia.com/compute/cuda/${version}/local_installers/${runfile} -O ${runfile}
-  chmod +x ${runfile}
-  ./${runfile} --toolkit --silent
-  rm -f ${runfile}
-  rm -f /usr/local/cuda && ln -s /usr/local/cuda-${major_minor} /usr/local/cuda
+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_cudnn {
-  cuda_major_version=$1
-  cudnn_version=$2
-  mkdir tmp_cudnn && cd tmp_cudnn
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  filepath="cudnn-linux-${arch_path}-${cudnn_version}_cuda${cuda_major_version}-archive"
-  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-${arch_path}/${filepath}.tar.xz
-  tar xf ${filepath}.tar.xz
-  cp -a ${filepath}/include/* /usr/local/cuda/include/
-  cp -a ${filepath}/lib/* /usr/local/cuda/lib64/
-  cd ..
-  rm -rf tmp_cudnn
+function install_cusparselt_052 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.5.2.1-archive.tar.xz
+    tar xf libcusparse_lt-linux-x86_64-0.5.2.1-archive.tar.xz
+    cp -a libcusparse_lt-linux-x86_64-0.5.2.1-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-x86_64-0.5.2.1-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
+
+function install_cusparselt_062 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
+    tar xf libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
+    cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
+
+function install_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"
-    install_cuda 11.8.0 cuda_11.8.0_520.61.05_linux
+    echo "Installing CUDA 11.8 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.4.0"
+    rm -rf /usr/local/cuda-11.8 /usr/local/cuda
+    # install CUDA 11.8.0 in the same container
+    wget -q https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
+    chmod +x cuda_11.8.0_520.61.05_linux.run
+    ./cuda_11.8.0_520.61.05_linux.run --toolkit --silent
+    rm -f cuda_11.8.0_520.61.05_linux.run
+    rm -f /usr/local/cuda && ln -s /usr/local/cuda-11.8 /usr/local/cuda
 
-    install_cudnn 11 $CUDNN_VERSION
+    # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+    mkdir tmp_cudnn && cd tmp_cudnn
+    wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
+    tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
+    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/include/* /usr/local/cuda/include/
+    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/lib/* /usr/local/cuda/lib64/
+    cd ..
+    rm -rf tmp_cudnn
 
-    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_121 {
+    echo "Installing CUDA 12.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.5.2"
+    rm -rf /usr/local/cuda-12.1 /usr/local/cuda
+    # install CUDA 12.1.0 in the same container
+    wget -q https://developer.download.nvidia.com/compute/cuda/12.1.1/local_installers/cuda_12.1.1_530.30.02_linux.run
+    chmod +x cuda_12.1.1_530.30.02_linux.run
+    ./cuda_12.1.1_530.30.02_linux.run --toolkit --silent
+    rm -f cuda_12.1.1_530.30.02_linux.run
+    rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.1 /usr/local/cuda
+
+    # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+    mkdir tmp_cudnn && cd tmp_cudnn
+    wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+    tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+    cd ..
+    rm -rf tmp_cudnn
+
+    # NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
+    # Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
+    git clone -b $NCCL_VERSION --depth 1 https://github.com/NVIDIA/nccl.git
+    cd nccl && make -j src.build
+    cp -a build/include/* /usr/local/cuda/include/
+    cp -a build/lib/* /usr/local/cuda/lib64/
+    cd ..
+    rm -rf nccl
+
+    install_cusparselt_052
 
     ldconfig
 }
 
 function install_124 {
   CUDNN_VERSION=9.1.0.70
-  echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.2"
-  install_cuda 12.4.1 cuda_12.4.1_550.54.15_linux
+  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
+  chmod +x cuda_12.4.1_550.54.15_linux.run
+  ./cuda_12.4.1_550.54.15_linux.run --toolkit --silent
+  rm -f cuda_12.4.1_550.54.15_linux.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
 
-  install_cudnn 12 $CUDNN_VERSION
+  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
 
-  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 {
-  CUDNN_VERSION=9.5.1.17
-  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
-  install_cuda 12.6.3 cuda_12.6.3_560.35.05_linux
+  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
+  chmod +x cuda_12.6.3_560.35.05_linux.run
+  ./cuda_12.6.3_560.35.05_linux.run --toolkit --silent
+  rm -f cuda_12.6.3_560.35.05_linux.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.6 /usr/local/cuda
 
-  install_cudnn 12 $CUDNN_VERSION
+  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
 
-  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
 }
@@ -113,6 +214,37 @@ function prune_118 {
     rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.3.0 $CUDA_BASE/nsight-systems-2022.4.2/
 }
 
+function prune_121 {
+  echo "Pruning CUDA 12.1"
+  #####################################################################################
+  # CUDA 12.1 prune static libs
+  #####################################################################################
+    export NVPRUNE="/usr/local/cuda-12.1/bin/nvprune"
+    export CUDA_LIB_DIR="/usr/local/cuda-12.1/lib64"
+
+    export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+    export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+
+    if [[ -n "$OVERRIDE_GENCODE" ]]; then
+        export GENCODE=$OVERRIDE_GENCODE
+    fi
+
+    # all CUDA libs except CuDNN and CuBLAS
+    ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
+      | xargs -I {} bash -c \
+                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
+
+    # prune CuDNN and CuBLAS
+    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
+    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
+
+    #####################################################################################
+    # CUDA 12.1 prune visual tools
+    #####################################################################################
+    export CUDA_BASE="/usr/local/cuda-12.1/"
+    rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2023.1.0 $CUDA_BASE/nsight-systems-2023.1.2/
+}
+
 function prune_124 {
   echo "Pruning CUDA 12.4"
   #####################################################################################
@@ -181,34 +313,18 @@ function prune_126 {
   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 {
-  CUDNN_VERSION=9.8.0.87
-  echo "Installing CUDA 12.8.1 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
-  # install CUDA 12.8.1 in the same container
-  install_cuda 12.8.1 cuda_12.8.1_570.124.06_linux
-
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  install_cudnn 12 $CUDNN_VERSION
-
-  CUDA_VERSION=12.8 bash install_nccl.sh
-
-  CUDA_VERSION=12.8 bash install_cusparselt.sh
-
-  ldconfig
-}
-
 # idiomatic parameter and option handling in sh
 while test $# -gt 0
 do
     case "$1" in
     11.8) install_118; prune_118
         ;;
+    12.1) install_121; prune_121
+        ;;
     12.4) install_124; prune_124
         ;;
     12.6) install_126; prune_126
         ;;
-    12.8) install_128;
-        ;;
     *) echo "bad argument $1"; exit 1
         ;;
     esac

.ci/docker/common/install_cuda_aarch64.sh

@@ -0,0 +1,175 @@
+#!/bin/bash
+# Script used only in CD pipeline
+
+set -ex
+
+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-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_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 ${NCCL_VERSION} --depth 1 https://github.com/NVIDIA/nccl.git
+  cd nccl && make -j src.build
+  cp -a build/include/* /usr/local/cuda/include/
+  cp -a build/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf nccl
+
+  install_cusparselt_062
+
+  ldconfig
+}
+
+function prune_124 {
+  echo "Pruning CUDA 12.4"
+  #####################################################################################
+  # CUDA 12.4 prune static libs
+  #####################################################################################
+  export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
+  export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
+
+  export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+  export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+
+  if [[ -n "$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/
+}
+
+# idiomatic parameter and option handling in sh
+while test $# -gt 0
+do
+    case "$1" in
+    12.4) install_124; prune_124
+        ;;
+    12.6) install_126; prune_126
+        ;;
+    *) echo "bad argument $1"; exit 1
+        ;;
+    esac
+    shift
+done

.ci/docker/common/install_cudnn.sh

@@ -4,9 +4,7 @@ if [[ -n "${CUDNN_VERSION}" ]]; then
     # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
     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"
-    elif [[ ${CUDA_VERSION:0:4} == "12.6" ]]; then
+    if [[ ${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
         CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda12-archive"

.ci/docker/common/install_cusparselt.sh

@@ -5,15 +5,7 @@ set -ex
 # cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
 mkdir tmp_cusparselt && cd tmp_cusparselt
 
-if [[ ${CUDA_VERSION:0:4} =~ ^12\.[5-8]$ ]]; then
-    arch_path='sbsa'
-    export TARGETARCH=${TARGETARCH:-$(uname -m)}
-    if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
-        arch_path='x86_64'
-    fi
-    CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.3.2-archive"
-    curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
-elif [[ ${CUDA_VERSION:0:4} == "12.4" ]]; then
+if [[ ${CUDA_VERSION:0:4} =~ ^12\.[2-6]$ ]]; then
     arch_path='sbsa'
     export TARGETARCH=${TARGETARCH:-$(uname -m)}
     if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
@@ -21,11 +13,17 @@ elif [[ ${CUDA_VERSION:0:4} == "12.4" ]]; then
     fi
     CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.2.3-archive"
     curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
+elif [[ ${CUDA_VERSION:0:4} == "12.1" ]]; then
+    arch_path='sbsa'
+    export TARGETARCH=${TARGETARCH:-$(uname -m)}
+    if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
+        arch_path='x86_64'
+    fi
+    CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.5.2.1-archive"
+    curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
 elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
     CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.4.0.7-archive"
     curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/${CUSPARSELT_NAME}.tar.xz
-else
-    echo "Not sure which libcusparselt version to install for this ${CUDA_VERSION}"
 fi
 
 tar xf ${CUSPARSELT_NAME}.tar.xz

.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

@@ -13,7 +13,7 @@ clone_executorch() {
   # and fetch the target commit
   pushd executorch
   git checkout "${EXECUTORCH_PINNED_COMMIT}"
-  git submodule update --init --recursive
+  git submodule update --init
   popd
 
   chown -R jenkins executorch
@@ -37,22 +37,20 @@ install_conda_dependencies() {
 
 install_pip_dependencies() {
   pushd executorch
-  as_jenkins bash install_executorch.sh
-
-  # A workaround, ExecuTorch has moved to numpy 2.0 which is not compatible with the current
-  # numba and scipy version used in PyTorch CI
-  conda_run pip uninstall -y numba scipy
-
+  as_jenkins bash install_requirements.sh --pybind xnnpack
   popd
 }
 
 setup_executorch() {
   pushd executorch
+  # Setup swiftshader and Vulkan SDK which are required to build the Vulkan delegate
+  as_jenkins bash .ci/scripts/setup-vulkan-linux-deps.sh
 
   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

@@ -17,7 +17,7 @@ if [ -n "${UBUNTU_VERSION}" ];then
                   libopenblas-dev libeigen3-dev libatlas-base-dev libzstd-dev
 fi
 
-pip_install numpy scipy imageio cmake ninja
+conda_install numpy scipy imageio cmake ninja
 
 git clone --depth 1 --branch release/16.x --recursive https://github.com/llvm/llvm-project.git
 cmake -DCMAKE_BUILD_TYPE=Release \
@@ -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_inductor_benchmark_deps.sh

@@ -7,16 +7,17 @@ source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
 function install_huggingface() {
   local version
   commit=$(get_pinned_commit huggingface)
+  pip_install pandas==2.0.3
   pip_install "git+https://github.com/huggingface/transformers@${commit}"
 }
 
 function install_timm() {
   local commit
   commit=$(get_pinned_commit timm)
-
+  pip_install pandas==2.0.3
   pip_install "git+https://github.com/huggingface/pytorch-image-models@${commit}"
   # Clean up
-  conda_run pip uninstall -y torch torchvision triton
+  conda_run pip uninstall -y cmake torch torchvision triton
 }
 
 # Pango is needed for weasyprint which is needed for doctr

.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.sh

@@ -3,6 +3,8 @@
 
 set -eou pipefail
 
+MAGMA_VERSION="2.5.2"
+
 function do_install() {
     cuda_version=$1
     cuda_version_nodot=${1/./}
@@ -15,7 +17,7 @@ function do_install() {
         set -x
         tmp_dir=$(mktemp -d)
         pushd ${tmp_dir}
-        curl -OLs https://ossci-linux.s3.us-east-1.amazonaws.com/${magma_archive}
+        curl -OLs https://anaconda.org/pytorch/magma-cuda${cuda_version_nodot}/${MAGMA_VERSION}/download/linux-64/${magma_archive}
         tar -xvf "${magma_archive}"
         mkdir -p "${cuda_dir}/magma"
         mv include "${cuda_dir}/magma/include"

.ci/docker/common/install_magma_conda.sh

@@ -1,23 +0,0 @@
-#!/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
-
-set -eou pipefail
-
-cuda_version_nodot=${1/./}
-anaconda_dir=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
-
-MAGMA_VERSION="2.6.1"
-magma_archive="magma-cuda${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
-)

.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

@@ -31,14 +31,15 @@ pip_install \
 pip_install coloredlogs packaging
 
 pip_install onnxruntime==1.18.1
-pip_install onnxscript==0.2.6 --no-deps
+pip_install onnx==1.16.2
+pip_install onnxscript==0.1.0.dev20241124 --no-deps
 # required by onnxscript
 pip_install ml_dtypes
 
 # Cache the transformers model to be used later by ONNX tests. We need to run the transformers
 # package to download the model. By default, the model is cached at ~/.cache/huggingface/hub/
 IMPORT_SCRIPT_FILENAME="/tmp/onnx_import_script.py"
-as_jenkins echo 'import transformers; transformers.GPTJForCausalLM.from_pretrained("hf-internal-testing/tiny-random-gptj");' > "${IMPORT_SCRIPT_FILENAME}"
+as_jenkins echo 'import transformers; transformers.AutoModel.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3");' > "${IMPORT_SCRIPT_FILENAME}"
 
 # Need a PyTorch version for transformers to work
 pip_install --pre torch --index-url https://download.pytorch.org/whl/nightly/cpu

.ci/docker/common/install_openblas.sh

@@ -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 v0.3.25 --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

@@ -1,15 +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

.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
@@ -65,30 +62,6 @@ EOF
         sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
     done
 
-    # ROCm 6.3 had a regression where initializing static code objects had significant overhead
-    # ROCm 6.4 did not yet fix the regression, also HIP branch names are different
-    if [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]] || [[ $(ver $ROCM_VERSION) -eq $(ver 6.4) ]]; then
-        if [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]]; then
-            HIP_BRANCH=rocm-6.3.x
-            VER_STR=6.3
-        elif [[ $(ver $ROCM_VERSION) -eq $(ver 6.4) ]]; then
-            HIP_BRANCH=release/rocm-rel-6.4
-            VER_STR=6.4
-        fi
-        # clr build needs CppHeaderParser but can only find it using conda's python
-        /opt/conda/bin/python -m pip install CppHeaderParser
-        git clone https://github.com/ROCm/HIP -b $HIP_BRANCH
-        HIP_COMMON_DIR=$(readlink -f HIP)
-        git clone https://github.com/jeffdaily/clr -b release/rocm-rel-${VER_STR}-statco-hotfix
-        mkdir -p clr/build
-        pushd clr/build
-        cmake .. -DCLR_BUILD_HIP=ON -DHIP_COMMON_DIR=$HIP_COMMON_DIR
-        make -j
-        cp hipamd/lib/libamdhip64.so.${VER_STR}.* /opt/rocm/lib/libamdhip64.so.${VER_STR}.*
-        popd
-        rm -rf HIP clr
-    fi
-
     # Cleanup
     apt-get autoclean && apt-get clean
     rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*

.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

@@ -2,16 +2,14 @@
 
 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_pip_version() {
-  conda_run pip list | grep -w $* | head -n 1 | awk '{print $2}'
+get_conda_version() {
+  as_jenkins conda list -n py_$ANACONDA_PYTHON_VERSION | grep -w $* | head -n 1 | awk '{print $2}'
+}
+
+conda_reinstall() {
+  as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y --force-reinstall $*
 }
 
 if [ -n "${XPU_VERSION}" ]; then
@@ -33,9 +31,11 @@ if [ -n "${UBUNTU_VERSION}" ];then
     apt-get install -y gpg-agent
 fi
 
