[WIP] functional autograd + compiled autograd

This commit refactors autograd so that nodes can be called in a
functional way. Furthermore, it refactors compiled autograd to use
the new functional autograd, without any behavior changes.

This is on the way to getting compiled autograd to stop tracing into
autograd nodes when it constructs an FX graph out of the autograd graph.
We also implement some very basic support for that, which can be toggled
via `old_inline_behavior=False` in compiled_autograd.py.

Functional autograd works like the following:
- All torch::autograd::Node must define a
  `retrieve_saved(SwapSavedVariables) -> ivalue_list` API. This function
  takes compiled autograd's SwapSavedVariables and packs the state that
  is relevant to the current Node into an ivalue_list.
- All torch::autograd::Node must define a
  `get_functional() -> std::function`.
  This returns a new stateless function that accepts the
  gradients and saved values as an ivalue_list and returns new
  gradients.
- We developed a mechanism to bind arbitrary C++ functions that take
  ivalue_list to Python.
  This is really similar to how we bind custom ops to Python and was
  done in consideration of the Windows symbol limit (otherwise, we'd be
  binding one symbol per Node into Python).

Here's an example of the new autograd generated code
- https://gist.github.com/zou3519/09bb98bb0f11445bc3da063201adb818

Here's an example of the FX graph compiled autograd produces (with
old_inline_behavior=False):
- https://gist.github.com/zou3519/43e8106176d15d623e1377850f585c97

.bazelversion

@@ -1 +1 @@
-6.5.0
+6.1.1

.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
 ###############################################################################

.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
     """
@@ -39,7 +42,7 @@ def build_ArmComputeLibrary() -> None:
             "clone",
             "https://github.com/ARM-software/ComputeLibrary.git",
             "-b",
-            "v25.02",
+            "v24.09",
             "--depth",
             "1",
             "--shallow-submodules",
@@ -55,7 +58,7 @@ def build_ArmComputeLibrary() -> None:
         shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
 
 
-def update_wheel(wheel_path, desired_cuda) -> None:
+def update_wheel(wheel_path) -> None:
     """
     Update the cuda wheel libraries
     """
@@ -77,6 +80,7 @@ def update_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",
@@ -96,18 +100,6 @@ def update_wheel(wheel_path, desired_cuda) -> None:
             "/usr/local/lib/libnvpl_lapack_core.so.0",
             "/usr/local/lib/libnvpl_blas_core.so.0",
         ]
-        if "126" in desired_cuda:
-            libs_to_copy += [
-                "/usr/local/cuda/lib64/libnvrtc-builtins.so.12.6",
-                "/usr/local/cuda/lib64/libcufile.so.0",
-                "/usr/local/cuda/lib64/libcufile_rdma.so.1",
-            ]
-        elif "128" in desired_cuda:
-            libs_to_copy += [
-                "/usr/local/cuda/lib64/libnvrtc-builtins.so.12.8",
-                "/usr/local/cuda/lib64/libcufile.so.0",
-                "/usr/local/cuda/lib64/libcufile_rdma.so.1",
-            ]
     else:
         libs_to_copy += [
             "/opt/OpenBLAS/lib/libopenblas.so.0",
@@ -179,22 +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 = "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()
@@ -204,11 +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()
@@ -232,6 +225,6 @@ if __name__ == "__main__":
         print("Updating Cuda Dependency")
         filename = os.listdir("/pytorch/dist/")
         wheel_path = f"/pytorch/dist/{filename[0]}"
-        update_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

@@ -12,7 +12,7 @@ import os
 import subprocess
 import sys
 import time
-from typing import Optional, Union
+from typing import Dict, List, Optional, Tuple, Union
 
 import boto3
 
@@ -24,12 +24,10 @@ os_amis = {
     "ubuntu22_04": "ami-0c6c29c5125214c77",  # login_name: ubuntu
     "redhat8": "ami-0698b90665a2ddcf1",  # login_name: ec2-user
 }
-
 ubuntu18_04_ami = os_amis["ubuntu18_04"]
-ubuntu20_04_ami = os_amis["ubuntu20_04"]
 
 
-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:
@@ -59,7 +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,
@@ -98,7 +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",
@@ -110,13 +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")
@@ -159,7 +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
@@ -180,7 +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
@@ -232,7 +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")
 
 
@@ -329,7 +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}")
@@ -360,7 +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):
@@ -621,11 +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))
@@ -683,7 +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
     )
@@ -710,7 +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")
@@ -761,7 +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:
@@ -934,9 +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,
@@ -966,13 +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:

.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
 
@@ -90,21 +86,32 @@ CMAKE_VERSION=3.18.5
 
 _UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
 _UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
-if [[ "$image" == *rocm* ]]; then
-  _UCX_COMMIT=cc312eaa4655c0cc5c2bcd796db938f90563bcf6
-  _UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d
-fi
 
 # It's annoying to rename jobs every time you want to rewrite a
 # configuration, so we hardcode everything here rather than do it
 # from scratch
 case "$image" in
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc11)
-    CUDA_VERSION=12.6.3
+  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.4.1
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
+    GCC_VERSION=9
     PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    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}
@@ -118,6 +125,37 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
     PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    INDUCTOR_BENCHMARKS=yes
+    ;;
+  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.1.1
+    CUDNN_VERSION=9
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    INDUCTOR_BENCHMARKS=yes
+    ;;
+  pytorch-linux-focal-cuda12.1-cudnn9-py3.12-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.1.1
+    CUDNN_VERSION=9
+    ANACONDA_PYTHON_VERSION=3.12
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
@@ -132,75 +170,7 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=9
     PROTOBUF=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.4-cudnn9-py3.13-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.4.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.13
-    GCC_VERSION=9
-    PROTOBUF=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.12
-    GCC_VERSION=9
-    PROTOBUF=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.13
-    GCC_VERSION=9
-    PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
@@ -215,6 +185,49 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
     PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    KATEX=yes
+    UCX_COMMIT=${_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}
@@ -226,6 +239,7 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=10
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     ONNX=yes
@@ -234,6 +248,7 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=10
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     VULKAN_SDK_VERSION=1.2.162.1
     SWIFTSHADER=yes
@@ -244,6 +259,7 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.11
     CLANG_VERSION=10
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     VULKAN_SDK_VERSION=1.2.162.1
     SWIFTSHADER=yes
@@ -254,42 +270,38 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=9
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
   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=6.2.4
+    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-focal-rocm-n-py3)
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
+    GCC_VERSION=9
     PROTOBUF=yes
+    DB=yes
     VISION=yes
-    ROCM_VERSION=6.3
+    ROCM_VERSION=6.2
     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-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
@@ -300,6 +312,7 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     XPU_VERSION=2025.0
     NINJA_VERSION=1.9.0
@@ -310,6 +323,7 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     CONDA_CMAKE=yes
@@ -323,6 +337,7 @@ case "$image" in
     CUDNN_VERSION=9
     CLANG_VERSION=12
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     TRITON=yes
     ;;
@@ -330,6 +345,7 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=12
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     TRITON=yes
@@ -350,6 +366,7 @@ case "$image" in
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     KATEX=yes
     CONDA_CMAKE=yes
@@ -364,7 +381,7 @@ case "$image" in
     EXECUTORCH=yes
     ;;
   pytorch-linux-jammy-py3.12-halide)
-    CUDA_VERSION=12.6
+    CUDA_VERSION=12.4
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
     CONDA_CMAKE=yes
@@ -372,7 +389,7 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-jammy-py3.12-triton-cpu)
-    CUDA_VERSION=12.6
+    CUDA_VERSION=12.4
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
     CONDA_CMAKE=yes
@@ -395,6 +412,7 @@ case "$image" in
     GCC_VERSION=11
     ACL=yes
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     # snadampal: skipping llvm src build install because the current version
@@ -406,6 +424,7 @@ case "$image" in
     GCC_VERSION=11
     ACL=yes
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     CONDA_CMAKE=yes
     # snadampal: skipping llvm src build install because the current version
@@ -416,6 +435,7 @@ case "$image" in
   *)
     # Catch-all for builds that are not hardcoded.
     PROTOBUF=yes
+    DB=yes
     VISION=yes
     echo "image '$image' did not match an existing build configuration"
     if [[ "$image" == *py* ]]; then
@@ -471,6 +491,7 @@ docker build \
        --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=${CENTOS_VERSION}" \
@@ -489,7 +510,7 @@ docker build \
        --build-arg "NINJA_VERSION=${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:-gfx906;gfx90a}" \
        --build-arg "IMAGE_NAME=${IMAGE_NAME}" \
        --build-arg "UCX_COMMIT=${UCX_COMMIT}" \
        --build-arg "UCC_COMMIT=${UCC_COMMIT}" \

.ci/docker/centos-rocm/Dockerfile

@@ -55,6 +55,13 @@ 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 ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -106,6 +113,13 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${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 @@
-5e4d6b6380d575e48e37e9d987fded4ec588e7bc
+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 @@
-v2.26.2-1

.ci/docker/ci_commit_pins/timm.txt

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

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

@@ -1 +1 @@
-83111ab22be6e4a588d184ac45175986a7dde9fc
+91b14bf5593cf58a8541f3e6b9125600a867d4ef

.ci/docker/ci_commit_pins/triton.txt

@@ -1 +1 @@
-96316ce50fade7e209553aba4898cd9b82aab83b
+cf34004b8a67d290a962da166f5aa2fc66751326

.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=2.25.1-1+cuda12.4 libnccl-dev=2.25.1-1+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

.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 v0.9.1
+  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_conda.sh

@@ -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}"
@@ -66,7 +65,7 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
 
   # Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
   if [[ $(uname -m) == "aarch64" ]]; then
-    conda_install "openblas==0.3.29=*openmp*"
+    conda_install "openblas==0.3.25=*openmp*"
   else
     conda_install "mkl=2021.4.0 mkl-include=2021.4.0"
   fi
@@ -85,9 +84,8 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
 
   # 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
-    ${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION}) ${ANACONDA_PYTHON_VERSION}
+    conda_install magma-cuda$(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

@@ -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

@@ -2,8 +2,8 @@
 
 set -ex
 
-NCCL_VERSION=v2.25.1-1
-CUDNN_VERSION=9.5.1.17
+NCCL_VERSION=v2.21.5-1
+CUDNN_VERSION=9.1.0.70
 
 function install_cusparselt_040 {
     # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
@@ -16,6 +16,17 @@ function install_cusparselt_040 {
     rm -rf tmp_cusparselt
 }
 
+function install_cusparselt_052 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.5.2.1-archive.tar.xz
+    tar xf libcusparse_lt-linux-x86_64-0.5.2.1-archive.tar.xz
+    cp -a libcusparse_lt-linux-x86_64-0.5.2.1-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-x86_64-0.5.2.1-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
+
 function install_cusparselt_062 {
     # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
     mkdir tmp_cusparselt && pushd tmp_cusparselt
@@ -27,20 +38,7 @@ function install_cusparselt_062 {
     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
-    NCCL_VERSION=v2.21.5-1
     echo "Installing CUDA 11.8 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.4.0"
     rm -rf /usr/local/cuda-11.8 /usr/local/cuda
     # install CUDA 11.8.0 in the same container
@@ -73,8 +71,40 @@ function install_118 {
     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 ${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
@@ -108,13 +138,13 @@ function install_124 {
 }
 
 function install_126 {
-  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
+  echo "Installing CUDA 12.6.2 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.2"
   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
+  # install CUDA 12.6.2 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.6.2/local_installers/cuda_12.6.2_560.35.03_linux.run
+  chmod +x cuda_12.6.2_560.35.03_linux.run
+  ./cuda_12.6.2_560.35.03_linux.run --toolkit --silent
+  rm -f cuda_12.6.2_560.35.03_linux.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
@@ -135,7 +165,7 @@ function install_126 {
   cd ..
   rm -rf nccl
 
-  install_cusparselt_063
+  install_cusparselt_062
 
   ldconfig
 }
@@ -171,6 +201,37 @@ 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"
   #####################################################################################
@@ -239,52 +300,18 @@ 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 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
-  rm -rf /usr/local/cuda-12.8 /usr/local/cuda
-  # install CUDA 12.8.0 in the same container
-  wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux.run
-  chmod +x cuda_12.8.0_570.86.10_linux.run
-  ./cuda_12.8.0_570.86.10_linux.run --toolkit --silent
-  rm -f cuda_12.8.0_570.86.10_linux.run
-  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.8 /usr/local/cuda
-
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  mkdir tmp_cudnn && cd tmp_cudnn
-  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_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_063
-
-  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

@@ -4,7 +4,7 @@
 set -ex
 
 NCCL_VERSION=v2.21.5-1
-CUDNN_VERSION=9.5.1.17
+CUDNN_VERSION=9.1.0.70
 
 function install_cusparselt_062 {
     # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
@@ -17,19 +17,7 @@ function install_cusparselt_062 {
     rm -rf tmp_cusparselt
 }
 
-function install_cusparselt_063 {
-    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
-    mkdir tmp_cusparselt && pushd tmp_cusparselt
-    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-sbsa/libcusparse_lt-linux-sbsa-0.6.3.2-archive.tar.xz
-    tar xf libcusparse_lt-linux-sbsa-0.6.3.2-archive.tar.xz
-    cp -a libcusparse_lt-linux-sbsa-0.6.3.2-archive/include/* /usr/local/cuda/include/
-    cp -a libcusparse_lt-linux-sbsa-0.6.3.2-archive/lib/* /usr/local/cuda/lib64/
-    popd
-    rm -rf tmp_cusparselt
-}
-
 function install_124 {
-  CUDNN_VERSION=9.1.0.70
   echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.2"
   rm -rf /usr/local/cuda-12.4 /usr/local/cuda
   # install CUDA 12.4.1 in the same container
@@ -57,7 +45,7 @@ function install_124 {
   cd ..
   rm -rf nccl
 
-  install_cusparselt_063
+  install_cusparselt_062
 
   ldconfig
 }
@@ -94,13 +82,13 @@ function prune_124 {
 }
 
 function install_126 {
-  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
+  echo "Installing CUDA 12.6.2 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.2"
   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
+  # install CUDA 12.6.2 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.6.2/local_installers/cuda_12.6.2_560.35.03_linux_sbsa.run
+  chmod +x cuda_12.6.2_560.35.03_linux_sbsa.run
+  ./cuda_12.6.2_560.35.03_linux_sbsa.run --toolkit --silent
+  rm -f cuda_12.6.2_560.35.03_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
@@ -121,7 +109,7 @@ function install_126 {
   cd ..
   rm -rf nccl
 
-  install_cusparselt_063
+  install_cusparselt_062
 
   ldconfig
 }
@@ -160,40 +148,6 @@ 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 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
-  rm -rf /usr/local/cuda-12.8 /usr/local/cuda
-  # install CUDA 12.8.0 in the same container
-  wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux_sbsa.run
-  chmod +x cuda_12.8.0_570.86.10_linux_sbsa.run
-  ./cuda_12.8.0_570.86.10_linux_sbsa.run --toolkit --silent
-  rm -f cuda_12.8.0_570.86.10_linux_sbsa.run
-  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.8 /usr/local/cuda
-
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  mkdir tmp_cudnn && cd tmp_cudnn
-  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-sbsa/cudnn-linux-sbsa-${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
-}
-
 # idiomatic parameter and option handling in sh
 while test $# -gt 0
 do
@@ -202,8 +156,6 @@ do
         ;;
     12.6) install_126; prune_126
         ;;
-    12.8) install_128;
-        ;;
     *) echo "bad argument $1"; exit 1
         ;;
     esac

.ci/docker/common/install_cudnn.sh

@@ -4,11 +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
-        CUDNN_NAME="cudnn-linux-x86_64-9.5.1.17_cuda12-archive"
-    elif [[ ${CUDA_VERSION:0:2} == "12" ]]; then
+    if [[ ${CUDA_VERSION:0:2} == "12" ]]; then
         CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda12-archive"
     elif [[ ${CUDA_VERSION:0:2} == "11" ]]; then
         CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda11-archive"

.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

@@ -37,17 +37,14 @@ 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 EXECUTORCH_BUILD_PYBIND=ON

.ci/docker/common/install_inductor_benchmark_deps.sh

@@ -7,20 +7,14 @@ 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=$(get_pinned_commit timm)
-
-  # TODO (huydhn): There is no torchvision release on 3.13 when I write this, so
-  # I'm using nightly here instead. We just need to package to be able to install
-  # TIMM. Removing this once vision has a release on 3.13
-  if [[ "${ANACONDA_PYTHON_VERSION}" == "3.13" ]]; then
-    pip_install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu124
-  fi
-
+  pip_install pandas==2.0.3
   pip_install "git+https://github.com/huggingface/pytorch-image-models@${commit}"
   # Clean up
   conda_run pip uninstall -y cmake torch torchvision triton

.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

@@ -1,26 +0,0 @@
-#!/usr/bin/env bash
-# Script that replaces the magma install from a conda package
-
-set -eou pipefail
-
-function do_install() {
-    cuda_version_nodot=${1/./}
-    anaconda_python_version=$2
-
-    MAGMA_VERSION="2.6.1"
-    magma_archive="magma-cuda${cuda_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
-
-    anaconda_dir="/opt/conda/envs/py_${anaconda_python_version}"
-    (
-        set -x
-        tmp_dir=$(mktemp -d)
-        pushd ${tmp_dir}
-        curl -OLs https://ossci-linux.s3.us-east-1.amazonaws.com/${magma_archive}
-        tar -xvf "${magma_archive}"
-        mv include/* "${anaconda_dir}/include/"
-        mv lib/* "${anaconda_dir}/lib"
-        popd
-    )
-}
-
-do_install $1 $2

.ci/docker/common/install_miopen.sh

@@ -16,7 +16,7 @@ case "$ID" in
   ubuntu)
     IS_UBUNTU=1
     ;;
-  centos|almalinux)
+  centos)
     IS_UBUNTU=0
     ;;
   *)
@@ -43,6 +43,12 @@ else
 fi
 ROCM_INT=$(($ROCM_VERSION_MAJOR * 10000 + $ROCM_VERSION_MINOR * 100 + $ROCM_VERSION_PATCH))
 
+# Install custom MIOpen + COMgr for ROCm >= 4.0.1
+if [[ $ROCM_INT -lt 40001 ]]; then
+    echo "ROCm version < 4.0.1; will not install custom MIOpen"
+    exit 0
+fi
+
 # Function to retry functions that sometimes timeout or have flaky failures
 retry () {
     $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
@@ -60,27 +66,55 @@ else
     ROCM_INSTALL_PATH="/opt/rocm-${ROCM_VERSION}"
 fi
 
