Trying to reduce flash-deps

ghstack-source-id: 8ba7b23dfde594e126977930e54395405573a598
Pull Request resolved: https://github.com/pytorch/pytorch/pull/144120

.ci/aarch64_linux/aarch64_ci_build.sh

@@ -3,12 +3,6 @@ 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
 
@@ -20,7 +14,7 @@ cd /
 # on the mounted pytorch repo
 git config --global --add safe.directory /pytorch
 pip install -r /pytorch/requirements.txt
-pip install auditwheel==6.2.0
+pip install auditwheel
 if [ "$DESIRED_CUDA" = "cpu" ]; then
     echo "BASE_CUDA_VERSION is not set. Building cpu wheel."
     #USE_PRIORITIZED_TEXT_FOR_LD for enable linker script optimization https://github.com/pytorch/pytorch/pull/121975/files

.ci/aarch64_linux/aarch64_ci_setup.sh

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

.ci/aarch64_linux/aarch64_wheel_ci_build.py

@@ -4,9 +4,12 @@
 import os
 import shutil
 from subprocess import check_call, check_output
+from typing import List
+
+from pygit2 import Repository
 
 
-def list_dir(path: str) -> list[str]:
+def list_dir(path: str) -> List[str]:
     """'
     Helper for getting paths for Python
     """
@@ -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.12.6",
         "/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",
@@ -136,9 +128,6 @@ def complete_wheel(folder: str) -> str:
     """
     wheel_name = list_dir(f"/{folder}/dist")[0]
 
-    # Please note for cuda we don't run auditwheel since we use custom script to package
-    # the cuda dependencies to the wheel file using update_wheel() method.
-    # However we need to make sure filename reflects the correct Manylinux platform.
     if "pytorch" in folder and not enable_cuda:
         print("Repairing Wheel with AuditWheel")
         check_call(["auditwheel", "repair", f"dist/{wheel_name}"], cwd=folder)
@@ -150,14 +139,7 @@ def complete_wheel(folder: str) -> str:
             f"/{folder}/dist/{repaired_wheel_name}",
         )
     else:
-        repaired_wheel_name = wheel_name.replace(
-            "linux_aarch64", "manylinux_2_28_aarch64"
-        )
-        print(f"Renaming {wheel_name} wheel to {repaired_wheel_name}")
-        os.rename(
-            f"/{folder}/dist/{wheel_name}",
-            f"/{folder}/dist/{repaired_wheel_name}",
-        )
+        repaired_wheel_name = wheel_name
 
     print(f"Copying {repaired_wheel_name} to artifacts")
     shutil.copy2(
@@ -189,22 +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()
@@ -214,11 +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()
@@ -242,6 +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):
@@ -683,7 +681,7 @@ 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 +708,7 @@ 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 +759,7 @@ 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 +932,9 @@ 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 +964,7 @@ 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 @@
+0.8b
+manylinux_2_28
+rocm6.2
+6f8cbcac8a92775291bb1ba8f514d4beb350baf4
+e938def5d32869fe2e00aec0300f354c9f157867bebdf2e104d732b94cb238d8

.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
 
@@ -90,20 +86,30 @@ 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=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.1.1
+    CUDNN_VERSION=9
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
@@ -128,6 +134,36 @@ case "$image" in
     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=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
+    TRITON=yes
+    INDUCTOR_BENCHMARKS=yes
+    ;;
   pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
     CUDA_VERSION=12.4.1
     CUDNN_VERSION=9
@@ -158,65 +194,6 @@ case "$image" in
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.12
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
-  pytorch-linux-focal-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6.3
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.13
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    INDUCTOR_BENCHMARKS=yes
-    ;;
   pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
     CUDA_VERSION=11.8.0
     CUDNN_VERSION=9
@@ -231,6 +208,20 @@ case "$image" in
     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-py3-clang10-onnx)
     ANACONDA_PYTHON_VERSION=3.9
     CLANG_VERSION=10
@@ -273,7 +264,18 @@ case "$image" in
     ;;
   pytorch-linux-focal-rocm-n-1-py3)
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
+    GCC_VERSION=9
+    PROTOBUF=yes
+    DB=yes
+    VISION=yes
+    ROCM_VERSION=6.1
+    NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-focal-rocm-n-py3)
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=9
     PROTOBUF=yes
     DB=yes
     VISION=yes
@@ -281,25 +283,6 @@ case "$image" in
     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
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    ROCM_VERSION=6.3
-    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
@@ -385,7 +368,7 @@ case "$image" in
     EXECUTORCH=yes
     ;;
   pytorch-linux-jammy-py3.12-halide)
-    CUDA_VERSION=12.6
+    CUDA_VERSION=12.4
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
     CONDA_CMAKE=yes
@@ -393,7 +376,7 @@ case "$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
@@ -514,7 +497,7 @@ 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=${PYTORCH_ROCM_ARCH:-gfx90a}" \
        --build-arg "IMAGE_NAME=${IMAGE_NAME}" \
        --build-arg "UCX_COMMIT=${UCX_COMMIT}" \
        --build-arg "UCC_COMMIT=${UCC_COMMIT}" \

.ci/docker/centos-rocm/Dockerfile

@@ -113,6 +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 @@
-01a22b6f16d117454b7d21ebdc691b0785b84a7f
+a29b208a06ab378bb29ab1aa68932e412f8e09f1

.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 @@
-0bcc8265e677e5321606a3311bf71470f14456a8
+e98b6fcb8df5b44eb0d0addb6767c573d37ba024

.ci/docker/ci_commit_pins/triton.txt

@@ -1 +1 @@
-96316ce50fade7e209553aba4898cd9b82aab83b
+0d4682f073ded4d1a8260dd4208a43d735ae3a2b

.ci/docker/common/install_acl.sh

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

.ci/docker/common/install_aotriton.sh

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

.ci/docker/common/install_base.sh

@@ -32,12 +32,8 @@ install_ubuntu() {
 
   # HACK: UCC testing relies on libnccl library from NVIDIA repo, and version 2.16 crashes
   # See https://github.com/pytorch/pytorch/pull/105260#issuecomment-1673399729
-  # TODO: Eliminate this hack, we should not relay on apt-get installation
-  # See https://github.com/pytorch/pytorch/issues/144768
   if [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "11.8"* ]]; then
     maybe_libnccl_dev="libnccl2=2.15.5-1+cuda11.8 libnccl-dev=2.15.5-1+cuda11.8 --allow-downgrades --allow-change-held-packages"
-  elif [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "12.4"* ]]; then
-    maybe_libnccl_dev="libnccl2=2.26.2-1+cuda12.4 libnccl-dev=2.26.2-1+cuda12.4 --allow-downgrades --allow-change-held-packages"
   else
     maybe_libnccl_dev=""
   fi

.ci/docker/common/install_cache.sh

@@ -9,7 +9,7 @@ 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
+  git clone https://github.com/mozilla/sccache -b v0.9.0
   cd sccache
   echo "Building sccache"
   cargo build --release

.ci/docker/common/install_conda.sh

@@ -66,7 +66,7 @@ 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==0.3.28=*openmp*"
   else
     conda_install "mkl=2021.4.0 mkl-include=2021.4.0"
   fi

.ci/docker/common/install_cuda.sh

@@ -2,7 +2,7 @@
 
 set -ex
 
-NCCL_VERSION=v2.26.2-1
+NCCL_VERSION=v2.21.5-1
 CUDNN_VERSION=9.5.1.17
 
 function install_cusparselt_040 {
@@ -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
@@ -40,7 +51,6 @@ function install_cusparselt_063 {
 
 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
@@ -73,6 +83,39 @@ 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"
@@ -171,6 +214,37 @@ function prune_118 {
     rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.3.0 $CUDA_BASE/nsight-systems-2022.4.2/
 }
 
+function prune_121 {
+  echo "Pruning CUDA 12.1"
+  #####################################################################################
+  # CUDA 12.1 prune static libs
+  #####################################################################################
+    export NVPRUNE="/usr/local/cuda-12.1/bin/nvprune"
+    export CUDA_LIB_DIR="/usr/local/cuda-12.1/lib64"
+
+    export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+    export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+
+    if [[ -n "$OVERRIDE_GENCODE" ]]; then
+        export GENCODE=$OVERRIDE_GENCODE
+    fi
+
+    # all CUDA libs except CuDNN and CuBLAS
+    ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
+      | xargs -I {} bash -c \
+                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
+
+    # prune CuDNN and CuBLAS
+    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
+    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
+
+    #####################################################################################
+    # CUDA 12.1 prune visual tools
+    #####################################################################################
+    export CUDA_BASE="/usr/local/cuda-12.1/"
+    rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2023.1.0 $CUDA_BASE/nsight-systems-2023.1.2/
+}
+
 function prune_124 {
   echo "Pruning CUDA 12.4"
   #####################################################################################
@@ -239,52 +313,18 @@ function prune_126 {
   rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.3.2 $CUDA_BASE/nsight-systems-2024.5.1/
 }
 