-# Keep the current cmake and numpy version here, so we can reinstall them later
-CMAKE_VERSION=$(get_pip_version cmake)
-NUMPY_VERSION=$(get_pip_version numpy)
+if [ -n "${CONDA_CMAKE}" ]; then
+  # Keep the current cmake and numpy version here, so we can reinstall them later
+  CMAKE_VERSION=$(get_conda_version cmake)
+  NUMPY_VERSION=$(get_conda_version numpy)
+fi
 
 if [ -z "${MAX_JOBS}" ]; then
     export MAX_JOBS=$(nproc)
@@ -52,7 +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
@@ -61,35 +60,28 @@ 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
-
-# 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
-# triton build step via pip will fail to detect conda MKL. Once that issue is fixed,
-# this can be removed.
-#
-# The correct numpy version also needs to be set here because conda claims that it
-# causes inconsistent environment.  Without this, conda will attempt to install the
-# latest numpy version, which fails ASAN tests with the following import error: Numba
-# needs NumPy 1.20 or less.
-# Note that we install numpy with pip as conda might not have the version we want
-if [ -n "${CMAKE_VERSION}" ]; then
-  pip_install "cmake==${CMAKE_VERSION}"
-fi
-if [ -n "${NUMPY_VERSION}" ]; then
-  pip_install "numpy==${NUMPY_VERSION}"
+if [ -n "${CONDA_CMAKE}" ]; then
+  # TODO: This is to make sure that the same cmake and numpy version from install conda
+  # script is used. Without this step, the newer cmake version (3.25.2) downloaded by
+  # triton build step via pip will fail to detect conda MKL. Once that issue is fixed,
+  # this can be removed.
+  #
+  # The correct numpy version also needs to be set here because conda claims that it
+  # causes inconsistent environment.  Without this, conda will attempt to install the
+  # latest numpy version, which fails ASAN tests with the following import error: Numba
+  # needs NumPy 1.20 or less.
+  conda_reinstall cmake="${CMAKE_VERSION}"
+  # Note that we install numpy with pip as conda might not have the version we want
+  pip_install --force-reinstall numpy=="${NUMPY_VERSION}"
 fi

.ci/docker/common/install_ucc.sh

@@ -8,12 +8,6 @@ else
   with_cuda=no
 fi
 
-if [[ -d "/opt/rocm" ]]; then
-  with_rocm=/opt/rocm
-else
-  with_rocm=no
-fi
-
 function install_ucx() {
   set -ex
   git clone --recursive https://github.com/openucx/ucx.git
@@ -25,7 +19,6 @@ function install_ucx() {
   ./configure --prefix=$UCX_HOME      \
       --enable-mt                     \
       --with-cuda=$with_cuda          \
-      --with-rocm=$with_rocm          \
       --enable-profiling              \
       --enable-stats
   time make -j
@@ -43,29 +36,12 @@ function install_ucc() {
   git submodule update --init --recursive
 
   ./autogen.sh
-
   # We only run distributed tests on Tesla M60 and A10G
   NVCC_GENCODE="-gencode=arch=compute_52,code=sm_52 -gencode=arch=compute_86,code=compute_86"
-
-  if [[ -n "$ROCM_VERSION" ]]; then
-    if [[ -n "$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 $amdgpu_targets; do
-      HIP_OFFLOAD="$HIP_OFFLOAD --offload-arch=$arch"
-    done
-  else
-    HIP_OFFLOAD="all-arch-no-native"
-  fi
-
   ./configure --prefix=$UCC_HOME          \
     --with-ucx=$UCX_HOME                  \
     --with-cuda=$with_cuda                \
-    --with-nvcc-gencode="${NVCC_GENCODE}" \
-    --with-rocm=$with_rocm                \
-    --with-rocm-arch="${HIP_OFFLOAD}"
+    --with-nvcc-gencode="${NVCC_GENCODE}"
   time make -j
   sudo make install
 

.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/common/install_xpu.sh

@@ -26,7 +26,7 @@ function install_ubuntu() {
     wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
         | gpg --dearmor > /usr/share/keyrings/oneapi-archive-keyring.gpg.gpg
     echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg.gpg] \
-        https://apt.repos.intel.com/oneapi all main" \
+        https://apt.repos.intel.com/${XPU_REPO_NAME} all main" \
         | tee /etc/apt/sources.list.d/oneAPI.list
 
     # Update the packages list and repository index
@@ -74,7 +74,7 @@ function install_rhel() {
     tee > /etc/yum.repos.d/oneAPI.repo << EOF
 [oneAPI]
 name=Intel for Pytorch GPU dev repository
-baseurl=https://yum.repos.intel.com/oneapi
+baseurl=https://yum.repos.intel.com/${XPU_REPO_NAME}
 enabled=1
 gpgcheck=1
 repo_gpgcheck=1
@@ -118,7 +118,7 @@ function install_sles() {
         https://repositories.intel.com/gpu/sles/${VERSION_SP}${XPU_DRIVER_VERSION}/unified/intel-gpu-${VERSION_SP}.repo
     rpm --import https://repositories.intel.com/gpu/intel-graphics.key
     # To add the online network network package repository for the Intel Support Packages
-    zypper addrepo https://yum.repos.intel.com/oneapi oneAPI
+    zypper addrepo https://yum.repos.intel.com/${XPU_REPO_NAME} oneAPI
     rpm --import https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
 
     # The xpu-smi packages
@@ -141,10 +141,10 @@ if [[ "${XPU_DRIVER_TYPE,,}" == "rolling" ]]; then
     XPU_DRIVER_VERSION=""
 fi
 
-# Default use Intel® oneAPI Deep Learning Essentials 2025.0
-if [[ "$XPU_VERSION" == "2025.1" ]]; then
-    XPU_PACKAGES="intel-deep-learning-essentials-2025.1"
-else
+XPU_REPO_NAME="intel-for-pytorch-gpu-dev"
+XPU_PACKAGES="intel-for-pytorch-gpu-dev-0.5 intel-pti-dev-0.9"
+if [[ "$XPU_VERSION" == "2025.0" ]]; then
+    XPU_REPO_NAME="oneapi"
     XPU_PACKAGES="intel-deep-learning-essentials-2025.0"
 fi
 

.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
@@ -59,6 +56,11 @@ RUN bash ./install_cuda.sh 11.8
 RUN bash ./install_magma.sh 11.8
 RUN ln -sf /usr/local/cuda-11.8 /usr/local/cuda
 
+FROM cuda as cuda12.1
+RUN bash ./install_cuda.sh 12.1
+RUN bash ./install_magma.sh 12.1
+RUN ln -sf /usr/local/cuda-12.1 /usr/local/cuda
+
 FROM cuda as cuda12.4
 RUN bash ./install_cuda.sh 12.4
 RUN bash ./install_magma.sh 12.4
@@ -69,13 +71,7 @@ RUN bash ./install_cuda.sh 12.6
 RUN bash ./install_magma.sh 12.6
 RUN ln -sf /usr/local/cuda-12.6 /usr/local/cuda
 
-FROM cuda as cuda12.8
-RUN bash ./install_cuda.sh 12.8
-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 +86,18 @@ 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
+
+# Install AOTriton
+COPY ./common/common_utils.sh common_utils.sh
+COPY ./aotriton_version.txt aotriton_version.txt
+COPY ./common/install_aotriton.sh install_aotriton.sh
+RUN bash ./install_aotriton.sh /opt/rocm && rm install_aotriton.sh aotriton_version.txt
+ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
 
 FROM ${BASE_TARGET} as final
 COPY --from=openssl            /opt/openssl           /opt/openssl

.ci/docker/libtorch/build.sh

@@ -1,63 +1,93 @@
 #!/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"
+        ROCM_REGEX="([0-9]+)\.([0-9]+)[\.]?([0-9]*)"
+        if [[ $GPU_ARCH_VERSION =~ $ROCM_REGEX ]]; then
+            ROCM_VERSION_INT=$((${BASH_REMATCH[1]}*10000 + ${BASH_REMATCH[2]}*100 + ${BASH_REMATCH[3]:-0}))
+        else
+            echo "ERROR: rocm regex failed"
+            exit 1
+        fi
+        if [[ $ROCM_VERSION_INT -ge 60000 ]]; then
+            PYTORCH_ROCM_ARCH+=";gfx942"
+        fi
+        DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}"
         ;;
     *)
-        echo "ERROR: Unrecognized 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 +18,27 @@ 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
+RUN bash ./install_conda.sh && rm install_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

@@ -15,17 +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
-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

@@ -0,0 +1,207 @@
+# syntax = docker/dockerfile:experimental
+ARG ROCM_VERSION=3.7
+ARG BASE_CUDA_VERSION=11.8
+
+ARG GPU_IMAGE=centos:7
+FROM centos:7 as base
+
+ENV LC_ALL en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US.UTF-8
+
+ARG DEVTOOLSET_VERSION=9
+
+# Note: This is required patch since CentOS have reached EOL
+# otherwise any yum install setp will fail
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+RUN yum install -y wget curl perl util-linux xz bzip2 git patch which perl zlib-devel
+# Just add everything as a safe.directory for git since these will be used in multiple places with git
+RUN git config --global --add safe.directory '*'
+RUN yum install -y yum-utils centos-release-scl
+RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
+# Note: After running yum-config-manager --enable rhel-server-rhscl-7-rpms
+# patch is required once again. Somehow this steps adds mirror.centos.org
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
+ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
+ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
+
+RUN yum --enablerepo=extras install -y epel-release
+
+# cmake-3.18.4 from pip
+RUN yum install -y python3-pip && \
+    python3 -mpip install cmake==3.18.4 && \
+    ln -s /usr/local/bin/cmake /usr/bin/cmake
+
+RUN yum install -y autoconf aclocal automake make sudo
+
+FROM base as openssl
+# Install openssl (this must precede `build python` step)
+# (In order to have a proper SSL module, Python is compiled
+# against a recent openssl [see env vars above], which is linked
+# statically. We delete openssl afterwards.)
+ADD ./common/install_openssl.sh install_openssl.sh
+RUN bash ./install_openssl.sh && rm install_openssl.sh
+
+# EPEL for cmake
+FROM base as patchelf
+# Install patchelf
+ADD ./common/install_patchelf.sh install_patchelf.sh
+RUN bash ./install_patchelf.sh && rm install_patchelf.sh
+RUN cp $(which patchelf) /patchelf
+
+FROM patchelf as python
+# build python
+COPY manywheel/build_scripts /build_scripts
+ADD ./common/install_cpython.sh /build_scripts/install_cpython.sh
+RUN bash build_scripts/build.sh && rm -r build_scripts
+
+FROM base as cuda
+ARG BASE_CUDA_VERSION=10.2
+# Install CUDA
+ADD ./common/install_cuda.sh install_cuda.sh
+RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
+
+FROM base as intel
+# MKL
+ADD ./common/install_mkl.sh install_mkl.sh
+RUN bash ./install_mkl.sh && rm install_mkl.sh
+
+FROM base as magma
+ARG BASE_CUDA_VERSION=10.2
+# Install magma
+ADD ./common/install_magma.sh install_magma.sh
+RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
+
+FROM base as jni
+# Install java jni header
+ADD ./common/install_jni.sh install_jni.sh
+ADD ./java/jni.h jni.h
+RUN bash ./install_jni.sh && rm install_jni.sh
+
+FROM base as libpng
+# Install libpng
+ADD ./common/install_libpng.sh install_libpng.sh
+RUN bash ./install_libpng.sh && rm install_libpng.sh
+
+FROM ${GPU_IMAGE} as common
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+ENV LC_ALL en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US.UTF-8
+RUN yum install -y \
+        aclocal \
+        autoconf \
+        automake \
+        bison \
+        bzip2 \
+        curl \
+        diffutils \
+        file \
+        git \
+        make \
+        patch \
+        perl \
+        unzip \
+        util-linux \
+        wget \
+        which \
+        xz \
+        yasm
+RUN yum install -y \
+    https://repo.ius.io/ius-release-el7.rpm \
+    https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
+
+RUN yum swap -y git git236-core
+# git236+ would refuse to run git commands in repos owned by other users
+# Which causes version check to fail, as pytorch repo is bind-mounted into the image
+# Override this behaviour by treating every folder as safe
+# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
+RUN git config --global --add safe.directory "*"
+
+ENV SSL_CERT_FILE=/opt/_internal/certs.pem
+# Install LLVM version
+COPY --from=openssl            /opt/openssl                          /opt/openssl
+COPY --from=python             /opt/python                           /opt/python
+COPY --from=python             /opt/_internal                        /opt/_internal
+COPY --from=python             /opt/python/cp39-cp39/bin/auditwheel /usr/local/bin/auditwheel
+COPY --from=intel              /opt/intel                            /opt/intel
+COPY --from=patchelf           /usr/local/bin/patchelf               /usr/local/bin/patchelf
+COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
+COPY --from=libpng             /usr/local/bin/png*                   /usr/local/bin/
+COPY --from=libpng             /usr/local/bin/libpng*                /usr/local/bin/
+COPY --from=libpng             /usr/local/include/png*               /usr/local/include/
+COPY --from=libpng             /usr/local/include/libpng*            /usr/local/include/
+COPY --from=libpng             /usr/local/lib/libpng*                /usr/local/lib/
+COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/lib/pkgconfig
+
+FROM common as cpu_final
+ARG BASE_CUDA_VERSION=10.1
+ARG DEVTOOLSET_VERSION=9
+# Install Anaconda
+ADD ./common/install_conda_docker.sh install_conda.sh
+RUN bash ./install_conda.sh && rm install_conda.sh
+ENV PATH /opt/conda/bin:$PATH
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+
+RUN yum install -y yum-utils centos-release-scl
+RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
+ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
+ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
+
+# cmake is already installed inside the rocm base image, so remove if present
+RUN rpm -e cmake || true
+# cmake-3.18.4 from pip
+RUN yum install -y python3-pip && \
+    python3 -mpip install cmake==3.18.4 && \
+    ln -s /usr/local/bin/cmake /usr/bin/cmake
+
+# ninja
+RUN yum install -y ninja-build
+
+FROM cpu_final as cuda_final
+RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
+COPY --from=cuda     /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
+COPY --from=magma    /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
+RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
+ENV PATH=/usr/local/cuda/bin:$PATH
+
+FROM cpu_final as rocm_final
+ARG ROCM_VERSION=3.7
+ARG PYTORCH_ROCM_ARCH
+ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
+# Adding ROCM_PATH env var so that LoadHip.cmake (even with logic updated for ROCm6.0)
+# find HIP works for ROCm5.7. Not needed for ROCm6.0 and above.
+# Remove below when ROCm5.7 is not in support matrix anymore.
+ENV ROCM_PATH /opt/rocm
+ENV MKLROOT /opt/intel
+# No need to install ROCm as base docker image should have full ROCm install
+#ADD ./common/install_rocm.sh install_rocm.sh
+#RUN ROCM_VERSION=${ROCM_VERSION} bash ./install_rocm.sh && rm install_rocm.sh
+ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
+RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
+# cmake3 is needed for the MIOpen build
+RUN ln -sf /usr/local/bin/cmake /usr/bin/cmake3
+ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
+RUN bash ./install_rocm_magma.sh && rm install_rocm_magma.sh
+ADD ./common/install_miopen.sh install_miopen.sh
+RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh
+
+# Install AOTriton
+COPY ./common/common_utils.sh common_utils.sh
+COPY ./aotriton_version.txt aotriton_version.txt
+COPY ./common/install_aotriton.sh install_aotriton.sh
+RUN bash ./install_aotriton.sh /opt/rocm && rm install_aotriton.sh aotriton_version.txt
+ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton

.ci/docker/manywheel/Dockerfile_2014

@@ -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

@@ -7,8 +7,8 @@ ENV LC_ALL en_US.UTF-8
 ENV LANG en_US.UTF-8
 ENV LANGUAGE en_US.UTF-8
 
-ARG DEVTOOLSET_VERSION=13
-RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel yum-utils gcc-toolset-${DEVTOOLSET_VERSION}-gcc gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran gcc-toolset-${DEVTOOLSET_VERSION}-gdb
+ARG DEVTOOLSET_VERSION=11
+RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel yum-utils gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
 ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
 ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
 