+# MIOPEN_USE_HIP_KERNELS is a Workaround for COMgr issues
 MIOPEN_CMAKE_COMMON_FLAGS="
 -DMIOPEN_USE_COMGR=ON
 -DMIOPEN_BUILD_DRIVER=OFF
 "
-if [[ $ROCM_INT -ge 60200 ]] && [[ $ROCM_INT -lt 60204 ]]; then
-    MIOPEN_BRANCH="release/rocm-rel-6.2-staging"
-else
-    echo "ROCm ${ROCM_VERSION} does not need any patches, do not build from source"
+# Pull MIOpen repo and set DMIOPEN_EMBED_DB based on ROCm version
+if [[ $ROCM_INT -ge 60300 ]]; then
+    echo "ROCm 6.3+ MIOpen does not need any patches, do not build from source"
     exit 0
+elif [[ $ROCM_INT -ge 60200 ]] && [[ $ROCM_INT -lt 60300 ]]; then
+    MIOPEN_BRANCH="release/rocm-rel-6.2-staging"
+elif [[ $ROCM_INT -ge 60100 ]] && [[ $ROCM_INT -lt 60200 ]]; then
+    echo "ROCm 6.1 MIOpen does not need any patches, do not build from source"
+    exit 0
+elif [[ $ROCM_INT -ge 60000 ]] && [[ $ROCM_INT -lt 60100 ]]; then
+    echo "ROCm 6.0 MIOpen does not need any patches, do not build from source"
+    exit 0
+elif [[ $ROCM_INT -ge 50700 ]] && [[ $ROCM_INT -lt 60000 ]]; then
+    echo "ROCm 5.7 MIOpen does not need any patches, do not build from source"
+    exit 0
+elif [[ $ROCM_INT -ge 50600 ]] && [[ $ROCM_INT -lt 50700 ]]; then
+    MIOPEN_BRANCH="release/rocm-rel-5.6-staging"
+elif [[ $ROCM_INT -ge 50500 ]] && [[ $ROCM_INT -lt 50600 ]]; then
+    MIOPEN_BRANCH="release/rocm-rel-5.5-gfx11"
+elif [[ $ROCM_INT -ge 50400 ]] && [[ $ROCM_INT -lt 50500 ]]; then
+    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
+    MIOPEN_BRANCH="release/rocm-rel-5.4-staging"
+elif [[ $ROCM_INT -ge 50300 ]] && [[ $ROCM_INT -lt 50400 ]]; then
+    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
+    MIOPEN_BRANCH="release/rocm-rel-5.3-staging"
+elif [[ $ROCM_INT -ge 50200 ]] && [[ $ROCM_INT -lt 50300 ]]; then
+    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36 -DMIOPEN_USE_MLIR=Off"
+    MIOPEN_BRANCH="release/rocm-rel-5.2-staging"
+elif [[ $ROCM_INT -ge 50100 ]] && [[ $ROCM_INT -lt 50200 ]]; then
+    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36"
+    MIOPEN_BRANCH="release/rocm-rel-5.1-staging"
+elif [[ $ROCM_INT -ge 50000 ]] && [[ $ROCM_INT -lt 50100 ]]; then
+    MIOPEN_CMAKE_DB_FLAGS="-DMIOPEN_EMBED_DB=gfx900_56;gfx906_60;gfx90878;gfx90a6e;gfx1030_36"
+    MIOPEN_BRANCH="release/rocm-rel-5.0-staging"
+else
+    echo "Unhandled ROCM_VERSION ${ROCM_VERSION}"
+    exit 1
 fi
 
 
 if [[ ${IS_UBUNTU} == 1 ]]; then
   apt-get remove -y miopen-hip
 else
-  # Workaround since almalinux manylinux image already has this and cget doesn't like that
-  rm -rf /usr/local/lib/pkgconfig/sqlite3.pc
-
-  # Versioned package name needs regex match
-  # Use --noautoremove to prevent other rocm packages from being uninstalled
-  yum remove -y miopen-hip* --noautoremove
+  yum remove -y miopen-hip
 fi
 
 git clone https://github.com/ROCm/MIOpen -b ${MIOPEN_BRANCH}
@@ -88,7 +122,16 @@ pushd MIOpen
 # remove .git to save disk space since CI runner was running out
 rm -rf .git
 # Don't build CK to save docker build time
-sed -i '/composable_kernel/d' requirements.txt
+if [[ $ROCM_INT -ge 60200 ]]; then
+    sed -i '/composable_kernel/d' requirements.txt
+fi
+# Don't build MLIR to save docker build time
+# since we are disabling MLIR backend for MIOpen anyway
+if [[ $ROCM_INT -ge 50400 ]] && [[ $ROCM_INT -lt 50500 ]]; then
+    sed -i '/rocMLIR/d' requirements.txt
+elif [[ $ROCM_INT -ge 50200 ]] && [[ $ROCM_INT -lt 50400 ]]; then
+    sed -i '/llvm-project-mlir/d' requirements.txt
+fi
 ## MIOpen minimum requirements
 cmake -P install_deps.cmake --minimum
 
@@ -110,7 +153,7 @@ cd build
 PKG_CONFIG_PATH=/usr/local/lib/pkgconfig CXX=${ROCM_INSTALL_PATH}/llvm/bin/clang++ cmake .. \
     ${MIOPEN_CMAKE_COMMON_FLAGS} \
     ${MIOPEN_CMAKE_DB_FLAGS} \
-    -DCMAKE_PREFIX_PATH="${ROCM_INSTALL_PATH}"
+    -DCMAKE_PREFIX_PATH="${ROCM_INSTALL_PATH}/hip;${ROCM_INSTALL_PATH}"
 make MIOpen -j $(nproc)
 
 # Build MIOpen package

.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

@@ -31,15 +31,15 @@ pip_install \
 pip_install coloredlogs packaging
 
 pip_install onnxruntime==1.18.1
-pip_install onnx==1.17.0
-pip_install onnxscript==0.2.2 --no-deps
+pip_install onnx==1.16.2
+pip_install onnxscript==0.1.0.dev20241009 --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_rocm.sh

@@ -62,22 +62,6 @@ install_ubuntu() {
         sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
     done
 
-    # ROCm 6.3 had a regression where initializing static code objects had significant overhead
-    if [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]]; then
-        # clr build needs CppHeaderParser but can only find it using conda's python
-        /opt/conda/bin/python -m pip install CppHeaderParser
-        git clone https://github.com/ROCm/HIP -b rocm-6.3.x
-        HIP_COMMON_DIR=$(readlink -f HIP)
-        git clone https://github.com/jeffdaily/clr -b release/rocm-rel-6.3-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.6.3.* /opt/rocm/lib/libamdhip64.so.6.3.*
-        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

@@ -12,7 +12,7 @@ case "$ID" in
     apt-get install -y libpciaccess-dev pkg-config
     apt-get clean
     ;;
-  centos|almalinux)
+  centos)
     yum install -y libpciaccess-devel pkgconfig
     ;;
   *)
@@ -25,9 +25,7 @@ python3 -m pip install meson ninja
 ###########################
 ### clone repo
 ###########################
-# TEMPORARY FIX: https://gitlab.freedesktop.org/mesa/drm.git is down until 2025/03/22
-# GIT_SSL_NO_VERIFY=true git clone https://gitlab.freedesktop.org/mesa/drm.git
-GIT_SSL_NO_VERIFY=true git clone git://anongit.freedesktop.org/mesa/drm
+GIT_SSL_NO_VERIFY=true git clone https://gitlab.freedesktop.org/mesa/drm.git
 pushd drm
 
 ###########################
@@ -117,7 +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

@@ -3,18 +3,6 @@
 
 set -ex
 
-# 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}
 

.ci/docker/common/install_triton.sh

@@ -60,15 +60,15 @@ 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 pip_install .
+  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 pip_install .
+  CXX=g++-9 pip_install -e .
 else
-  pip_install .
+  pip_install -e .
 fi
 
 if [ -n "${CONDA_CMAKE}" ]; then

.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_xpu.sh

@@ -57,13 +57,13 @@ function install_ubuntu() {
 function install_rhel() {
     . /etc/os-release
     if [[ "${ID}" == "rhel" ]]; then
-        if [[ ! " 8.8 8.9 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
+        if [[ ! " 8.6 8.8 8.9 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
             echo "RHEL version ${VERSION_ID} not supported"
             exit
         fi
     elif [[ "${ID}" == "almalinux" ]]; then
         # Workaround for almalinux8 which used by quay.io/pypa/manylinux_2_28_x86_64
-        VERSION_ID="8.8"
+        VERSION_ID="8.6"
     fi
 
     dnf install -y 'dnf-command(config-manager)'
@@ -81,8 +81,6 @@ repo_gpgcheck=1
 gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
 EOF
 
-    # Install Intel Support Packages
-    yum install -y ${XPU_PACKAGES}
     # The xpu-smi packages
     dnf install -y xpu-smi
     # Compute and Media Runtimes
@@ -97,6 +95,8 @@ EOF
     dnf install -y --refresh \
         intel-igc-opencl-devel level-zero-devel intel-gsc-devel libmetee-devel \
         level-zero-devel
+    # Install Intel Support Packages
+    yum install -y ${XPU_PACKAGES}
 
     # Cleanup
     dnf clean all

.ci/docker/libtorch/Dockerfile

@@ -56,6 +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
@@ -66,11 +71,6 @@ 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 PYTORCH_ROCM_ARCH
 ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
@@ -92,6 +92,13 @@ RUN apt-get update -y && \
 RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
 RUN bash ./install_rocm_magma.sh && rm install_rocm_magma.sh
 
+# Install AOTriton
+COPY ./common/common_utils.sh common_utils.sh
+COPY ./aotriton_version.txt aotriton_version.txt
+COPY ./common/install_aotriton.sh install_aotriton.sh
+RUN bash ./install_aotriton.sh /opt/rocm && rm install_aotriton.sh aotriton_version.txt
+ENV AOTRITON_INSTALLED_PREFIX /opt/rocm/aotriton
+
 FROM ${BASE_TARGET} as final
 COPY --from=openssl            /opt/openssl           /opt/openssl
 # Install patchelf

.ci/docker/libtorch/build.sh

@@ -39,7 +39,17 @@ case ${GPU_ARCH_TYPE} in
         BASE_TARGET=rocm
         DOCKER_TAG=rocm${GPU_ARCH_VERSION}
         GPU_IMAGE=rocm/dev-ubuntu-20.04:${GPU_ARCH_VERSION}-complete
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
+        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}"
         ;;
     *)

.ci/docker/linter-cuda/Dockerfile

@@ -25,8 +25,7 @@ ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
 COPY requirements-ci.txt /opt/conda/requirements-ci.txt
 COPY ./common/install_conda.sh install_conda.sh
 COPY ./common/common_utils.sh common_utils.sh
-COPY ./common/install_magma_conda.sh install_magma_conda.sh
-RUN bash ./install_conda.sh && rm install_conda.sh install_magma_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
+RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
 
 # Install cuda and cudnn
 ARG CUDA_VERSION

.ci/docker/manywheel/Dockerfile

@@ -198,3 +198,10 @@ 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

@@ -1,4 +1,5 @@
 # syntax = docker/dockerfile:experimental
+ARG ROCM_VERSION=3.7
 ARG BASE_CUDA_VERSION=11.8
 ARG GPU_IMAGE=amd64/almalinux:8
 FROM quay.io/pypa/manylinux_2_28_x86_64 as base
@@ -129,10 +130,10 @@ RUN for cpython_version in "cp312-cp312" "cp313-cp313" "cp313-cp313t"; do \
     done;
 
 
-# cmake-3.18.4 from pip; force in case cmake3 already exists
+# cmake-3.18.4 from pip
 RUN yum install -y python3-pip && \
     python3 -mpip install cmake==3.18.4 && \
-    ln -sf /usr/local/bin/cmake /usr/bin/cmake3
+    ln -s /usr/local/bin/cmake /usr/bin/cmake3
 
 FROM cpu_final as cuda_final
 RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
@@ -141,24 +142,17 @@ COPY --from=magma    /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BAS
 RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
 ENV PATH=/usr/local/cuda/bin:$PATH
 
-FROM cpu_final as rocm_final
-ARG ROCM_VERSION=6.0
-ARG PYTORCH_ROCM_ARCH
-ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
-ARG DEVTOOLSET_VERSION=11
-ENV LDFLAGS="-Wl,-rpath=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64 -Wl,-rpath=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib"
-# Somewhere in ROCm stack, we still use non-existing /opt/rocm/hip path,
-# below workaround helps avoid error
-ENV ROCM_PATH /opt/rocm
-# cmake-3.28.4 from pip to get enable_language(HIP)
-# 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
-ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
-RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
-ENV MKLROOT /opt/intel
-ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
-RUN bash ./install_rocm_magma.sh && rm install_rocm_magma.sh
+
+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
 
@@ -169,6 +163,5 @@ 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 2025.0
 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

@@ -38,12 +38,6 @@ RUN yum install -y \
   sudo \
   gcc-toolset-${GCCTOOLSET_VERSION}-toolchain
 
-# (optional) Install non-default Ninja version
-ARG NINJA_VERSION
-COPY ./common/install_ninja.sh install_ninja.sh
-RUN if [ -n "${NINJA_VERSION}" ]; then bash ./install_ninja.sh; fi
-RUN rm install_ninja.sh
-
 # Ensure the expected devtoolset is used
 ENV PATH=/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/bin:$PATH
 ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${GCCTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH

.ci/docker/manywheel/Dockerfile_aarch64

@@ -61,7 +61,7 @@ RUN git config --global --add safe.directory "*"
 # 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 \
+  && curl -L -o ~/libgfortran-10-dev.deb http://ports.ubuntu.com/ubuntu-ports/pool/universe/g/gcc-10/libgfortran-10-dev_10.5.0-1ubuntu1_arm64.deb \
   && ar x ~/libgfortran-10-dev.deb \
   && tar --use-compress-program=unzstd -xvf data.tar.zst -C ~/ \
   && cp -f ~/usr/lib/gcc/aarch64-linux-gnu/10/libgfortran.a /opt/rh/devtoolset-10/root/usr/lib/gcc/aarch64-redhat-linux/10/

.ci/docker/manywheel/build.sh

@@ -48,7 +48,7 @@ case ${GPU_ARCH_TYPE} in
         TARGET=final
         DOCKER_TAG=cpu-aarch64
         GPU_IMAGE=arm64v8/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11 --build-arg NINJA_VERSION=1.12.1"
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28_aarch64"
         ;;
     cpu-cxx11-abi)
@@ -87,18 +87,22 @@ case ${GPU_ARCH_TYPE} in
         MANY_LINUX_VERSION="aarch64"
         DOCKERFILE_SUFFIX="_cuda_aarch64"
         ;;
-    rocm|rocm-manylinux_2_28)
+    rocm)
         TARGET=rocm_final
         DOCKER_TAG=rocm${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
+        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 + ${BASH_REMATCH[3]:-0}))
+        else
+            echo "ERROR: rocm regex failed"
+            exit 1
         fi
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
-        DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
+        if [[ $ROCM_VERSION_INT -ge 60000 ]]; then
+            PYTORCH_ROCM_ARCH+=";gfx942"
+        fi
+        DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=9"
         ;;
     xpu)
         TARGET=xpu_final
@@ -121,8 +125,7 @@ fi
 (
     set -x
 
-    # Only activate this if in CI
-    if [ "$(uname -m)" != "s390x" ] && [ -v CI ]; then
+    if [ "$(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
@@ -140,7 +143,7 @@ fi
         "${TOPDIR}/.ci/docker/"
 )
 
-GITHUB_REF=${GITHUB_REF:-"dev")}
+GITHUB_REF=${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}

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

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

.ci/docker/requirements-ci.txt

@@ -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==1.14.0
+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
@@ -161,7 +155,7 @@ 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:
@@ -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:
@@ -307,32 +296,31 @@ 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:
@@ -342,7 +330,7 @@ onnx==1.17.0
 #Pinned versions:
 #test that import:
 
-onnxscript==0.2.2
+onnxscript==0.1.0.dev20240817
 #Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
@@ -365,17 +353,12 @@ pwlf==2.2.1 ; python_version >= "3.8"
 # 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 ; 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:

.ci/docker/requirements-docs.txt

@@ -14,8 +14,7 @@ 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
 

.ci/docker/triton_version.txt

@@ -1 +1 @@
-3.3.0
+3.1.0

.ci/docker/ubuntu-cuda/Dockerfile

@@ -30,8 +30,7 @@ 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
@@ -50,6 +49,13 @@ 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 ./
@@ -74,8 +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

.ci/docker/ubuntu-rocm/Dockerfile

@@ -14,20 +14,21 @@ 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
-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
@@ -38,11 +39,6 @@ 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
@@ -50,6 +46,13 @@ RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
 RUN rm install_protobuf.sh
 ENV INSTALLED_PROTOBUF ${PROTOBUF}
 
+# (optional) Install database packages like LMDB and LevelDB
+ARG DB
+COPY ./common/install_db.sh install_db.sh
+RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
+RUN rm install_db.sh
+ENV INSTALLED_DB ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -82,32 +85,6 @@ 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 "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
-RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
-
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
 COPY ./common/install_cmake.sh install_cmake.sh
@@ -130,17 +107,18 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${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

@@ -77,6 +77,13 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
 RUN rm install_triton.sh common_utils.sh triton-xpu.txt triton_version.txt
 
+# (optional) Install database packages like LMDB and LevelDB
+ARG DB
+COPY ./common/install_db.sh install_db.sh
+RUN if [ -n "${DB}" ]; then bash ./install_db.sh; fi
+RUN rm install_db.sh
+ENV INSTALLED_DB ${DB}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./

.ci/docker/ubuntu/Dockerfile

@@ -36,8 +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
@@ -74,6 +73,13 @@ 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 ./

.ci/magma/Makefile

@@ -12,13 +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="${CUDA_ARCH_LIST}" \
-	"pytorch/manylinux2_28-builder:cuda${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:
@@ -26,12 +26,6 @@ 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:
@@ -42,6 +36,11 @@ 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.sh

@@ -15,12 +15,9 @@ case "${GPU_ARCH_TYPE:-BLANK}" in
     rocm)
         bash "${SCRIPTPATH}/build_rocm.sh"
         ;;
-    cpu | cpu-cxx11-abi | cpu-s390x)
+    cpu | cpu-cxx11-abi | cpu-s390x | xpu)
         bash "${SCRIPTPATH}/build_cpu.sh"
         ;;
-    xpu)
-        bash "${SCRIPTPATH}/build_xpu.sh"
-        ;;
     *)
         echo "Un-recognized GPU_ARCH_TYPE '${GPU_ARCH_TYPE}', exiting..."
         exit 1

.ci/manywheel/build_common.sh

@@ -18,14 +18,12 @@ retry () {
     $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
 }
 
-PLATFORM="manylinux2014_x86_64"
 # TODO move this into the Docker images
 OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
 if [[ "$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
@@ -255,11 +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
 }
 
@@ -379,12 +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 $record_file ]]; then
@@ -424,20 +416,12 @@ for pkg in /$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) $pkg
     cd ..
     rm -rf tmp
 done
@@ -490,9 +474,9 @@ if [[ -z "$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_cpu.sh

@@ -2,6 +2,8 @@
 
 set -ex
 
+GPU_ARCH_TYPE=${GPU_ARCH_TYPE:-cpu}
+
 export TH_BINARY_BUILD=1
 export USE_CUDA=0
 