-function install_128 {
-  CUDNN_VERSION=9.7.1.26
-  echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
-  rm -rf /usr/local/cuda-12.8 /usr/local/cuda
-  # install CUDA 12.8.0 in the same container
-  wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux.run
-  chmod +x cuda_12.8.0_570.86.10_linux.run
-  ./cuda_12.8.0_570.86.10_linux.run --toolkit --silent
-  rm -f cuda_12.8.0_570.86.10_linux.run
-  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.8 /usr/local/cuda
-
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  mkdir tmp_cudnn && cd tmp_cudnn
-  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${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

@@ -3,8 +3,19 @@
 
 set -ex
 
-NCCL_VERSION=v2.26.2-1
-CUDNN_VERSION=9.8.0.87
+NCCL_VERSION=v2.21.5-1
+CUDNN_VERSION=9.5.1.17
+
+function install_cusparselt_062 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-sbsa/libcusparse_lt-linux-sbsa-0.6.2.3-archive.tar.xz
+    tar xf libcusparse_lt-linux-sbsa-0.6.2.3-archive.tar.xz
+    cp -a libcusparse_lt-linux-sbsa-0.6.2.3-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-sbsa-0.6.2.3-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
 
 function install_cusparselt_063 {
     # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
@@ -17,15 +28,80 @@ function install_cusparselt_063 {
     rm -rf tmp_cusparselt
 }
 
-function install_128 {
-  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
+function install_124 {
+  CUDNN_VERSION=9.1.0.70
+  echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.2"
+  rm -rf /usr/local/cuda-12.4 /usr/local/cuda
+  # install CUDA 12.4.1 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux_sbsa.run
+  chmod +x cuda_12.4.1_550.54.15_linux_sbsa.run
+  ./cuda_12.4.1_550.54.15_linux_sbsa.run --toolkit --silent
+  rm -f cuda_12.4.1_550.54.15_linux_sbsa.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
+
+  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-sbsa/cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
+
+  # NCCL license: https://docs.nvidia.com/deeplearning/nccl/#licenses
+  # Follow build: https://github.com/NVIDIA/nccl/tree/master?tab=readme-ov-file#build
+  git clone -b ${NCCL_VERSION} --depth 1 https://github.com/NVIDIA/nccl.git
+  cd nccl && make -j src.build
+  cp -a build/include/* /usr/local/cuda/include/
+  cp -a build/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf nccl
+
+  install_cusparselt_062
+
+  ldconfig
+}
+
+function prune_124 {
+  echo "Pruning CUDA 12.4"
+  #####################################################################################
+  # CUDA 12.4 prune static libs
+  #####################################################################################
+  export NVPRUNE="/usr/local/cuda-12.4/bin/nvprune"
+  export CUDA_LIB_DIR="/usr/local/cuda-12.4/lib64"
+
+  export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+  export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+
+  if [[ -n "$OVERRIDE_GENCODE" ]]; then
+      export GENCODE=$OVERRIDE_GENCODE
+  fi
+
+  # all CUDA libs except CuDNN and CuBLAS
+  ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
+      | xargs -I {} bash -c \
+                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
+
+  # prune CuDNN and CuBLAS
+  $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
+  $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
+
+  #####################################################################################
+  # CUDA 12.4 prune visual tools
+  #####################################################################################
+  export CUDA_BASE="/usr/local/cuda-12.4/"
+  rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.1.0 $CUDA_BASE/nsight-systems-2023.4.4/
+}
+
+function install_126 {
+  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL ${NCCL_VERSION} and cuSparseLt-0.6.3"
+  rm -rf /usr/local/cuda-12.6 /usr/local/cuda
+  # install CUDA 12.6.3 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux_sbsa.run
+  chmod +x cuda_12.6.3_560.35.05_linux_sbsa.run
+  ./cuda_12.6.3_560.35.05_linux_sbsa.run --toolkit --silent
+  rm -f cuda_12.6.3_560.35.05_linux_sbsa.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.6 /usr/local/cuda
 
   # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
   mkdir tmp_cudnn && cd tmp_cudnn
@@ -50,11 +126,47 @@ function install_128 {
   ldconfig
 }
 
+function prune_126 {
+  echo "Pruning CUDA 12.6"
+  #####################################################################################
+  # CUDA 12.6 prune static libs
+  #####################################################################################
+  export NVPRUNE="/usr/local/cuda-12.6/bin/nvprune"
+  export CUDA_LIB_DIR="/usr/local/cuda-12.6/lib64"
+
+  export GENCODE="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+  export GENCODE_CUDNN="-gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+
+  if [[ -n "$OVERRIDE_GENCODE" ]]; then
+      export GENCODE=$OVERRIDE_GENCODE
+  fi
+  if [[ -n "$OVERRIDE_GENCODE_CUDNN" ]]; then
+      export GENCODE_CUDNN=$OVERRIDE_GENCODE_CUDNN
+  fi
+
+  # all CUDA libs except CuDNN and CuBLAS
+  ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
+      | xargs -I {} bash -c \
+                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
+
+  # prune CuDNN and CuBLAS
+  $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
+  $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
+
+  #####################################################################################
+  # CUDA 12.6 prune visual tools
+  #####################################################################################
+  export CUDA_BASE="/usr/local/cuda-12.6/"
+  rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2024.3.2 $CUDA_BASE/nsight-systems-2024.5.1/
+}
+
 # idiomatic parameter and option handling in sh
 while test $# -gt 0
 do
     case "$1" in
-    12.8) install_128;
+    12.4) install_124; prune_124
+        ;;
+    12.6) install_126; prune_126
         ;;
     *) echo "bad argument $1"; exit 1
         ;;

.ci/docker/common/install_cudnn.sh

@@ -4,9 +4,7 @@ if [[ -n "${CUDNN_VERSION}" ]]; then
     # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
     mkdir tmp_cudnn
     pushd tmp_cudnn
-    if [[ ${CUDA_VERSION:0:4} == "12.8" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-9.7.1.26_cuda12-archive"
-    elif [[ ${CUDA_VERSION:0:4} == "12.6" ]]; then
+    if [[ ${CUDA_VERSION:0:4} == "12.6" ]]; then
         CUDNN_NAME="cudnn-linux-x86_64-9.5.1.17_cuda12-archive"
     elif [[ ${CUDA_VERSION:0:2} == "12" ]]; then
         CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda12-archive"

.ci/docker/common/install_cusparselt.sh

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

.ci/docker/common/install_executorch.sh

@@ -37,12 +37,7 @@ 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
 }
 
@@ -53,7 +48,7 @@ setup_executorch() {
   export EXECUTORCH_BUILD_PYBIND=ON
   export CMAKE_ARGS="-DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
 
-  as_jenkins .ci/scripts/setup-linux.sh --build-tool cmake || true
+  as_jenkins .ci/scripts/setup-linux.sh cmake || true
   popd
 }
 

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

.ci/docker/common/install_openblas.sh

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

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

.ci/docker/common/install_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

@@ -47,9 +47,6 @@ function install_ubuntu() {
     # Development Packages
     apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev level-zero-dev
     # Install Intel Support Packages
-    if [[ "$XPU_VERSION" == "2025.0" ]]; then
-        XPU_PACKAGES="${XPU_PACKAGES} intel-oneapi-dnnl=2025.0.1-6"
-    fi
     apt-get install -y ${XPU_PACKAGES}
 
     # Cleanup
@@ -85,9 +82,6 @@ gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.
 EOF
 
     # Install Intel Support Packages
-    if [[ "$XPU_VERSION" == "2025.0" ]]; then
-        XPU_PACKAGES="${XPU_PACKAGES} intel-oneapi-dnnl-2025.0.1-6"
-    fi
     yum install -y ${XPU_PACKAGES}
     # The xpu-smi packages
     dnf install -y xpu-smi

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

.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_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/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)
@@ -97,7 +97,7 @@ case ${GPU_ARCH_TYPE} in
             DEVTOOLSET_VERSION="11"
             GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
         fi
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
+        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101"
         DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
         ;;
     xpu)
@@ -121,8 +121,7 @@ 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 +139,7 @@ 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

@@ -90,10 +90,10 @@ librosa>=0.6.2 ; python_version < "3.11"
 #Pinned versions:
 #test that import:
 
-mypy==1.14.0
+mypy==1.13.0
 # Pin MyPy version because new errors are likely to appear with each release
 #Description: linter
-#Pinned versions: 1.14.0
+#Pinned versions: 1.10.0
 #test that import: test_typing.py, test_type_hints.py
 
 networkx==2.8.8
@@ -294,7 +294,7 @@ ghstack==0.8.0
 #Pinned versions: 0.8.0
 #test that import:
 
-jinja2==3.1.6
+jinja2==3.1.5
 #Description: jinja2 template engine
 #Pinned versions: 3.1.4
 #test that import:
@@ -304,7 +304,7 @@ 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:
@@ -329,7 +329,7 @@ lxml==5.3.0
 
 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:
@@ -339,7 +339,7 @@ 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:
@@ -362,7 +362,6 @@ pwlf==2.2.1 ; python_version >= "3.8"
 # To build PyTorch itself
 astunparse
 PyYAML
-pyzstd
 setuptools
 
 ninja==1.11.1 ; platform_machine == "aarch64"
@@ -372,8 +371,3 @@ 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/triton_version.txt

@@ -1 +1 @@
-3.3.1
+3.2.0

.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
@@ -89,32 +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 "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
-RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
-
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
 COPY ./common/install_cmake.sh install_cmake.sh
@@ -137,17 +107,24 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${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
+
+# This is needed by sccache
+COPY ./common/install_openssl.sh install_openssl.sh
+ENV OPENSSL_ROOT_DIR /opt/openssl
+RUN bash ./install_openssl.sh
+ENV OPENSSL_DIR /opt/openssl
 
 # 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/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_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 "$CMAKE_ARGS" ]]; then
@@ -53,15 +52,23 @@ cuda_version_nodot=$(echo $CUDA_VERSION | tr -d '.')
 
 TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;7.5;8.0;8.6"
 case ${CUDA_VERSION} in
-    12.8)
-        TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;12.0+PTX" #removing sm_50-sm_70 as these architectures are deprecated in CUDA 12.8 and will be removed in future releases
-        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
-        ;;
     12.6)
-        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
+        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")
         ;;
     12.4)
+        if [[ "$GPU_ARCH_TYPE" = "cuda-aarch64" ]]; then
+            TORCH_CUDA_ARCH_LIST="9.0"
+        else
+            TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
+        fi
+        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
+        ;;
+    12.1)
         TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
@@ -119,16 +126,7 @@ 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 +167,6 @@ 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 +183,6 @@ 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'

.ci/manywheel/build_rocm.sh

@@ -186,6 +186,15 @@ do
     OS_SO_FILES[${#OS_SO_FILES[@]}]=$file_name # Append lib to array
 done
 
+# FIXME: Temporary until https://github.com/pytorch/pytorch/pull/137443 lands
+# Install AOTriton
+if [ -e ${PYTORCH_ROOT}/.ci/docker/aotriton_version.txt ]; then
+    cp -a ${PYTORCH_ROOT}/.ci/docker/aotriton_version.txt aotriton_version.txt
+    bash ${PYTORCH_ROOT}/.ci/docker/common/install_aotriton.sh ${ROCM_HOME} && rm aotriton_version.txt
+    export AOTRITON_INSTALLED_PREFIX=${ROCM_HOME}/aotriton
+    ROCM_SO_FILES+=("libaotriton_v2.so")
+fi
+
 # rocBLAS library files
 ROCBLAS_LIB_SRC=$ROCM_HOME/lib/rocblas/library
 ROCBLAS_LIB_DST=lib/rocblas/library
@@ -257,6 +266,20 @@ RCCL_SHARE_FILES=($(ls $RCCL_SHARE_SRC))
 DEPS_AUX_SRCLIST+=(${RCCL_SHARE_FILES[@]/#/$RCCL_SHARE_SRC/})
 DEPS_AUX_DSTLIST+=(${RCCL_SHARE_FILES[@]/#/$RCCL_SHARE_DST/})
 
+# PyTorch 2.6+ (AOTriton 0.8b+)
+# AKS = "AOTriton Kernel Storage", a file format to store GPU kernels compactly
+if (( $(echo "${PYTORCH_VERSION} 2.6" | awk '{print ($1 >= $2)}') )); then
+    LIBAOTRITON_DIR=$(find "$ROCM_HOME/lib/" -name "libaotriton_v2.so" -printf '%h\n')
+    if [[ -z ${LIBAOTRITON_DIR} ]]; then
+        LIBAOTRITON_DIR=$(find "$ROCM_HOME/" -name "libaotriton_v2.so" -printf '%h\n')
+    fi
+    AKS_FILES=($(find "${LIBAOTRITON_DIR}/aotriton.images" -type f -name '*.aks?' -printf '%P\n'))
+    AKS_SRC="${LIBAOTRITON_DIR}/aotriton.images"
+    AKS_DST="lib/aotriton.images"
+    DEPS_AUX_SRCLIST+=(${AKS_FILES[@]/#/${AKS_SRC}/})
+    DEPS_AUX_DSTLIST+=(${AKS_FILES[@]/#/${AKS_DST}/})
+fi
+
 echo "PYTORCH_ROCM_ARCH: ${PYTORCH_ROCM_ARCH}"
 
 SCRIPTPATH="$( cd "$(dirname "$0")" ; pwd -P )"

.ci/pytorch/build.sh

@@ -173,7 +173,6 @@ if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   source /opt/intel/oneapi/compiler/latest/env/vars.sh
   # XPU kineto feature dependencies are not fully ready, disable kineto build as temp WA
   export USE_KINETO=0
-  export TORCH_XPU_ARCH_LIST=pvc
 fi
 
 # sccache will fail for CUDA builds if all cores are used for compiling
@@ -192,7 +191,7 @@ fi
 
 # We only build FlashAttention files for CUDA 8.0+, and they require large amounts of
 # memory to build and will OOM
-if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ 1 -eq $(echo "${TORCH_CUDA_ARCH_LIST} >= 8.0" | bc) ]] && [ -z "$MAX_JOBS_OVERRIDE" ]; then
+if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ 1 -eq $(echo "${TORCH_CUDA_ARCH_LIST} >= 8.0" | bc) ]]; then
   echo "WARNING: FlashAttention files require large amounts of memory to build and will OOM"
   echo "Setting MAX_JOBS=(nproc-2)/3 to reduce memory usage"
   export MAX_JOBS="$(( $(nproc --ignore=2) / 3 ))"
@@ -229,7 +228,7 @@ if [[ "$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
   # Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
@@ -378,10 +377,8 @@ else
     # This is an attempt to mitigate flaky libtorch build OOM error. By default, the build parallelization
     # is set to be the number of CPU minus 2. So, let's try a more conservative value here. A 4xlarge has
     # 16 CPUs
-    if [ -z "$MAX_JOBS_OVERRIDE" ]; then
-      MAX_JOBS=$(nproc --ignore=4)
-      export MAX_JOBS
-    fi
+    MAX_JOBS=$(nproc --ignore=4)
+    export MAX_JOBS
 
     # NB: Install outside of source directory (at the same level as the root
     # pytorch folder) so that it doesn't get cleaned away prior to docker push.

.ci/pytorch/check_binary.sh

@@ -387,7 +387,7 @@ fi
 ###############################################################################
 # Check for C++ ABI compatibility between gcc7 and gcc9 compiled binaries
 ###############################################################################
-if [[ "$(uname)" == 'Linux' &&  "$PACKAGE_TYPE" == 'manywheel' ]]; then
+if [[ "$(uname)" == 'Linux' && ("$PACKAGE_TYPE" == 'conda' || "$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

.ci/pytorch/common_utils.sh

@@ -169,40 +169,30 @@ 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
 }
 
 function clone_pytorch_xla() {
   if [[ ! -d ./xla ]]; then
-    git clone --recursive -b r2.7 https://github.com/pytorch/xla.git
+    git clone --recursive --quiet https://github.com/pytorch/xla.git
     pushd xla
     # pin the xla hash so that we don't get broken by changes to xla
     git checkout "$(cat ../.github/ci_commit_pins/xla.txt)"
@@ -226,11 +216,6 @@ function checkout_install_torchbench() {
     # to install and test other models
     python install.py --continue_on_fail
   fi
-
-  # TODO (huydhn): transformers-4.44.2 added by https://github.com/pytorch/benchmark/pull/2488
-  # is regressing speedup metric. This needs to be investigated further
-  pip install transformers==4.38.1
-
   echo "Print all dependencies after TorchBench is installed"
   python -mpip freeze
   popd

.ci/pytorch/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

.ci/pytorch/run_tests.sh

@@ -40,7 +40,7 @@ retry () {
 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 PACKAGE_TYPE must be set to 'conda' or '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

.ci/pytorch/smoke_test/check_binary_symbols.py

@@ -6,7 +6,7 @@ import itertools
 import os
 import re
 from pathlib import Path
-from typing import Any
+from typing import Any, List, Tuple
 
 
 # We also check that there are [not] cxx11 symbols in libtorch
@@ -46,17 +46,17 @@ LIBTORCH_PRE_CXX11_PATTERNS = _apply_libtorch_symbols(PRE_CXX11_SYMBOLS)
 
 
 @functools.lru_cache(100)
-def get_symbols(lib: str) -> list[tuple[str, str, str]]:
+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(lib: str, patterns: List[Any]) -> List[str]:
     def _grep_symbols(
-        symbols: list[tuple[str, str, str]], patterns: list[Any]
-    ) -> list[str]:
+        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:

.ci/pytorch/smoke_test/max_autotune.py

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

.ci/pytorch/smoke_test/smoke_test.py

@@ -6,7 +6,6 @@ import re
 import subprocess
 import sys
 from pathlib import Path
-from tempfile import NamedTemporaryFile
 
 import torch
 import torch._dynamo
@@ -76,13 +75,10 @@ def read_release_matrix():
 
 
 def test_numpy():
-    try:
-        import numpy as np
+    import numpy as np
 
-        x = np.arange(5)
-        torch.tensor(x)
-    except ImportError:
-        print("Numpy check skipped. Numpy is not installed.")
+    x = np.arange(5)
+    torch.tensor(x)
 
 
 def check_version(package: str) -> None:
@@ -165,36 +161,6 @@ def test_cuda_runtime_errors_captured() -> None:
         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:
@@ -413,10 +379,8 @@ def main() -> None:
     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()