@@ -33,13 +33,10 @@ 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=12.6
+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
@@ -47,7 +44,7 @@ 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=12.6
+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
@@ -64,7 +61,7 @@ ADD ./common/install_libpng.sh install_libpng.sh
 RUN bash ./install_libpng.sh && rm install_libpng.sh
 
 FROM ${GPU_IMAGE} as common
-ARG DEVTOOLSET_VERSION=13
+ARG DEVTOOLSET_VERSION=11
 ENV LC_ALL en_US.UTF-8
 ENV LANG en_US.UTF-8
 ENV LANGUAGE en_US.UTF-8
@@ -87,12 +84,13 @@ RUN yum install -y \
         wget \
         which \
         xz \
-        glibc-langpack-en \
-        gcc-toolset-${DEVTOOLSET_VERSION}-gcc \
-        gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ \
-        gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
-        gcc-toolset-${DEVTOOLSET_VERSION}-gdb
+        gcc-toolset-${DEVTOOLSET_VERSION}-toolchain \
+        glibc-langpack-en
+RUN yum install -y \
+    https://repo.ius.io/ius-release-el7.rpm \
+    https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
 
+RUN yum swap -y git git236-core
 # git236+ would refuse to run git commands in repos owned by other users
 # Which causes version check to fail, as pytorch repo is bind-mounted into the image
 # Override this behaviour by treating every folder as safe
@@ -116,8 +114,8 @@ COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/
 COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
 
 FROM common as cpu_final
-ARG BASE_CUDA_VERSION=12.6
-ARG DEVTOOLSET_VERSION=13
+ARG BASE_CUDA_VERSION=11.8
+ARG DEVTOOLSET_VERSION=11
 # Install Anaconda
 ADD ./common/install_conda_docker.sh install_conda.sh
 RUN bash ./install_conda.sh && rm install_conda.sh
@@ -156,14 +154,11 @@ ENV ROCM_PATH /opt/rocm
 # and avoid 3.21.0 cmake+ninja issues with ninja inserting "-Wl,--no-as-needed" in LINK_FLAGS for static linker
 RUN python3 -m pip install --upgrade pip && \
     python3 -mpip install cmake==3.28.4
-# replace the libdrm in /opt/amdgpu with custom amdgpu.ids lookup path
 ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
 RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
-# ROCm 6.4 rocm-smi depends on system drm.h header
-RUN yum install -y libdrm-devel
 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
 
@@ -174,6 +169,6 @@ ENV XPU_DRIVER_TYPE ROLLING
 RUN python3 -m pip install --upgrade pip && \
     python3 -mpip install cmake==3.28.4
 ADD ./common/install_xpu.sh install_xpu.sh
-ENV XPU_VERSION 2025.1
+ENV XPU_VERSION 2025.0
 RUN bash ./install_xpu.sh && rm install_xpu.sh
 RUN pushd /opt/_internal && tar -xJf static-libs-for-embedding-only.tar.xz && popd

.ci/docker/manywheel/Dockerfile_2_28_aarch64

@@ -1,6 +1,7 @@
 FROM quay.io/pypa/manylinux_2_28_aarch64 as base
 
-ARG GCCTOOLSET_VERSION=13
+# Graviton needs GCC 10 or above for the build. GCC12 is the default version in almalinux-8.
+ARG GCCTOOLSET_VERSION=11
 
 # Language variabes
 ENV LC_ALL=en_US.UTF-8
@@ -35,16 +36,7 @@ RUN yum install -y \
   yasm \
   zstd \
   sudo \
-  gcc-toolset-${GCCTOOLSET_VERSION}-gcc \
-  gcc-toolset-${GCCTOOLSET_VERSION}-gcc-c++ \
-  gcc-toolset-${GCCTOOLSET_VERSION}-gcc-gfortran \
-  gcc-toolset-${GCCTOOLSET_VERSION}-gdb
-
-# (optional) Install non-default Ninja version
-ARG NINJA_VERSION
-COPY ./common/install_ninja.sh install_ninja.sh
-RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
-RUN rm install_ninja.sh
+  gcc-toolset-${GCCTOOLSET_VERSION}-toolchain
 
 # Ensure the expected devtoolset is used
 ENV PATH=/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/bin:$PATH

.ci/docker/manywheel/Dockerfile_aarch64

@@ -0,0 +1,94 @@
+FROM quay.io/pypa/manylinux2014_aarch64 as base
+
+
+# Graviton needs GCC 10 for the build
+ARG DEVTOOLSET_VERSION=10
+
+# Language variabes
+ENV LC_ALL=en_US.UTF-8
+ENV LANG=en_US.UTF-8
+ENV LANGUAGE=en_US.UTF-8
+
+# Installed needed OS packages. This is to support all
+# the binary builds (torch, vision, audio, text, data)
+RUN yum -y install epel-release
+RUN yum -y update
+RUN yum install -y \
+  autoconf \
+  automake \
+  bison \
+  bzip2 \
+  curl \
+  diffutils \
+  file \
+  git \
+  make \
+  patch \
+  perl \
+  unzip \
+  util-linux \
+  wget \
+  which \
+  xz \
+  yasm \
+  less \
+  zstd \
+  libgomp \
+  sudo \
+  devtoolset-${DEVTOOLSET_VERSION}-gcc \
+  devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ \
+  devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
+  devtoolset-${DEVTOOLSET_VERSION}-binutils
+
+# Ensure the expected devtoolset is used
+ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
+ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
+
+
+# git236+ would refuse to run git commands in repos owned by other users
+# Which causes version check to fail, as pytorch repo is bind-mounted into the image
+# Override this behaviour by treating every folder as safe
+# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
+RUN git config --global --add safe.directory "*"
+
+
+###############################################################################
+# libglfortran.a hack
+#
+# libgfortran.a from quay.io/pypa/manylinux2014_aarch64 is not compiled with -fPIC.
+# This causes __stack_chk_guard@@GLIBC_2.17 on pytorch build. To solve, get
+# ubuntu's libgfortran.a which is compiled with -fPIC
+# NOTE: Need a better way to get this library as Ubuntu's package can be removed by the vender, or changed
+###############################################################################
+RUN cd ~/ \
+  && curl -L -o ~/libgfortran-10-dev.deb http://ports.ubuntu.com/ubuntu-ports/pool/universe/g/gcc-10/libgfortran-10-dev_10.5.0-4ubuntu2_arm64.deb \
+  && ar x ~/libgfortran-10-dev.deb \
+  && tar --use-compress-program=unzstd -xvf data.tar.zst -C ~/ \
+  && cp -f ~/usr/lib/gcc/aarch64-linux-gnu/10/libgfortran.a /opt/rh/devtoolset-10/root/usr/lib/gcc/aarch64-redhat-linux/10/
+
+# install cmake
+RUN yum install -y cmake3 && \
+    ln -s /usr/bin/cmake3 /usr/bin/cmake
+
+FROM base as openssl
+# Install openssl (this must precede `build python` step)
+# (In order to have a proper SSL module, Python is compiled
+# against a recent openssl [see env vars above], which is linked
+# statically. We delete openssl afterwards.)
+ADD ./common/install_openssl.sh install_openssl.sh
+RUN bash ./install_openssl.sh && rm install_openssl.sh
+ENV SSL_CERT_FILE=/opt/_internal/certs.pem
+
+FROM base as openblas
+# Install openblas
+ADD ./common/install_openblas.sh install_openblas.sh
+RUN bash ./install_openblas.sh && rm install_openblas.sh
+
+FROM openssl as final
+# remove unncessary python versions
+RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
+RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
+RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
+RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
+COPY --from=openblas     /opt/OpenBLAS/  /opt/OpenBLAS/
+ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH

.ci/docker/manywheel/Dockerfile_cuda_aarch64

@@ -1,7 +1,7 @@
 FROM quay.io/pypa/manylinux_2_28_aarch64 as base
 
 # Cuda ARM build needs gcc 11
-ARG DEVTOOLSET_VERSION=13
+ARG DEVTOOLSET_VERSION=11
 
 # Language variables
 ENV LC_ALL=en_US.UTF-8
@@ -34,10 +34,7 @@ RUN yum install -y \
   zstd \
   libgomp \
   sudo \
-  gcc-toolset-${DEVTOOLSET_VERSION}-gcc \
-  gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ \
-  gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
-  gcc-toolset-${DEVTOOLSET_VERSION}-gdb
+  gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
 
 # Ensure the expected devtoolset is used
 ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
@@ -69,11 +66,8 @@ RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
 FROM base as cuda
 ARG BASE_CUDA_VERSION
 # Install CUDA
-ADD ./common/install_cuda.sh install_cuda.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.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh ci_commit_pins/nccl-cu* install_cusparselt.sh
+ADD ./common/install_cuda_aarch64.sh install_cuda_aarch64.sh
+RUN bash ./install_cuda_aarch64.sh ${BASE_CUDA_VERSION} && rm install_cuda_aarch64.sh
 
 FROM base as magma
 ARG BASE_CUDA_VERSION

.ci/docker/manywheel/Dockerfile_s390x

@@ -5,9 +5,7 @@ ENV LC_ALL=C.UTF-8
 ENV LANG=C.UTF-8
 ENV LANGUAGE=C.UTF-8
 
-# there is a bugfix in gcc >= 14 for precompiled headers and s390x vectorization interaction.
-# with earlier gcc versions test/inductor/test_cpu_cpp_wrapper.py will fail.
-ARG DEVTOOLSET_VERSION=14
+ARG DEVTOOLSET_VERSION=13
 # Installed needed OS packages. This is to support all
 # the binary builds (torch, vision, audio, text, data)
 RUN yum -y install epel-release
@@ -44,7 +42,6 @@ RUN yum install -y \
   llvm-devel \
   libzstd-devel \
   python3.12-devel \
-  python3.12-test \
   python3.12-setuptools \
   python3.12-pip \
   python3-virtualenv \
@@ -60,8 +57,7 @@ RUN yum install -y \
   libxslt-devel \
   libxml2-devel \
   openssl-devel \
-  valgrind \
-  ninja-build
+  valgrind
 
 ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
 ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
@@ -105,33 +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 \
-  hdf5-devel \
-  python3-h5py \
-  git
+  protobuf-devel \
+  protobuf-c-devel \
+  protobuf-lite-devel \
+  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 \
-  --compile_no_warning_as_error && \
-  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)
 
@@ -9,108 +9,158 @@ 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 ${GPU_ARCH_TYPE} in
+    cpu)
         TARGET=cpu_final
+        DOCKER_TAG=cpu
+        GPU_IMAGE=centos:7
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
+        ;;
+    cpu-manylinux_2_28)
+        TARGET=cpu_final
+        DOCKER_TAG=cpu
         GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13"
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28"
         ;;
-    manylinux2_28_aarch64-builder:cpu-aarch64)
+    cpu-aarch64)
         TARGET=final
+        DOCKER_TAG=cpu-aarch64
+        GPU_IMAGE=arm64v8/centos:7
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=10"
+        MANY_LINUX_VERSION="aarch64"
+        ;;
+    cpu-aarch64-2_28)
+        TARGET=final
+        DOCKER_TAG=cpu-aarch64
         GPU_IMAGE=arm64v8/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13 --build-arg NINJA_VERSION=1.12.1"
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28_aarch64"
         ;;
-    manylinuxcxx11-abi-builder:cpu-cxx11-abi)
+    cpu-cxx11-abi)
         TARGET=final
+        DOCKER_TAG=cpu-cxx11-abi
         GPU_IMAGE=""
         DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
         MANY_LINUX_VERSION="cxx11-abi"
         ;;
-    manylinuxs390x-builder:cpu-s390x)
+    cpu-s390x)
         TARGET=final
+        DOCKER_TAG=cpu-s390x
         GPU_IMAGE=s390x/almalinux:8
         DOCKER_GPU_BUILD_ARG=""
         MANY_LINUX_VERSION="s390x"
         ;;
-    manylinux2_28-builder:cuda11*)
+    cuda)
         TARGET=cuda_final
+        DOCKER_TAG=cuda${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=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28"
         ;;
-    manylinux2_28-builder:cuda12*)
+    cuda-aarch64)
         TARGET=cuda_final
-        GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=13"
-        MANY_LINUX_VERSION="2_28"
-        ;;
-    manylinuxaarch64-builder:cuda*)
-        TARGET=cuda_final
-        GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=13"
+        DOCKER_TAG=cuda${GPU_ARCH_VERSION}
+        GPU_IMAGE=arm64v8/centos:7
+        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="aarch64"
         DOCKERFILE_SUFFIX="_cuda_aarch64"
         ;;
-    manylinux2_28-builder:rocm*)
+    rocm|rocm-manylinux_2_28)
         TARGET=rocm_final
-        MANY_LINUX_VERSION="2_28"
-        DEVTOOLSET_VERSION="11"
-        GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
+        DOCKER_TAG=rocm${GPU_ARCH_VERSION}
+        GPU_IMAGE=rocm/dev-centos-7:${GPU_ARCH_VERSION}-complete
+        DEVTOOLSET_VERSION="9"
+        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"
+        ROCM_REGEX="([0-9]+)\.([0-9]+)[\.]?([0-9]*)"
+        if [[ $GPU_ARCH_VERSION =~ $ROCM_REGEX ]]; then
+            ROCM_VERSION_INT=$((${BASH_REMATCH[1]}*10000 + ${BASH_REMATCH[2]}*100 + ${BASH_REMATCH[3]:-0}))
+        else
+            echo "ERROR: rocm regex failed"
+            exit 1
+        fi
         DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${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.sh

@@ -97,7 +97,7 @@ find /opt/_internal -type f -print0 \
     | xargs -0 -n1 strip --strip-unneeded 2>/dev/null || true
 # We do not need the Python test suites, or indeed the precompiled .pyc and
 # .pyo files. Partially cribbed from:
-#    https://github.com/docker-library/python/blob/master/3.4/slim/Dockerfile  # @lint-ignore
+#    https://github.com/docker-library/python/blob/master/3.4/slim/Dockerfile
 find /opt/_internal \
      \( -type d -a -name test -o -name tests \) \
   -o \( -type f -a -name '*.pyc' -o -name '*.pyo' \) \

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

@@ -2,8 +2,8 @@
 # Helper utilities for build
 # Script used only in CD pipeline
 
-OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/  # @lint-ignore
-CURL_DOWNLOAD_URL=https://curl.se/download
+OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/
+CURL_DOWNLOAD_URL=https://curl.askapache.com/download
 
 AUTOCONF_DOWNLOAD_URL=https://ftp.gnu.org/gnu/autoconf
 

.ci/docker/requirements-ci.txt

@@ -30,10 +30,10 @@ dill==0.3.7
 #Pinned versions: 0.3.7
 #test that import: dynamo/test_replay_record.py test_dataloader.py test_datapipe.py test_serialization.py
 
-expecttest==0.3.0
+expecttest==0.2.1
 #Description: method for writing tests where test framework auto populates
 # the expected output based on previous runs
-#Pinned versions: 0.3.0
+#Pinned versions: 0.2.1
 #test that import:
 
 fbscribelogger==0.1.7
@@ -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==1.15.0
+mypy==1.11.2
 # 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"
@@ -135,9 +132,6 @@ numpy==1.22.4; python_version == "3.9" or python_version == "3.10"
 numpy==1.26.2; python_version == "3.11" or python_version == "3.12"
 numpy==2.1.2; python_version >= "3.13"
 
-pandas==2.0.3; python_version < "3.13"
-pandas==2.2.3; python_version >= "3.13"
-
 #onnxruntime
 #Description: scoring engine for Open Neural Network Exchange (ONNX) models
 #Pinned versions: 1.9.0
@@ -161,15 +155,15 @@ optree==0.13.0
 #test_pointwise_ops.py, test_dtensor_ops.py, test_torchinductor.py, test_fx.py,
 #test_fake_tensor.py, test_mps.py
 
-pillow==11.0.0
+pillow==10.3.0
 #Description:  Python Imaging Library fork
 #Pinned versions: 10.3.0
 #test that import:
 
-protobuf==5.29.4
-#Description:  Google's data interchange format
-#Pinned versions: 5.29.4
-#test that import: test_tensorboard.py, test/onnx/*
+protobuf==3.20.2
+#Description:  Google’s data interchange format
+#Pinned versions: 3.20.1
+#test that import: test_tensorboard.py
 
 psutil
 #Description: information on running processes and system utilization
@@ -196,11 +190,6 @@ pytest-rerunfailures>=10.3
 #Pinned versions:
 #test that import:
 