@@ -15,13 +17,22 @@ if [[ -z "$EXTRA_CAFFE2_CMAKE_FLAGS" ]]; then
     EXTRA_CAFFE2_CMAKE_FLAGS=()
 fi
 
-WHEELHOUSE_DIR="wheelhousecpu"
-LIBTORCH_HOUSE_DIR="libtorch_housecpu"
+DIR_SUFFIX=cpu
+if [[ "$GPU_ARCH_TYPE" == "xpu" ]]; then
+    DIR_SUFFIX=xpu
+    # Refer https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-5.html
+    source /opt/intel/oneapi/pytorch-gpu-dev-0.5/oneapi-vars.sh
+    source /opt/intel/oneapi/pti/latest/env/vars.sh
+    export USE_STATIC_MKL=1
+fi
+
+WHEELHOUSE_DIR="wheelhouse$DIR_SUFFIX"
+LIBTORCH_HOUSE_DIR="libtorch_house$DIR_SUFFIX"
 if [[ -z "$PYTORCH_FINAL_PACKAGE_DIR" ]]; then
     if [[ -z "$BUILD_PYTHONLESS" ]]; then
-        PYTORCH_FINAL_PACKAGE_DIR="/remote/wheelhousecpu"
+        PYTORCH_FINAL_PACKAGE_DIR="/remote/wheelhouse$DIR_SUFFIX"
     else
-        PYTORCH_FINAL_PACKAGE_DIR="/remote/libtorch_housecpu"
+        PYTORCH_FINAL_PACKAGE_DIR="/remote/libtorch_house$DIR_SUFFIX"
     fi
 fi
 mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
@@ -49,6 +60,34 @@ DEPS_SONAME=(
     "libgomp.so.1"
 )
 
+if [[ "$GPU_ARCH_TYPE" == "xpu" ]]; then
+    echo "Bundling with xpu support package libs."
+    DEPS_LIST+=(
+        "/opt/intel/oneapi/compiler/latest/lib/libsycl-preview.so.7"
+        "/opt/intel/oneapi/compiler/latest/lib/libOpenCL.so.1"
+        "/opt/intel/oneapi/compiler/latest/lib/libxptifw.so"
+        "/opt/intel/oneapi/compiler/latest/lib/libsvml.so"
+        "/opt/intel/oneapi/compiler/latest/lib/libirng.so"
+        "/opt/intel/oneapi/compiler/latest/lib/libimf.so"
+        "/opt/intel/oneapi/compiler/latest/lib/libintlc.so.5"
+        "/opt/intel/oneapi/compiler/latest/lib/libpi_level_zero.so"
+        "/opt/intel/oneapi/pti/latest/lib/libpti_view.so.0.9"
+        "/opt/intel/oneapi/pti/latest/lib/libpti.so.0.9"
+    )
+    DEPS_SONAME+=(
+        "libsycl-preview.so.7"
+        "libOpenCL.so.1"
+        "libxptifw.so"
+        "libsvml.so"
+        "libirng.so"
+        "libimf.so"
+        "libintlc.so.5"
+        "libpi_level_zero.so"
+        "libpti_view.so.0.9"
+        "libpti.so.0.9"
+    )
+fi
+
 rm -rf /usr/local/cuda*
 
 SOURCE_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"

.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 "$CMAKE_ARGS" ]]; then
@@ -44,6 +43,13 @@ if [[ -n "$DESIRED_CUDA" ]]; then
         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 $CUDA_VERSION Detected"
@@ -53,15 +59,15 @@ cuda_version_nodot=$(echo $CUDA_VERSION | tr -d '.')
 
 TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;7.5;8.0;8.6"
 case ${CUDA_VERSION} in
-    12.8)
-        TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;12.0+PTX" #removing sm_50-sm_70 as these architectures are deprecated in CUDA 12.8 and will be removed in future releases
+    12.4 | 12.6)
+        if [[ "$GPU_ARCH_TYPE" = "cuda-aarch64" ]]; then
+            TORCH_CUDA_ARCH_LIST="9.0"
+        else
+            TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0+PTX"
+        fi
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
-    12.6)
-        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
-        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
-        ;;
-    12.4)
+    12.1)
         TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
@@ -69,6 +75,10 @@ case ${CUDA_VERSION} in
         TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};3.7;9.0"
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
+    11.[67])
+        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};3.7"
+        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
+        ;;
     *)
         echo "unknown cuda version $CUDA_VERSION"
         exit 1
@@ -119,16 +129,7 @@ if [[ $USE_CUSPARSELT == "1" && $CUDA_VERSION == "11.8" ]]; then
         )
 fi
 
-
-# Turn USE_CUFILE off for CUDA 11.8, 12.4 since nvidia-cufile-cu11 and 1.9.0.20 are
-# not available in PYPI
-if [[ $CUDA_VERSION == "11.8" || $CUDA_VERSION == "12.4" ]]; then
-    export USE_CUFILE=0
-fi
-
-
-# CUDA_VERSION 12.4, 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"
@@ -169,16 +170,6 @@ if [[ $CUDA_VERSION == 12* ]]; then
             "libnvrtc.so.12"
             "libnvrtc-builtins.so"
         )
-        if [[ $USE_CUFILE == 1 ]]; then
-            DEPS_LIST+=(
-                "/usr/local/cuda/lib64/libcufile.so.0"
-                "/usr/local/cuda/lib64/libcufile_rdma.so.1"
-            )
-            DEPS_SONAME+=(
-                "libcufile.so.0"
-                "libcufile_rdma.so.1"
-            )
-        fi
     else
         echo "Using nvidia libs from pypi."
         CUDA_RPATHS=(
@@ -195,11 +186,6 @@ if [[ $CUDA_VERSION == 12* ]]; then
             '$ORIGIN/../../nvidia/nccl/lib'
             '$ORIGIN/../../nvidia/nvtx/lib'
         )
-        if [[ $USE_CUFILE == 1 ]]; then
-            CUDA_RPATHS+=(
-                '$ORIGIN/../../nvidia/cufile/lib'
-            )
-        fi
         CUDA_RPATHS=$(IFS=: ; echo "${CUDA_RPATHS[*]}")
         export C_SO_RPATH=$CUDA_RPATHS':$ORIGIN:$ORIGIN/lib'
         export LIB_SO_RPATH=$CUDA_RPATHS':$ORIGIN'
@@ -285,7 +271,7 @@ 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

@@ -225,11 +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

@@ -1,108 +0,0 @@
-#!/usr/bin/env bash
-
-set -ex
-
-export TH_BINARY_BUILD=1
-export USE_CUDA=0
-
-# Keep an array of cmake variables to add to
-if [[ -z "$CMAKE_ARGS" ]]; then
-    # These are passed to tools/build_pytorch_libs.sh::build()
-    CMAKE_ARGS=()
-fi
-if [[ -z "$EXTRA_CAFFE2_CMAKE_FLAGS" ]]; then
-    # These are passed to tools/build_pytorch_libs.sh::build_caffe2()
-    EXTRA_CAFFE2_CMAKE_FLAGS=()
-fi
-
-
-# Refer https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html
-source /opt/intel/oneapi/compiler/latest/env/vars.sh
-source /opt/intel/oneapi/pti/latest/env/vars.sh
-source /opt/intel/oneapi/umf/latest/env/vars.sh
-export USE_STATIC_MKL=1
-
-WHEELHOUSE_DIR="wheelhousexpu"
-LIBTORCH_HOUSE_DIR="libtorch_housexpu"
-if [[ -z "$PYTORCH_FINAL_PACKAGE_DIR" ]]; then
-    if [[ -z "$BUILD_PYTHONLESS" ]]; then
-        PYTORCH_FINAL_PACKAGE_DIR="/remote/wheelhousexpu"
-    else
-        PYTORCH_FINAL_PACKAGE_DIR="/remote/libtorch_housexpu"
-    fi
-fi
-mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
-
-OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
-if [[ "$OS_NAME" == *"CentOS Linux"* ]]; 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" == *"AlmaLinux"* ]]; then
-    LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
-elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
-    if [[ "$(uname -m)" == "s390x" ]]; then
-        LIBGOMP_PATH="/usr/lib/s390x-linux-gnu/libgomp.so.1"
-    else
-        LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
-    fi
-fi
-
-DEPS_LIST=(
-    "$LIBGOMP_PATH"
-    "/opt/intel/oneapi/compiler/latest/lib/libOpenCL.so.1"
-)
-
-DEPS_SONAME=(
-    "libgomp.so.1"
-    "libOpenCL.so.1"
-)
-
-if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
-    echo "Bundling with xpu support package libs."
-    DEPS_LIST+=(
-        "/opt/intel/oneapi/compiler/latest/lib/libsycl.so.8"
-        "/opt/intel/oneapi/compiler/latest/lib/libur_loader.so.0"
-        "/opt/intel/oneapi/compiler/latest/lib/libur_adapter_level_zero.so.0"
-        "/opt/intel/oneapi/compiler/latest/lib/libur_adapter_opencl.so.0"
-        "/opt/intel/oneapi/compiler/latest/lib/libsvml.so"
-        "/opt/intel/oneapi/compiler/latest/lib/libirng.so"
-        "/opt/intel/oneapi/compiler/latest/lib/libimf.so"
-        "/opt/intel/oneapi/compiler/latest/lib/libintlc.so.5"
-        "/opt/intel/oneapi/pti/latest/lib/libpti_view.so.0.10"
-        "/opt/intel/oneapi/umf/latest/lib/libumf.so.0"
-        "/opt/intel/oneapi/tcm/latest/lib/libhwloc.so.15"
-    )
-    DEPS_SONAME+=(
-        "libsycl.so.8"
-        "libur_loader.so.0"
-        "libur_adapter_level_zero.so.0"
-        "libur_adapter_opencl.so.0"
-        "libsvml.so"
-        "libirng.so"
-        "libimf.so"
-        "libintlc.so.5"
-        "libpti_view.so.0.10"
-        "libumf.so.0"
-        "libhwloc.so.15"
-    )
-else
-    echo "Using xpu runtime libs from pypi."
-    XPU_RPATHS=(
-        '$ORIGIN/../../../..'
-    )
-    XPU_RPATHS=$(IFS=: ; echo "${XPU_RPATHS[*]}")
-    export C_SO_RPATH=$XPU_RPATHS':$ORIGIN:$ORIGIN/lib'
-    export LIB_SO_RPATH=$XPU_RPATHS':$ORIGIN'
-    export FORCE_RPATH="--force-rpath"
-fi
-
-rm -rf /usr/local/cuda*
-
-SOURCE_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"
-if [[ -z "$BUILD_PYTHONLESS" ]]; then
-    BUILD_SCRIPT=build_common.sh
-else
-    BUILD_SCRIPT=build_libtorch.sh
-fi
-source ${SOURCE_DIR}/${BUILD_SCRIPT}

.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
@@ -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_$ANACONDA_PYTHON_VERSION/include/"
   fi
@@ -173,7 +173,6 @@ if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   source /opt/intel/oneapi/compiler/latest/env/vars.sh
   # XPU kineto feature dependencies are not fully ready, disable kineto build as temp WA
   export USE_KINETO=0
-  export TORCH_XPU_ARCH_LIST=pvc
 fi
 
 # sccache will fail for CUDA builds if all cores are used for compiling
@@ -192,7 +191,7 @@ fi
 
 # We only build FlashAttention files for CUDA 8.0+, and they require large amounts of
 # memory to build and will OOM
-if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ 1 -eq $(echo "${TORCH_CUDA_ARCH_LIST} >= 8.0" | bc) ]] && [ -z "$MAX_JOBS_OVERRIDE" ]; then
+if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ "$TORCH_CUDA_ARCH_LIST" == *"8.6"* || "$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="$(( $(nproc --ignore=2) / 3 ))"
@@ -229,9 +228,9 @@ if [[ "$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=$(stat -c '%u' "/var/lib/jenkins/workspace")
   cleanup_workspace() {
@@ -248,9 +247,10 @@ if [[ "$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
@@ -279,13 +279,14 @@ else
           "$BUILD_ENVIRONMENT" != *xla* ]]; then
       if [[ "$BUILD_ENVIRONMENT" != *py3.8* ]]; then
         # Install numpy-2.0.2 for builds which are backward compatible with 1.X
-        python -mpip install numpy==2.0.2
+        python -mpip install --pre numpy==2.0.2
       fi
 
       WERROR=1 python setup.py clean
 
       if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
-        python3 tools/packaging/split_wheel.py bdist_wheel
+        BUILD_LIBTORCH_WHL=1 BUILD_PYTHON_ONLY=0 python setup.py bdist_wheel
+        BUILD_LIBTORCH_WHL=0 BUILD_PYTHON_ONLY=1 python setup.py bdist_wheel --cmake
       else
         WERROR=1 python setup.py bdist_wheel
       fi
@@ -378,10 +379,8 @@ else
     # This is an attempt to mitigate flaky libtorch build OOM error. By default, the build parallelization
     # is set to be the number of CPU minus 2. So, let's try a more conservative value here. A 4xlarge has
     # 16 CPUs
-    if [ -z "$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.
@@ -398,7 +397,7 @@ 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

@@ -1,382 +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
-
-###############################################################################
-# Setup XPU ENV
-###############################################################################
-if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
-  set +u
-  # Refer https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html
-  source /opt/intel/oneapi/compiler/latest/env/vars.sh
-  source /opt/intel/oneapi/pti/latest/env/vars.sh
-fi
-
-###############################################################################
-# Check GCC ABI
-###############################################################################
-
-# NOTE: As of https://github.com/pytorch/pytorch/issues/126551 we only produce
-#       wheels with cxx11-abi
-
-echo "Checking that the gcc ABI is what we expect"
-if [[ "$(uname)" != 'Darwin' ]]; then
-  function is_expected() {
-    if [[ "$1" -gt 0 || "$1" == "ON " ]]; then
-      echo 1
-    fi
-  }
-
-  # First we check that the env var in TorchConfig.cmake is correct
-
-  # We search for D_GLIBCXX_USE_CXX11_ABI=1 in torch/TorchConfig.cmake
-  torch_config="${install_root}/share/cmake/Torch/TorchConfig.cmake"
-  if [[ ! -f "$torch_config" ]]; then
-    echo "No TorchConfig.cmake found!"
-    ls -lah "$install_root/share/cmake/Torch"
-    exit 1
-  fi
-  echo "Checking the TorchConfig.cmake"
-  cat "$torch_config"
-
-  # The sed call below is
-  #   don't print lines by default (only print the line we want)
-  # -n
-  #   execute the following expression
-  # e
-  #   replace lines that match with the first capture group and print
-  # s/.*D_GLIBCXX_USE_CXX11_ABI=\(.\)".*/\1/p
-  #   any characters, D_GLIBCXX_USE_CXX11_ABI=, exactly one any character, a
-  #   quote, any characters
-  #   Note the exactly one single character after the '='. In the case that the
-  #     variable is not set the '=' will be followed by a '"' immediately and the
-  #     line will fail the match and nothing will be printed; this is what we
-  #     want.  Otherwise it will capture the 0 or 1 after the '='.
-  # /.*D_GLIBCXX_USE_CXX11_ABI=\(.\)".*/
-  #   replace the matched line with the capture group and print
-  # /\1/p
-  actual_gcc_abi="$(sed -ne 's/.*D_GLIBCXX_USE_CXX11_ABI=\(.\)".*/\1/p' < "$torch_config")"
-  if [[ "$(is_expected "$actual_gcc_abi")" != 1 ]]; then
-    echo "gcc ABI $actual_gcc_abi not as expected."
-    exit 1
-  fi
-
-  # We also check that there are [not] cxx11 symbols in libtorch
-  #
-  echo "Checking that symbols in libtorch.so have the right gcc abi"
-  python3 "$(dirname ${BASH_SOURCE[0]})/smoke_test/check_binary_symbols.py"
-
-  echo "cxx11 symbols seem to be in order"
-fi # if on Darwin
-
-###############################################################################
-# Check for no OpenBLAS
-# TODO Check for no Protobuf symbols (not finished)
-# Print *all* runtime dependencies
-###############################################################################
-# We have to loop through all shared libraries for this
-if [[ "$(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 ${BASH_SOURCE[0]}))/test_example_code"
-build_and_run_example_cpp () {
-  if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
-    GLIBCXX_USE_CXX11_ABI=1
-  else
-    GLIBCXX_USE_CXX11_ABI=0
-  fi
-  setup_link_flags
-  g++ ${TEST_CODE_DIR}/$1.cpp -I${install_root}/include -I${install_root}/include/torch/csrc/api/include -D_GLIBCXX_USE_CXX11_ABI=$GLIBCXX_USE_CXX11_ABI -std=gnu++17 -L${install_root}/lib ${REF_LIB} ${ADDITIONAL_LINKER_FLAGS} -ltorch $TORCH_CPU_LINK_FLAGS $TORCH_CUDA_LINK_FLAGS $C10_LINK_FLAGS -o $1
-  ./$1
-}
-
-build_example_cpp_with_incorrect_abi () {
-  if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
-    GLIBCXX_USE_CXX11_ABI=0
-  else
-    GLIBCXX_USE_CXX11_ABI=1
-  fi
-  set +e
-  setup_link_flags
-  g++ ${TEST_CODE_DIR}/$1.cpp -I${install_root}/include -I${install_root}/include/torch/csrc/api/include -D_GLIBCXX_USE_CXX11_ABI=$GLIBCXX_USE_CXX11_ABI -std=gnu++17 -L${install_root}/lib ${REF_LIB} ${ADDITIONAL_LINKER_FLAGS} -ltorch $TORCH_CPU_LINK_FLAGS $TORCH_CUDA_LINK_FLAGS $C10_LINK_FLAGS -o $1
-  ERRCODE=$?
-  set -e
-  if [ "$ERRCODE" -eq "0" ]; then
-    echo "Building example with incorrect ABI didn't throw error. Aborting."
-    exit 1
-  else
-    echo "Building example with incorrect ABI throws expected error. Proceeding."
-  fi
-}
-
-###############################################################################
-# Check simple Python/C++ calls
-###############################################################################
-if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
-  # NS: Set LD_LIBRARY_PATH for CUDA builds, but perhaps it should be removed
-  if [[ "$DESIRED_CUDA" == "cu"* ]]; then
-    export LD_LIBRARY_PATH=/usr/local/cuda/lib64
-  fi
-  build_and_run_example_cpp simple-torch-test
-  # `_GLIBCXX_USE_CXX11_ABI` is always ignored by gcc in devtoolset7, so we test
-  # the expected failure case for Ubuntu 16.04 + gcc 5.4 only.
-  if [[ "$DESIRED_DEVTOOLSET" == *"cxx11-abi"* ]]; then
-    build_example_cpp_with_incorrect_abi simple-torch-test
-  fi
-else
-  pushd /tmp
-  python -c 'import torch'
-  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 ]] && [[ "$(uname -m)" != "s390x"  ]]; then
-    echo "Checking that XNNPACK is available"
-    pushd /tmp
-    python -c 'import torch.backends.xnnpack; exit(0 if torch.backends.xnnpack.enabled else 1)'
-    popd
-  fi
-fi
-
-###############################################################################
-# Check CUDA configured correctly
-###############################################################################
-# Skip these for Windows machines without GPUs
-if [[ "$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" =~ "$GLOO_TRANSPORT_IS_NOT_SUPPORTED" ]]; then
-    echo "PyTorch doesn't support TLS_TCP transport, please build with USE_GLOO_WITH_OPENSSL=1"
-    exit 1
-  fi
-fi
-
-###############################################################################
-# Check for C++ ABI compatibility between gcc7 and gcc9 compiled binaries
-###############################################################################
-if [[ "$(uname)" == 'Linux' &&  "$PACKAGE_TYPE" == 'manywheel' ]]; then
-  pushd /tmp
-  python -c "import torch; exit(0 if torch.compiled_with_cxx11_abi() else (0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi1011' else 1))"
-  popd
-fi