.ci/pytorch/test.sh

@@ -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 [[ "$BUILD_ENVIRONMENT" != *rocm* && -d /var/lib/jenkins/workspace ]]; then
   # Workaround for dind-rootless userid mapping (https://github.com/pytorch/ci-infra/issues/96)
   WORKSPACE_ORIGINAL_OWNER_ID=$(stat -c '%u' "/var/lib/jenkins/workspace")
   cleanup_workspace() {
@@ -46,9 +46,6 @@ 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
@@ -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" ]] || [[ "${CONTINUE_THROUGH_ERROR}" == "1" ]]; then
   # When rerunning disable tests, do not generate core dumps as it could consume
   # the runner disk space when crashed tests are run multiple times. Running out
@@ -177,9 +167,6 @@ if [[ "$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 +301,6 @@ 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
@@ -424,10 +404,7 @@ test_inductor_cpp_wrapper_shard() {
 
   # 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
+  python test/run_test.py --include inductor/test_torchinductor --verbose
 
   # Run inductor benchmark tests with cpp wrapper.
   # Skip benchmark tests if it's in rerun-disabled-mode.
@@ -440,7 +417,7 @@ 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 "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
@@ -450,7 +427,7 @@ test_inductor_cpp_wrapper_shard() {
       --bfloat16 --inference --inductor --only moco --output "$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 +460,6 @@ 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 +474,6 @@ 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 "$TEST_REPORTS_DIR"
@@ -580,10 +502,6 @@ test_perf_for_dashboard() {
     test_inductor_set_cpu_affinity
   elif [[ "${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 "${modes[@]}"; do
@@ -616,7 +534,7 @@ test_perf_for_dashboard() {
             --dynamic-batch-only "$@" \
             --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"
@@ -700,16 +618,16 @@ 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
 }
 
@@ -732,7 +650,7 @@ 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 +680,6 @@ 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 +714,7 @@ 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 +910,10 @@ 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
@@ -1173,9 +1079,8 @@ build_xla() {
   apply_patches
   SITE_PACKAGES="$(python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())')"
   # These functions are defined in .circleci/common.sh in pytorch/xla repo
-  retry install_pre_deps_pytorch_xla $XLA_DIR $USE_CACHE
+  retry install_deps_pytorch_xla $XLA_DIR $USE_CACHE
   CMAKE_PREFIX_PATH="${SITE_PACKAGES}/torch:${CMAKE_PREFIX_PATH}" XLA_SANDBOX_BUILD=1 build_torch_xla $XLA_DIR
-  retry install_post_deps_pytorch_xla
   assert_git_not_dirty
 }
 
@@ -1482,7 +1387,7 @@ test_executorch() {
   bash examples/models/llama3_2_vision/install_requirements.sh
   # NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
   # from the PR
-  bash .ci/scripts/setup-linux.sh --build-tool cmake
+  bash .ci/scripts/setup-linux.sh cmake
 
   echo "Run ExecuTorch unit tests"
   pytest -v -n auto
@@ -1506,7 +1411,7 @@ test_executorch() {
 test_linux_aarch64() {
   python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
         test_transformers test_multiprocessing test_numpy_interop test_autograd test_binary_ufuncs test_complex test_spectral_ops \
-        test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
+        test_foreach test_reductions test_unary_ufuncs \
         --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 
   # Dynamo tests
@@ -1574,16 +1479,6 @@ 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 [[ "${TEST_CONFIG}" == *cpu* ]]; then
     install_torchaudio cpu
@@ -1639,7 +1534,6 @@ elif [[ "${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/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_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/win-test.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

.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.

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

@@ -1,22 +0,0 @@
-:: change to source directory
-cd %PYTORCH_ROOT%
-
-:: activate visual studio
-call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
-where cl.exe
-
-:: create virtual environment
-python -m venv .venv
-echo * > .venv\.gitignore
-call .\.venv\Scripts\activate
-where python
-
-:: install dependencies
-python -m pip install --upgrade pip
-pip install -r requirements.txt
-pip install pytest numpy protobuf expecttest hypothesis
-
-:: find file name for pytorch wheel
-for /f "delims=" %%f in ('dir /b "%PYTORCH_FINAL_PACKAGE_DIR%" ^| findstr "torch-"') do set "TORCH_WHEEL_FILENAME=%PYTORCH_FINAL_PACKAGE_DIR%\%%f"
-
-pip install %TORCH_WHEEL_FILENAME%

.ci/pytorch/windows/arm64/build_libtorch.bat

@@ -1,101 +0,0 @@
-@echo on
-
-:: environment variables
-set CMAKE_BUILD_TYPE=%BUILD_TYPE%
-set CMAKE_C_COMPILER_LAUNCHER=sccache
-set CMAKE_CXX_COMPILER_LAUNCHER=sccache
-set libuv_ROOT=%DEPENDENCIES_DIR%\libuv\install
-set MSSdk=1
-if defined PYTORCH_BUILD_VERSION (
-  set PYTORCH_BUILD_VERSION=%PYTORCH_BUILD_VERSION%
-  set PYTORCH_BUILD_NUMBER=1
-)
-
-:: Set BLAS type
-if %ENABLE_APL% == 1 (
-    set BLAS=APL
-    set USE_LAPACK=1
-) else if %ENABLE_OPENBLAS% == 1 (
-    set BLAS=OpenBLAS
-    set OpenBLAS_HOME=%DEPENDENCIES_DIR%\OpenBLAS\install
-)
-
-:: activate visual studio
-call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
-where cl.exe
-
-:: change to source directory
-cd %PYTORCH_ROOT%
-
-:: copy libuv.dll
-copy %libuv_ROOT%\lib\Release\uv.dll torch\lib\uv.dll
-
-:: create virtual environment
-python -m venv .venv
-echo * > .venv\.gitignore
-call .\.venv\Scripts\activate
-where python
-
-:: python install dependencies
-python -m pip install --upgrade pip
-pip install -r requirements.txt
-:: DISTUTILS_USE_SDK should be set after psutil dependency
-set DISTUTILS_USE_SDK=1
-
-:: start sccache server and reset sccache stats
-sccache --start-server
-sccache --zero-stats
-sccache --show-stats
- 
-:: Prepare the environment
-mkdir libtorch
-mkdir libtorch\bin
-mkdir libtorch\cmake
-mkdir libtorch\include
-mkdir libtorch\lib
-mkdir libtorch\share
-mkdir libtorch\test
-
-:: Call LibTorch build script
-python ./tools/build_libtorch.py
-
-:: Check if there is an error
-IF ERRORLEVEL 1 exit /b 1
-IF NOT ERRORLEVEL 0 exit /b 1
- 
-:: Move the files to the correct location
-move /Y torch\bin\*.* libtorch\bin\
-move /Y torch\cmake\*.* libtorch\cmake\
-robocopy /move /e torch\include\ libtorch\include\
-move /Y torch\lib\*.* libtorch\lib\
-robocopy /move /e torch\share\ libtorch\share\
-move /Y torch\test\*.* libtorch\test\
-move /Y libtorch\bin\*.dll libtorch\lib\
-
-:: Set version
-echo %PYTORCH_BUILD_VERSION% > libtorch\build-version
-git rev-parse HEAD > libtorch\build-hash
-
-:: Set LIBTORCH_PREFIX
-IF "%DEBUG%" == "" (
-    set LIBTORCH_PREFIX=libtorch-win-arm64-shared-with-deps
-) ELSE (
-    set LIBTORCH_PREFIX=libtorch-win-arm64-shared-with-deps-debug
-)
-
-:: Create output
-C:\Windows\System32\tar.exe -cvaf %LIBTORCH_PREFIX%-%PYTORCH_BUILD_VERSION%.zip -C libtorch *
-
-:: Copy output to target directory
-if not exist ..\output mkdir ..\output
-copy /Y "%LIBTORCH_PREFIX%-%PYTORCH_BUILD_VERSION%.zip" "%PYTORCH_FINAL_PACKAGE_DIR%\"
-copy /Y "%LIBTORCH_PREFIX%-%PYTORCH_BUILD_VERSION%.zip" "%PYTORCH_FINAL_PACKAGE_DIR%\%LIBTORCH_PREFIX%-latest.zip"
-
-:: Cleanup raw data to save space
-rmdir /s /q libtorch
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed on build_libtorch. (exitcode = %errorlevel%)"
-    exit /b 1
-)