-pytest-subtests==0.13.1
-#Description: plugin for subtest support
-#Pinned versions:
-#test that import:
-
 #pytest-benchmark
 #Description: fixture for benchmarking code
 #Pinned versions: 3.2.3
@@ -248,7 +237,7 @@ scikit-image==0.22.0 ; python_version >= "3.10"
 #test that import:
 
 scipy==1.10.1 ; python_version <= "3.11"
-scipy==1.14.1 ; python_version >= "3.12"
+scipy==1.12.0 ; python_version == "3.12"
 # Pin SciPy because of failing distribution tests (see #60347)
 #Description: scientific python
 #Pinned versions: 1.10.1
@@ -283,9 +272,9 @@ unittest-xml-reporting<=3.2.0,>=2.0.0
 #test that import:
 
 #lintrunner is supported on aarch64-linux only from 0.12.4 version
-lintrunner==0.12.7
+lintrunner==0.12.5
 #Description: all about linters!
-#Pinned versions: 0.12.7
+#Pinned versions: 0.12.5
 #test that import:
 
 redis>=4.0.0
@@ -297,7 +286,7 @@ ghstack==0.8.0
 #Pinned versions: 0.8.0
 #test that import:
 
-jinja2==3.1.6
+jinja2==3.1.4
 #Description: jinja2 template engine
 #Pinned versions: 3.1.4
 #test that import:
@@ -307,42 +296,41 @@ pytest-cpp==2.3.0
 #Pinned versions: 2.3.0
 #test that import:
 
-z3-solver==4.12.6.0
+z3-solver==4.12.2.0
 #Description: The Z3 Theorem Prover Project
 #Pinned versions:
 #test that import:
 
-tensorboard==2.13.0 ; python_version < "3.13"
-tensorboard==2.18.0 ; python_version >= "3.13"
+tensorboard==2.13.0
 #Description: Also included in .ci/docker/requirements-docs.txt
 #Pinned versions:
 #test that import: test_tensorboard
 
 pywavelets==1.4.1 ; python_version < "3.12"
-pywavelets==1.7.0 ; python_version >= "3.12"
+pywavelets==1.5.0 ; python_version >= "3.12"
 #Description: This is a requirement of scikit-image, we need to pin
 # it here because 1.5.0 conflicts with numpy 1.21.2 used in CI
 #Pinned versions: 1.4.1
 #test that import:
 
-lxml==5.3.0
+lxml==5.0.0
 #Description: This is a requirement of unittest-xml-reporting
 
 # Python-3.9 binaries
 
 PyGithub==2.3.0
 
-sympy==1.13.3
+sympy==1.13.1 ; python_version >= "3.9"
 #Description: Required by coremltools, also pinned in .github/requirements/pip-requirements-macOS.txt
 #Pinned versions:
 #test that import:
 
-onnx==1.18.0
-#Description: Required by onnx tests, and mypy and test_public_bindings.py when checking torch.onnx._internal
+onnx==1.17.0
+#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
 
-onnxscript==0.2.6
+onnxscript==0.1.0.dev20240817
 #Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
@@ -356,7 +344,7 @@ 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
@@ -365,20 +353,12 @@ pwlf==2.2.1
 # To build PyTorch itself
 astunparse
 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
-
-dataclasses_json==0.6.7
-#Description: required for data pipeline and scripts under tools/stats
-#Pinned versions: 0.6.7
-#test that import:
-
-cmake==4.0.0
-#Description: required for building

.ci/docker/requirements-docs.txt

@@ -1,30 +1,20 @@
 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
-
-sphinx_sitemap==2.6.0
-#Description: This is used to generate sitemap for PyTorch docs
-#Pinned versions: 2.6.0
-
 matplotlib==3.5.3
 #Description: This is used to generate PyTorch docs
 #Pinned versions: 3.5.3
 
-tensorboard==2.13.0 ; python_version < "3.13"
-tensorboard==2.18.0 ; python_version >= "3.13"
+tensorboard==2.13.0
 #Description: This is used to generate PyTorch docs
 #Pinned versions: 2.13.0
 
@@ -55,6 +45,5 @@ 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 @@
-3.3.1
+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
@@ -26,11 +26,11 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
 ARG ANACONDA_PYTHON_VERSION
 ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
 ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
+ARG CONDA_CMAKE
 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
+RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
 
 # Install gcc
 ARG GCC_VERSION
@@ -42,6 +42,20 @@ 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 ./
@@ -66,8 +80,6 @@ RUN bash ./install_openssl.sh
 ENV OPENSSL_DIR /opt/openssl
 
 ARG INDUCTOR_BENCHMARKS
-ARG ANACONDA_PYTHON_VERSION
-ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
 COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
 COPY ./common/common_utils.sh common_utils.sh
 COPY ci_commit_pins/huggingface.txt huggingface.txt
@@ -75,21 +87,21 @@ COPY ci_commit_pins/timm.txt timm.txt
 RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
 RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
 
-ARG TRITON
+# (optional) Install non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
 
-FROM base as triton-builder
+ARG TRITON
 # Install triton, this needs to be done before sccache because the latter will
 # try to reach out to S3, which docker build runners don't have access
 COPY ./common/install_triton.sh install_triton.sh
 COPY ./common/common_utils.sh common_utils.sh
 COPY ci_commit_pins/triton.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
@@ -144,16 +156,6 @@ 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

@@ -14,17 +14,19 @@ ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
 COPY ./common/install_base.sh install_base.sh
 RUN bash ./install_base.sh && rm install_base.sh
 
+# Install clang
+ARG LLVMDEV
+ARG CLANG_VERSION
+COPY ./common/install_clang.sh install_clang.sh
+RUN bash ./install_clang.sh && rm install_clang.sh
+
 # Install user
 COPY ./common/install_user.sh install_user.sh
 RUN bash ./install_user.sh && rm install_user.sh
 
-# Install katex
-ARG KATEX
-COPY ./common/install_docs_reqs.sh install_docs_reqs.sh
-RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
-
 # Install conda and other packages (e.g., numpy, pytest)
 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
@@ -37,10 +39,19 @@ ARG GCC_VERSION
 COPY ./common/install_gcc.sh install_gcc.sh
 RUN bash ./install_gcc.sh && rm install_gcc.sh
 
-# Install clang
-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
@@ -55,7 +66,7 @@ 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
@@ -74,31 +85,11 @@ COPY ./common/install_amdsmi.sh install_amdsmi.sh
 RUN bash ./install_amdsmi.sh
 RUN rm install_amdsmi.sh
 
-# (optional) Install UCC
-ARG UCX_COMMIT
-ARG UCC_COMMIT
-ENV UCX_COMMIT $UCX_COMMIT
-ENV UCC_COMMIT $UCC_COMMIT
-ENV UCX_HOME /usr
-ENV UCC_HOME /usr
-ADD ./common/install_ucc.sh install_ucc.sh
-RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
-RUN rm install_ucc.sh
-
-COPY ./common/install_openssl.sh install_openssl.sh
-ENV OPENSSL_ROOT_DIR /opt/openssl
-RUN bash ./install_openssl.sh
-ENV OPENSSL_DIR /opt/openssl
-
-ARG INDUCTOR_BENCHMARKS
-ARG ANACONDA_PYTHON_VERSION
-ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
-COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
-COPY ./common/common_utils.sh common_utils.sh
-COPY ci_commit_pins/huggingface.txt huggingface.txt
-COPY ci_commit_pins/timm.txt timm.txt
-RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
-RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
+# (optional) Install non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
 
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
@@ -116,17 +107,18 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
 RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
 
+# Install AOTriton
+COPY ./aotriton_version.txt aotriton_version.txt
+COPY ./common/common_utils.sh common_utils.sh
+COPY ./common/install_aotriton.sh install_aotriton.sh
+RUN ["/bin/bash", "-c", "./install_aotriton.sh /opt/rocm && rm -rf install_aotriton.sh aotriton_version.txt common_utils.sh"]
+ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
 
 # Install ccache/sccache (do this last, so we get priority in PATH)
 COPY ./common/install_cache.sh install_cache.sh
 ENV PATH /opt/cache/bin:$PATH
 RUN bash ./install_cache.sh && rm install_cache.sh
 
-# Install Open MPI for ROCm
-COPY ./common/install_openmpi.sh install_openmpi.sh
-RUN if [ -n "${CUDA_VERSION}" ]; then bash install_openmpi.sh; fi
-RUN rm install_openmpi.sh
-
 # Include BUILD_ENVIRONMENT environment variable in image
 ARG BUILD_ENVIRONMENT
 ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}

.ci/docker/ubuntu-xpu/Dockerfile

@@ -28,6 +28,7 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
 ARG ANACONDA_PYTHON_VERSION
+ARG CONDA_CMAKE
 ARG DOCS
 ARG BUILD_ENVIRONMENT
 ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
@@ -76,6 +77,13 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${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 ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -83,6 +91,12 @@ RUN if [ -n "${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 non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
+
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
 COPY ./common/install_ninja.sh install_ninja.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
 
@@ -28,6 +28,7 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
 ARG ANACONDA_PYTHON_VERSION
+ARG CONDA_CMAKE
 ARG DOCS
 ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
 ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
@@ -35,8 +36,7 @@ ENV DOCS=$DOCS
 COPY requirements-ci.txt requirements-docs.txt /opt/conda/
 COPY ./common/install_conda.sh install_conda.sh
 COPY ./common/common_utils.sh common_utils.sh
-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 /opt/conda/requirements-docs.txt
+RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt /opt/conda/requirements-docs.txt
 RUN if [ -n "${UNINSTALL_DILL}" ]; then pip uninstall -y dill; fi
 
 # Install gcc
@@ -51,17 +51,9 @@ 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
@@ -74,6 +66,20 @@ 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 ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -81,6 +87,24 @@ RUN if [ -n "${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
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
+
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
 COPY ./common/install_ninja.sh install_ninja.sh
@@ -102,21 +126,20 @@ RUN if [ -n "${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

@@ -1,35 +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/almalinux-builder:rocm${DESIRED_ROCM}" \
-	magma-rocm/build_magma.sh
-
-.PHONY: all
-all: magma-rocm64
-all: magma-rocm63
-
-.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)

.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

@@ -12,12 +12,13 @@ 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="${CUDA_ARCH_LIST}" \
-	"pytorch/almalinux-builder:cuda${DESIRED_CUDA}-main" \
+	"pytorch/manylinux-builder:cuda${DESIRED_CUDA}-main" \
 	magma/build_magma.sh
 
 .PHONY: all
-all: magma-cuda128
 all: magma-cuda126
+all: magma-cuda124
+all: magma-cuda121
 all: magma-cuda118
 
 .PHONY:
@@ -25,17 +26,21 @@ clean:
 	$(RM) -r magma-*
 	$(RM) -r output
 
-.PHONY: magma-cuda128
-magma-cuda128: DESIRED_CUDA := 12.8
-magma-cuda128: CUDA_ARCH_LIST += -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120
-magma-cuda128:
-	$(DOCKER_RUN)
-
 .PHONY: magma-cuda126
 magma-cuda126: DESIRED_CUDA := 12.6
 magma-cuda126:
 	$(DOCKER_RUN)
 
+.PHONY: magma-cuda124
+magma-cuda124: DESIRED_CUDA := 12.4
+magma-cuda124:
+	$(DOCKER_RUN)
+
+.PHONY: magma-cuda121
+magma-cuda121: DESIRED_CUDA := 12.1
+magma-cuda121:
+	$(DOCKER_RUN)
+
 .PHONY: magma-cuda118
 magma-cuda118: DESIRED_CUDA := 11.8
 magma-cuda118: CUDA_ARCH_LIST += -gencode arch=compute_37,code=sm_37

.ci/manywheel/build_common.sh

@@ -18,12 +18,12 @@ retry () {
     $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
 }
 
-PLATFORM=""
 # TODO move this into the Docker images
 OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
-if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
+if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
+    retry yum install -q -y zip openssl
+elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
     retry yum install -q -y zip openssl
-    PLATFORM="manylinux_2_28_x86_64"
 elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
     retry dnf install -q -y zip openssl
 elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
@@ -34,9 +34,6 @@ elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
 
     retry apt-get update
     retry apt-get -y install zip openssl
-else
-    echo "Unknown OS: '$OS_NAME'"
-    exit 1
 fi
 
 # We use the package name to test the package by passing this to 'pip install'
@@ -80,6 +77,8 @@ if [[ -e /opt/openssl ]]; then
     export CMAKE_INCLUDE_PATH="/opt/openssl/include":$CMAKE_INCLUDE_PATH
 fi
 
+
+
 mkdir -p /tmp/$WHEELHOUSE_DIR
 
 export PATCHELF_BIN=/usr/local/bin/patchelf
@@ -110,6 +109,12 @@ 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 $(date)"
     python tools/amd_build/build_amd.py
@@ -202,6 +207,12 @@ if [[ -n "$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
@@ -242,11 +253,11 @@ make_wheel_record() {
     FPATH=$1
     if echo $FPATH | grep RECORD >/dev/null 2>&1; then
         # if the RECORD file, then
-        echo "\"$FPATH\",,"
+        echo "$FPATH,,"
     else
         HASH=$(openssl dgst -sha256 -binary $FPATH | openssl base64 | sed -e 's/+/-/g' | sed -e 's/\//_/g' | sed -e 's/=//g')
         FSIZE=$(ls -nl $FPATH | awk '{print $5}')
-        echo "\"$FPATH\",sha256=$HASH,$FSIZE"
+        echo "$FPATH,sha256=$HASH,$FSIZE"
     fi
 }
 
@@ -320,8 +331,8 @@ for pkg in /$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/torch*linux*.w
             # ROCm workaround for roctracer dlopens
             if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
                 patchedpath=$(fname_without_so_number $destpath)
-            # Keep the so number for XPU dependencies and libgomp.so.1 to avoid twice load
-            elif [[ "$DESIRED_CUDA" == *"xpu"* || "$filename" == "libgomp.so.1" ]]; then
+            # Keep the so number for XPU dependencies
+            elif [[ "$DESIRED_CUDA" == *"xpu"* ]]; then
                 patchedpath=$destpath
             else
                 patchedpath=$(fname_with_sha256 $destpath)
@@ -366,12 +377,6 @@ for pkg in /$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/torch*linux*.w
         $PATCHELF_BIN --print-rpath $sofile
     done
 
-    # create Manylinux 2_28 tag this needs to happen before regenerate the RECORD
-    if [[ $PLATFORM == "manylinux_2_28_x86_64" && $GPU_ARCH_TYPE != "cpu-s390x" && $GPU_ARCH_TYPE != "xpu" ]]; then
-        wheel_file=$(echo $(basename $pkg) | sed -e 's/-cp.*$/.dist-info\/WHEEL/g')
-        sed -i -e s#linux_x86_64#"${PLATFORM}"# $wheel_file;
-    fi
-
     # regenerate the RECORD file with new hashes
     record_file=$(echo $(basename $pkg) | sed -e 's/-cp.*$/.dist-info\/RECORD/g')
     if [[ -e $record_file ]]; then
@@ -411,20 +416,12 @@ for pkg in /$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/torch*linux*.w
         popd
     fi
 
-    # Rename wheel for Manylinux 2_28
-    if [[ $PLATFORM == "manylinux_2_28_x86_64" && $GPU_ARCH_TYPE != "cpu-s390x" && $GPU_ARCH_TYPE != "xpu" ]]; then
-        pkg_name=$(echo $(basename $pkg) | sed -e s#linux_x86_64#"${PLATFORM}"#)
-        zip -rq $pkg_name $PREIX*
-        rm -f $pkg
-        mv $pkg_name $(dirname $pkg)/$pkg_name
-    else
-        # zip up the wheel back
-        zip -rq $(basename $pkg) $PREIX*
-        # remove original wheel
-        rm -f $pkg
-        mv $(basename $pkg) $pkg
-    fi
+    # zip up the wheel back
+    zip -rq $(basename $pkg) $PREIX*
 