.ci/pytorch/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)

.ci/pytorch/common_utils.sh

@@ -105,12 +105,32 @@ function get_bazel() {
   # version of Bazelisk to fetch the platform specific version of
   # Bazel to use from .bazelversion.
   retry curl --location --output tools/bazel \
-    https://raw.githubusercontent.com/bazelbuild/bazelisk/v1.23.0/bazelisk.py
+    https://raw.githubusercontent.com/bazelbuild/bazelisk/v1.16.0/bazelisk.py
   shasum --algorithm=1 --check \
-    <(echo '01df9cf7f08dd80d83979ed0d0666a99349ae93c  tools/bazel')
+    <(echo 'd4369c3d293814d3188019c9f7527a948972d9f8  tools/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
 }
 
@@ -226,22 +236,11 @@ 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
 }
 
-function install_torchao() {
-  local commit
-  commit=$(get_pinned_commit torchao)
-  pip_install --no-use-pep517 --user "git+https://github.com/pytorch/ao.git@${commit}"
-}
-
 function print_sccache_stats() {
   echo 'PyTorch Build Statistics'
   sccache --show-stats

.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

@@ -6,7 +6,7 @@
 # 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"

.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
@@ -193,19 +190,11 @@ test_torchbench_perf() {
   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"
 }
@@ -220,27 +209,26 @@ test_torchbench_smoketest() {
 
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
-
-  local backend=eager
-  local dtype=notset
-  local device=mps
-
-  touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
-  touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
+  touch "$TEST_REPORTS_DIR"/torchbench_training.csv
+  touch "$TEST_REPORTS_DIR"/torchbench_inference.csv
 
   echo "Setup complete, launching torchbench training performance run"
-  for model in hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152; do
-    PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-      --performance --only "$model" --backend "$backend" --training --devices "$device" \
-      --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
-  done
+  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"
 
   echo "Launching torchbench inference performance run"
-  for model in hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152; do
-    PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-      --performance --only "$model" --backend "$backend" --inference --devices "$device" \
-      --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
-  done
+  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"
 }
@@ -279,6 +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
@@ -291,19 +298,4 @@ elif [[ $TEST_CONFIG == *"perf_timm"* ]]; then
   test_timm_perf
 elif [[ $TEST_CONFIG == *"perf_smoketest"* ]]; then
   test_torchbench_smoketest
-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/python_doc_push_script.sh

@@ -7,7 +7,7 @@ source "$pt_checkout/.ci/pytorch/common_utils.sh"
 
 echo "python_doc_push_script.sh: Invoked with $*"
 
-set -ex -o pipefail
+set -ex
 
 # for statements like ${1:-${DOCS_INSTALL_PATH:-docs/}}
 # the order of operations goes:
@@ -63,7 +63,7 @@ build_docs () {
     echo "(tried to echo the WARNINGS above the ==== line)"
     echo =========================
   fi
-  set -ex -o pipefail
+  set -ex
   return $code
 }
 

.ci/pytorch/run_tests.sh

@@ -1,436 +0,0 @@
-#!/bin/bash
-# shellcheck disable=SC2086,SC2048,SC2068,SC2145,SC2034,SC2207,SC2143
-# TODO: Re-enable shellchecks above
-
-set -eux -o pipefail
-
-# Essentially runs pytorch/test/run_test.py, but keeps track of which tests to
-# skip in a centralized place.
-#
-# TODO Except for a few tests, this entire file is a giant TODO. Why are these
-# tests # failing?
-# TODO deal with Windows
-
-# This script expects to be in the pytorch root folder
-if [[ ! -d 'test' || ! -f 'test/run_test.py' ]]; then
-    echo "run_tests.sh expects to be run from the Pytorch root directory " \
-         "but I'm actually in $(pwd)"
-    exit 2
-fi
-
-# Allow master skip of all tests
-if [[ -n "${SKIP_ALL_TESTS:-}" ]]; then
-    exit 0
-fi
-
-# If given specific test params then just run those
-if [[ -n "${RUN_TEST_PARAMS:-}" ]]; then
-    echo "$(date) :: Calling user-command $(pwd)/test/run_test.py ${RUN_TEST_PARAMS[@]}"
-    python test/run_test.py ${RUN_TEST_PARAMS[@]}
-    exit 0
-fi
-
-# Function to retry functions that sometimes timeout or have flaky failures
-retry () {
-    $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
-}
-
-# Parameters
-##############################################################################
-if [[ "$#" != 3 ]]; then
-  if [[ -z "${DESIRED_PYTHON:-}" || -z "${DESIRED_CUDA:-}" || -z "${PACKAGE_TYPE:-}" ]]; then
-    echo "USAGE: run_tests.sh  PACKAGE_TYPE  DESIRED_PYTHON  DESIRED_CUDA"
-    echo "The env variable PACKAGE_TYPE must be set to 'manywheel' or 'libtorch'"
-    echo "The env variable DESIRED_PYTHON must be set like '2.7mu' or '3.6m' etc"
-    echo "The env variable DESIRED_CUDA must be set like 'cpu' or 'cu80' etc"
-    exit 1
-  fi
-  package_type="$PACKAGE_TYPE"
-  py_ver="$DESIRED_PYTHON"
-  cuda_ver="$DESIRED_CUDA"
-else
-  package_type="$1"
-  py_ver="$2"
-  cuda_ver="$3"
-fi
-
-if [[ "$cuda_ver" == 'cpu-cxx11-abi' ]]; then
-    cuda_ver="cpu"
-fi
-
-# cu80, cu90, cu100, cpu
-if [[ ${#cuda_ver} -eq 4 ]]; then
-    cuda_ver_majmin="${cuda_ver:2:1}.${cuda_ver:3:1}"
-elif [[ ${#cuda_ver} -eq 5 ]]; then
-    cuda_ver_majmin="${cuda_ver:2:2}.${cuda_ver:4:1}"
-fi
-
-NUMPY_PACKAGE=""
-if [[ ${py_ver} == "3.10" ]]; then
-    PROTOBUF_PACKAGE="protobuf>=3.17.2"
-    NUMPY_PACKAGE="numpy>=1.21.2"
-else
-    PROTOBUF_PACKAGE="protobuf=3.14.0"
-fi
-
-# Environment initialization
-if [[ "$(uname)" == Darwin ]]; then
-    # Install the testing dependencies
-    retry conda install -yq future hypothesis ${NUMPY_PACKAGE} ${PROTOBUF_PACKAGE} pytest setuptools six typing_extensions pyyaml
-else
-    retry pip install -qr requirements.txt || true
-    retry pip install -q hypothesis protobuf pytest setuptools || true
-    numpy_ver=1.15
-    case "$(python --version 2>&1)" in
-      *2* | *3.5* | *3.6*)
-        numpy_ver=1.11
-        ;;
-    esac
-    retry pip install -q "numpy==${numpy_ver}" || true
-fi
-
-echo "Testing with:"
-pip freeze
-conda list || true
-
-##############################################################################
-# Smoke tests
-##############################################################################
-# TODO use check_binary.sh, which requires making sure it runs on Windows
-pushd /
-echo "Smoke testing imports"
-python -c 'import torch'
-
-# Test that MKL is there
-if [[ "$(uname)" == 'Darwin' && "$package_type" == *wheel ]]; then
-    echo 'Not checking for MKL on Darwin wheel packages'
-else
-    echo "Checking that MKL is available"
-    python -c 'import torch; exit(0 if torch.backends.mkl.is_available() else 1)'
-fi
-
-if [[ "$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 the version number is consistent during building and testing
-if [[ "$PYTORCH_BUILD_NUMBER" -gt 1 ]]; then
-    expected_version="${PYTORCH_BUILD_VERSION}.post${PYTORCH_BUILD_NUMBER}"
-else
-    expected_version="${PYTORCH_BUILD_VERSION}"
-fi
-echo "Checking that we are testing the package that is just built"
-python -c "import torch; exit(0 if torch.__version__ == '$expected_version' else 1)"
-
-# Test that CUDA builds are setup correctly
-if [[ "$cuda_ver" != 'cpu' ]]; then
-    cuda_installed=1
-    nvidia-smi || cuda_installed=0
-    if [[ "$cuda_installed" == 0 ]]; then
-      echo "Skip CUDA tests for machines without a Nvidia GPU card"
-    else
-      # Test CUDA archs
-      echo "Checking that CUDA archs are setup correctly"
-      timeout 20 python -c 'import torch; torch.randn([3,5]).cuda()'
-
-      # These have to run after CUDA is initialized
-      echo "Checking that magma is available"
-      python -c 'import torch; torch.rand(1).cuda(); exit(0 if torch.cuda.has_magma else 1)'
-      echo "Checking that CuDNN is available"
-      python -c 'import torch; exit(0 if torch.backends.cudnn.is_available() else 1)'
-    fi
-fi
-
-# Check that OpenBlas is not linked to on MacOS
-if [[ "$(uname)" == 'Darwin' ]]; then
-    echo "Checking the OpenBLAS is not linked to"
-    all_dylibs=($(find "$(python -c "import site; print(site.getsitepackages()[0])")"/torch -name '*.dylib'))
-    for dylib in "${all_dylibs[@]}"; do
-        if [[ -n "$(otool -L $dylib | grep -i openblas)" ]]; then
-            echo "Found openblas as a dependency of $dylib"
-            echo "Full dependencies is: $(otool -L $dylib)"
-            exit 1
-        fi
-    done
-
-    echo "Checking that OpenMP is available"
-    python -c "import torch; exit(0 if torch.backends.openmp.is_available() else 1)"
-fi
-
-popd
-
-# TODO re-enable the other tests after the nightlies are moved to CI. This is
-# because the binaries keep breaking, often from additional tests, that aren't
-# real problems. Once these are on circleci and a smoke-binary-build is added
-# to PRs then this should stop happening and these can be re-enabled.
-echo "Not running unit tests. Hopefully these problems are caught by CI"
-exit 0
-
-
-##############################################################################
-# Running unit tests (except not right now)
-##############################################################################
-echo "$(date) :: Starting tests for $package_type package for python$py_ver and $cuda_ver"
-
-# We keep track of exact tests to skip, as otherwise we would be hardly running
-# any tests. But b/c of issues working with pytest/normal-python-test/ and b/c
-# of special snowflake tests in test/run_test.py we also take special care of
-# those
-tests_to_skip=()
-
-#
-# Entire file exclusions
-##############################################################################
-entire_file_exclusions=("-x")
-
-# cpp_extensions doesn't work with pytest, so we exclude it from the pytest run
-# here and then manually run it later. Note that this is only because this
-# entire_fil_exclusions flag is only passed to the pytest run
-entire_file_exclusions+=("cpp_extensions")
-
-# TODO temporary line to fix next days nightlies, but should be removed when
-# issue is fixed
-entire_file_exclusions+=('type_info')
-
-if [[ "$cuda_ver" == 'cpu' ]]; then
-    # test/test_cuda.py exits early if the installed torch is not built with
-    # CUDA, but the exit doesn't work when running with pytest, so pytest will
-    # still try to run all the CUDA tests and then fail
-    entire_file_exclusions+=("cuda")
-    entire_file_exclusions+=("nccl")
-fi
-
-if [[ "$(uname)" == 'Darwin' || "$OSTYPE" == "msys" ]]; then
-    # pytest on Mac doesn't like the exits in these files
-    entire_file_exclusions+=('c10d')
-    entire_file_exclusions+=('distributed')
-
-    # pytest doesn't mind the exit but fails the tests. On Mac we run this
-    # later without pytest
-    entire_file_exclusions+=('thd_distributed')
-fi
-
-
-#
-# Universal flaky tests
-##############################################################################
-
-# RendezvousEnvTest sometimes hangs forever
-# Otherwise it will fail on CUDA with
-#   Traceback (most recent call last):
-#     File "test_c10d.py", line 179, in test_common_errors
-#       next(gen)
-#   AssertionError: ValueError not raised
-tests_to_skip+=('RendezvousEnvTest and test_common_errors')
-
-# This hung forever once on conda_3.5_cu92
-tests_to_skip+=('TestTorch and test_sum_dim')
-
-# test_trace_warn isn't actually flaky, but it doesn't work with pytest so we
-# just skip it
-tests_to_skip+=('TestJit and test_trace_warn')
-#
-# Python specific flaky tests
-##############################################################################
-
-# test_dataloader.py:721: AssertionError
-# looks like a timeout, but interestingly only appears on python 3
-if [[ "$py_ver" == 3* ]]; then
-    tests_to_skip+=('TestDataLoader and test_proper_exit')
-fi
-
-#
-# CUDA flaky tests, all package types
-##############################################################################
-if [[ "$cuda_ver" != 'cpu' ]]; then
-
-    #
-    # DistributedDataParallelTest
-    # All of these seem to fail
-    tests_to_skip+=('DistributedDataParallelTest')
-
-    #
-    # RendezvousEnvTest
-    # Traceback (most recent call last):
-    #   File "test_c10d.py", line 201, in test_nominal
-    #     store0, rank0, size0 = next(gen0)
-    #   File "/opt/python/cp36-cp36m/lib/python3.6/site-packages/torch/distributed/rendezvous.py", line 131, in _env_rendezvous_handler
-    #     store = TCPStore(master_addr, master_port, start_daemon)
-    # RuntimeError: Address already in use
-    tests_to_skip+=('RendezvousEnvTest and test_nominal')
-
-    #
-    # TestCppExtension
-    #
-    # Traceback (most recent call last):
-    #   File "test_cpp_extensions.py", line 134, in test_jit_cudnn_extension
-    #     with_cuda=True)
-    #   File "/opt/python/cp35-cp35m/lib/python3.5/site-packages/torch/utils/cpp_extension.py", line 552, in load
-    #     with_cuda)
-    #   File "/opt/python/cp35-cp35m/lib/python3.5/site-packages/torch/utils/cpp_extension.py", line 729, in _jit_compile
-    #     return _import_module_from_library(name, build_directory)
-    #   File "/opt/python/cp35-cp35m/lib/python3.5/site-packages/torch/utils/cpp_extension.py", line 867, in _import_module_from_library
-    #     return imp.load_module(module_name, file, path, description)
-    #   File "/opt/python/cp35-cp35m/lib/python3.5/imp.py", line 243, in load_module
-    #     return load_dynamic(name, filename, file)
-    #   File "/opt/python/cp35-cp35m/lib/python3.5/imp.py", line 343, in load_dynamic
-    #     return _load(spec)
-    #   File "<frozen importlib._bootstrap>", line 693, in _load
-    #   File "<frozen importlib._bootstrap>", line 666, in _load_unlocked
-    #   File "<frozen importlib._bootstrap>", line 577, in module_from_spec
-    #   File "<frozen importlib._bootstrap_external>", line 938, in create_module
-    #   File "<frozen importlib._bootstrap>", line 222, in _call_with_frames_removed
-    # ImportError: libcudnn.so.7: cannot open shared object file: No such file or directory
-    tests_to_skip+=('TestCppExtension and test_jit_cudnn_extension')
-
-    #
-    # TestCuda
-    #
-
-    # 3.7_cu80
-    #  RuntimeError: CUDA error: out of memory
-    tests_to_skip+=('TestCuda and test_arithmetic_large_tensor')
-
-    # 3.7_cu80
-    # RuntimeError: cuda runtime error (2) : out of memory at /opt/conda/conda-bld/pytorch-nightly_1538097262541/work/aten/src/THC/THCTensorCopy.cu:205
-    tests_to_skip+=('TestCuda and test_autogpu')
-
-    #
-    # TestDistBackend
-    #
-
-    # Traceback (most recent call last):
-    #   File "test_thd_distributed.py", line 1046, in wrapper
-    #     self._join_and_reduce(fn)
-    #   File "test_thd_distributed.py", line 1108, in _join_and_reduce
-    #     self.assertEqual(p.exitcode, first_process.exitcode)
-    #   File "/pytorch/test/common.py", line 399, in assertEqual
-    #     super(TestCase, self).assertEqual(x, y, message)
-    # AssertionError: None != 77 :
-    tests_to_skip+=('TestDistBackend and test_all_gather_group')
-    tests_to_skip+=('TestDistBackend and test_all_reduce_group_max')
-    tests_to_skip+=('TestDistBackend and test_all_reduce_group_min')
-    tests_to_skip+=('TestDistBackend and test_all_reduce_group_sum')
-    tests_to_skip+=('TestDistBackend and test_all_reduce_group_product')
-    tests_to_skip+=('TestDistBackend and test_barrier_group')
-    tests_to_skip+=('TestDistBackend and test_broadcast_group')
-
-    # Traceback (most recent call last):
-    #   File "test_thd_distributed.py", line 1046, in wrapper
-    #     self._join_and_reduce(fn)
-    #   File "test_thd_distributed.py", line 1108, in _join_and_reduce
-    #     self.assertEqual(p.exitcode, first_process.exitcode)
-    #   File "/pytorch/test/common.py", line 397, in assertEqual
-    #     super(TestCase, self).assertLessEqual(abs(x - y), prec, message)
-    # AssertionError: 12 not less than or equal to 1e-05
-    tests_to_skip+=('TestDistBackend and test_barrier')
-
-    # Traceback (most recent call last):
-    #   File "test_distributed.py", line 1267, in wrapper
-    #     self._join_and_reduce(fn)
-    #   File "test_distributed.py", line 1350, in _join_and_reduce
-    #     self.assertEqual(p.exitcode, first_process.exitcode)
-    #   File "/pytorch/test/common.py", line 399, in assertEqual
-    #     super(TestCase, self).assertEqual(x, y, message)
-    # AssertionError: None != 1
-    tests_to_skip+=('TestDistBackend and test_broadcast')
-
-    # Memory leak very similar to all the conda ones below, but appears on manywheel
-    # 3.6m_cu80
-    # AssertionError: 1605632 not less than or equal to 1e-05 : __main__.TestEndToEndHybridFrontendModels.test_vae_cuda leaked 1605632 bytes CUDA memory on device 0
-    tests_to_skip+=('TestEndToEndHybridFrontendModels and test_vae_cuda')
-
-    # ________________________ TestNN.test_embedding_bag_cuda ________________________
-    #
-    # self = <test_nn.TestNN testMethod=test_embedding_bag_cuda>
-    # dtype = torch.float32
-    #
-    #     @unittest.skipIf(not TEST_CUDA, "CUDA unavailable")
-    #     @repeat_test_for_types(ALL_TENSORTYPES)
-    #     @skipIfRocm
-    #     def test_embedding_bag_cuda(self, dtype=torch.float):
-    #         self._test_EmbeddingBag(True, 'sum', False, dtype)
-    #         self._test_EmbeddingBag(True, 'mean', False, dtype)
-    #         self._test_EmbeddingBag(True, 'max', False, dtype)
-    #         if dtype != torch.half:
-    #             # torch.cuda.sparse.HalfTensor is not enabled.
-    #             self._test_EmbeddingBag(True, 'sum', True, dtype)
-    # >           self._test_EmbeddingBag(True, 'mean', True, dtype)
-    #
-    # test_nn.py:2144:
-    # _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
-    # test_nn.py:2062: in _test_EmbeddingBag
-    #     _test_vs_Embedding(N, D, B, L)
-    # test_nn.py:2059: in _test_vs_Embedding
-    #     self.assertEqual(es_weight_grad, e.weight.grad, needed_prec)
-    # common.py:373: in assertEqual
-    #     assertTensorsEqual(x, y)
-    # common.py:365: in assertTensorsEqual
-    #     self.assertLessEqual(max_err, prec, message)
-    # E   AssertionError: tensor(0.0000, device='cuda:0', dtype=torch.float32) not less than or equal to 2e-05 :
-    #  1 failed, 1202 passed, 19 skipped, 2 xfailed, 796 warnings in 1166.73 seconds =
-    # Traceback (most recent call last):
-    #   File "test/run_test.py", line 391, in <module>
-    #     main()
-    #   File "test/run_test.py", line 383, in main
-    #     raise RuntimeError(message)
-    tests_to_skip+=('TestNN and test_embedding_bag_cuda')
-fi
-
-##############################################################################
-# MacOS specific flaky tests
-##############################################################################
-
-if [[ "$(uname)" == 'Darwin' ]]; then
-    # TestCppExtensions by default uses a temp folder in /tmp. This doesn't
-    # work for this Mac machine cause there is only one machine and /tmp is
-    # shared. (All the linux builds are on docker so have their own /tmp).
-    tests_to_skip+=('TestCppExtension')
-fi
-
-# Turn the set of tests to skip into an invocation that pytest understands
-excluded_tests_logic=''
-for exclusion in "${tests_to_skip[@]}"; do
-    if [[ -z "$excluded_tests_logic" ]]; then
-        # Only true for i==0
-        excluded_tests_logic="not ($exclusion)"
-    else
-        excluded_tests_logic="$excluded_tests_logic and not ($exclusion)"
-    fi
-done
-
-
-##############################################################################
-# Run the tests
-##############################################################################
-echo
-echo "$(date) :: Calling 'python test/run_test.py -v -p pytest ${entire_file_exclusions[@]} -- --disable-pytest-warnings -k '$excluded_tests_logic'"
-
-python test/run_test.py -v -p pytest ${entire_file_exclusions[@]} -- --disable-pytest-warnings -k "'" "$excluded_tests_logic" "'"
-
-echo
-echo "$(date) :: Finished 'python test/run_test.py -v -p pytest ${entire_file_exclusions[@]} -- --disable-pytest-warnings -k '$excluded_tests_logic'"
-
-# cpp_extensions don't work with pytest, so we run them without pytest here,
-# except there's a failure on CUDA builds (documented above), and
-# cpp_extensions doesn't work on a shared mac machine (also documented above)
-if [[ "$cuda_ver" == 'cpu' && "$(uname)" != 'Darwin' ]]; then
-    echo
-    echo "$(date) :: Calling 'python test/run_test.py -v -i cpp_extensions'"
-    python test/run_test.py -v -i cpp_extensions
-    echo
-    echo "$(date) :: Finished 'python test/run_test.py -v -i cpp_extensions'"
-fi
-
-# thd_distributed can run on Mac but not in pytest
-if [[ "$(uname)" == 'Darwin' ]]; then
-    echo
-    echo "$(date) :: Calling 'python test/run_test.py -v -i thd_distributed'"
-    python test/run_test.py -v -i thd_distributed
-    echo
-    echo "$(date) :: Finished 'python test/run_test.py -v -i thd_distributed'"
-fi