.ci/pytorch/windows/arm64/build_pytorch.bat

@@ -1,60 +0,0 @@
-@echo on
-
-:: environment variables
-set CMAKE_BUILD_TYPE=%BUILD_TYPE%
-set CMAKE_C_COMPILER_LAUNCHER=sccache
-set CMAKE_CXX_COMPILER_LAUNCHER=sccache
-set libuv_ROOT=%DEPENDENCIES_DIR%\libuv\install
-set MSSdk=1
-if defined PYTORCH_BUILD_VERSION (
-  set PYTORCH_BUILD_VERSION=%PYTORCH_BUILD_VERSION%
-  set PYTORCH_BUILD_NUMBER=1
-)
-
-:: Set BLAS type
-if %ENABLE_APL% == 1 (
-    set BLAS=APL
-    set USE_LAPACK=1
-) else if %ENABLE_OPENBLAS% == 1 (
-    set BLAS=OpenBLAS
-    set OpenBLAS_HOME=%DEPENDENCIES_DIR%\OpenBLAS\install
-)
-
-:: activate visual studio
-call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
-where cl.exe
-
-:: change to source directory
-cd %PYTORCH_ROOT%
-
-:: copy libuv.dll
-copy %libuv_ROOT%\lib\Release\uv.dll torch\lib\uv.dll
-
-:: create virtual environment
-python -m venv .venv
-echo * > .venv\.gitignore
-call .\.venv\Scripts\activate
-where python
-
-:: python install dependencies
-python -m pip install --upgrade pip
-pip install -r requirements.txt
-:: DISTUTILS_USE_SDK should be set after psutil dependency
-set DISTUTILS_USE_SDK=1
-
-:: start sccache server and reset sccache stats
-sccache --start-server
-sccache --zero-stats
-sccache --show-stats
-
-:: Call PyTorch build script
-python setup.py bdist_wheel -d "%PYTORCH_FINAL_PACKAGE_DIR%"
-
-:: show sccache stats
-sccache --show-stats
-
-:: Check if installation was successful
-if %errorlevel% neq 0 (
-    echo "Failed on build_pytorch. (exitcode = %errorlevel%)"
-    exit /b 1
-)

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

@@ -1,49 +0,0 @@
-@echo off
-setlocal
-
-if "%PACKAGE_TYPE%" == "wheel" goto wheel
-if "%PACKAGE_TYPE%" == "libtorch" goto libtorch
-
-echo "unknown package type"
-exit /b 1
-
-:wheel
-call %PYTORCH_ROOT%\.ci\pytorch\windows\arm64\bootstrap_tests.bat
-
-echo Running python rnn_smoke.py...
-python %PYTORCH_ROOT%\.ci\pytorch\test_example_code\rnn_smoke_win_arm64.py
-if errorlevel 1 exit /b 1
-
-echo Checking that basic CNN works...
-python %PYTORCH_ROOT%\.ci\pytorch\test_example_code\cnn_smoke_win_arm64.py
-if errorlevel 1 exit /b 1
-
-goto end
-
-:libtorch
-echo "install and test libtorch"
-
-if not exist tmp mkdir tmp
-
-for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *-latest.zip') do C:\Windows\System32\tar.exe -xf "%%i" -C tmp
-if ERRORLEVEL 1 exit /b 1
-
-pushd tmp
-
-set VC_VERSION_LOWER=14
-set VC_VERSION_UPPER=36
-
-call "%DEPENDENCIES_DIR%\VSBuildTools\VC\Auxiliary\Build\vcvarsall.bat" arm64
-
-set install_root=%CD%
-set INCLUDE=%INCLUDE%;%install_root%\include;%install_root%\include\torch\csrc\api\include
-set LIB=%LIB%;%install_root%\lib
-set PATH=%PATH%;%install_root%\lib
-
-cl %PYTORCH_ROOT%\.ci\pytorch\test_example_code\simple-torch-test.cpp c10.lib torch_cpu.lib /EHsc /std:c++17
-if ERRORLEVEL 1 exit /b 1
-
-.\simple-torch-test.exe
-if ERRORLEVEL 1 exit /b 1
-
-:end

.ci/pytorch/windows/condaenv.bat

@@ -9,13 +9,12 @@ FOR %%v IN (%DESIRED_PYTHON%) DO (
     set PYTHON_VERSION_STR=%%v
     set PYTHON_VERSION_STR=!PYTHON_VERSION_STR:.=!
     conda remove -n py!PYTHON_VERSION_STR! --all -y || rmdir %CONDA_HOME%\envs\py!PYTHON_VERSION_STR! /s
-    if "%%v" == "3.9" call conda create -n py!PYTHON_VERSION_STR! -y numpy=2.0.1 boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
-    if "%%v" == "3.10" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.0.1  boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
-    if "%%v" == "3.11" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.0.1  boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
-    if "%%v" == "3.12" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.0.1  boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
-    if "%%v" == "3.13" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.1.2  boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
-    if "%%v" == "3.13t" call conda create -n py!PYTHON_VERSION_STR! -y -c=conda-forge numpy=2.1.2 boto3 cmake ninja typing_extensions setuptools=72.1.0 python-freethreading python=3.13
-    call conda run -n py!PYTHON_VERSION_STR! pip install pyyaml
+    if "%%v" == "3.8" call conda create -n py!PYTHON_VERSION_STR! -y -q numpy=1.11 pyyaml boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
+    if "%%v" == "3.9" call conda create -n py!PYTHON_VERSION_STR! -y -q numpy=2.0.1 pyyaml boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
+    if "%%v" == "3.10" call conda create -n py!PYTHON_VERSION_STR! -y -q -c=conda-forge numpy=2.0.1 pyyaml boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
+    if "%%v" == "3.11" call conda create -n py!PYTHON_VERSION_STR! -y -q -c=conda-forge numpy=2.0.1 pyyaml boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
+    if "%%v" == "3.12" call conda create -n py!PYTHON_VERSION_STR! -y -q -c=conda-forge numpy=2.0.1 pyyaml boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
+    if "%%v" == "3.13" call conda create -n py!PYTHON_VERSION_STR! -y -q -c=conda-forge numpy=2.1.2 pyyaml boto3 cmake ninja typing_extensions setuptools=72.1.0 python=%%v
     call conda run -n py!PYTHON_VERSION_STR! pip install mkl-include
     call conda run -n py!PYTHON_VERSION_STR! pip install mkl-static
 )

.ci/pytorch/windows/cuda128.bat

@@ -1,59 +0,0 @@
-@echo off
-
-set MODULE_NAME=pytorch
-
-IF NOT EXIST "setup.py" IF NOT EXIST "%MODULE_NAME%" (
-    call internal\clone.bat
-    cd %~dp0
-) ELSE (
-    call internal\clean.bat
-)
-IF ERRORLEVEL 1 goto :eof
-
-call internal\check_deps.bat
-IF ERRORLEVEL 1 goto :eof
-
-REM Check for optional components
-
-set USE_CUDA=
-set CMAKE_GENERATOR=Visual Studio 15 2017 Win64
-
-IF "%NVTOOLSEXT_PATH%"=="" (
-    IF EXIST "C:\Program Files\NVIDIA Corporation\NvToolsExt\lib\x64\nvToolsExt64_1.lib"  (
-        set NVTOOLSEXT_PATH=C:\Program Files\NVIDIA Corporation\NvToolsExt
-    ) ELSE (
-        echo NVTX ^(Visual Studio Extension ^for CUDA^) ^not installed, failing
-        exit /b 1
-    )
-)
-
-IF "%CUDA_PATH_V128%"=="" (
-    IF EXIST "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin\nvcc.exe" (
-        set "CUDA_PATH_V128=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8"
-    ) ELSE (
-        echo CUDA 12.8 not found, failing
-        exit /b 1
-    )
-)
-
-IF "%BUILD_VISION%" == "" (
-    set TORCH_CUDA_ARCH_LIST=5.0;6.0;6.1;7.0;7.5;8.0;8.6;9.0;10.0;12.0
-    set TORCH_NVCC_FLAGS=-Xfatbin -compress-all
-) ELSE (
-    set NVCC_FLAGS=-D__CUDA_NO_HALF_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75 -gencode=arch=compute_80,code=compute_80 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_90,code=compute_90 -gencode=arch=compute_100,code=compute_100 -gencode=arch=compute_120,code=compute_120
-)
-
-set "CUDA_PATH=%CUDA_PATH_V128%"
-set "PATH=%CUDA_PATH_V128%\bin;%PATH%"
-
-:optcheck
-
-call internal\check_opts.bat
-IF ERRORLEVEL 1 goto :eof
-
-if exist "%NIGHTLIES_PYTORCH_ROOT%" cd %NIGHTLIES_PYTORCH_ROOT%\..
-call  %~dp0\internal\copy.bat
-IF ERRORLEVEL 1 goto :eof
-
-call  %~dp0\internal\setup.bat
-IF ERRORLEVEL 1 goto :eof

.ci/pytorch/windows/internal/cuda_install.bat

@@ -9,8 +9,7 @@ if "%CUDA_VERSION%" == "xpu" (
     exit /b 0
 )
 