+    # replace original wheel
+    rm -f $pkg
+    mv $(basename $pkg) $pkg
     cd ..
     rm -rf tmp
 done
@@ -477,9 +474,9 @@ if [[ -z "$BUILD_PYTHONLESS" ]]; then
   echo "$(date) :: Running tests"
   pushd "$PYTORCH_ROOT"
 
-
+  #TODO: run_tests.sh and check_binary.sh should be moved to pytorch/pytorch project
   LD_LIBRARY_PATH=/usr/local/nvidia/lib64 \
-          "${PYTORCH_ROOT}/.ci/pytorch/run_tests.sh" manywheel "${py_majmin}" "$DESIRED_CUDA"
+          "/builder/run_tests.sh" manywheel "${py_majmin}" "$DESIRED_CUDA"
   popd
   echo "$(date) :: Finished tests"
 fi

.ci/manywheel/build_cuda.sh

@@ -14,7 +14,6 @@ export USE_CUDA_STATIC_LINK=1
 export INSTALL_TEST=0 # dont install test binaries into site-packages
 export USE_CUPTI_SO=0
 export USE_CUSPARSELT=${USE_CUSPARSELT:-1} # Enable if not disabled by libtorch build
-export USE_CUFILE=${USE_CUFILE:-1}
 
 # Keep an array of cmake variables to add to
 if [[ -z "$CMAKE_ARGS" ]]; then
@@ -36,12 +35,21 @@ if [[ -n "$DESIRED_CUDA" ]]; then
     if [[ ${DESIRED_CUDA} =~ ^[0-9]+\.[0-9]+$ ]]; then
         CUDA_VERSION=${DESIRED_CUDA}
     else
-        # cu126, cu128 etc...
-        if [[ ${#DESIRED_CUDA} -eq 5 ]]; then
+        # cu90, cu92, cu100, cu101
+        if [[ ${#DESIRED_CUDA} -eq 4 ]]; then
+            CUDA_VERSION="${DESIRED_CUDA:2:1}.${DESIRED_CUDA:3:1}"
+        elif [[ ${#DESIRED_CUDA} -eq 5 ]]; then
             CUDA_VERSION="${DESIRED_CUDA:2:2}.${DESIRED_CUDA:4:1}"
         fi
     fi
     echo "Using CUDA $CUDA_VERSION as determined by DESIRED_CUDA"
+
+    # There really has to be a better way to do this - eli
+    # Possibly limiting builds to specific cuda versions be delimiting images would be a choice
+    if [[ "$OS_NAME" == *"Ubuntu"* ]]; then
+        echo "Switching to CUDA version ${DESIRED_CUDA}"
+        /builder/conda/switch_cuda_version.sh "${DESIRED_CUDA}"
+    fi
 else
     CUDA_VERSION=$(nvcc --version|grep release|cut -f5 -d" "|cut -f1 -d",")
     echo "CUDA $CUDA_VERSION Detected"
@@ -51,11 +59,23 @@ cuda_version_nodot=$(echo $CUDA_VERSION | tr -d '.')
 
 TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;7.5;8.0;8.6"
 case ${CUDA_VERSION} in
-    12.8)
-        TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;12.0+PTX" #removing sm_50-sm_70 as these architectures are deprecated in CUDA 12.8 and will be removed in future releases
+    12.6)
+        if [[ "$GPU_ARCH_TYPE" = "cuda-aarch64" ]]; then
+            TORCH_CUDA_ARCH_LIST="9.0"
+        else
+            TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0+PTX"
+        fi
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
-    12.6)
+    12.4)
+        if [[ "$GPU_ARCH_TYPE" = "cuda-aarch64" ]]; then
+            TORCH_CUDA_ARCH_LIST="9.0"
+        else
+            TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
+        fi
+        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
+        ;;
+    12.1)
         TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
@@ -85,15 +105,14 @@ fi
 mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
 
 OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
-if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
+if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
+    LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
+elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
     LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
 elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
     LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
 elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
     LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
-else
-    echo "Unknown OS: '$OS_NAME'"
-    exit 1
 fi
 
 DEPS_LIST=(
@@ -103,9 +122,18 @@ DEPS_SONAME=(
     "libgomp.so.1"
 )
 
+# CUDA 11.8 have to ship the libcusparseLt.so.0 with the binary
+# since nvidia-cusparselt-cu11 is not available in PYPI
+if [[ $USE_CUSPARSELT == "1" && $CUDA_VERSION == "11.8" ]]; then
+        DEPS_SONAME+=(
+            "libcusparseLt.so.0"
+        )
+        DEPS_LIST+=(
+            "/usr/local/cuda/lib64/libcusparseLt.so.0"
+        )
+fi
 
-# CUDA_VERSION 12.6, 12.8
-if [[ $CUDA_VERSION == 12* ]]; then
+if [[ $CUDA_VERSION == "12.4" || $CUDA_VERSION == "12.6" ]]; then
     export USE_STATIC_CUDNN=0
     # Try parallelizing nvcc as well
     export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"
@@ -128,8 +156,6 @@ if [[ $CUDA_VERSION == 12* ]]; then
             "/usr/local/cuda/lib64/libnvToolsExt.so.1"
             "/usr/local/cuda/lib64/libnvrtc.so.12"
             "/usr/local/cuda/lib64/libnvrtc-builtins.so"
-            "/usr/local/cuda/lib64/libcufile.so.0"
-            "/usr/local/cuda/lib64/libcufile_rdma.so.1"
         )
         DEPS_SONAME+=(
             "libcudnn_adv.so.9"
@@ -147,8 +173,6 @@ if [[ $CUDA_VERSION == 12* ]]; then
             "libnvToolsExt.so.1"
             "libnvrtc.so.12"
             "libnvrtc-builtins.so"
-            "libcufile.so.0"
-            "libcufile_rdma.so.1"
         )
     else
         echo "Using nvidia libs from pypi."
@@ -165,7 +189,6 @@ if [[ $CUDA_VERSION == 12* ]]; then
             '$ORIGIN/../../cusparselt/lib'
             '$ORIGIN/../../nvidia/nccl/lib'
             '$ORIGIN/../../nvidia/nvtx/lib'
-            '$ORIGIN/../../nvidia/cufile/lib'
         )
         CUDA_RPATHS=$(IFS=: ; echo "${CUDA_RPATHS[*]}")
         export C_SO_RPATH=$CUDA_RPATHS':$ORIGIN:$ORIGIN/lib'
@@ -181,25 +204,11 @@ if [[ $CUDA_VERSION == 12* ]]; then
     fi
 elif [[ $CUDA_VERSION == "11.8" ]]; then
     export USE_STATIC_CUDNN=0
-    # Turn USE_CUFILE off for CUDA 11.8 since nvidia-cufile-cu11 and 1.9.0.20 are
-    # not available in PYPI
-    export USE_CUFILE=0
     # Try parallelizing nvcc as well
     export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"
     # Bundle ptxas into the wheel, see https://github.com/pytorch/pytorch/pull/119750
     export BUILD_BUNDLE_PTXAS=1
 
-    # CUDA 11.8 have to ship the libcusparseLt.so.0 with the binary
-    # since nvidia-cusparselt-cu11 is not available in PYPI
-    if [[ $USE_CUSPARSELT == "1" ]]; then
-        DEPS_SONAME+=(
-            "libcusparseLt.so.0"
-        )
-        DEPS_LIST+=(
-            "/usr/local/cuda/lib64/libcusparseLt.so.0"
-        )
-    fi
-
     if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
         echo "Bundling with cudnn and cublas."
         DEPS_LIST+=(
@@ -266,7 +275,7 @@ else
     exit 1
 fi
 
-# run_tests.sh requires DESIRED_CUDA to know what tests to exclude
+# builder/test.sh requires DESIRED_CUDA to know what tests to exclude
 export DESIRED_CUDA="$cuda_version_nodot"
 
 # Switch `/usr/local/cuda` to the desired CUDA version

.ci/manywheel/build_libtorch.sh

@@ -22,7 +22,9 @@ retry () {
 
 # TODO move this into the Docker images
 OS_NAME=`awk -F= '/^NAME/{print $2}' /etc/os-release`
-if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
+if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
+    retry yum install -q -y zip openssl
+elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
     retry yum install -q -y zip openssl
 elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
     retry dnf install -q -y zip openssl
@@ -33,9 +35,6 @@ elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
     sed -i 's/.*nvidia.*/# &/' $(find /etc/apt/ -type f -name "*.list")
     retry apt-get update
     retry apt-get -y install zip openssl
-else
-    echo "Unknown OS: '$OS_NAME'"
-    exit 1
 fi
 
 # Version: setup.py uses $PYTORCH_BUILD_VERSION.post$PYTORCH_BUILD_NUMBER if
@@ -96,6 +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
@@ -164,6 +169,12 @@ fi
 
 )
 
+if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
+    LIBTORCH_ABI="cxx11-abi-"
+else
+    LIBTORCH_ABI=
+fi
+
 (
     set -x
 
@@ -214,11 +225,11 @@ make_wheel_record() {
     FPATH=$1
     if echo $FPATH | grep RECORD >/dev/null 2>&1; then
         # if the RECORD file, then
-        echo "\"$FPATH\",,"
+        echo "$FPATH,,"
     else
         HASH=$(openssl dgst -sha256 -binary $FPATH | openssl base64 | sed -e 's/+/-/g' | sed -e 's/\//_/g' | sed -e 's/=//g')
         FSIZE=$(ls -nl $FPATH | awk '{print $5}')
-        echo "\"$FPATH\",sha256=$HASH,$FSIZE"
+        echo "$FPATH,sha256=$HASH,$FSIZE"
     fi
 }
 

.ci/manywheel/build_rocm.sh

@@ -107,29 +107,17 @@ if [[ $ROCM_INT -ge 60200 ]]; then
 fi
 
 OS_NAME=`awk -F= '/^NAME/{print $2}' /etc/os-release`
-if [[ "$OS_NAME" == *"CentOS Linux"* || "$OS_NAME" == *"AlmaLinux"* ]]; then
+if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
     LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
     LIBNUMA_PATH="/usr/lib64/libnuma.so.1"
     LIBELF_PATH="/usr/lib64/libelf.so.1"
-    if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
-        LIBTINFO_PATH="/usr/lib64/libtinfo.so.5"
-    else
-        LIBTINFO_PATH="/usr/lib64/libtinfo.so.6"
-    fi
+    LIBTINFO_PATH="/usr/lib64/libtinfo.so.5"
     LIBDRM_PATH="/opt/amdgpu/lib64/libdrm.so.2"
     LIBDRM_AMDGPU_PATH="/opt/amdgpu/lib64/libdrm_amdgpu.so.1"
-    if [[ $ROCM_INT -ge 60100 && $ROCM_INT -lt 60300 ]]; then
+    if [[ $ROCM_INT -ge 60100 ]]; then
         # Below libs are direct dependencies of libhipsolver
         LIBSUITESPARSE_CONFIG_PATH="/lib64/libsuitesparseconfig.so.4"
-        if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
-            LIBCHOLMOD_PATH="/lib64/libcholmod.so.2"
-            # Below libs are direct dependencies of libsatlas
-            LIBGFORTRAN_PATH="/lib64/libgfortran.so.3"
-        else
-            LIBCHOLMOD_PATH="/lib64/libcholmod.so.3"
-            # Below libs are direct dependencies of libsatlas
-            LIBGFORTRAN_PATH="/lib64/libgfortran.so.5"
-        fi
+        LIBCHOLMOD_PATH="/lib64/libcholmod.so.2"
         # Below libs are direct dependencies of libcholmod
         LIBAMD_PATH="/lib64/libamd.so.2"
         LIBCAMD_PATH="/lib64/libcamd.so.2"
@@ -137,6 +125,7 @@ if [[ "$OS_NAME" == *"CentOS Linux"* || "$OS_NAME" == *"AlmaLinux"* ]]; then
         LIBCOLAMD_PATH="/lib64/libcolamd.so.2"
         LIBSATLAS_PATH="/lib64/atlas/libsatlas.so.3"
         # Below libs are direct dependencies of libsatlas
+        LIBGFORTRAN_PATH="/lib64/libgfortran.so.3"
         LIBQUADMATH_PATH="/lib64/libquadmath.so.0"
     fi
     MAYBE_LIB64=lib64
@@ -151,7 +140,7 @@ elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
     fi
     LIBDRM_PATH="/usr/lib/x86_64-linux-gnu/libdrm.so.2"
     LIBDRM_AMDGPU_PATH="/usr/lib/x86_64-linux-gnu/libdrm_amdgpu.so.1"
-    if [[ $ROCM_INT -ge 60100 && $ROCM_INT -lt 60300 ]]; then
+    if [[ $ROCM_INT -ge 60100 ]]; then
         # Below libs are direct dependencies of libhipsolver
         LIBCHOLMOD_PATH="/lib/x86_64-linux-gnu/libcholmod.so.3"
         # Below libs are direct dependencies of libcholmod
@@ -186,6 +175,12 @@ do
     OS_SO_FILES[${#OS_SO_FILES[@]}]=$file_name # Append lib to array
 done
 
+# PyTorch-version specific
+# AOTriton dependency only for PyTorch >= 2.4
+if (( $(echo "${PYTORCH_VERSION} 2.4" | awk '{print ($1 >= $2)}') )); then
+    ROCM_SO_FILES+=("libaotriton_v2.so")
+fi
+
 # rocBLAS library files
 ROCBLAS_LIB_SRC=$ROCM_HOME/lib/rocblas/library
 ROCBLAS_LIB_DST=lib/rocblas/library

.ci/manywheel/build_xpu.sh

@@ -20,11 +20,7 @@ fi
 source /opt/intel/oneapi/compiler/latest/env/vars.sh
 source /opt/intel/oneapi/pti/latest/env/vars.sh
 source /opt/intel/oneapi/umf/latest/env/vars.sh
-source /opt/intel/oneapi/ccl/latest/env/vars.sh
-source /opt/intel/oneapi/mpi/latest/env/vars.sh
 export USE_STATIC_MKL=1
-export USE_ONEMKL=1
-export USE_XCCL=1
 
 WHEELHOUSE_DIR="wheelhousexpu"
 LIBTORCH_HOUSE_DIR="libtorch_housexpu"

.ci/onnx/README.md

@@ -10,3 +10,5 @@ example: `py2-cuda9.0-cudnn7-ubuntu16.04`. The Docker images that are
 built on Jenkins and are used in triggered builds already have this
 environment variable set in their manifest. Also see
 `./docker/jenkins/*/Dockerfile` and search for `BUILD_ENVIRONMENT`.
+
+Our Jenkins installation is located at https://ci.pytorch.org/jenkins/.