.ci/pytorch/smoke_test/check_binary_symbols.py

@@ -1,130 +0,0 @@
-#!/usr/bin/env python3
-import concurrent.futures
-import distutils.sysconfig
-import functools
-import itertools
-import os
-import re
-from pathlib import Path
-from typing import Any
-
-
-# We also check that there are [not] cxx11 symbols in libtorch
-#
-# To check whether it is using cxx11 ABI, check non-existence of symbol:
-PRE_CXX11_SYMBOLS = (
-    "std::basic_string<",
-    "std::list",
-)
-# To check whether it is using pre-cxx11 ABI, check non-existence of symbol:
-CXX11_SYMBOLS = (
-    "std::__cxx11::basic_string",
-    "std::__cxx11::list",
-)
-# NOTE: Checking the above symbols in all namespaces doesn't work, because
-# devtoolset7 always produces some cxx11 symbols even if we build with old ABI,
-# and CuDNN always has pre-cxx11 symbols even if we build with new ABI using gcc 5.4.
-# Instead, we *only* check the above symbols in the following namespaces:
-LIBTORCH_NAMESPACE_LIST = (
-    "c10::",
-    "at::",
-    "caffe2::",
-    "torch::",
-)
-
-
-def _apply_libtorch_symbols(symbols):
-    return [
-        re.compile(f"{x}.*{y}")
-        for (x, y) in itertools.product(LIBTORCH_NAMESPACE_LIST, symbols)
-    ]
-
-
-LIBTORCH_CXX11_PATTERNS = _apply_libtorch_symbols(CXX11_SYMBOLS)
-
-LIBTORCH_PRE_CXX11_PATTERNS = _apply_libtorch_symbols(PRE_CXX11_SYMBOLS)
-
-
-@functools.lru_cache(100)
-def get_symbols(lib: str) -> list[tuple[str, str, str]]:
-    from subprocess import check_output
-
-    lines = check_output(f'nm "{lib}"|c++filt', shell=True)
-    return [x.split(" ", 2) for x in lines.decode("latin1").split("\n")[:-1]]
-
-
-def grep_symbols(lib: str, patterns: list[Any]) -> list[str]:
-    def _grep_symbols(
-        symbols: list[tuple[str, str, str]], patterns: list[Any]
-    ) -> list[str]:
-        rc = []
-        for _s_addr, _s_type, s_name in symbols:
-            for pattern in patterns:
-                if pattern.match(s_name):
-                    rc.append(s_name)
-                    continue
-        return rc
-
-    all_symbols = get_symbols(lib)
-    num_workers = 32
-    chunk_size = (len(all_symbols) + num_workers - 1) // num_workers
-
-    def _get_symbols_chunk(i):
-        return all_symbols[i * chunk_size : (i + 1) * chunk_size]
-
-    with concurrent.futures.ThreadPoolExecutor(max_workers=32) as executor:
-        tasks = [
-            executor.submit(_grep_symbols, _get_symbols_chunk(i), patterns)
-            for i in range(num_workers)
-        ]
-        return functools.reduce(list.__add__, (x.result() for x in tasks), [])
-
-
-def check_lib_symbols_for_abi_correctness(lib: str, pre_cxx11_abi: bool = True) -> None:
-    print(f"lib: {lib}")
-    cxx11_symbols = grep_symbols(lib, LIBTORCH_CXX11_PATTERNS)
-    pre_cxx11_symbols = grep_symbols(lib, LIBTORCH_PRE_CXX11_PATTERNS)
-    num_cxx11_symbols = len(cxx11_symbols)
-    num_pre_cxx11_symbols = len(pre_cxx11_symbols)
-    print(f"num_cxx11_symbols: {num_cxx11_symbols}")
-    print(f"num_pre_cxx11_symbols: {num_pre_cxx11_symbols}")
-    if pre_cxx11_abi:
-        if num_cxx11_symbols > 0:
-            raise RuntimeError(
-                f"Found cxx11 symbols, but there shouldn't be any, see: {cxx11_symbols[:100]}"
-            )
-        if num_pre_cxx11_symbols < 1000:
-            raise RuntimeError("Didn't find enough pre-cxx11 symbols.")
-        # Check for no recursive iterators, regression test for https://github.com/pytorch/pytorch/issues/133437
-        rec_iter_symbols = grep_symbols(
-            lib, [re.compile("std::filesystem::recursive_directory_iterator.*")]
-        )
-        if len(rec_iter_symbols) > 0:
-            raise RuntimeError(
-                f"recursive_directory_iterator in used pre-CXX11 binaries, see; {rec_iter_symbols}"
-            )
-    else:
-        if num_pre_cxx11_symbols > 0:
-            raise RuntimeError(
-                f"Found pre-cxx11 symbols, but there shouldn't be any, see: {pre_cxx11_symbols[:100]}"
-            )
-        if num_cxx11_symbols < 100:
-            raise RuntimeError("Didn't find enought cxx11 symbols")
-
-
-def main() -> None:
-    if "install_root" in os.environ:
-        install_root = Path(os.getenv("install_root"))  # noqa: SIM112
-    else:
-        if os.getenv("PACKAGE_TYPE") == "libtorch":
-            install_root = Path(os.getcwd())
-        else:
-            install_root = Path(distutils.sysconfig.get_python_lib()) / "torch"
-
-    libtorch_cpu_path = str(install_root / "lib" / "libtorch_cpu.so")
-    # NOTE: All binaries are built with cxx11abi now
-    check_lib_symbols_for_abi_correctness(libtorch_cpu_path, False)
-
-
-if __name__ == "__main__":
-    main()

.ci/pytorch/smoke_test/max_autotune.py

@@ -1,209 +0,0 @@
-import argparse
-
-from torchvision import datasets, transforms
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.optim as optim
-from torch.optim.lr_scheduler import StepLR
-
-
-class Net(nn.Module):
-    def __init__(self):
-        super(Net, self).__init__()  # noqa: UP008
-        self.conv1 = nn.Conv2d(1, 32, 3, 1)
-        self.conv2 = nn.Conv2d(32, 64, 3, 1)
-        self.dropout1 = nn.Dropout(0.25)
-        self.dropout2 = nn.Dropout(0.5)
-        self.fc1 = nn.Linear(9216, 128)
-        self.fc2 = nn.Linear(128, 10)
-
-    def forward(self, x):
-        x = self.conv1(x)
-        x = F.relu(x)
-        x = self.conv2(x)
-        x = F.relu(x)
-        x = F.max_pool2d(x, 2)
-        x = self.dropout1(x)
-        x = torch.flatten(x, 1)
-        x = self.fc1(x)
-        x = F.relu(x)
-        x = self.dropout2(x)
-        x = self.fc2(x)
-        output = F.log_softmax(x, dim=1)
-        return output
-
-
-def train(args, model, device, train_loader, optimizer, epoch):
-    model.train()
-    for batch_idx, (data, target) in enumerate(train_loader):
-        data, target = data.to(device), target.to(device)
-        optimizer.zero_grad()
-        output = model(data)
-        loss = F.nll_loss(output, target)
-        loss.backward()
-        optimizer.step()
-        if batch_idx % args.log_interval == 0:
-            print(
-                f"Train Epoch: {epoch} "
-                f"[{batch_idx * len(data)}/{len(train_loader.dataset)} "
-                f"({100.0 * batch_idx / len(train_loader):.0f}%)]\tLoss: {loss.item():.6f}"
-            )
-            if args.dry_run:
-                break
-
-
-def test(model, device, test_loader):
-    model.eval()
-    test_loss = 0
-    correct = 0
-    with torch.no_grad():
-        for data, target in test_loader:
-            data, target = data.to(device), target.to(device)
-            output = model(data)
-            test_loss += F.nll_loss(
-                output, target, reduction="sum"
-            ).item()  # sum up batch loss
-            pred = output.argmax(
-                dim=1, keepdim=True
-            )  # get the index of the max log-probability
-            correct += pred.eq(target.view_as(pred)).sum().item()
-
-    test_loss /= len(test_loader.dataset)
-
-    print(
-        f"\nTest set: Average loss: {test_loss:.4f}, "
-        f"Accuracy: {correct}/{len(test_loader.dataset)} "
-        f"({100.0 * correct / len(test_loader.dataset):.0f}%)\n"
-    )
-
-
-def timed(fn):
-    start = torch.cuda.Event(enable_timing=True)
-    end = torch.cuda.Event(enable_timing=True)
-    start.record()
-    result = fn()
-    end.record()
-    torch.cuda.synchronize()
-    return result, start.elapsed_time(end) / 1000
-
-
-def main():
-    # Training settings
-    parser = argparse.ArgumentParser(description="PyTorch MNIST Example")
-    parser.add_argument(
-        "--batch-size",
-        type=int,
-        default=64,
-        metavar="N",
-        help="input batch size for training (default: 64)",
-    )
-    parser.add_argument(
-        "--test-batch-size",
-        type=int,
-        default=1000,
-        metavar="N",
-        help="input batch size for testing (default: 1000)",
-    )
-    parser.add_argument(
-        "--epochs",
-        type=int,
-        default=4,
-        metavar="N",
-        help="number of epochs to train (default: 14)",
-    )
-    parser.add_argument(
-        "--lr",
-        type=float,
-        default=1.0,
-        metavar="LR",
-        help="learning rate (default: 1.0)",
-    )
-    parser.add_argument(
-        "--gamma",
-        type=float,
-        default=0.7,
-        metavar="M",
-        help="Learning rate step gamma (default: 0.7)",
-    )
-    parser.add_argument(
-        "--no-cuda", action="store_true", default=False, help="disables CUDA training"
-    )
-    parser.add_argument(
-        "--no-mps",
-        action="store_true",
-        default=False,
-        help="disables macOS GPU training",
-    )
-    parser.add_argument(
-        "--dry-run",
-        action="store_true",
-        default=False,
-        help="quickly check a single pass",
-    )
-    parser.add_argument(
-        "--seed", type=int, default=1, metavar="S", help="random seed (default: 1)"
-    )
-    parser.add_argument(
-        "--log-interval",
-        type=int,
-        default=100,
-        metavar="N",
-        help="how many batches to wait before logging training status",
-    )
-    parser.add_argument(
-        "--save-model",
-        action="store_true",
-        default=False,
-        help="For Saving the current Model",
-    )
-    args = parser.parse_args()
-    use_cuda = not args.no_cuda and torch.cuda.is_available()
-    use_mps = not args.no_mps and torch.backends.mps.is_available()
-
-    torch.manual_seed(args.seed)
-    torch.backends.cuda.matmul.allow_tf32 = True
-
-    if use_cuda:
-        device = torch.device("cuda")
-    elif use_mps:
-        device = torch.device("mps")
-    else:
-        device = torch.device("cpu")
-
-    train_kwargs = {"batch_size": args.batch_size}
-    test_kwargs = {"batch_size": args.test_batch_size}
-    if use_cuda:
-        cuda_kwargs = {"num_workers": 1, "pin_memory": True, "shuffle": True}
-        train_kwargs.update(cuda_kwargs)
-        test_kwargs.update(cuda_kwargs)
-
-    transform = transforms.Compose(
-        [transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))]
-    )
-    dataset1 = datasets.MNIST("../data", train=True, download=True, transform=transform)
-    dataset2 = datasets.MNIST("../data", train=False, transform=transform)
-    train_loader = torch.utils.data.DataLoader(dataset1, **train_kwargs)
-    test_loader = torch.utils.data.DataLoader(dataset2, **test_kwargs)
-
-    model = Net().to(device)
-    opt_model = torch.compile(model, mode="max-autotune")
-    optimizer = optim.Adadelta(opt_model.parameters(), lr=args.lr)
-
-    scheduler = StepLR(optimizer, step_size=1, gamma=args.gamma)
-    for epoch in range(1, args.epochs + 1):
-        print(
-            f"Training Time: {timed(lambda: train(args, opt_model, device, train_loader, optimizer, epoch))[1]}"
-        )
-        print(
-            f"Evaluation Time: {timed(lambda: test(opt_model, device, test_loader))[1]}"
-        )
-        scheduler.step()
-
-    if args.save_model:
-        torch.save(opt_model.state_dict(), "mnist_cnn.pt")
-
-
-if __name__ == "__main__":
-    main()