-set SRC_DIR=%~dp0\..
-
+set SRC_DIR=%NIGHTLIES_PYTORCH_ROOT%
 if not exist "%SRC_DIR%\temp_build" mkdir "%SRC_DIR%\temp_build"
 
 set /a CUDA_VER=%CUDA_VERSION%
@@ -24,9 +23,9 @@ set CUDNN_LIB_FOLDER="lib\x64"
 if exist "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v%CUDA_VERSION_STR%\bin\nvcc.exe" goto set_cuda_env_vars
 
 if %CUDA_VER% EQU 118 goto cuda118
+if %CUDA_VER% EQU 121 goto cuda121
 if %CUDA_VER% EQU 124 goto cuda124
 if %CUDA_VER% EQU 126 goto cuda126
-if %CUDA_VER% EQU 128 goto cuda128
 
 echo CUDA %CUDA_VERSION_STR% is not supported
 exit /b 1
@@ -112,33 +111,6 @@ xcopy /Y "%SRC_DIR%\temp_build\zlib\dll_x64\*.dll" "C:\Windows\System32"
 
 goto cuda_common
 
-:cuda128
-
-set CUDA_INSTALL_EXE=cuda_12.8.0_571.96_windows.exe
-if not exist "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%" (
-    curl -k -L "https://ossci-windows.s3.amazonaws.com/%CUDA_INSTALL_EXE%" --output "%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
-    if errorlevel 1 exit /b 1
-    set "CUDA_SETUP_FILE=%SRC_DIR%\temp_build\%CUDA_INSTALL_EXE%"
-    set "ARGS=cuda_profiler_api_12.8 thrust_12.8 nvcc_12.8 cuobjdump_12.8 nvprune_12.8 nvprof_12.8 cupti_12.8 cublas_12.8 cublas_dev_12.8 cudart_12.8 cufft_12.8 cufft_dev_12.8 curand_12.8 curand_dev_12.8 cusolver_12.8 cusolver_dev_12.8 cusparse_12.8 cusparse_dev_12.8 npp_12.8 npp_dev_12.8 nvrtc_12.8 nvrtc_dev_12.8 nvml_dev_12.8 nvjitlink_12.8 nvtx_12.8"
-)
-
-set CUDNN_FOLDER=cudnn-windows-x86_64-9.7.0.66_cuda12-archive
-set CUDNN_LIB_FOLDER="lib"
-set "CUDNN_INSTALL_ZIP=%CUDNN_FOLDER%.zip"
-if not exist "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%" (
-    curl -k -L "http://s3.amazonaws.com/ossci-windows/%CUDNN_INSTALL_ZIP%" --output "%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
-    if errorlevel 1 exit /b 1
-    set "CUDNN_SETUP_FILE=%SRC_DIR%\temp_build\%CUDNN_INSTALL_ZIP%"
-)
-
-@REM cuDNN 8.3+ required zlib to be installed on the path
-echo Installing ZLIB dlls
-curl -k -L "http://s3.amazonaws.com/ossci-windows/zlib123dllx64.zip" --output "%SRC_DIR%\temp_build\zlib123dllx64.zip"
-7z x "%SRC_DIR%\temp_build\zlib123dllx64.zip" -o"%SRC_DIR%\temp_build\zlib"
-xcopy /Y "%SRC_DIR%\temp_build\zlib\dll_x64\*.dll" "C:\Windows\System32"
-
-goto cuda_common
-
 :cuda_common
 :: NOTE: We only install CUDA if we don't have it installed already.
 :: With GHA runners these should be pre-installed as part of our AMI process

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

@@ -27,6 +27,7 @@ for /F "delims=" %%i in ('wmic path win32_VideoController get name') do (
 endlocal & set NVIDIA_GPU_EXISTS=%NVIDIA_GPU_EXISTS%
 
 if "%PACKAGE_TYPE%" == "wheel" goto wheel
+if "%PACKAGE_TYPE%" == "conda" goto conda
 if "%PACKAGE_TYPE%" == "libtorch" goto libtorch
 
 echo "unknown package type"
@@ -36,7 +37,6 @@ exit /b 1
 echo "install wheel package"
 
 set PYTHON_INSTALLER_URL=
-if "%DESIRED_PYTHON%" == "3.13t" set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.13.0/python-3.13.0-amd64.exe"
 if "%DESIRED_PYTHON%" == "3.13" set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.13.0/python-3.13.0-amd64.exe"
 if "%DESIRED_PYTHON%" == "3.12" set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.12.0/python-3.12.0-amd64.exe"
 if "%DESIRED_PYTHON%" == "3.11" set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.11.0/python-3.11.0-amd64.exe"
@@ -47,13 +47,6 @@ if "%PYTHON_INSTALLER_URL%" == "" (
     echo Python %DESIRED_PYTHON% not supported yet
 )
 
-set ADDITIONAL_OPTIONS=""
-set PYTHON_EXEC="python"
-if "%DESIRED_PYTHON%" == "3.13t" (
-    set ADDITIONAL_OPTIONS="Include_freethreaded=1"
-    set PYTHON_EXEC="python3.13t"
-)
-
 del python-amd64.exe
 curl --retry 3 -kL "%PYTHON_INSTALLER_URL%" --output python-amd64.exe
 if errorlevel 1 exit /b 1
@@ -62,39 +55,85 @@ if errorlevel 1 exit /b 1
 :: the installed Python to PATH system-wide. Even calling set PATH=%ORIG_PATH% later on won't make
 :: a change. As the builder directory will be removed after the smoke test, all subsequent non-binary
 :: jobs will fail to find any Python executable there
-start /wait "" python-amd64.exe /quiet InstallAllUsers=1 PrependPath=0 Include_test=0 %ADDITIONAL_OPTIONS% TargetDir=%CD%\Python
+start /wait "" python-amd64.exe /quiet InstallAllUsers=1 PrependPath=0 Include_test=0 TargetDir=%CD%\Python
 if errorlevel 1 exit /b 1
 
 set "PATH=%CD%\Python%PYTHON_VERSION%\Scripts;%CD%\Python;%PATH%"
-if "%DESIRED_PYTHON%" == "3.13t" %PYTHON_EXEC% -m pip install --pre numpy==2.2.1 protobuf
-if "%DESIRED_PYTHON%" == "3.13" %PYTHON_EXEC% -m pip install --pre numpy==2.1.2 protobuf
-if "%DESIRED_PYTHON%" == "3.12" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf
-if "%DESIRED_PYTHON%" == "3.11" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf
-if "%DESIRED_PYTHON%" == "3.10" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf
-if "%DESIRED_PYTHON%" == "3.9" %PYTHON_EXEC% -m pip install --pre numpy==2.0.2 protobuf networkx
+
+if "%DESIRED_PYTHON%" == "3.13" pip install -q --pre numpy==2.1.0 protobuf
+if "%DESIRED_PYTHON%" == "3.12" pip install -q --pre numpy==2.0.2 protobuf
+if "%DESIRED_PYTHON%" == "3.11" pip install -q --pre numpy==2.0.2 protobuf
+if "%DESIRED_PYTHON%" == "3.10" pip install -q --pre numpy==2.0.2 protobuf
+if "%DESIRED_PYTHON%" == "3.9" pip install -q --pre numpy==2.0.2 protobuf
+if "%DESIRED_PYTHON%" == "3.8" pip install -q numpy protobuf
 
 if errorlevel 1 exit /b 1
 
-if "%PYTORCH_BUILD_VERSION:dev=%" NEQ "%PYTORCH_BUILD_VERSION%" (
-    set "CHANNEL=nightly"
-) else (
-    set "CHANNEL=test"
-)
-
-set "EXTRA_INDEX= "
-if "%CUDA_VERSION%" == "xpu" set "EXTRA_INDEX=--index-url https://download.pytorch.org/whl/%CHANNEL%/xpu"
-
-for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *.whl') do %PYTHON_EXEC% -m pip install "%%i" %EXTRA_INDEX%
+for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *.whl') do pip install "%%i"
 if errorlevel 1 exit /b 1
 
 goto smoke_test
 
+:conda
+echo "install conda package"
+
+:: Install Miniconda3
+set "CONDA_HOME=%CD%\conda"
+set "tmp_conda=%CONDA_HOME%"
+set "miniconda_exe=%CD%\miniconda.exe"
+set "CONDA_EXTRA_ARGS=cpuonly -c pytorch-nightly"
+if "%CUDA_VERSION%" == "118" (
+    set "CONDA_EXTRA_ARGS=pytorch-cuda=11.8 -c nvidia -c pytorch-nightly"
+)
+if "%CUDA_VERSION%" == "121" (
+    set "CONDA_EXTRA_ARGS=pytorch-cuda=12.1 -c nvidia -c pytorch-nightly"
+)
+if "%CUDA_VERSION%" == "124" (
+    set "CONDA_EXTRA_ARGS=pytorch-cuda=12.4 -c nvidia -c pytorch-nightly"
+)
+if "%CUDA_VERSION%" == "126" (
+    set "CONDA_EXTRA_ARGS=pytorch-cuda=12.6 -c nvidia -c pytorch-nightly"
+)
+
+rmdir /s /q conda
+del miniconda.exe
+curl -k https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe -o "%miniconda_exe%"
+start /wait "" "%miniconda_exe%" /S /InstallationType=JustMe /RegisterPython=0 /AddToPath=0 /D=%tmp_conda%
+if ERRORLEVEL 1 exit /b 1
+
+set "PATH=%CONDA_HOME%;%CONDA_HOME%\scripts;%CONDA_HOME%\Library\bin;%PATH%"
+
+conda create -qyn testenv python=%DESIRED_PYTHON%
+if errorlevel 1 exit /b 1
+call conda install -yq conda-build
+if errorlevel 1 exit /b 1
+call %CONDA_HOME%\condabin\activate.bat testenv
+if errorlevel 1 exit /b 1
+set "NO_ARCH_PATH=%PYTORCH_FINAL_PACKAGE_DIR:/=\%\noarch"
+mkdir %NO_ARCH_PATH%
+for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *') do xcopy "%%i" %NO_ARCH_PATH% /Y
+if ERRORLEVEL 1 exit /b 1
+call conda index %PYTORCH_FINAL_PACKAGE_DIR%
+if errorlevel 1 exit /b 1
+call conda install -yq -c "file:///%PYTORCH_FINAL_PACKAGE_DIR%" pytorch==%PYTORCH_BUILD_VERSION% -c pytorch -c numba/label/dev -c nvidia
+if ERRORLEVEL 1 exit /b 1
+call conda install -yq numpy
+if ERRORLEVEL 1 exit /b 1
+
+set /a CUDA_VER=%CUDA_VERSION%
+set CUDA_VER_MAJOR=%CUDA_VERSION:~0,-1%
+set CUDA_VER_MINOR=%CUDA_VERSION:~-1,1%
+set CUDA_VERSION_STR=%CUDA_VER_MAJOR%.%CUDA_VER_MINOR%
+
+:: Install package we just build
+
+
 :smoke_test
-%PYTHON_EXEC% -c "import torch"
+python -c "import torch"
 if ERRORLEVEL 1 exit /b 1
 