.ci/pytorch/build.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 
-set -ex -o pipefail
+set -ex
 
 # Required environment variable: $BUILD_ENVIRONMENT
 # (This is set by default in the Docker images we build, so you don't
@@ -35,7 +35,7 @@ if [[ "$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
@@ -87,7 +87,7 @@ else
 
   # Workaround required for MKL library linkage
   # https://github.com/pytorch/pytorch/issues/119557
-  if [[ "$ANACONDA_PYTHON_VERSION" = "3.12" || "$ANACONDA_PYTHON_VERSION" = "3.13" ]]; then
+  if [ "$ANACONDA_PYTHON_VERSION" = "3.12" ]; then
     export CMAKE_LIBRARY_PATH="/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/lib/"
     export CMAKE_INCLUDE_PATH="/opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/include/"
   fi
@@ -171,15 +171,8 @@ fi
 if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   # shellcheck disable=SC1091
   source /opt/intel/oneapi/compiler/latest/env/vars.sh
-  # shellcheck disable=SC1091
-  source /opt/intel/oneapi/ccl/latest/env/vars.sh
-  # shellcheck disable=SC1091
-  source /opt/intel/oneapi/mpi/latest/env/vars.sh
-  # Enable XCCL build
-  export USE_XCCL=1
   # 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
@@ -198,7 +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* ]] && [[ "$TORCH_CUDA_ARCH_LIST" == *"8.6"* || "$TORCH_CUDA_ARCH_LIST" == *"8.0"* ]]; 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="$(( $(nproc --ignore=2) / 3 ))"
@@ -235,9 +228,9 @@ if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
   export CMAKE_BUILD_TYPE=RelWithAssert
 fi
 
-# Do not change workspace permissions for ROCm and s390x CI jobs
+# Do not change workspace permissions for ROCm CI jobs
 # as it can leave workspace with bad permissions for cancelled jobs
-if [[ "$BUILD_ENVIRONMENT" != *rocm* && "$BUILD_ENVIRONMENT" != *s390x* && -d /var/lib/jenkins/workspace ]]; then
+if [[ "$BUILD_ENVIRONMENT" != *rocm* && "$BUILD_ENVIRONMENT" != *s390x* ]]; then
   # Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
   WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
   cleanup_workspace() {
@@ -254,9 +247,10 @@ if [[ "$BUILD_ENVIRONMENT" != *rocm* && "$BUILD_ENVIRONMENT" != *s390x* && -d /v
 fi
 
 if [[ "$BUILD_ENVIRONMENT" == *-bazel-* ]]; then
-  set -e -o pipefail
+  set -e
 
   get_bazel
+  install_sccache_nvcc_for_bazel
 
   # Leave 1 CPU free and use only up to 80% of memory to reduce the change of crashing
   # the runner
@@ -283,8 +277,10 @@ 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 --pre numpy==2.0.2
+      fi
 
       WERROR=1 python setup.py clean
 
@@ -307,18 +303,6 @@ 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
 
@@ -394,10 +378,8 @@ 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.
@@ -414,7 +396,7 @@ if [[ "$BUILD_ENVIRONMENT" != *libtorch* && "$BUILD_ENVIRONMENT" != *bazel* ]];
   # don't do this for libtorch as libtorch is C++ only and thus won't have python tests run on its build
   python tools/stats/export_test_times.py
 fi
-# don't do this for bazel or s390x as they don't use sccache
-if [[ "$BUILD_ENVIRONMENT" != *s390x* && "$BUILD_ENVIRONMENT" != *-bazel-* ]]; then
+
+if [[ "$BUILD_ENVIRONMENT" != *s390x* ]]; then
   print_sccache_stats
 fi

.ci/pytorch/check_binary.sh

@@ -1,323 +0,0 @@
-#!/bin/bash
-
-# shellcheck disable=SC2086,SC2006,SC2207,SC2076,SC2155,SC2046,SC1091,SC2143
-# TODO: Re-enable shellchecks above
-
-set -eux -o pipefail
-
-# This script checks the following things on binaries
-# 1. The gcc abi matches DESIRED_DEVTOOLSET
-# 2. MacOS binaries do not link against OpenBLAS
-# 3. There are no protobuf symbols of any sort anywhere (turned off, because
-#    this is currently not true)
-# 4. Standard Python imports work
-# 5. MKL is available everywhere except for MacOS wheels
-# 6. XNNPACK is available everywhere except for MacOS wheels
-# 7. CUDA is setup correctly and does not hang
-# 8. Magma is available for CUDA builds
-# 9. CuDNN is available for CUDA builds
-#
-# This script needs the env variables DESIRED_PYTHON, DESIRED_CUDA,
-# DESIRED_DEVTOOLSET and PACKAGE_TYPE
-#
-# This script expects PyTorch to be installed into the active Python (the
-# Python returned by `which python`). Or, if this is testing a libtorch
-# Pythonless binary, then it expects to be in the root folder of the unzipped
-# libtorch package.
-
-
-if [[ -z ${DESIRED_PYTHON:-} ]]; then
-  export DESIRED_PYTHON=${MATRIX_PYTHON_VERSION:-}
-fi
-if [[ -z ${DESIRED_CUDA:-} ]]; then
-  export DESIRED_CUDA=${MATRIX_DESIRED_CUDA:-}
-fi
-if [[ -z ${DESIRED_DEVTOOLSET:-} ]]; then
-  export DESIRED_DEVTOOLSET=${MATRIX_DESIRED_DEVTOOLSET:-}
-fi
-if [[ -z ${PACKAGE_TYPE:-} ]]; then
-  export PACKAGE_TYPE=${MATRIX_PACKAGE_TYPE:-}
-fi
-
-# The install root depends on both the package type and the os
-# All MacOS packages use conda, even for the wheel packages.
-if [[ "$PACKAGE_TYPE" == libtorch ]]; then
-  # NOTE: Only $PWD works on both CentOS and Ubuntu
-  export install_root="$PWD"
-else
-
-  if [[ $DESIRED_PYTHON =~ ([0-9].[0-9]+)t ]]; then
-    # For python that is maj.mint keep original version
-    py_dot="$DESIRED_PYTHON"
-  elif [[ $DESIRED_PYTHON =~ ([0-9].[0-9]+) ]];  then
-    # Strip everything but major.minor from DESIRED_PYTHON version
-    py_dot="${BASH_REMATCH[0]}"
-  else
-    echo "Unexpected ${DESIRED_PYTHON} format"
-    exit 1
-  fi
-  export install_root="$(dirname $(which python))/../lib/python${py_dot}/site-packages/torch/"
-fi
-
-###############################################################################
-# Check GCC ABI
-###############################################################################
-
-# NOTE: As of https://github.com/pytorch/pytorch/issues/126551 we only produce
-#       wheels with cxx11-abi
-
-echo "Checking that the gcc ABI is what we expect"
-if [[ "$(uname)" != 'Darwin' ]]; then
-  # We also check that there are cxx11 symbols in libtorch
-  #
-  echo "Checking that symbols in libtorch.so have the right gcc abi"
-  python3 "$(dirname ${BASH_SOURCE[0]})/smoke_test/check_binary_symbols.py"
-
-  echo "cxx11 symbols seem to be in order"
-fi # if on Darwin
-
-###############################################################################
-# Check for no OpenBLAS
-# TODO Check for no Protobuf symbols (not finished)
-# Print *all* runtime dependencies
-###############################################################################
-# We have to loop through all shared libraries for this
-if [[ "$(uname)" == 'Darwin' ]]; then
-  all_dylibs=($(find "$install_root" -name '*.dylib'))
-  for dylib in "${all_dylibs[@]}"; do
-    echo "All dependencies of $dylib are $(otool -L $dylib) with rpath $(otool -l $dylib | grep LC_RPATH -A2)"
-
-    # Check that OpenBlas is not linked to on Macs
-    echo "Checking the OpenBLAS is not linked to"
-    if [[ -n "$(otool -L $dylib | grep -i openblas)" ]]; then
-      echo "ERROR: Found openblas as a dependency of $dylib"
-      echo "Full dependencies is: $(otool -L $dylib)"
-      exit 1
-    fi
-
-    # Check for protobuf symbols
-    #proto_symbols="$(nm $dylib | grep protobuf)" || true
-    #if [[ -n "$proto_symbols" ]]; then
-    #  echo "ERROR: Detected protobuf symbols in $dylib"
-    #  echo "Symbols are $proto_symbols"
-    #  exit 1
-    #fi
-  done
-else
-  all_libs=($(find "$install_root" -name '*.so'))
-  for lib in "${all_libs[@]}"; do
-    echo "All dependencies of $lib are $(ldd $lib) with runpath $(objdump -p $lib | grep RUNPATH)"
-
-    # Check for protobuf symbols
-    #proto_symbols=$(nm $lib | grep protobuf) || true
-    #if [[ -n "$proto_symbols" ]]; then
-    #  echo "ERROR: Detected protobuf symbols in $lib"
-    #  echo "Symbols are $proto_symbols"
-    #  exit 1
-    #fi
-  done
-fi
-
-setup_link_flags () {
-  REF_LIB="-Wl,-R${install_root}/lib"
-  if [[ "$(uname)" == 'Darwin' ]]; then
-    REF_LIB="-Wl,-rpath ${install_root}/lib"
-  fi
-  ADDITIONAL_LINKER_FLAGS=""
-  if [[ "$(uname)" == 'Linux' ]]; then
-    ADDITIONAL_LINKER_FLAGS="-Wl,--no-as-needed"
-  fi
-  C10_LINK_FLAGS=""
-  if [ -f "${install_root}/lib/libc10.so" ] || [ -f "${install_root}/lib/libc10.dylib" ]; then
-    C10_LINK_FLAGS="-lc10"
-  fi
-  TORCH_CPU_LINK_FLAGS=""
-  if [ -f "${install_root}/lib/libtorch_cpu.so" ] || [ -f "${install_root}/lib/libtorch_cpu.dylib" ]; then
-    TORCH_CPU_LINK_FLAGS="-ltorch_cpu"
-  fi
-  TORCH_CUDA_LINK_FLAGS=""
-  if [ -f "${install_root}/lib/libtorch_cuda.so" ] || [ -f "${install_root}/lib/libtorch_cuda.dylib" ]; then
-    TORCH_CUDA_LINK_FLAGS="-ltorch_cuda"
-  elif [ -f "${install_root}/lib/libtorch_cuda_cpp.so" ] && [ -f "${install_root}/lib/libtorch_cuda_cpp.so" ] || \
-    [ -f "${install_root}/lib/libtorch_cuda_cu.dylib" ] && [ -f "${install_root}/lib/libtorch_cuda_cu.dylib" ]; then
-    TORCH_CUDA_LINK_FLAGS="-ltorch_cuda_cpp -ltorch_cuda_cu"
-  fi
-}
-
-TEST_CODE_DIR="$(dirname $(realpath ${BASH_SOURCE[0]}))/test_example_code"
-build_and_run_example_cpp () {
-  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
-  ./$1
-}
-
-###############################################################################
-# Check simple Python/C++ calls
-###############################################################################
-if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
-  # NS: Set LD_LIBRARY_PATH for CUDA builds, but perhaps it should be removed
-  if [[ "$DESIRED_CUDA" == "cu"* ]]; then
-    export LD_LIBRARY_PATH=/usr/local/cuda/lib64
-  fi
-  build_and_run_example_cpp simple-torch-test
-else
-  pushd /tmp
-  python -c 'import torch'
-  popd
-fi
-
-###############################################################################
-# Check torch.git_version
-###############################################################################
-if [[ "$PACKAGE_TYPE" != 'libtorch' ]]; then
-  pushd /tmp
-  python -c 'import torch; assert torch.version.git_version != "Unknown"'
-  python -c 'import torch; assert torch.version.git_version != None'
-  popd
-fi
-
-
-###############################################################################
-# Check for MKL
-###############################################################################
-
-if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
-  echo "Checking that MKL is available"
-  build_and_run_example_cpp check-torch-mkl
-elif [[ "$(uname -m)" != "arm64" && "$(uname -m)" != "s390x" ]]; then
-  if [[ "$(uname)" != 'Darwin' || "$PACKAGE_TYPE" != *wheel ]]; then
-    if [[ "$(uname -m)" == "aarch64" ]]; then
-      echo "Checking that MKLDNN is available on aarch64"
-      pushd /tmp
-      python -c 'import torch; exit(0 if torch.backends.mkldnn.is_available() else 1)'
-      popd
-    else
-      echo "Checking that MKL is available"
-      pushd /tmp
-      python -c 'import torch; exit(0 if torch.backends.mkl.is_available() else 1)'
-      popd
-    fi
-  fi
-fi
-
-###############################################################################
-# Check for XNNPACK
-###############################################################################
-
-if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
-  echo "Checking that XNNPACK is available"
-  build_and_run_example_cpp check-torch-xnnpack
-else
-  if [[ "$(uname)" != 'Darwin' || "$PACKAGE_TYPE" != *wheel ]] && [[ "$(uname -m)" != "s390x"  ]]; then
-    echo "Checking that XNNPACK is available"
-    pushd /tmp
-    python -c 'import torch.backends.xnnpack; exit(0 if torch.backends.xnnpack.enabled else 1)'
-    popd
-  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
-###############################################################################
-# Skip these for Windows machines without GPUs
-if [[ "$OSTYPE" == "msys" ]]; then
-    GPUS=$(wmic path win32_VideoController get name)
-    if [[ ! "$GPUS" == *NVIDIA* ]]; then
-        echo "Skip CUDA tests for machines without a Nvidia GPU card"
-        exit 0
-    fi
-fi
-
-# Test that CUDA builds are setup correctly
-if [[ "$DESIRED_CUDA" != 'cpu' && "$DESIRED_CUDA" != 'xpu' && "$DESIRED_CUDA" != 'cpu-cxx11-abi' && "$DESIRED_CUDA" != *"rocm"* && "$(uname -m)" != "s390x" ]]; then
-  if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
-    build_and_run_example_cpp check-torch-cuda
-  else
-    pushd /tmp
-    echo "Checking that CUDA archs are setup correctly"
-    timeout 20 python -c 'import torch; torch.randn([3,5]).cuda()'
-
-    # These have to run after CUDA is initialized
-
-    echo "Checking that magma is available"
-    python -c 'import torch; torch.rand(1).cuda(); exit(0 if torch.cuda.has_magma else 1)'
-
-    echo "Checking that CuDNN is available"
-    python -c 'import torch; exit(0 if torch.backends.cudnn.is_available() else 1)'
-
-    # Validates builds is free of linker regressions reported in https://github.com/pytorch/pytorch/issues/57744
-    echo "Checking that exception handling works"
-    python -c "import torch; from unittest import TestCase;TestCase().assertRaises(RuntimeError, lambda:torch.eye(7, 7, device='cuda:7'))"
-
-    echo "Checking that basic RNN works"
-    python ${TEST_CODE_DIR}/rnn_smoke.py
-
-    echo "Checking that basic CNN works"
-    python "${TEST_CODE_DIR}/cnn_smoke.py"
-
-    echo "Test that linalg works"
-    python -c "import torch;x=torch.rand(3,3,device='cuda');print(torch.linalg.svd(torch.mm(x.t(), x)))"
-
-    popd
-  fi # if libtorch
-fi # if cuda
-
-##########################
-# Run parts of smoke tests
-##########################
-if [[ "$PACKAGE_TYPE" != 'libtorch' ]]; then
-  pushd "$(dirname ${BASH_SOURCE[0]})/smoke_test"
-  python -c "from smoke_test import test_linalg; test_linalg()"
-  if [[ "$DESIRED_CUDA" == *cuda* ]]; then
-    python -c "from smoke_test import test_linalg; test_linalg('cuda')"
-  fi
-  popd
-fi
-
-###############################################################################
-# Check PyTorch supports TCP_TLS gloo transport
-###############################################################################
-
-if [[ "$(uname)" == 'Linux' && "$PACKAGE_TYPE" != 'libtorch' ]]; then
-  GLOO_CHECK="import torch.distributed as dist
-try:
-    dist.init_process_group('gloo', rank=0, world_size=1)
-except RuntimeError as e:
-    print(e)
-"
-  RESULT=`GLOO_DEVICE_TRANSPORT=TCP_TLS MASTER_ADDR=localhost MASTER_PORT=63945 python -c "$GLOO_CHECK"`
-  GLOO_TRANSPORT_IS_NOT_SUPPORTED='gloo transport is not supported'
-  if [[ "$RESULT" =~ "$GLOO_TRANSPORT_IS_NOT_SUPPORTED" ]]; then
-    echo "PyTorch doesn't support TLS_TCP transport, please build with USE_GLOO_WITH_OPENSSL=1"
-    exit 1
-  fi
-fi
-
-###############################################################################
-# Check for C++ ABI compatibility to GCC-11 - GCC 13
-###############################################################################
-if [[ "$(uname)" == 'Linux' &&  "$PACKAGE_TYPE" == 'manywheel' ]]; then
-  pushd /tmp
-  # Per https://gcc.gnu.org/onlinedocs/gcc/C_002b_002b-Dialect-Options.html
-  # gcc-11 is ABI16, gcc-13 is ABI18, gcc-14 is ABI19
-  # gcc 11 - CUDA 11.8, xpu, rocm
-  # gcc 13 - CUDA 12.6, 12.8 and cpu
-  # Please see issue for reference: https://github.com/pytorch/pytorch/issues/152426
-  if [[ "$(uname -m)" == "s390x" ]]; then
-    cxx_abi="19"
-  elif [[ "$DESIRED_CUDA" != 'cu118' && "$DESIRED_CUDA" != 'xpu' && "$DESIRED_CUDA" != 'rocm'* ]]; then
-    cxx_abi="18"
-  else
-    cxx_abi="16"
-  fi
-  python -c "import torch; exit(0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi10${cxx_abi}' else 1)"
-  popd
-fi