.ci/pytorch/smoke_test/smoke_test.py

@@ -1,430 +0,0 @@
-import argparse
-import importlib
-import json
-import os
-import re
-import subprocess
-import sys
-from pathlib import Path
-from tempfile import NamedTemporaryFile
-
-import torch
-import torch._dynamo
-import torch.nn as nn
-import torch.nn.functional as F
-
-
-if "MATRIX_GPU_ARCH_VERSION" in os.environ:
-    gpu_arch_ver = os.getenv("MATRIX_GPU_ARCH_VERSION")
-else:
-    gpu_arch_ver = os.getenv("GPU_ARCH_VERSION")  # Use fallback if available
-gpu_arch_type = os.getenv("MATRIX_GPU_ARCH_TYPE")
-channel = os.getenv("MATRIX_CHANNEL")
-package_type = os.getenv("MATRIX_PACKAGE_TYPE")
-target_os = os.getenv("TARGET_OS", sys.platform)
-BASE_DIR = Path(__file__).parent.parent.parent
-
-is_cuda_system = gpu_arch_type == "cuda"
-NIGHTLY_ALLOWED_DELTA = 3
-
-MODULES = [
-    {
-        "name": "torchvision",
-        "repo": "https://github.com/pytorch/vision.git",
-        "smoke_test": "./vision/test/smoke_test.py",
-        "extension": "extension",
-        "repo_name": "vision",
-    },
-    {
-        "name": "torchaudio",
-        "repo": "https://github.com/pytorch/audio.git",
-        "smoke_test": "./audio/test/smoke_test/smoke_test.py --no-ffmpeg",
-        "extension": "_extension",
-        "repo_name": "audio",
-    },
-]
-
-
-class Net(nn.Module):
-    def __init__(self):
-        super().__init__()
-        self.conv1 = nn.Conv2d(1, 32, 3, 1)
-        self.conv2 = nn.Conv2d(32, 64, 3, 1)
-        self.fc1 = nn.Linear(9216, 1)
-
-    def forward(self, x):
-        x = self.conv1(x)
-        x = self.conv2(x)
-        x = F.max_pool2d(x, 2)
-        x = torch.flatten(x, 1)
-        output = self.fc1(x)
-        return output
-
-
-def load_json_from_basedir(filename: str):
-    try:
-        with open(BASE_DIR / filename) as fptr:
-            return json.load(fptr)
-    except FileNotFoundError as exc:
-        raise ImportError(f"File {filename} not found error: {exc.strerror}") from exc
-    except json.JSONDecodeError as exc:
-        raise ImportError(f"Invalid JSON {filename}") from exc
-
-
-def read_release_matrix():
-    return load_json_from_basedir("release_matrix.json")
-
-
-def test_numpy():
-    try:
-        import numpy as np
-
-        x = np.arange(5)
-        torch.tensor(x)
-    except ImportError:
-        print("Numpy check skipped. Numpy is not installed.")
-
-
-def check_version(package: str) -> None:
-    release_version = os.getenv("RELEASE_VERSION")
-    # if release_version is specified, use it to validate the packages
-    if release_version:
-        release_matrix = read_release_matrix()
-        stable_version = release_matrix["torch"]
-    else:
-        stable_version = os.getenv("MATRIX_STABLE_VERSION")
-
-    # only makes sense to check nightly package where dates are known
-    if channel == "nightly":
-        check_nightly_binaries_date(package)
-    elif stable_version is not None:
-        if not torch.__version__.startswith(stable_version):
-            raise RuntimeError(
-                f"Torch version mismatch, expected {stable_version} for channel {channel}. But its {torch.__version__}"
-            )
-
-        if release_version and package == "all":
-            for module in MODULES:
-                imported_module = importlib.import_module(module["name"])
-                module_version = imported_module.__version__
-                if not module_version.startswith(release_matrix[module["name"]]):
-                    raise RuntimeError(
-                        f"{module['name']} version mismatch, expected: \
-                            {release_matrix[module['name']]} for channel {channel}. But its {module_version}"
-                    )
-                else:
-                    print(
-                        f"{module['name']} version actual: {module_version} expected: \
-                        {release_matrix[module['name']]} for channel {channel}."
-                    )
-
-    else:
-        print(f"Skip version check for channel {channel} as stable version is None")
-
-
-def check_nightly_binaries_date(package: str) -> None:
-    from datetime import datetime
-
-    format_dt = "%Y%m%d"
-
-    date_t_str = re.findall("dev\\d+", torch.__version__)
-    date_t_delta = datetime.now() - datetime.strptime(date_t_str[0][3:], format_dt)
-    if date_t_delta.days >= NIGHTLY_ALLOWED_DELTA:
-        raise RuntimeError(
-            f"the binaries are from {date_t_str} and are more than {NIGHTLY_ALLOWED_DELTA} days old!"
-        )
-
-    if package == "all":
-        for module in MODULES:
-            imported_module = importlib.import_module(module["name"])
-            module_version = imported_module.__version__
-            date_m_str = re.findall("dev\\d+", module_version)
-            date_m_delta = datetime.now() - datetime.strptime(
-                date_m_str[0][3:], format_dt
-            )
-            print(f"Nightly date check for {module['name']} version {module_version}")
-            if date_m_delta.days > NIGHTLY_ALLOWED_DELTA:
-                raise RuntimeError(
-                    f"Expected {module['name']} to be less then {NIGHTLY_ALLOWED_DELTA} days. But its {date_m_delta}"
-                )
-
-
-def test_cuda_runtime_errors_captured() -> None:
-    cuda_exception_missed = True
-    try:
-        print("Testing test_cuda_runtime_errors_captured")
-        torch._assert_async(torch.tensor(0, device="cuda"))
-        torch._assert_async(torch.tensor(0 + 0j, device="cuda"))
-    except RuntimeError as e:
-        if re.search("CUDA", f"{e}"):
-            print(f"Caught CUDA exception with success: {e}")
-            cuda_exception_missed = False
-        else:
-            raise e
-    if cuda_exception_missed:
-        raise RuntimeError("Expected CUDA RuntimeError but have not received!")
-
-
-def test_cuda_gds_errors_captured() -> None:
-    major_version = int(torch.version.cuda.split(".")[0])
-    minor_version = int(torch.version.cuda.split(".")[1])
-
-    if target_os == "windows":
-        print(f"{target_os} is not supported for GDS smoke test")
-        return
-
-    if major_version < 12 or (major_version == 12 and minor_version < 6):
-        print("CUDA version is not supported for GDS smoke test")
-        return
-
-    cuda_exception_missed = True
-    try:
-        print("Testing test_cuda_gds_errors_captured")
-        with NamedTemporaryFile() as f:
-            torch.cuda.gds.GdsFile(f.name, os.O_CREAT | os.O_RDWR)
-    except RuntimeError as e:
-        expected_error = "cuFileHandleRegister failed"
-        if re.search(expected_error, f"{e}"):
-            print(f"Caught CUDA exception with success: {e}")
-            cuda_exception_missed = False
-        else:
-            raise e
-    if cuda_exception_missed:
-        raise RuntimeError(
-            "Expected cuFileHandleRegister failed RuntimeError but have not received!"
-        )
-
-
-def smoke_test_cuda(
-    package: str, runtime_error_check: str, torch_compile_check: str
-) -> None:
-    if not torch.cuda.is_available() and is_cuda_system:
-        raise RuntimeError(f"Expected CUDA {gpu_arch_ver}. However CUDA is not loaded.")
-
-    if package == "all" and is_cuda_system:
-        for module in MODULES:
-            imported_module = importlib.import_module(module["name"])
-            # TBD for vision move extension module to private so it will
-            # be _extention.
-            version = "N/A"
-            if module["extension"] == "extension":
-                version = imported_module.extension._check_cuda_version()
-            else:
-                version = imported_module._extension._check_cuda_version()
-            print(f"{module['name']} CUDA: {version}")
-
-    # torch.compile is available on macos-arm64 and Linux for python 3.8-3.13
-    if (
-        torch_compile_check == "enabled"
-        and sys.version_info < (3, 14, 0)
-        and target_os in ["linux", "linux-aarch64", "macos-arm64", "darwin"]
-    ):
-        smoke_test_compile("cuda" if torch.cuda.is_available() else "cpu")
-
-    if torch.cuda.is_available():
-        if torch.version.cuda != gpu_arch_ver:
-            raise RuntimeError(
-                f"Wrong CUDA version. Loaded: {torch.version.cuda} Expected: {gpu_arch_ver}"
-            )
-        print(f"torch cuda: {torch.version.cuda}")
-        # todo add cudnn version validation
-        print(f"torch cudnn: {torch.backends.cudnn.version()}")
-        print(f"cuDNN enabled? {torch.backends.cudnn.enabled}")
-
-        torch.cuda.init()
-        print("CUDA initialized successfully")
-        print(f"Number of CUDA devices: {torch.cuda.device_count()}")
-        for i in range(torch.cuda.device_count()):
-            print(f"Device {i}: {torch.cuda.get_device_name(i)}")
-
-        # nccl is availbale only on Linux
-        if sys.platform in ["linux", "linux2"]:
-            print(f"torch nccl version: {torch.cuda.nccl.version()}")
-
-        if runtime_error_check == "enabled":
-            test_cuda_runtime_errors_captured()
-
-
-def smoke_test_conv2d() -> None:
-    import torch.nn as nn
-
-    print("Testing smoke_test_conv2d")
-    # With square kernels and equal stride
-    m = nn.Conv2d(16, 33, 3, stride=2)
-    # non-square kernels and unequal stride and with padding
-    m = nn.Conv2d(16, 33, (3, 5), stride=(2, 1), padding=(4, 2))
-    assert m is not None
-    # non-square kernels and unequal stride and with padding and dilation
-    basic_conv = nn.Conv2d(
-        16, 33, (3, 5), stride=(2, 1), padding=(4, 2), dilation=(3, 1)
-    )
-    input = torch.randn(20, 16, 50, 100)
-    output = basic_conv(input)
-
-    if is_cuda_system:
-        print("Testing smoke_test_conv2d with cuda")
-        conv = nn.Conv2d(3, 3, 3).cuda()
-        x = torch.randn(1, 3, 24, 24, device="cuda")
-        with torch.cuda.amp.autocast():
-            out = conv(x)
-        assert out is not None
-
-        supported_dtypes = [torch.float16, torch.float32, torch.float64]
-        for dtype in supported_dtypes:
-            print(f"Testing smoke_test_conv2d with cuda for {dtype}")
-            conv = basic_conv.to(dtype).cuda()
-            input = torch.randn(20, 16, 50, 100, device="cuda").type(dtype)
-            output = conv(input)
-            assert output is not None
-
-
-def test_linalg(device="cpu") -> None:
-    print(f"Testing smoke_test_linalg on {device}")
-    A = torch.randn(5, 3, device=device)
-    U, S, Vh = torch.linalg.svd(A, full_matrices=False)
-    assert (
-        U.shape == A.shape
-        and S.shape == torch.Size([3])
-        and Vh.shape == torch.Size([3, 3])
-    )
-    torch.dist(A, U @ torch.diag(S) @ Vh)
-
-    U, S, Vh = torch.linalg.svd(A)
-    assert (
-        U.shape == torch.Size([5, 5])
-        and S.shape == torch.Size([3])
-        and Vh.shape == torch.Size([3, 3])
-    )
-    torch.dist(A, U[:, :3] @ torch.diag(S) @ Vh)
-
-    A = torch.randn(7, 5, 3, device=device)
-    U, S, Vh = torch.linalg.svd(A, full_matrices=False)
-    torch.dist(A, U @ torch.diag_embed(S) @ Vh)
-
-    if device == "cuda":
-        supported_dtypes = [torch.float32, torch.float64]
-        for dtype in supported_dtypes:
-            print(f"Testing smoke_test_linalg with cuda for {dtype}")
-            A = torch.randn(20, 16, 50, 100, device=device, dtype=dtype)
-            torch.linalg.svd(A)
-
-
-def smoke_test_compile(device: str = "cpu") -> None:
-    supported_dtypes = [torch.float16, torch.float32, torch.float64]
-
-    def foo(x: torch.Tensor) -> torch.Tensor:
-        return torch.sin(x) + torch.cos(x)
-
-    for dtype in supported_dtypes:
-        print(f"Testing smoke_test_compile for {device} and {dtype}")
-        x = torch.rand(3, 3, device=device).type(dtype)
-        x_eager = foo(x)
-        x_pt2 = torch.compile(foo)(x)
-        torch.testing.assert_close(x_eager, x_pt2)
-
-    # Check that SIMD were detected for the architecture
-    if device == "cpu":
-        from torch._inductor.codecache import pick_vec_isa
-
-        isa = pick_vec_isa()
-        if not isa:
-            raise RuntimeError("Can't detect vectorized ISA for CPU")
-        print(f"Picked CPU ISA {type(isa).__name__} bit width {isa.bit_width()}")
-
-    # Reset torch dynamo since we are changing mode
-    torch._dynamo.reset()
-    dtype = torch.float32
-    torch.set_float32_matmul_precision("high")
-    print(f"Testing smoke_test_compile with mode 'max-autotune' for {dtype}")
-    x = torch.rand(64, 1, 28, 28, device=device).type(torch.float32)
-    model = Net().to(device=device)
-    x_pt2 = torch.compile(model, mode="max-autotune")(x)
-
-
-def smoke_test_modules():
-    cwd = os.getcwd()
-    for module in MODULES:
-        if module["repo"]:
-            if not os.path.exists(f"{cwd}/{module['repo_name']}"):
-                print(f"Path does not exist: {cwd}/{module['repo_name']}")
-                try:
-                    subprocess.check_output(
-                        f"git clone --depth 1 {module['repo']}",
-                        stderr=subprocess.STDOUT,
-                        shell=True,
-                    )
-                except subprocess.CalledProcessError as exc:
-                    raise RuntimeError(
-                        f"Cloning {module['repo']} FAIL: {exc.returncode} Output: {exc.output}"
-                    ) from exc
-            try:
-                smoke_test_command = f"python3 {module['smoke_test']}"
-                if target_os == "windows":
-                    smoke_test_command = f"python {module['smoke_test']}"
-                output = subprocess.check_output(
-                    smoke_test_command,
-                    stderr=subprocess.STDOUT,
-                    shell=True,
-                    universal_newlines=True,
-                )
-            except subprocess.CalledProcessError as exc:
-                raise RuntimeError(
-                    f"Module {module['name']} FAIL: {exc.returncode} Output: {exc.output}"
-                ) from exc
-            else:
-                print(f"Output: \n{output}\n")
-
-
-def parse_args():
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--package",
-        help="Package to include in smoke testing",
-        type=str,
-        choices=["all", "torchonly"],
-        default="all",
-    )
-    parser.add_argument(
-        "--runtime-error-check",
-        help="No Runtime Error check",
-        type=str,
-        choices=["enabled", "disabled"],
-        default="enabled",
-    )
-    parser.add_argument(
-        "--torch-compile-check",
-        help="Check torch compile",
-        type=str,
-        choices=["enabled", "disabled"],
-        default="enabled",
-    )
-    return parser.parse_args()
-
-
-def main() -> None:
-    options = parse_args()
-    print(f"torch: {torch.__version__}")
-    print(torch.__config__.parallel_info())
-    # All PyTorch binary builds should be built with OpenMP
-    if not torch.backends.openmp.is_available():
-        raise RuntimeError("PyTorch must be built with OpenMP support")
-
-    check_version(options.package)
-    smoke_test_conv2d()
-    test_linalg()
-    test_numpy()
-
-    if is_cuda_system:
-        test_linalg("cuda")
-        test_cuda_gds_errors_captured()
-
-    if options.package == "all":
-        smoke_test_modules()
-
-    smoke_test_cuda(
-        options.package, options.runtime_error_check, options.torch_compile_check
-    )
-
-
-if __name__ == "__main__":
-    main()

.ci/pytorch/test.sh

@@ -4,7 +4,7 @@
 # (This is set by default in the Docker images we build, so you don't
 # need to set it yourself.
 
-set -ex -o pipefail
+set -ex
 
 # Suppress ANSI color escape sequences
 export TERM=vt100
@@ -12,9 +12,9 @@ export TERM=vt100
 # shellcheck source=./common.sh
 source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
 
-# 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 [[ "$BUILD_ENVIRONMENT" != *rocm* ]]; then
   # Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
   WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
   cleanup_workspace() {
@@ -46,12 +46,9 @@ BUILD_BIN_DIR="$BUILD_DIR"/bin
 SHARD_NUMBER="${SHARD_NUMBER:=1}"
 NUM_TEST_SHARDS="${NUM_TEST_SHARDS:=1}"
 
-# enable debug asserts in serialization
-export TORCH_SERIALIZATION_DEBUG=1
-
 export VALGRIND=ON
 # export TORCH_INDUCTOR_INSTALL_GXX=ON
-if [[ "$BUILD_ENVIRONMENT" == *clang9* || "$BUILD_ENVIRONMENT" == *xpu* ]]; then
+if [[ "$BUILD_ENVIRONMENT" == *clang9* ]]; then
   # clang9 appears to miscompile code involving std::optional<c10::SymInt>,
   # such that valgrind complains along these lines:
   #
@@ -89,13 +86,6 @@ if [[ "$BUILD_ENVIRONMENT" == *clang9* || "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   export VALGRIND=OFF
 fi
 
-
-if [[ "$BUILD_ENVIRONMENT" == *s390x* ]]; then
-  # There are additional warnings on s390x, maybe due to newer gcc.
-  # Skip this check for now
-  export VALGRIND=OFF
-fi
-
 if [[ "${PYTORCH_TEST_RERUN_DISABLED_TESTS}" == "1" ]] || [[ "${CONTINUE_THROUGH_ERROR}" == "1" ]]; then
   # When rerunning disable tests, do not generate core dumps as it could consume
   # the runner disk space when crashed tests are run multiple times. Running out
@@ -139,7 +129,7 @@ if [[ "$TEST_CONFIG" == 'default' ]]; then
 fi
 
 if [[ "$TEST_CONFIG" == 'distributed' ]] && [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
-  export HIP_VISIBLE_DEVICES=0,1,2,3
+  export HIP_VISIBLE_DEVICES=0,1
 fi
 
 if [[ "$TEST_CONFIG" == 'slow' ]]; then
@@ -163,8 +153,6 @@ elif [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   export PYTORCH_TESTING_DEVICE_ONLY_FOR="xpu"
   # setting PYTHON_TEST_EXTRA_OPTION
   export PYTHON_TEST_EXTRA_OPTION="--xpu"
-  # Disable sccache for xpu test due to flaky issue https://github.com/pytorch/pytorch/issues/143585
-  sudo rm -rf /opt/cache
 fi
 
 if [[ "$TEST_CONFIG" == *crossref* ]]; then
@@ -177,9 +165,6 @@ if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
   # Print GPU info
   rocminfo
   rocminfo | grep -E 'Name:.*\sgfx|Marketing'
-
-  # for benchmarks/dynamo/check_accuracy.py, we need to put results in a rocm specific directory to avoid clashes with cuda
-  MAYBE_ROCM="rocm/"
 fi
 
 if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
@@ -314,13 +299,6 @@ test_python() {
   assert_git_not_dirty
 }
 
-test_lazy_tensor_meta_reference_disabled() {
-  export TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1
-  echo "Testing lazy tensor operations without meta reference"
-  time python test/run_test.py --include lazy/test_ts_opinfo.py --verbose
-  export -n TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE
-}
-
 
 test_dynamo_wrapped_shard() {
   if [[ -z "$NUM_TEST_SHARDS" ]]; then
@@ -335,7 +313,6 @@ test_dynamo_wrapped_shard() {
     --exclude-jit-executor \
     --exclude-distributed-tests \
     --exclude-torch-export-tests \
-    --exclude-aot-dispatch-tests \
     --shard "$1" "$NUM_TEST_SHARDS" \
     --verbose \
     --upload-artifacts-while-running
@@ -349,7 +326,7 @@ test_inductor_distributed() {
   python test/run_test.py -i inductor/test_aot_inductor.py -k test_non_default_cuda_device --verbose
   python test/run_test.py -i inductor/test_aot_inductor.py -k test_replicate_on_devices --verbose
   python test/run_test.py -i distributed/test_c10d_functional_native.py --verbose
-  python test/run_test.py -i distributed/tensor/test_dtensor_compile.py --verbose
+  python test/run_test.py -i distributed/_tensor/test_dtensor_compile.py --verbose
   python test/run_test.py -i distributed/tensor/parallel/test_micro_pipeline_tp.py --verbose
   python test/run_test.py -i distributed/_composable/test_replicate_with_compiler.py --verbose
   python test/run_test.py -i distributed/_composable/fsdp/test_fully_shard_comm.py --verbose
@@ -402,32 +379,15 @@ test_inductor_aoti() {
   CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference
 }
 
-test_inductor_cpp_wrapper_shard() {
-  if [[ -z "$NUM_TEST_SHARDS" ]]; then
-    echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
-    exit 1
-  fi
-
+test_inductor_cpp_wrapper() {
   export TORCHINDUCTOR_CPP_WRAPPER=1
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
 