 echo Checking that MKL is available
-%PYTHON_EXEC% -c "import torch; exit(0 if torch.backends.mkl.is_available() else 1)"
+python -c "import torch; exit(0 if torch.backends.mkl.is_available() else 1)"
 if ERRORLEVEL 1 exit /b 1
 
 if "%NVIDIA_GPU_EXISTS%" == "0" (
@@ -103,24 +142,24 @@ if "%NVIDIA_GPU_EXISTS%" == "0" (
 )
 
 echo Checking that CUDA archs are setup correctly
-%PYTHON_EXEC% -c "import torch; torch.randn([3,5]).cuda()"
+python -c "import torch; torch.randn([3,5]).cuda()"
 if ERRORLEVEL 1 exit /b 1
 
 echo Checking that magma is available
-%PYTHON_EXEC% -c "import torch; torch.rand(1).cuda(); exit(0 if torch.cuda.has_magma else 1)"
+python -c "import torch; torch.rand(1).cuda(); exit(0 if torch.cuda.has_magma else 1)"
 if ERRORLEVEL 1 exit /b 1
 
 echo Checking that CuDNN is available
-%PYTHON_EXEC% -c "import torch; exit(0 if torch.backends.cudnn.is_available() else 1)"
+python -c "import torch; exit(0 if torch.backends.cudnn.is_available() else 1)"
 if ERRORLEVEL 1 exit /b 1
 
 echo Checking that basic RNN works
-%PYTHON_EXEC% %PYTORCH_ROOT%\.ci\pytorch\test_example_code\rnn_smoke.py
+python %PYTORCH_ROOT%\.ci\pytorch\test_example_code\rnn_smoke.py
 
 if ERRORLEVEL 1 exit /b 1
 
 echo Checking that basic CNN works
-%PYTHON_EXEC% %PYTORCH_ROOT%\.ci\pytorch\test_example_code\cnn_smoke.py
+python %PYTORCH_ROOT%\.ci\pytorch\test_example_code\cnn_smoke.py
 if ERRORLEVEL 1 exit /b 1
 
 goto end

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

@@ -47,9 +47,9 @@ set XPU_EXTRA_INSTALLED=0
 set XPU_EXTRA_UNINSTALL=0
 
 if not [%XPU_VERSION%]==[] if [%XPU_VERSION%]==[2025.0] (
-    set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/9d6d6c17-ca2d-4735-9331-99447e4a1280/intel-deep-learning-essentials-2025.0.1.28_offline.exe
+    set XPU_BUNDLE_URL=https://registrationcenter-download.intel.com/akdlm/IRC_NAS/efc86abd-cb77-452e-a03f-a741895b8ece/intel-deep-learning-essentials-2025.0.0.336_offline.exe
     set XPU_BUNDLE_PRODUCT_NAME=intel.oneapi.win.deep-learning-essentials.product
-    set XPU_BUNDLE_VERSION=2025.0.1+20
+    set XPU_BUNDLE_VERSION=2025.0.0+335
     set XPU_BUNDLE_INSTALLED=0
     set XPU_BUNDLE_UNINSTALL=0
     set XPU_EXTRA_URL=NULL
@@ -104,6 +104,14 @@ goto xpu_install_end
 
 :xpu_bundle_install
 
+:: 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%"
+
+:: Install Bundle
 curl -o xpu_bundle.exe --retry 3 --retry-all-errors -k %XPU_BUNDLE_URL%
 echo "XPU Bundle installing..."
 start /wait "Intel Pytorch Bundle Installer" "xpu_bundle.exe" --action=install --eula=accept --silent --log-dir install_bundle
@@ -120,14 +128,3 @@ 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/windows/xpu.bat

@@ -28,6 +28,11 @@ call "%XPU_BUNDLE_ROOT%\compiler\latest\env\vars.bat"
 call "%XPU_BUNDLE_ROOT%\ocloc\latest\env\vars.bat"
 IF ERRORLEVEL 1 goto :eof
 
+:: Workaround for https://github.com/pytorch/pytorch/issues/134989
+set CMAKE_SHARED_LINKER_FLAGS=/FORCE:MULTIPLE
+set CMAKE_MODULE_LINKER_FLAGS=/FORCE:MULTIPLE
+set CMAKE_EXE_LINKER_FLAGS=/FORCE:MULTIPLE
+
 if exist "%NIGHTLIES_PYTORCH_ROOT%" cd %NIGHTLIES_PYTORCH_ROOT%\..
 call %~dp0\internal\copy_cpu.bat
 IF ERRORLEVEL 1 goto :eof

.ci/wheel/build_wheel.sh

@@ -130,19 +130,7 @@ export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
 SETUPTOOLS_PINNED_VERSION="=46.0.0"
 PYYAML_PINNED_VERSION="=5.3"
 EXTRA_CONDA_INSTALL_FLAGS=""
-CONDA_ENV_CREATE_FLAGS=""
-RENAME_WHEEL=true
 case $desired_python in
-    3.13t)
-        echo "Using 3.13 deps"
-        SETUPTOOLS_PINNED_VERSION=">=68.0.0"
-        PYYAML_PINNED_VERSION=">=6.0.1"
-        NUMPY_PINNED_VERSION="=2.1.0"
-        CONDA_ENV_CREATE_FLAGS="python-freethreading"
-        EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge"
-        desired_python="3.13"
-        RENAME_WHEEL=false
-        ;;
     3.13)
         echo "Using 3.13 deps"
         SETUPTOOLS_PINNED_VERSION=">=68.0.0"
@@ -181,15 +169,18 @@ esac
 
 # Install into a fresh env
 tmp_env_name="wheel_py$python_nodot"
-conda create ${EXTRA_CONDA_INSTALL_FLAGS} -yn "$tmp_env_name" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS}
+conda create ${EXTRA_CONDA_INSTALL_FLAGS} -yn "$tmp_env_name" python="$desired_python"
 source activate "$tmp_env_name"
 
-pip install "numpy=${NUMPY_PINNED_VERSION}"  "pyyaml${PYYAML_PINNED_VERSION}" requests ninja "setuptools${SETUPTOOLS_PINNED_VERSION}" typing_extensions
-retry pip install -r "${pytorch_rootdir}/requirements.txt" || true
-retry brew install libomp
+pip install -q "numpy=${NUMPY_PINNED_VERSION}"  "pyyaml${PYYAML_PINNED_VERSION}" requests
+retry pip install -qr "${pytorch_rootdir}/requirements.txt" || true
+# TODO : Remove me later (but in the interim, use Anaconda cmake, to find Anaconda installed OpenMP)
+retry pip uninstall -y cmake
+retry conda install ${EXTRA_CONDA_INSTALL_FLAGS} -yq  llvm-openmp=14.0.6 cmake ninja "setuptools${SETUPTOOLS_PINNED_VERSION}" typing_extensions
 
-# For USE_DISTRIBUTED=1 on macOS, need libuv, which is build as part of tensorpipe submodule
+# For USE_DISTRIBUTED=1 on macOS, need libuv and pkg-config to find libuv.
 export USE_DISTRIBUTED=1
+retry conda install ${EXTRA_CONDA_INSTALL_FLAGS} -yq libuv pkg-config
 
 if [[ -n "$CROSS_COMPILE_ARM64" ]]; then
     export CMAKE_OSX_ARCHITECTURES=arm64
@@ -231,13 +222,10 @@ echo "The wheel is in $(find $whl_tmp_dir -name '*.whl')"
 wheel_filename_gen=$(find $whl_tmp_dir -name '*.whl' | head -n1 | xargs -I {} basename {})
 popd
 
-if [[ -z "$BUILD_PYTHONLESS" && $RENAME_WHEEL == true  ]]; then
+if [[ -z "$BUILD_PYTHONLESS" ]]; then
     # Copy the whl to a final destination before tests are run
     echo "Renaming Wheel file: $wheel_filename_gen to $wheel_filename_new"
     cp "$whl_tmp_dir/$wheel_filename_gen" "$PYTORCH_FINAL_PACKAGE_DIR/$wheel_filename_new"
-elif [[ $RENAME_WHEEL == false ]]; then
-    echo "Copying Wheel file: $wheel_filename_gen to $PYTORCH_FINAL_PACKAGE_DIR"
-    cp "$whl_tmp_dir/$wheel_filename_gen" "$PYTORCH_FINAL_PACKAGE_DIR/$wheel_filename_gen"
 else
     pushd "$pytorch_rootdir"
 