.ci/pytorch/common.sh

@@ -3,7 +3,7 @@
 # Common setup for all Jenkins scripts
 # shellcheck source=./common_utils.sh
 source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
-set -ex -o pipefail
+set -ex
 
 # Required environment variables:
 #   $BUILD_ENVIRONMENT (should be set by your Docker image)
@@ -13,6 +13,10 @@ if [[ "${BUILD_ENVIRONMENT}" == *rocm* ]]; then
   # HIP_PLATFORM is auto-detected by hipcc; unset to avoid build errors
   unset HIP_PLATFORM
   export PYTORCH_TEST_WITH_ROCM=1
+  # temporary to locate some kernel issues on the CI nodes
+  export HSAKMT_DEBUG_LEVEL=4
+  # improve rccl performance for distributed tests
+  export HSA_FORCE_FINE_GRAIN_PCIE=1
 fi
 
 # TODO: Renable libtorch testing for MacOS, see https://github.com/pytorch/pytorch/issues/62598

.ci/pytorch/common_utils.sh

@@ -111,6 +111,26 @@ function get_bazel() {
   chmod u+x tools/bazel
 }
 
+# This function is bazel specific because of the bug
+# in the bazel that requires some special paths massaging
+# as a workaround. See
+# https://github.com/bazelbuild/bazel/issues/10167
+function install_sccache_nvcc_for_bazel() {
+  sudo mv /usr/local/cuda/bin/nvcc /usr/local/cuda/bin/nvcc-real
+
+  # Write the `/usr/local/cuda/bin/nvcc`
+  cat << EOF | sudo tee /usr/local/cuda/bin/nvcc
+#!/bin/sh
+if [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
+  exec sccache /usr/local/cuda/bin/nvcc "\$@"
+else
+  exec external/local_cuda/cuda/bin/nvcc-real "\$@"
+fi
+EOF
+
+  sudo chmod +x /usr/local/cuda/bin/nvcc
+}
+
 function install_monkeytype {
   # Install MonkeyType
   pip_install MonkeyType
@@ -160,7 +180,7 @@ function install_torchvision() {
 }
 
 function install_tlparse() {
-  pip_install --user "tlparse==0.3.30"
+  pip_install --user "tlparse==0.3.25"
   PATH="$(python -m site --user-base)/bin:$PATH"
 }
 
@@ -169,34 +189,24 @@ function install_torchrec_and_fbgemm() {
   torchrec_commit=$(get_pinned_commit torchrec)
   local fbgemm_commit
   fbgemm_commit=$(get_pinned_commit fbgemm)
-  if [[ "$BUILD_ENVIRONMENT" == *rocm* ]] ; then
-    fbgemm_commit=$(get_pinned_commit fbgemm_rocm)
-  fi
   pip_uninstall torchrec-nightly
   pip_uninstall fbgemm-gpu-nightly
   pip_install setuptools-git-versioning scikit-build pyre-extensions
 
-  if [[ "$BUILD_ENVIRONMENT" == *rocm* ]] ; then
-    # install torchrec first because it installs fbgemm nightly on top of rocm fbgemm
-    pip_install --no-use-pep517 --user "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
-    pip_uninstall fbgemm-gpu-nightly
+  # TODO (huydhn): I still have no clue on why sccache doesn't work with only fbgemm_gpu here, but it
+  # seems to be an sccache-related issue
+  if [[ "$IS_A100_RUNNER" == "1" ]]; then
+    unset CMAKE_CUDA_COMPILER_LAUNCHER
+    sudo mv /opt/cache/bin /opt/cache/bin-backup
+  fi
 
-    pip_install tabulate  # needed for newer fbgemm
-    pip_install patchelf  # needed for rocm fbgemm
-    git clone --recursive https://github.com/pytorch/fbgemm
-    pushd fbgemm/fbgemm_gpu
-    git checkout "${fbgemm_commit}"
-    python setup.py install \
-      --package_variant=rocm \
-      -DHIP_ROOT_DIR="${ROCM_PATH}" \
-      -DCMAKE_C_FLAGS="-DTORCH_USE_HIP_DSA" \
-      -DCMAKE_CXX_FLAGS="-DTORCH_USE_HIP_DSA"
-    popd
-    rm -rf fbgemm
-  else
-    # See https://github.com/pytorch/pytorch/issues/106971
-    CUDA_PATH=/usr/local/cuda-12.1 pip_install --no-use-pep517 --user "git+https://github.com/pytorch/FBGEMM.git@${fbgemm_commit}#egg=fbgemm-gpu&subdirectory=fbgemm_gpu"
-    pip_install --no-use-pep517 --user "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
+  # See https://github.com/pytorch/pytorch/issues/106971
+  CUDA_PATH=/usr/local/cuda-12.1 pip_install --no-use-pep517 --user "git+https://github.com/pytorch/FBGEMM.git@${fbgemm_commit}#egg=fbgemm-gpu&subdirectory=fbgemm_gpu"
+  pip_install --no-use-pep517 --user "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
+
+  if [[ "$IS_A100_RUNNER" == "1" ]]; then
+    export CMAKE_CUDA_COMPILER_LAUNCHER=/opt/cache/bin/sccache
+    sudo mv /opt/cache/bin-backup /opt/cache/bin
   fi
 }
 
@@ -226,11 +236,6 @@ function checkout_install_torchbench() {
     # to install and test other models
     python install.py --continue_on_fail
   fi
-
-  # TODO (huydhn): transformers-4.44.2 added by https://github.com/pytorch/benchmark/pull/2488
-  # is regressing speedup metric. This needs to be investigated further
-  pip install transformers==4.38.1
-
   echo "Print all dependencies after TorchBench is installed"
   python -mpip freeze
   popd

.ci/pytorch/cpp_doc_push_script.sh

@@ -40,7 +40,7 @@ echo "Building PyTorch C++ API docs..."
 rm -rf cppdocs
 git clone https://github.com/pytorch/cppdocs
 
-set -ex -o pipefail
+set -ex
 
 # Generate ATen files
 pushd "${pt_checkout}"

.ci/pytorch/functorch_doc_push_script.sh

@@ -5,7 +5,7 @@ pt_checkout="/var/lib/jenkins/workspace"
 source "$pt_checkout/.ci/pytorch/common_utils.sh"
 echo "functorch_doc_push_script.sh: Invoked with $*"
 
-set -ex -o pipefail
+set -ex
 
 version=${DOCS_VERSION:-nightly}
 echo "version: $version"

.ci/pytorch/install_cache_xla.sh

@@ -1,50 +1,31 @@
 #!/bin/bash
 
 # Script for installing sccache on the xla build job, which uses xla's docker
-# image, which has sccache installed but doesn't write the stubs.  This is
-# mostly copied from .ci/docker/install_cache.sh.  Changes are: removing checks
-# that will always return the same thing, ex checks for for rocm, CUDA, changing
-# the path where sccache is installed, not changing /etc/environment, and not
-# installing/downloading sccache as it is already in the docker image.
+# image and doesn't have sccache installed on it.  This is mostly copied from
+# .ci/docker/install_cache.sh.  Changes are: removing checks that will always
+# return the same thing, ex checks for for rocm, CUDA, and changing the path
+# where sccache is installed, and not changing /etc/environment.
 
-set -ex -o pipefail
+set -ex
+
+install_binary() {
+  echo "Downloading sccache binary from S3 repo"
+  curl --retry 3 https://s3.amazonaws.com/ossci-linux/sccache -o /tmp/cache/bin/sccache
+}
 
 mkdir -p /tmp/cache/bin
+mkdir -p /tmp/cache/lib
 export PATH="/tmp/cache/bin:$PATH"
 
+install_binary
+chmod a+x /tmp/cache/bin/sccache
+
 function write_sccache_stub() {
   # Unset LD_PRELOAD for ps because of asan + ps issues
   # https://gcc.gnu.org/bugzilla/show_bug.cgi?id=90589
-  if [ "$1" == "gcc" ]; then
-    # Do not call sccache recursively when dumping preprocessor argument
-    # For some reason it's very important for the first cached nvcc invocation
-    cat >"/tmp/cache/bin/$1" <<EOF
-#!/bin/sh
-
-# sccache does not support -E flag, so we need to call the original compiler directly in order to avoid calling this wrapper recursively
-for arg in "\$@"; do
-  if [ "\$arg" = "-E" ]; then
-    exec $(which "$1") "\$@"
-  fi
-done
-
-if [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
-  exec sccache $(which "$1") "\$@"
-else
-  exec $(which "$1") "\$@"
-fi
-EOF
-  else
-    cat >"/tmp/cache/bin/$1" <<EOF
-#!/bin/sh
-
-if [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then
-  exec sccache $(which "$1") "\$@"
-else
-  exec $(which "$1") "\$@"
-fi
-EOF
-  fi
+  # shellcheck disable=SC2086
+  # shellcheck disable=SC2059
+  printf "#!/bin/sh\nif [ \$(env -u LD_PRELOAD ps -p \$PPID -o comm=) != sccache ]; then\n  exec sccache $(which $1) \"\$@\"\nelse\n  exec $(which $1) \"\$@\"\nfi" > "/tmp/cache/bin/$1"
   chmod a+x "/tmp/cache/bin/$1"
 }
 

.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 [[ ${BUILD_ENVIRONMENT} == *"distributed"* ]]; then
-  # Needed for inductor benchmarks, as lots of HF networks make `torch.distribtued` calls
-  USE_DISTRIBUTED=1 USE_OPENMP=1 WERROR=1 python setup.py bdist_wheel
-else
+cross_compile_arm64() {
+  # Cross compilation for arm64
   # Explicitly set USE_DISTRIBUTED=0 to align with the default build config on mac. This also serves as the sole CI config that tests
   # that building with USE_DISTRIBUTED=0 works at all. See https://github.com/pytorch/pytorch/issues/86448
-  USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel --plat-name macosx_11_0_arm64
+  USE_DISTRIBUTED=0 CMAKE_OSX_ARCHITECTURES=arm64 MACOSX_DEPLOYMENT_TARGET=11.0 USE_MKLDNN=OFF USE_QNNPACK=OFF WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel
+}
+
+compile_arm64() {
+  # Compilation for arm64
+  # TODO: Compile with OpenMP support (but this causes CI regressions as cross-compilation were done with OpenMP disabled)
+  USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel
+}
+
+compile_x86_64() {
+  USE_DISTRIBUTED=0 WERROR=1 python setup.py bdist_wheel --plat-name=macosx_10_9_x86_64
+}
+
+build_lite_interpreter() {
+    echo "Testing libtorch (lite interpreter)."
+
+    CPP_BUILD="$(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-common.sh

@@ -20,4 +20,14 @@ print_cmake_info() {
   CONDA_INSTALLATION_DIR=$(dirname "$CMAKE_EXEC")
   # Print all libraries under cmake rpath for debugging
   ls -la "$CONDA_INSTALLATION_DIR/../lib"
+
+  export CMAKE_EXEC
+  # Explicitly add conda env lib folder to cmake rpath to address the flaky issue
+  # where cmake dependencies couldn't be found. This seems to point to how conda
+  # links $CMAKE_EXEC to its package cache when cloning a new environment
+  install_name_tool -add_rpath @executable_path/../lib "${CMAKE_EXEC}" || true
+  # Adding the rpath will invalidate cmake signature, so signing it again here
+  # to trust the executable. EXC_BAD_ACCESS (SIGKILL (Code Signature Invalid))
+  # with an exit code 137 otherwise
+  codesign -f -s - "${CMAKE_EXEC}" || true
 }

.ci/pytorch/macos-test.sh

@@ -18,9 +18,6 @@ if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available(
 fi
 popd
 
-# enable debug asserts in serialization
-export TORCH_SERIALIZATION_DEBUG=1
-
 setup_test_python() {
   # The CircleCI worker hostname doesn't resolve to an address.
   # This environment variable makes ProcessGroupGloo default to
@@ -42,16 +39,6 @@ test_python_all() {
   assert_git_not_dirty
 }
 
-test_python_mps() {
-  setup_test_python
-
-  time python test/run_test.py --verbose --mps
-  MTL_CAPTURE_ENABLED=1 ${CONDA_RUN} python3 test/test_mps.py --verbose -k test_metal_capture
-
-  assert_git_not_dirty
-}
-
-
 test_python_shard() {
   if [[ -z "$NUM_TEST_SHARDS" ]]; then
     echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
@@ -165,7 +152,6 @@ test_jit_hooks() {
 torchbench_setup_macos() {
   git clone --recursive https://github.com/pytorch/vision torchvision
   git clone --recursive https://github.com/pytorch/audio torchaudio
-  brew install jpeg-turbo libpng
 
   pushd torchvision
   git fetch
@@ -180,8 +166,7 @@ torchbench_setup_macos() {
   git checkout "$(cat ../.github/ci_commit_pins/audio.txt)"
   git submodule update --init --recursive
   python setup.py clean
-  #TODO: Remove me, when figure out how to make TorchAudio find brew installed openmp
-  USE_OPENMP=0 python setup.py develop
+  python setup.py develop
   popd
 
   # Shellcheck doesn't like it when you pass no arguments to a function that can take args. See https://www.shellcheck.net/wiki/SC2120
@@ -189,8 +174,9 @@ torchbench_setup_macos() {
   checkout_install_torchbench
 }
 
-pip_benchmark_deps() {
-  python -mpip install --no-input astunparse requests cython scikit-learn
+conda_benchmark_deps() {
+  conda install -y astunparse numpy scipy ninja pyyaml setuptools cmake typing-extensions requests protobuf numba cython scikit-learn
+  conda install -y -c conda-forge librosa
 }
 
 
@@ -198,25 +184,17 @@ test_torchbench_perf() {
   print_cmake_info
 
   echo "Launching torchbench setup"
-  pip_benchmark_deps
+  conda_benchmark_deps
   torchbench_setup_macos
 
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
 
-  local backend=eager
-  local dtype=notset
-  local device=mps
-
   echo "Setup complete, launching torchbench training performance run"
-  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-    --performance --backend "$backend" --training --devices "$device" \
-    --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --backend eager --training --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
 
   echo "Launching torchbench inference performance run"
-  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-    --performance --backend "$backend" --inference --devices "$device" \
-    --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --backend eager --inference --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
 
   echo "Pytorch benchmark on mps device completed"
 }
@@ -225,63 +203,32 @@ test_torchbench_smoketest() {
   print_cmake_info
 
   echo "Launching torchbench setup"
-  pip_benchmark_deps
+  conda_benchmark_deps
   # shellcheck disable=SC2119,SC2120
   torchbench_setup_macos
 
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
+  touch "$TEST_REPORTS_DIR"/torchbench_training.csv
+  touch "$TEST_REPORTS_DIR"/torchbench_inference.csv
 
-  local device=mps
-  local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor)
-  local hf_models=(GoogleFnet YituTechConvBert Speech2Text2ForCausalLM)
+  echo "Setup complete, launching torchbench training performance run"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only hf_T5 --backend eager --training --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only llama --backend eager --training --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only BERT_pytorch --backend eager --training --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only dcgan --backend eager --training --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only hf_GPT2 --backend eager --training --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only yolov3 --backend eager --training --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only resnet152 --backend eager --training --devices mps --output "$TEST_REPORTS_DIR/torchbench_training.csv"
 