-  if [[ "$1" -eq "2" ]]; then
-    # For now, manually put the opinfo tests in shard 2, and all other tests in
-    # shard 1.  Test specific things triggering past bugs, for now.
-    python test/run_test.py \
-      --include inductor/test_torchinductor_opinfo \
-      -k 'linalg or to_sparse' \
-      --verbose
-    exit
-  fi
+  # Run certain inductor unit tests with cpp wrapper. In the end state, we should be able to run all the inductor
+  # unit tests with cpp wrapper.
+  python test/run_test.py --include inductor/test_torchinductor.py --verbose
 
-  # Run certain inductor unit tests with cpp wrapper. In the end state, we
-  # should be able to run all the inductor unit tests with cpp_wrapper.
-  python test/run_test.py \
-    --include inductor/test_torchinductor inductor/test_max_autotune inductor/test_cpu_repro \
-    --verbose
-  python test/run_test.py --inductor --include test_torch -k 'take' --verbose
 
   # Run inductor benchmark tests with cpp wrapper.
   # Skip benchmark tests if it's in rerun-disabled-mode.
@@ -440,7 +400,7 @@ test_inductor_cpp_wrapper_shard() {
     --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv"
     python benchmarks/dynamo/check_accuracy.py \
       --actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}inductor_timm_training.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/inductor_timm_training.csv"
 
     python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
       --bfloat16 --inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
@@ -450,7 +410,7 @@ test_inductor_cpp_wrapper_shard() {
       --bfloat16 --inference --inductor --only moco --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
     python benchmarks/dynamo/check_accuracy.py \
       --actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}inductor_torchbench_inference.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_inference.csv"
   fi
 }
 
@@ -483,8 +443,6 @@ elif [[ "${TEST_CONFIG}" == *aot_eager* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--backend aot_eager)
 elif [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--export-aot-inductor)
-elif [[ "${TEST_CONFIG}" == *max_autotune_inductor* ]]; then
-  DYNAMO_BENCHMARK_FLAGS+=(--inductor --inductor-compile-mode max-autotune)
 elif [[ "${TEST_CONFIG}" == *inductor* && "${TEST_CONFIG}" != *perf* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--inductor)
 fi
@@ -499,59 +457,6 @@ else
   DYNAMO_BENCHMARK_FLAGS+=(--device cuda)
 fi
 
-test_cachebench() {
-  TEST_REPORTS_DIR=$(pwd)/test/test-reports
-  mkdir -p "$TEST_REPORTS_DIR"
-
-  local BENCHMARK
-  if [[ "${SHARD_NUMBER}" == 1 ]]; then
-    local BENCHMARK=torchbench
-  elif [[ "${SHARD_NUMBER}" == 2 ]]; then
-    local BENCHMARK=huggingface
-  else
-    echo "invalid SHARD_NUMBER: ${SHARD_NUMBER}"
-    exit 1
-  fi
-
-  local mode_options=("training" "inference")
-
-  for mode in "${mode_options[@]}"; do
-    $TASKSET python "benchmarks/dynamo/cachebench.py" \
-        --mode "$mode" \
-        --device cuda \
-        --benchmark "$BENCHMARK" \
-        --repeat 3 \
-        --output "$TEST_REPORTS_DIR/cachebench_${BENCHMARK}_${mode}.json"
-
-    $TASKSET python "benchmarks/dynamo/cachebench.py" \
-        --mode "$mode" \
-        --dynamic \
-        --device cuda \
-        --benchmark "$BENCHMARK" \
-        --repeat 3 \
-        --output "$TEST_REPORTS_DIR/cachebench_${BENCHMARK}_${mode}_dynamic.json"
-  done
-}
-
-test_verify_cachebench() {
-  TMP_TEST_REPORTS_DIR=$(mktemp -d)
-  TEST_OUTPUT="$TMP_TEST_REPORTS_DIR/test.json"
-
-  $TASKSET python "benchmarks/dynamo/cachebench.py" \
-      --mode training \
-      --device cpu \
-      --model nanogpt \
-      --benchmark torchbench \
-      --output "$TEST_OUTPUT"
-
-  # -s checks file exists and is non empty
-  if [[ ! -s "$TEST_OUTPUT" ]]; then
-    echo "Cachebench failed to produce an output."
-    echo "Run 'python benchmarks/dynamo/cachebench.py' to make sure it works"
-    exit 1
-  fi
-}
-
 test_perf_for_dashboard() {
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
@@ -580,10 +485,6 @@ test_perf_for_dashboard() {
     test_inductor_set_cpu_affinity
   elif [[ "${TEST_CONFIG}" == *cuda_a10g* ]]; then
     device=cuda_a10g
-  elif [[ "${TEST_CONFIG}" == *h100* ]]; then
-    device=cuda_h100
-  elif [[ "${TEST_CONFIG}" == *rocm* ]]; then
-    device=rocm
   fi
 
   for mode in "${modes[@]}"; do
@@ -616,7 +517,7 @@ test_perf_for_dashboard() {
             --dynamic-batch-only "$@" \
             --output "$TEST_REPORTS_DIR/${backend}_dynamic_${suite}_${dtype}_${mode}_${device}_${target}.csv"
       fi
-      if [[ "$DASHBOARD_TAG" == *cppwrapper-true* ]]; then
+      if [[ "$DASHBOARD_TAG" == *cppwrapper-true* ]] && [[ "$mode" == "inference" ]]; then
         TORCHINDUCTOR_CPP_WRAPPER=1 $TASKSET python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs "$@" \
             --output "$TEST_REPORTS_DIR/${backend}_cpp_wrapper_${suite}_${dtype}_${mode}_${device}_${target}.csv"
@@ -700,25 +601,20 @@ test_single_dynamo_benchmark() {
       TEST_CONFIG=${TEST_CONFIG//_avx512/}
     fi
     python "benchmarks/dynamo/$suite.py" \
-      --ci --accuracy --timing --explain --print-compilation-time \
+      --ci --accuracy --timing --explain \
       "${DYNAMO_BENCHMARK_FLAGS[@]}" \
       "$@" "${partition_flags[@]}" \
       --output "$TEST_REPORTS_DIR/${name}_${suite}.csv"
     python benchmarks/dynamo/check_accuracy.py \
       --actual "$TEST_REPORTS_DIR/${name}_$suite.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}${TEST_CONFIG}_${name}.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG}_${name}.csv"
     python benchmarks/dynamo/check_graph_breaks.py \
       --actual "$TEST_REPORTS_DIR/${name}_$suite.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}${TEST_CONFIG}_${name}.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG}_${name}.csv"
   fi
 }
 
 test_inductor_micro_benchmark() {
-  # torchao requires cuda 8.0 or above for bfloat16 support
-  if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
-    export TORCH_CUDA_ARCH_LIST="8.0;8.6"
-  fi
-  install_torchao
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   if [[ "${TEST_CONFIG}" == *cpu* ]]; then
     test_inductor_set_cpu_affinity
@@ -732,7 +628,7 @@ test_inductor_halide() {
 }
 
 test_inductor_triton_cpu() {
-  python test/run_test.py --include inductor/test_triton_cpu_backend.py inductor/test_torchinductor_strided_blocks.py --verbose
+  python test/run_test.py --include inductor/test_triton_cpu_backend.py --verbose
   assert_git_not_dirty
 }
 
@@ -762,8 +658,6 @@ test_dynamo_benchmark() {
       fi
     elif [[ "${TEST_CONFIG}" == *aot_inductor* ]]; then
       test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
-    elif [[ "${TEST_CONFIG}" == *max_autotune_inductor* ]]; then
-      test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
     else
       test_single_dynamo_benchmark "inference" "$suite" "$shard_id" --inference --bfloat16 "$@"
       test_single_dynamo_benchmark "training" "$suite" "$shard_id" --training --amp "$@"
@@ -798,7 +692,7 @@ test_inductor_torchbench_smoketest_perf() {
       --only $test --output "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv"
     python benchmarks/dynamo/check_accuracy.py \
       --actual "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}inductor_huggingface_training.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/inductor_huggingface_training.csv"
   done
 }
 
@@ -994,20 +888,10 @@ test_libtorch_api() {
   else
     # Exclude IMethodTest that relies on torch::deploy, which will instead be ran in test_deploy
     OMP_NUM_THREADS=2 TORCH_CPP_TEST_MNIST_PATH="${MNIST_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_api -k "not IMethodTest"
-
-    # On s390x, pytorch is built without llvm.
-    # Even if it would be built with llvm, llvm currently doesn't support used features on s390x and
-    # test fails with errors like:
-    # JIT session error: Unsupported target machine architecture in ELF object pytorch-jitted-objectbuffer
-    # unknown file: Failure
-    # C++ exception with description "valOrErr INTERNAL ASSERT FAILED at "/var/lib/jenkins/workspace/torch/csrc/jit/tensorexpr/llvm_jit.h":34, please report a bug to PyTorch. Unexpected failure in LLVM JIT: Failed to materialize symbols: { (main, { func }) }
-    if [[ "${BUILD_ENVIRONMENT}" != *s390x* ]]; then
-      python test/run_test.py --cpp --verbose -i cpp/test_tensorexpr
-    fi
+    python test/run_test.py --cpp --verbose -i cpp/test_tensorexpr
   fi
 
-  # quantization is not fully supported on s390x yet
-  if [[ "${BUILD_ENVIRONMENT}" != *android* && "${BUILD_ENVIRONMENT}" != *cuda* && "${BUILD_ENVIRONMENT}" != *asan* && "${BUILD_ENVIRONMENT}" != *s390x* ]]; then
+  if [[ "${BUILD_ENVIRONMENT}" != *android* && "${BUILD_ENVIRONMENT}" != *cuda* && "${BUILD_ENVIRONMENT}" != *asan* ]]; then
     # NB: This test is not under TORCH_BIN_DIR but under BUILD_BIN_DIR
     export CPP_TESTS_DIR="${BUILD_BIN_DIR}"
     python test/run_test.py --cpp --verbose -i cpp/static_runtime_test
@@ -1068,9 +952,6 @@ test_distributed() {
     python test/run_test.py --cpp --verbose -i cpp/HashStoreTest
     python test/run_test.py --cpp --verbose -i cpp/TCPStoreTest
 
-    echo "Testing multi-GPU linalg tests"
-    python test/run_test.py -i test_linalg.py -k test_matmul_offline_mgpu_tunable --verbose
-
     if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
       MPIEXEC=$(command -v mpiexec)
       if [[ -n "$MPIEXEC" ]]; then
@@ -1354,7 +1235,7 @@ EOF
 }
 
 test_bazel() {
-  set -e -o pipefail
+  set -e
 
   # bazel test needs sccache setup.
   # shellcheck source=./common-build.sh
@@ -1504,8 +1385,7 @@ test_executorch() {
 
 test_linux_aarch64() {
   python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
-        test_transformers test_multiprocessing test_numpy_interop test_autograd test_binary_ufuncs test_complex test_spectral_ops \
-        test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
+        test_transformers test_multiprocessing test_numpy_interop \
         --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 
   # Dynamo tests
@@ -1523,7 +1403,6 @@ test_linux_aarch64() {
        inductor/test_pattern_matcher inductor/test_perf inductor/test_profiler inductor/test_select_algorithm inductor/test_smoke \
        inductor/test_split_cat_fx_passes inductor/test_standalone_compile inductor/test_torchinductor \
        inductor/test_torchinductor_codegen_dynamic_shapes inductor/test_torchinductor_dynamic_shapes inductor/test_memory \
-       inductor/test_triton_cpu_backend inductor/test_triton_extension_backend inductor/test_mkldnn_pattern_matcher inductor/test_cpu_cpp_wrapper \
        --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 }
 
@@ -1531,11 +1410,7 @@ if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-baze
   (cd test && python -c "import torch; print(torch.__config__.show())")
   (cd test && python -c "import torch; print(torch.__config__.parallel_info())")
 fi
-if [[ "${TEST_CONFIG}" == *numpy_2* ]]; then
-  # Install numpy-2.0.2 and compatible scipy & numba versions
-  python -mpip install --pre numpy==2.0.2 scipy==1.13.1 numba==0.60.0
-  python test/run_test.py --include dynamo/test_functions.py dynamo/test_unspec.py test_binary_ufuncs.py test_fake_tensor.py test_linalg.py test_numpy_interop.py test_tensor_creation_ops.py test_torch.py torch_np/test_basic.py
-elif [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" != *perf_cpu_aarch64* ]]; then
+if [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" != *perf_cpu_aarch64* ]]; then
   test_linux_aarch64
 elif [[ "${TEST_CONFIG}" == *backward* ]]; then
   test_forward_backward_compatibility
@@ -1573,16 +1448,6 @@ elif [[ "${TEST_CONFIG}" == *timm* ]]; then
   install_torchvision
   id=$((SHARD_NUMBER-1))
   test_dynamo_benchmark timm_models "$id"
-elif [[ "${TEST_CONFIG}" == cachebench ]]; then
-  install_torchaudio cuda
-  install_torchvision
-  checkout_install_torchbench nanogpt BERT_pytorch resnet50 hf_T5 llama moco
-  PYTHONPATH=$(pwd)/torchbench test_cachebench
-elif [[ "${TEST_CONFIG}" == verify_cachebench ]]; then
-  install_torchaudio cpu
-  install_torchvision
-  checkout_install_torchbench nanogpt
-  PYTHONPATH=$(pwd)/torchbench test_verify_cachebench
 elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
   if [[ "${TEST_CONFIG}" == *cpu* ]]; then
     install_torchaudio cpu
@@ -1618,8 +1483,7 @@ elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper* ]]; then
   install_torchaudio cuda
   install_torchvision
   checkout_install_torchbench hf_T5 llama moco
-  PYTHONPATH=$(pwd)/torchbench test_inductor_cpp_wrapper_shard "$SHARD_NUMBER"
-  test_inductor_aoti
+  PYTHONPATH=$(pwd)/torchbench test_inductor_cpp_wrapper
 elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
   install_torchvision
   test_inductor_shard "${SHARD_NUMBER}"
@@ -1639,7 +1503,6 @@ elif [[ "${BUILD_ENVIRONMENT}" == *rocm* && -n "$TESTS_TO_INCLUDE" ]]; then
   test_python_shard "$SHARD_NUMBER"
   test_aten
 elif [[ "${SHARD_NUMBER}" == 1 && $NUM_TEST_SHARDS -gt 1 ]]; then
-  test_lazy_tensor_meta_reference_disabled
   test_without_numpy
   install_torchvision
   test_python_shard 1

.ci/pytorch/test_example_code/CMakeLists.txt

@@ -1,26 +0,0 @@
-cmake_minimum_required(VERSION 3.0 FATAL_ERROR)
-project(simple-torch-test)
-
-find_package(Torch REQUIRED)
-set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}")
-
-
-add_executable(simple-torch-test simple-torch-test.cpp)
-target_include_directories(simple-torch-test PRIVATE  ${TORCH_INCLUDE_DIRS})
-target_link_libraries(simple-torch-test "${TORCH_LIBRARIES}")
-set_property(TARGET simple-torch-test PROPERTY CXX_STANDARD 17)
-
-find_package(CUDAToolkit 11.8)
-
-target_link_libraries(simple-torch-test CUDA::cudart CUDA::cufft CUDA::cusparse CUDA::cublas CUDA::cusolver)
-find_library(CUDNN_LIBRARY NAMES cudnn)
-target_link_libraries(simple-torch-test  ${CUDNN_LIBRARY} )
-if(MSVC)
-  file(GLOB TORCH_DLLS  "$ENV{CUDA_PATH}/bin/cudnn64_8.dll" "$ENV{NVTOOLSEXT_PATH}/bin/x64/*.dll")
-  message("dlls to copy "  ${TORCH_DLLS})
-  add_custom_command(TARGET simple-torch-test
-                     POST_BUILD
-                     COMMAND ${CMAKE_COMMAND} -E copy_if_different
-                     ${TORCH_DLLS}
-                     $<TARGET_FILE_DIR:simple-torch-test>)
-endif(MSVC)

.ci/pytorch/test_example_code/check-torch-cuda.cpp

@@ -1,15 +0,0 @@
-#include <torch/torch.h>
-
-int main(int argc, const char* argv[]) {
-    std::cout << "Checking that CUDA archs are setup correctly" << std::endl;
-    TORCH_CHECK(torch::rand({ 3, 5 }, torch::Device(torch::kCUDA)).defined(), "CUDA archs are not setup correctly");
-
-    // These have to run after CUDA is initialized
-
-    std::cout << "Checking that magma is available" << std::endl;
-    TORCH_CHECK(torch::hasMAGMA(), "MAGMA is not available");
-
-    std::cout << "Checking that CuDNN is available" << std::endl;
-    TORCH_CHECK(torch::cuda::cudnn_is_available(), "CuDNN is not available");
-    return 0;
-}

.ci/pytorch/test_example_code/check-torch-mkl.cpp

@@ -1,6 +0,0 @@
-#include <torch/torch.h>
-
-int main(int argc, const char* argv[]) {
-    TORCH_CHECK(torch::hasMKL(), "MKL is not available");
-    return 0;
-}

.ci/pytorch/test_example_code/check-torch-xnnpack.cpp

@@ -1,7 +0,0 @@
-#include <ATen/ATen.h>
-#include <torch/torch.h>
-
-int main(int argc, const char* argv[]) {
-    TORCH_CHECK(at::globalContext().isXNNPACKAvailable(), "XNNPACK is not available");
-    return 0;
-}

.ci/pytorch/test_example_code/cnn_smoke.py

@@ -1,38 +0,0 @@
-r"""
-It's used to check basic rnn features with cuda.
-For example, it would throw exception if some components are missing
-"""
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.optim as optim
-
-
-class SimpleCNN(nn.Module):
-    def __init__(self):
-        super().__init__()
-        self.conv = nn.Conv2d(1, 1, 3)
-        self.pool = nn.MaxPool2d(2, 2)
-
-    def forward(self, inputs):
-        output = self.pool(F.relu(self.conv(inputs)))
-        output = output.view(1)
-        return output
-
-
-# Mock one infer
-device = torch.device("cuda:0")
-net = SimpleCNN().to(device)
-net_inputs = torch.rand((1, 1, 5, 5), device=device)
-outputs = net(net_inputs)
-print(outputs)
-
-criterion = nn.MSELoss()
-optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.1)
-
-# Mock one step training
-label = torch.full((1,), 1.0, dtype=torch.float, device=device)
-loss = criterion(outputs, label)
-loss.backward()
-optimizer.step()

.ci/pytorch/test_example_code/cnn_smoke_win_arm64.py

@@ -1,41 +0,0 @@
-r"""
-It's used to check basic rnn features with cpu-only.
-For example, it would throw exception if some components are missing
-"""
-
-import torch
-import torch.nn as nn
-import torch.nn.functional as F
-import torch.optim as optim
-
-
-class SimpleCNN(nn.Module):
-    def __init__(self):
-        super().__init__()
-        self.conv = nn.Conv2d(1, 1, 3)
-        self.pool = nn.MaxPool2d(2, 2)
-
-    def forward(self, inputs):
-        output = self.pool(F.relu(self.conv(inputs)))
-        output = output.view(1)
-        return output
-
-
-try:
-    # Mock one infer
-    net = SimpleCNN()
-    net_inputs = torch.rand((1, 1, 5, 5))
-    outputs = net(net_inputs)
-    print(outputs)
-
-    criterion = nn.MSELoss()
-    optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.1)
-
-    # Mock one step training
-    label = torch.full((1,), 1.0, dtype=torch.float)
-    loss = criterion(outputs, label)
-    loss.backward()
-    optimizer.step()
-
-except Exception as e:
-    print(f"An error occurred: {e}")

.ci/pytorch/test_example_code/rnn_smoke.py

@@ -1,14 +0,0 @@
-r"""
-It's used to check basic rnn features with cuda.
-For example, it would throw exception if missing some components are missing
-"""
-
-import torch
-import torch.nn as nn
-
-
-device = torch.device("cuda:0")
-rnn = nn.RNN(10, 20, 2).to(device)
-inputs = torch.randn(5, 3, 10).to(device)
-h0 = torch.randn(2, 3, 20).to(device)
-output, hn = rnn(inputs, h0)

.ci/pytorch/test_example_code/rnn_smoke_win_arm64.py

@@ -1,13 +0,0 @@
-r"""
-It's used to check basic rnn features with cpu-only.
-For example, it would throw exception if missing some components are missing
-"""
-
-import torch
-import torch.nn as nn
-
-
-rnn = nn.RNN(10, 20, 2)
-inputs = torch.randn(5, 3, 10)
-h0 = torch.randn(2, 3, 20)
-output, hn = rnn(inputs, h0)

.ci/pytorch/test_example_code/simple-torch-test.cpp

@@ -1,6 +0,0 @@
-#include <torch/torch.h>
-
-int main(int argc, const char* argv[]) {
-    TORCH_WARN("Simple test passed!");
-    return 0;
-}

.ci/pytorch/win-build.sh

@@ -38,7 +38,7 @@ if [[ $PYLONG_API_CHECK == 0 ]]; then
   echo "PyLong_AsUnsignedLong -> THPUtils_unpackUInt32 / THPUtils_unpackUInt64"
   exit 1
 fi
-set -ex -o pipefail
+set -ex
 
 "$SCRIPT_HELPERS_DIR"/build_pytorch.bat
 

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

@@ -26,8 +26,7 @@ if not errorlevel 0 goto fail
 
 if "%USE_XPU%"=="1" (
   :: Install xpu support packages
-  set CUDA_VERSION=xpu
-  call %SCRIPT_HELPERS_DIR%\..\windows\internal\xpu_install.bat
+  call %INSTALLER_DIR%\install_xpu.bat
   if errorlevel 1 exit /b 1
 )
 

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

@@ -2,14 +2,6 @@
 REM Description: Install Intel Support Packages on Windows
 REM BKM reference: https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpus.html
 
-if not "%CUDA_VERSION%" == "xpu" (
-    echo Skipping for non XPU builds
-    exit /b 0
-)
-
-set SRC_DIR=%NIGHTLIES_PYTORCH_ROOT%
-if not exist "%SRC_DIR%\temp_build" mkdir "%SRC_DIR%\temp_build"
-
 set XPU_INSTALL_MODE=%~1
 if "%XPU_INSTALL_MODE%"=="" goto xpu_bundle_install_start
 if "%XPU_INSTALL_MODE%"=="bundle" goto xpu_bundle_install_start
@@ -47,9 +39,9 @@ set XPU_EXTRA_INSTALLED=0
 set XPU_EXTRA_UNINSTALL=0
 
 if not [%XPU_VERSION%]==[] if [%XPU_VERSION%]==[2025.0] (
-    set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/9d6d6c17-ca2d-4735-9331-99447e4a1280/intel-deep-learning-essentials-2025.0.1.28_offline.exe
+    set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/efc86abd-cb77-452e-a03f-a741895b8ece/intel-deep-learning-essentials-2025.0.0.336_offline.exe
     set XPU_BUNDLE_PRODUCT_NAME=intel.oneapi.win.deep-learning-essentials.product
-    set XPU_BUNDLE_VERSION=2025.0.1+20
+    set XPU_BUNDLE_VERSION=2025.0.0+335
     set XPU_BUNDLE_INSTALLED=0
     set XPU_BUNDLE_UNINSTALL=0
     set XPU_EXTRA_URL=NULL
@@ -120,14 +112,3 @@ if errorlevel 1 exit /b 1
 del xpu_extra.exe
 
 :xpu_install_end
-
-if not "%XPU_ENABLE_KINETO%"=="1" goto install_end
-:: Install Level Zero SDK
-set XPU_EXTRA_LZ_URL=https://github.com/oneapi-src/level-zero/releases/download/v1.14.0/level-zero-sdk_1.14.0.zip
-curl -k -L %XPU_EXTRA_LZ_URL% --output "%SRC_DIR%\temp_build\level_zero_sdk.zip"
-echo "Installing level zero SDK..."
-7z x "%SRC_DIR%\temp_build\level_zero_sdk.zip" -o"%SRC_DIR%\temp_build\level_zero"
-set "INCLUDE=%SRC_DIR%\temp_build\level_zero\include;%INCLUDE%"
-del "%SRC_DIR%\temp_build\level_zero_sdk.zip"
-
-:install_end

.ci/pytorch/win-test.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-set -ex -o pipefail
+set -ex
 
 SCRIPT_PARENT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )
 # shellcheck source=./common.sh
@@ -18,9 +18,6 @@ export PYTORCH_FINAL_PACKAGE_DIR="${PYTORCH_FINAL_PACKAGE_DIR:-/c/w/build-result
 PYTORCH_FINAL_PACKAGE_DIR_WIN=$(cygpath -w "${PYTORCH_FINAL_PACKAGE_DIR}")
 export PYTORCH_FINAL_PACKAGE_DIR_WIN
 
-# enable debug asserts in serialization
-export TORCH_SERIALIZATION_DEBUG=1
-
 mkdir -p "$TMP_DIR"/build/torch
 
 export SCRIPT_HELPERS_DIR=$SCRIPT_PARENT_DIR/win-test-helpers
@@ -38,13 +35,13 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
 fi
 
 # TODO: Move both of them to Windows AMI
-python -m pip install pytest-rerunfailures==10.3 pytest-cpp==2.3.0 tensorboard==2.13.0 pytest-subtests==0.13.1
+python -m pip install pytest-rerunfailures==10.3 pytest-cpp==2.3.0 tensorboard==2.13.0
 
 # Install Z3 optional dependency for Windows builds.
 python -m pip install z3-solver==4.12.2.0
 
 # Install tlparse for test\dynamo\test_structured_trace.py UTs.
-python -m pip install tlparse==0.3.30
+python -m pip install tlparse==0.3.25
 
 # Install parameterized
 python -m pip install parameterized==0.8.1

.ci/pytorch/windows/arm64/bootstrap_apl.bat

@@ -1,31 +0,0 @@
-@echo off
-
-echo Dependency ARM Performance Libraries (APL) installation started.
-
-:: Pre-check for downloads and dependencies folders
-if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
-if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
-
-:: Set download URL for the ARM Performance Libraries (APL)
-set DOWNLOAD_URL="https://developer.arm.com/-/cdn-downloads/permalink/Arm-Performance-Libraries/Version_24.10/arm-performance-libraries_24.10_Windows.msi"
-set INSTALLER_FILE=%DOWNLOADS_DIR%\arm-performance-libraries.msi
-
-:: Download installer
-echo Downloading ARM Performance Libraries (APL)...
-curl -L -o "%INSTALLER_FILE%" %DOWNLOAD_URL%
-
-:: Install ARM Performance Libraries (APL)
-echo Installing ARM Performance Libraries (APL)...
-msiexec /i "%INSTALLER_FILE%" /qn /norestart ACCEPT_EULA=1 INSTALLFOLDER="%DEPENDENCIES_DIR%"
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed to install ARM Performance Libraries (APL) components. (exitcode = %errorlevel%)"
-    exit /b 1
-)
-
-:: Add to environment
-echo ARMPL_DIR=%DEPENDENCIES_DIR%\armpl_24.10\>> %GITHUB_ENV%
-echo %DEPENDENCIES_DIR%\armpl_24.10\bin\>> %GITHUB_PATH%
-
-echo Dependency ARM Performance Libraries (APL) installation finished.

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

@@ -1,41 +0,0 @@
-@echo off
-
-echo Dependency MSVC Build Tools with C++ with ARM64/ARM64EC components installation started.
-
-:: Pre-check for downloads and dependencies folders
-if not exist "%DOWNLOADS_DIR%" mkdir "%DOWNLOADS_DIR%"
-if not exist "%DEPENDENCIES_DIR%" mkdir "%DEPENDENCIES_DIR%"
-
-:: Set download URL for the Visual Studio Installer
-set DOWNLOAD_URL=https://aka.ms/vs/17/release/vs_BuildTools.exe
-set INSTALLER_FILE=%DOWNLOADS_DIR%\vs_BuildTools.exe
-
-:: Download installer
-echo Downloading Visual Studio Build Tools with C++ installer...
-curl -L -o "%INSTALLER_FILE%" %DOWNLOAD_URL%
-
-:: Install the Visual Studio Build Tools with C++ components
-echo Installing Visual Studio Build Tools with C++ components...
-echo Installing MSVC %MSVC_VERSION%
-"%INSTALLER_FILE%" --norestart --quiet --wait --installPath "%DEPENDENCIES_DIR%\VSBuildTools" ^
-    --add Microsoft.VisualStudio.Workload.VCTools ^
-    --add Microsoft.VisualStudio.Component.Windows10SDK ^
-    --add Microsoft.VisualStudio.Component.Windows11SDK.22621 ^
-    --add Microsoft.VisualStudio.Component.VC.ASAN ^
-    --add Microsoft.VisualStudio.Component.VC.CMake.Project ^
-    --add Microsoft.VisualStudio.Component.VC.CoreBuildTools ^
-    --add Microsoft.VisualStudio.Component.VC.CoreIde ^
-    --add Microsoft.VisualStudio.Component.VC.Redist.14.Latest ^
-    --add Microsoft.VisualStudio.Component.VC.Tools.ARM64EC ^
-    --add Microsoft.VisualStudio.Component.VC.Tools.ARM64 ^
-    --add Microsoft.VisualStudio.Component.VC.Tools.x86.x64
-
-echo exitcode = %errorlevel%
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo Failed to install Visual Studio Build Tools with C++ components.
-    exit /b 1
-)
-
-echo Dependency Visual Studio Build Tools with C++ installation finished.

.ci/pytorch/windows/arm64/bootstrap_git.bat

@@ -1,37 +0,0 @@
-:: we need to install newer version of Git manually as "-submodules" function is not supported in the default version of runner.
-
-@echo off
-
-echo Dependency Git installation started.
-
-:: Pre-check for downloads and dependencies folders
-if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
-if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
-
-:: Set download URL for the Git
-set DOWNLOAD_URL="https://github.com/git-for-windows/git/releases/download/v2.46.0.windows.1/Git-2.46.0-64-bit.exe"
-set INSTALLER_FILE=%DOWNLOADS_DIR%\Git-2.46.0-64-bit.exe
-
-:: Download installer
-echo Downloading Git...
-curl -L -o "%INSTALLER_FILE%" %DOWNLOAD_URL%
-
-:: Install Git
-echo Installing Git...
-"%INSTALLER_FILE%" /VERYSILENT /DIR="%DEPENDENCIES_DIR%\git"
-
-dir %DEPENDENCIES_DIR%\git
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed to install Git. (exitcode = %errorlevel%)"
-    exit /b 1
-)
-
-:: Enable long paths
-call "%DEPENDENCIES_DIR%\git\cmd\git.exe" config --system core.longpaths true
-
-:: Add to PATH
-echo %DEPENDENCIES_DIR%\git\cmd\;%DEPENDENCIES_DIR%\git\bin\>> %GITHUB_PATH%
-
-echo Dependency Git installation finished.

.ci/pytorch/windows/arm64/bootstrap_libuv.bat

@@ -1,33 +0,0 @@
-@echo off
-
-echo Dependency libuv installation started.
-
-:: Pre-check for downloads and dependencies folders
-if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
-if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
-
-:: activate visual studio
-call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
-where cl.exe
-
-cd %DEPENDENCIES_DIR%
-git clone https://github.com/libuv/libuv.git -b v1.39.0
-
-echo Configuring libuv...
-mkdir libuv\build
-cd libuv\build
-cmake .. -DBUILD_TESTING=OFF
-
-echo Building libuv...
-cmake --build . --config Release
-
-echo Installing libuv...
-cmake --install . --prefix ../install
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed to install libuv. (exitcode = %errorlevel%)"
-    exit /b 1
-)
-
-echo Dependency libuv installation finished.

.ci/pytorch/windows/arm64/bootstrap_openblas.bat

@@ -1,46 +0,0 @@
-@echo off
-
-echo Dependency OpenBLAS installation started.
-
-:: Pre-check for downloads and dependencies folders
-if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
-if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
-
-:: activate visual studio
-call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
-where cl.exe
-
-:: Clone OpenBLAS
-cd %DEPENDENCIES_DIR%
-git clone https://github.com/OpenMathLib/OpenBLAS.git -b v0.3.29
-
-echo Configuring OpenBLAS...
-mkdir OpenBLAS\build
-cd OpenBLAS\build
-cmake .. -G Ninja ^
-  -DBUILD_TESTING=0 ^
-  -DBUILD_BENCHMARKS=0 ^
-  -DC_LAPACK=1 ^
-  -DNOFORTRAN=1 ^
-  -DDYNAMIC_ARCH=0 ^
-  -DARCH=arm64 ^
-  -DBINARY=64 ^
-  -DTARGET=GENERIC ^
-  -DUSE_OPENMP=1 ^
-  -DCMAKE_SYSTEM_PROCESSOR=ARM64 ^
-  -DCMAKE_SYSTEM_NAME=Windows ^
-  -DCMAKE_BUILD_TYPE=Release
-
-echo Building OpenBLAS...
-cmake --build . --config Release
-
-echo Installing OpenBLAS...
-cmake --install . --prefix ../install
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed to install OpenBLAS. (exitcode = %errorlevel%)"
-    exit /b 1
-)
-
-echo Dependency OpenBLAS installation finished.

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

@@ -1,44 +0,0 @@
-@echo off
-
-echo Dependency Python installation started.
-
-:: Pre-check for downloads and dependencies folders
-if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
-if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
-
-if "%DESIRED_PYTHON%" == "3.13" (
-    echo Python version is set to 3.13
-    set DOWNLOAD_URL=https://www.python.org/ftp/python/3.13.2/python-3.13.2-arm64.exe
-) else if "%DESIRED_PYTHON%" == "3.12" (
-    echo Python version is set to 3.12
-    set DOWNLOAD_URL=https://www.python.org/ftp/python/3.12.7/python-3.12.7-arm64.exe
-) else if "%DESIRED_PYTHON%" == "3.11" (
-    echo Python version is set to 3.11
-    set DOWNLOAD_URL=https://www.python.org/ftp/python/3.11.9/python-3.11.9-arm64.exe
-) else (
-    echo DESIRED_PYTHON not defined, Python version is set to 3.12
-    set DOWNLOAD_URL=https://www.python.org/ftp/python/3.12.7/python-3.12.7-arm64.exe
-)
-
-set INSTALLER_FILE=%DOWNLOADS_DIR%\python-installer.exe
-
-:: Download installer
-echo Downloading Python...
-curl -L -o "%INSTALLER_FILE%" "%DOWNLOAD_URL%"
-
-:: Install Python
-echo Installing Python...
-"%INSTALLER_FILE%" /quiet Include_debug=1 TargetDir="%DEPENDENCIES_DIR%\Python"
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed to install Python. (exitcode = %errorlevel%)"
-    exit /b 1
-)
-
-:: Add to PATH
-echo %DEPENDENCIES_DIR%\Python\>> %GITHUB_PATH%
-echo %DEPENDENCIES_DIR%\Python\scripts\>> %GITHUB_PATH%
-echo %DEPENDENCIES_DIR%\Python\libs\>> %GITHUB_PATH%
-
-echo Dependency Python installation finished.

.ci/pytorch/windows/arm64/bootstrap_rust.bat

@@ -1,33 +0,0 @@
-@echo off
-
-echo Dependency Rust installation started.
-
-:: Pre-check for downloads and dependencies folders
-if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
-if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
-
-set DOWNLOAD_URL="https://static.rust-lang.org/rustup/dist/x86_64-pc-windows-msvc/rustup-init.exe"
-set INSTALLER_FILE=%DOWNLOADS_DIR%\rustup-init.exe
-set RUSTUP_HOME=%DEPENDENCIES_DIR%\rust
-set CARGO_HOME=%DEPENDENCIES_DIR%\cargo
-
-:: Download installer
-echo Downloading Rust...
-curl -L -o "%INSTALLER_FILE%" %DOWNLOAD_URL%
-
-:: Install APL
-echo Installing Rust...
-"%INSTALLER_FILE%" -q -y --default-host aarch64-pc-windows-msvc --default-toolchain stable --profile default
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed to install Rust. (exitcode = %errorlevel%)"
-    exit /b 1
-)
-
-:: Add to PATH
-echo %DEPENDENCIES_DIR%\cargo\bin\>> %GITHUB_PATH%
-echo RUSTUP_HOME=%DEPENDENCIES_DIR%\rust>> %GITHUB_ENV%
-echo CARGO_HOME=%DEPENDENCIES_DIR%\cargo>> %GITHUB_ENV%
-
-echo Dependency Rust installation finished.

.ci/pytorch/windows/arm64/bootstrap_sccache.bat

@@ -1,33 +0,0 @@
-@echo off
-
-echo Dependency sccache installation started.
-
-:: Pre-check for downloads and dependencies folders
-if not exist "%DOWNLOADS_DIR%" mkdir %DOWNLOADS_DIR%
-if not exist "%DEPENDENCIES_DIR%" mkdir %DEPENDENCIES_DIR%
-
-:: Set download URL for the sccache
-set DOWNLOAD_URL="https://github.com/mozilla/sccache/releases/download/v0.8.1/sccache-v0.8.1-x86_64-pc-windows-msvc.zip"
-set INSTALLER_FILE=%DOWNLOADS_DIR%\sccache.zip
-
-:: Download installer
-echo Downloading sccache.zip...
-curl -L -o "%INSTALLER_FILE%" %DOWNLOAD_URL%
-
-:: Install sccache
-echo Extracting sccache.zip...
-tar -xf "%INSTALLER_FILE%" -C %DEPENDENCIES_DIR%
-cd %DEPENDENCIES_DIR%
-ren sccache-v0.8.1-x86_64-pc-windows-msvc sccache
-cd ..
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed to install sccache. (exitcode = %errorlevel%)"
-    exit /b 1
-)
-
-:: Add to PATH
-echo %DEPENDENCIES_DIR%\sccache\>> %GITHUB_PATH%
-
-echo Dependency sccache installation finished.