-  for backend in eager inductor; do
-
-    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_${device}_performance.csv" || true
-        if [ "$backend" == "inductor" ]; then
-          PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-            --accuracy --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
-            --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_accuracy.csv" || true
-        fi
-      done
-      for model in "${hf_models[@]}"; do
-        if [ "$backend" == "inductor" ]; then
-          PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/huggingface.py \
-            --performance --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
-            --output "$TEST_REPORTS_DIR/inductor_${backend}_huggingface_${dtype}_inference_${device}_performance.csv" || true
-          PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/huggingface.py \
-            --accuracy --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
-            --output "$TEST_REPORTS_DIR/inductor_${backend}_huggingface_${dtype}_inference_${device}_accuracy.csv" || true
-        fi
-      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_${device}_performance.csv" || true
-      done
-    done
-
-  done
+  echo "Launching torchbench inference performance run"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only hf_T5 --backend eager --inference --devices mps --output "$TEST_REPORTS_DIR/torchbench_inference.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only llama --backend eager --inference --devices mps --output "$TEST_REPORTS_DIR/torchbench_inference.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only BERT_pytorch --backend eager --inference --devices mps --output "$TEST_REPORTS_DIR/torchbench_inference.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only dcgan --backend eager --inference --devices mps --output "$TEST_REPORTS_DIR/torchbench_inference.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only hf_GPT2 --backend eager --inference --devices mps --output "$TEST_REPORTS_DIR/torchbench_inference.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only yolov3 --backend eager --inference --devices mps --output "$TEST_REPORTS_DIR/torchbench_inference.csv"
+  PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py --performance --only resnet152 --backend eager --inference --devices mps --output "$TEST_REPORTS_DIR/torchbench_inference.csv"
 
   echo "Pytorch benchmark on mps device completed"
 }
@@ -290,7 +237,7 @@ test_hf_perf() {
   print_cmake_info
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
-  pip_benchmark_deps
+  conda_benchmark_deps
   torchbench_setup_macos
 
   echo "Launching HuggingFace training perf run"
@@ -306,7 +253,7 @@ test_timm_perf() {
   print_cmake_info
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
-  pip_benchmark_deps
+  conda_benchmark_deps
   torchbench_setup_macos
 
   echo "Launching timm training perf run"
@@ -320,6 +267,25 @@ test_timm_perf() {
 
 install_tlparse
 
+if [[ $TEST_CONFIG == *"test_mps"* ]]; then
+  if [[ $NUM_TEST_SHARDS -gt 1 ]]; then
+    test_python_shard "${SHARD_NUMBER}"
+    if [[ "${SHARD_NUMBER}" == 1 ]]; then
+      test_libtorch
+      test_custom_script_ops
+    elif [[ "${SHARD_NUMBER}" == 2 ]]; then
+      test_jit_hooks
+      test_custom_backend
+    fi
+  else
+    test_python_all
+    test_libtorch
+    test_custom_script_ops
+    test_jit_hooks
+    test_custom_backend
+  fi
+fi
+
 if [[ $TEST_CONFIG == *"perf_all"* ]]; then
   test_torchbench_perf
   test_hf_perf
@@ -332,21 +298,4 @@ elif [[ $TEST_CONFIG == *"perf_timm"* ]]; then
   test_timm_perf
 elif [[ $TEST_CONFIG == *"perf_smoketest"* ]]; then
   test_torchbench_smoketest
-elif [[ $TEST_CONFIG == *"mps"* ]]; then
-  test_python_mps
-elif [[ $NUM_TEST_SHARDS -gt 1 ]]; then
-  test_python_shard "${SHARD_NUMBER}"
-  if [[ "${SHARD_NUMBER}" == 1 ]]; then
-    test_libtorch
-    test_custom_script_ops
-  elif [[ "${SHARD_NUMBER}" == 2 ]]; then
-    test_jit_hooks
-    test_custom_backend
-  fi
-else
-  test_python_all
-  test_libtorch
-  test_custom_script_ops
-  test_jit_hooks
-  test_custom_backend
 fi

.ci/pytorch/multigpu-test.sh

@@ -8,62 +8,55 @@
 source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
 
 echo "Testing pytorch"
-# When adding more tests, please use HUD to see which shard is shorter
-if [[ "${SHARD_NUMBER:-1}" == "1" ]]; then
-    # FSDP tests
-    for f in test/distributed/fsdp/*.py ; do time python test/run_test.py --verbose -i "${f#*/}" ; done
-fi
+time python test/run_test.py --include test_cuda_multigpu test_cuda_primary_ctx --verbose
 
-if [[ "${SHARD_NUMBER:-2}" == "2" ]]; then
-    time python test/run_test.py --include test_cuda_multigpu test_cuda_primary_ctx --verbose
+# Disabling tests to see if they solve timeout issues; see https://github.com/pytorch/pytorch/issues/70015
+# python tools/download_mnist.py --quiet -d test/cpp/api/mnist
+# OMP_NUM_THREADS=2 TORCH_CPP_TEST_MNIST_PATH="test/cpp/api/mnist" build/bin/test_api
+time python test/run_test.py --verbose -i distributed/test_c10d_common
+time python test/run_test.py --verbose -i distributed/test_c10d_gloo
+time python test/run_test.py --verbose -i distributed/test_c10d_nccl
+time python test/run_test.py --verbose -i distributed/test_c10d_spawn_gloo
+time python test/run_test.py --verbose -i distributed/test_c10d_spawn_nccl
+time python test/run_test.py --verbose -i distributed/test_compute_comm_reordering
+time python test/run_test.py --verbose -i distributed/test_store
+time python test/run_test.py --verbose -i distributed/test_symmetric_memory
+time python test/run_test.py --verbose -i distributed/test_pg_wrapper
+time python test/run_test.py --verbose -i distributed/rpc/cuda/test_tensorpipe_agent
+# FSDP tests
+for f in test/distributed/fsdp/*.py ; do time python test/run_test.py --verbose -i "${f#*/}" ; done
+# ShardedTensor tests
+time python test/run_test.py --verbose -i distributed/checkpoint/test_checkpoint
+time python test/run_test.py --verbose -i distributed/checkpoint/test_file_system_checkpoint
+time python test/run_test.py --verbose -i distributed/_shard/sharding_spec/test_sharding_spec
+time python test/run_test.py --verbose -i distributed/_shard/sharding_plan/test_sharding_plan
+time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test_sharded_tensor
+time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test_sharded_tensor_reshard
 
-    # Disabling tests to see if they solve timeout issues; see https://github.com/pytorch/pytorch/issues/70015
-    # python tools/download_mnist.py --quiet -d test/cpp/api/mnist
-    # OMP_NUM_THREADS=2 TORCH_CPP_TEST_MNIST_PATH="test/cpp/api/mnist" build/bin/test_api
-    time python test/run_test.py --verbose -i distributed/test_c10d_common
-    time python test/run_test.py --verbose -i distributed/test_c10d_gloo
-    time python test/run_test.py --verbose -i distributed/test_c10d_nccl
-    time python test/run_test.py --verbose -i distributed/test_c10d_spawn_gloo
-    time python test/run_test.py --verbose -i distributed/test_c10d_spawn_nccl
-    time python test/run_test.py --verbose -i distributed/test_compute_comm_reordering
-    time python test/run_test.py --verbose -i distributed/test_store
-    time python test/run_test.py --verbose -i distributed/test_symmetric_memory
-    time python test/run_test.py --verbose -i distributed/test_pg_wrapper
-    time python test/run_test.py --verbose -i distributed/rpc/cuda/test_tensorpipe_agent
+# functional collective tests
+time python test/run_test.py --verbose -i distributed/test_functional_api
 
-    # ShardedTensor tests
-    time python test/run_test.py --verbose -i distributed/checkpoint/test_checkpoint
-    time python test/run_test.py --verbose -i distributed/checkpoint/test_file_system_checkpoint
-    time python test/run_test.py --verbose -i distributed/_shard/sharding_spec/test_sharding_spec
-    time python test/run_test.py --verbose -i distributed/_shard/sharding_plan/test_sharding_plan
-    time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test_sharded_tensor
-    time python test/run_test.py --verbose -i distributed/_shard/sharded_tensor/test_sharded_tensor_reshard
+# DTensor tests
+time python test/run_test.py --verbose -i distributed/_tensor/test_random_ops
+time python test/run_test.py --verbose -i distributed/_tensor/test_dtensor_compile
 
-    # functional collective tests
-    time python test/run_test.py --verbose -i distributed/test_functional_api
+# DeviceMesh test
+time python test/run_test.py --verbose -i distributed/test_device_mesh
 
-    # DTensor tests
-    time python test/run_test.py --verbose -i distributed/tensor/test_random_ops
-    time python test/run_test.py --verbose -i distributed/tensor/test_dtensor_compile
+# DTensor/TP tests
+time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_examples
+time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_random_state
 
-    # DeviceMesh test
-    time python test/run_test.py --verbose -i distributed/test_device_mesh
+# FSDP2 tests
+time python test/run_test.py --verbose -i distributed/_composable/fsdp/test_fully_shard_training -- -k test_2d_mlp_with_nd_mesh
 
-    # DTensor/TP tests
-    time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_examples
-    time python test/run_test.py --verbose -i distributed/tensor/parallel/test_tp_random_state
+# ND composability tests
+time python test/run_test.py --verbose -i distributed/_composable/test_composability/test_2d_composability
+time python test/run_test.py --verbose -i distributed/_composable/test_composability/test_pp_composability
 
-    # FSDP2 tests
-    time python test/run_test.py --verbose -i distributed/_composable/fsdp/test_fully_shard_training -- -k test_2d_mlp_with_nd_mesh
-
-    # ND composability tests
-    time python test/run_test.py --verbose -i distributed/_composable/test_composability/test_2d_composability
-    time python test/run_test.py --verbose -i distributed/_composable/test_composability/test_pp_composability
-
-    # Other tests
-    time python test/run_test.py --verbose -i test_cuda_primary_ctx
-    time python test/run_test.py --verbose -i test_optim -- -k test_forloop_goes_right_direction_multigpu
-    time python test/run_test.py --verbose -i test_optim -- -k test_mixed_device_dtype
-    time python test/run_test.py --verbose -i test_foreach -- -k test_tensors_grouping
-fi
+# Other tests
+time python test/run_test.py --verbose -i test_cuda_primary_ctx
+time python test/run_test.py --verbose -i test_optim -- -k test_forloop_goes_right_direction_multigpu
+time python test/run_test.py --verbose -i test_optim -- -k test_mixed_device_dtype
+time python test/run_test.py --verbose -i test_foreach -- -k test_tensors_grouping
 assert_git_not_dirty

.ci/pytorch/perf_test/common.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+set -e
+
+run_test () {
+  rm -rf test_tmp/ && mkdir test_tmp/ && cd test_tmp/
+  "$@"
+  cd .. && rm -rf test_tmp/
+}
+
+get_runtime_of_command () {
+  TIMEFORMAT=%R
+
+  # runtime=$( { time ($@ &> /dev/null); } 2>&1 1>/dev/null)
+  runtime=$( { time "$@"; } 2>&1 1>/dev/null)
+  if [[ $runtime == *"Error"* ]]; then
+    exit 1
+  fi
+  runtime=${runtime#+++ $@}
+  runtime=$(python -c "print($runtime)")
+
+  echo "$runtime"
+}

.ci/pytorch/perf_test/compare_with_baseline.py

@@ -0,0 +1,91 @@
+import argparse
+import json
+import math
+import sys
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument(
+    "--test-name", dest="test_name", action="store", required=True, help="test name"
+)
+parser.add_argument(
+    "--sample-stats",
+    dest="sample_stats",
+    action="store",
+    required=True,
+    help="stats from sample",
+)
+parser.add_argument(
+    "--update",
+    action="store_true",
+    help="whether to update baseline using stats from sample",
+)
+args = parser.parse_args()
+
+test_name = args.test_name
+
+if "cpu" in test_name:
+    backend = "cpu"
+elif "gpu" in test_name:
+    backend = "gpu"
+
+data_file_path = f"../{backend}_runtime.json"
+
+with open(data_file_path) as data_file:
+    data = json.load(data_file)
+
+if test_name in data:
+    mean = float(data[test_name]["mean"])
+    sigma = float(data[test_name]["sigma"])
+else:
+    # Let the test pass if baseline number doesn't exist
+    mean = sys.maxsize
+    sigma = 0.001
+
+print("population mean: ", mean)
+print("population sigma: ", sigma)
+
+# Let the test pass if baseline number is NaN (which happened in
+# the past when we didn't have logic for catching NaN numbers)
+if math.isnan(mean) or math.isnan(sigma):
+    mean = sys.maxsize
+    sigma = 0.001
+
+sample_stats_data = json.loads(args.sample_stats)
+
+sample_mean = float(sample_stats_data["mean"])
+sample_sigma = float(sample_stats_data["sigma"])
+
+print("sample mean: ", sample_mean)
+print("sample sigma: ", sample_sigma)
+
+if math.isnan(sample_mean):
+    raise Exception("""Error: sample mean is NaN""")  # noqa: TRY002
+elif math.isnan(sample_sigma):
+    raise Exception("""Error: sample sigma is NaN""")  # noqa: TRY002
+
+z_value = (sample_mean - mean) / sigma
+
+print("z-value: ", z_value)
+
+if z_value >= 3:
+    raise Exception(  # noqa: TRY002
+        f"""\n
+z-value >= 3, there is high chance of perf regression.\n
+To reproduce this regression, run
+`cd .ci/pytorch/perf_test/ && bash {test_name}.sh` on your local machine
+and compare the runtime before/after your code change.
+"""
+    )
+else:
+    print("z-value < 3, no perf regression detected.")
+    if args.update:
+        print("We will use these numbers as new baseline.")
+        new_data_file_path = f"../new_{backend}_runtime.json"
+        with open(new_data_file_path) as new_data_file:
+            new_data = json.load(new_data_file)
+        new_data[test_name] = {}
+        new_data[test_name]["mean"] = sample_mean
+        new_data[test_name]["sigma"] = max(sample_sigma, sample_mean * 0.1)
+        with open(new_data_file_path, "w") as new_data_file:
+            json.dump(new_data, new_data_file, indent=4)

.ci/pytorch/perf_test/get_stats.py

@@ -0,0 +1,18 @@
+import json
+import sys
+
+import numpy
+
+
+sample_data_list = sys.argv[1:]
+sample_data_list = [float(v.strip()) for v in sample_data_list]
+
+sample_mean = numpy.mean(sample_data_list)
+sample_sigma = numpy.std(sample_data_list)
+
+data = {
+    "mean": sample_mean,
+    "sigma": sample_sigma,
+}
+
+print(json.dumps(data))

.ci/pytorch/perf_test/test_cpu_speed_mini_sequence_labeler.sh

@@ -0,0 +1,43 @@
+#!/bin/bash
+set -e
+
+. ./common.sh
+
+test_cpu_speed_mini_sequence_labeler () {
+  echo "Testing: mini sequence labeler, CPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/pytorch/benchmark.git
+
+  cd benchmark/
+
+  git checkout 726567a455edbfda6199445922a8cfee82535664
+
+  cd scripts/mini_sequence_labeler
+
+  SAMPLE_ARRAY=()
+  NUM_RUNS=$1
+
+  for (( i=1; i<=NUM_RUNS; i++ )) do
+    runtime=$(get_runtime_of_command python main.py)
+    SAMPLE_ARRAY+=("${runtime}")
+  done
+
+  cd ../../..
+
+  stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
+  echo "Runtime stats in seconds:"
+  echo "$stats"
+
+  if [ "$2" == "compare_with_baseline" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
+  elif [ "$2" == "compare_and_update" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_cpu_speed_mini_sequence_labeler "$@"
+fi

.ci/pytorch/perf_test/test_cpu_speed_mnist.sh

@@ -0,0 +1,45 @@
+#!/bin/bash
+set -e
+
+. ./common.sh
+
+test_cpu_speed_mnist () {
+  echo "Testing: MNIST, CPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/pytorch/examples.git -b perftests
+
+  cd examples/mnist
+
+  conda install -c pytorch torchvision-cpu
+
+  # Download data
+  python main.py --epochs 0
+
+  SAMPLE_ARRAY=()
+  NUM_RUNS=$1
+
+  for (( i=1; i<=NUM_RUNS; i++ )) do
+    runtime=$(get_runtime_of_command python main.py --epochs 1 --no-log)
+    echo "$runtime"
+    SAMPLE_ARRAY+=("${runtime}")
+  done
+
+  cd ../..
+
+  stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
+  echo "Runtime stats in seconds:"
+  echo "$stats"
+
+  if [ "$2" == "compare_with_baseline" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
+  elif [ "$2" == "compare_and_update" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_cpu_speed_mnist "$@"
+fi