.circleci/scripts/binary_populate_env.sh

@@ -30,10 +30,12 @@ fi
 # Pick docker image
 export DOCKER_IMAGE=${DOCKER_IMAGE:-}
 if [[ -z "$DOCKER_IMAGE" ]]; then
-  if [[ "$DESIRED_CUDA" == cpu ]]; then
-    export DOCKER_IMAGE="pytorch/manylinux2_28:cpu"
+  if [[ "$PACKAGE_TYPE" == conda ]]; then
+    export DOCKER_IMAGE="pytorch/conda-cuda"
+  elif [[ "$DESIRED_CUDA" == cpu ]]; then
+    export DOCKER_IMAGE="pytorch/manylinux:cpu"
   else
-    export DOCKER_IMAGE="pytorch/manylinux2_28-builder:${DESIRED_CUDA:2}"
+    export DOCKER_IMAGE="pytorch/manylinux-builder:${DESIRED_CUDA:2}"
   fi
 fi
 
@@ -61,7 +63,7 @@ if tagged_version >/dev/null; then
   # Turns tag v1.6.0-rc1 -> v1.6.0
   BASE_BUILD_VERSION="$(tagged_version | sed -e 's/^v//' -e 's/-.*$//')"
 fi
-if [[ "$(uname)" == 'Darwin' ]]; then
+if [[ "$(uname)" == 'Darwin' ]] || [[ "$PACKAGE_TYPE" == conda ]]; then
   export PYTORCH_BUILD_VERSION="${BASE_BUILD_VERSION}"
 else
   export PYTORCH_BUILD_VERSION="${BASE_BUILD_VERSION}+$DESIRED_CUDA"
@@ -74,12 +76,6 @@ TRITON_VERSION=$(cat $PYTORCH_ROOT/.ci/docker/triton_version.txt)
 
 # Here PYTORCH_EXTRA_INSTALL_REQUIREMENTS is already set for the all the wheel builds hence append TRITON_CONSTRAINT
 TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64'"
-
-# CUDA 12.8 builds have triton for Linux and Linux aarch64 binaries.
-if [[ "$DESIRED_CUDA" == cu128 ]]; then
-  TRITON_CONSTRAINT="platform_system == 'Linux'"
-fi
-
 if [[ "$PACKAGE_TYPE" =~ .*wheel.* &&  -n "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" && ! "$PYTORCH_BUILD_VERSION" =~ .*xpu.* ]]; then
   TRITON_REQUIREMENT="triton==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
   if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
@@ -104,11 +100,11 @@ if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_B
 fi
 
 # Set triton via PYTORCH_EXTRA_INSTALL_REQUIREMENTS for triton xpu package
-if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*xpu.* ]]; then
-    TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}"
+if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*xpu.* && $(uname) == "Linux" ]]; then
+    TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
     if [[ -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
         TRITON_SHORTHASH=$(cut -c1-8 $PYTORCH_ROOT/.ci/docker/ci_commit_pins/triton-xpu.txt)
-        TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}+git${TRITON_SHORTHASH}"
+        TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}+git${TRITON_SHORTHASH}; ${TRITON_CONSTRAINT}"
     fi
     if [[ -z "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
         export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${TRITON_REQUIREMENT}"
@@ -153,6 +149,8 @@ export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:
 
 # TODO: We don't need this anymore IIUC
 export TORCH_PACKAGE_NAME='torch'
+export TORCH_CONDA_BUILD_FOLDER='pytorch-nightly'
+export ANACONDA_USER='pytorch'
 
 export USE_FBGEMM=1
 export PIP_UPLOAD_FOLDER="$PIP_UPLOAD_FOLDER"

.circleci/scripts/binary_upload.sh

@@ -2,7 +2,7 @@
 
 set -euo pipefail
 
-PACKAGE_TYPE=${PACKAGE_TYPE:-wheel}
+PACKAGE_TYPE=${PACKAGE_TYPE:-conda}
 
 PKG_DIR=${PKG_DIR:-/tmp/workspace/final_pkgs}
 
@@ -18,8 +18,10 @@ BUILD_NAME=${BUILD_NAME:-}
 
 DRY_RUN=${DRY_RUN:-enabled}
 # Don't actually do work unless explicit
+ANACONDA="true anaconda"
 AWS_S3_CP="aws s3 cp --dryrun"
 if [[ "${DRY_RUN}" = "disabled" ]]; then
+  ANACONDA="anaconda"
   AWS_S3_CP="aws s3 cp"
 fi
 
@@ -32,6 +34,10 @@ if [[ ${BUILD_NAME} == *-full* ]]; then
   UPLOAD_SUBFOLDER="${UPLOAD_SUBFOLDER}_full"
 fi
 
+# Sleep 2 minutes between retries for conda upload
+retry () {
+  "$@"  || (sleep 5m && "$@") || (sleep 5m && "$@") || (sleep 5m && "$@") || (sleep 5m && "$@")
+}
 
 do_backup() {
   local backup_dir
@@ -43,33 +49,72 @@ do_backup() {
   )
 }
 
+conda_upload() {
+  (
+    set -x
+    retry \
+    ${ANACONDA} \
+    upload  \
+    ${PKG_DIR}/*.tar.bz2 \
+    -u "pytorch-${UPLOAD_CHANNEL}" \
+    --label main \
+    --no-progress \
+    --force
+  )
+}
+
 s3_upload() {
   local extension
   local pkg_type
   extension="$1"
   pkg_type="$2"
-  s3_root_dir="${UPLOAD_BUCKET}/${pkg_type}/${UPLOAD_CHANNEL}"
+  s3_key_prefix="${pkg_type}/${UPLOAD_CHANNEL}"
   if [[ -z ${UPLOAD_SUBFOLDER:-} ]]; then
-    s3_upload_dir="${s3_root_dir}/"
+    s3_upload_dir="${UPLOAD_BUCKET}/${s3_key_prefix}/"
   else
-    s3_upload_dir="${s3_root_dir}/${UPLOAD_SUBFOLDER}/"
+    s3_key_prefix="${s3_key_prefix}/${UPLOAD_SUBFOLDER}"
+    s3_upload_dir="${UPLOAD_BUCKET}/${s3_key_prefix}/"
   fi
   (
     for pkg in ${PKG_DIR}/*.${extension}; do
       (
         set -x
-        shm_id=$(sha256sum "${pkg}" | awk '{print $1}')
-        ${AWS_S3_CP} --no-progress --acl public-read "${pkg}" "${s3_upload_dir}" \
-          --metadata "checksum-sha256=${shm_id}"
+        ${AWS_S3_CP} --no-progress --acl public-read "${pkg}" "${s3_upload_dir}"
+        if [[ ${pkg_type} == "whl" ]]; then
+          dry_run_arg="--dry-run"
+          if [[ "${DRY_RUN}" = "disabled" ]]; then
+            dry_run_arg=""
+          fi
+          uv run scripts/release/upload_metadata_file.py \
+            --package "${pkg}" \
+            --bucket "${UPLOAD_BUCKET}" \
+            --key-prefix "${s3_key_prefix}" \
+            ${dry_run_arg}
+        fi
       )
     done
   )
 }
 
 # Install dependencies (should be a no-op if previously installed)
+conda install -yq anaconda-client
 pip install -q awscli uv
 
 case "${PACKAGE_TYPE}" in
+  conda)
+    conda_upload
+    for conda_archive in ${PKG_DIR}/*.tar.bz2; do
+      # Fetch  platform (eg. win-64, linux-64, etc.) from index file because
+      # there's no actual conda command to read this
+      subdir=$(\
+        tar -xOf "${conda_archive}" info/index.json \
+          | grep subdir  \
+          | cut -d ':' -f2 \
+          | sed -e 's/[[:space:]]//' -e 's/"//g' -e 's/,//' \
+      )
+      BACKUP_DIR="conda/${subdir}"
+    done
+    ;;
   libtorch)
     s3_upload "zip" "libtorch"
     BACKUP_DIR="libtorch/${UPLOAD_CHANNEL}/${UPLOAD_SUBFOLDER}"

.circleci/scripts/binary_windows_arm64_build.sh

@@ -1,22 +0,0 @@
-#!/bin/bash
-set -eux -o pipefail
-
-source "${BINARY_ENV_FILE:-/c/w/env}"
-mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR"
-
-export USE_SCCACHE=1
-export SCCACHE_IGNORE_SERVER_IO_ERROR=1
-
-echo "Free space on filesystem before build:"
-df -h
-
-export NIGHTLIES_PYTORCH_ROOT="$PYTORCH_ROOT"
-
-if [[ "$PACKAGE_TYPE" == 'libtorch' ]]; then
-    pytorch/.ci/pytorch/windows/arm64/build_libtorch.bat
-elif [[ "$PACKAGE_TYPE" == 'wheel' ]]; then
-    pytorch/.ci/pytorch/windows/arm64/build_pytorch.bat
-fi
-
-echo "Free space on filesystem after build:"
-df -h

.circleci/scripts/binary_windows_arm64_test.sh

@@ -1,6 +0,0 @@
-#!/bin/bash
-set -eux -o pipefail
-
-source "${BINARY_ENV_FILE:-/c/w/env}"
-
-pytorch/.ci/pytorch/windows/arm64/smoke_test.bat

.circleci/scripts/binary_windows_build.sh

@@ -14,7 +14,6 @@ if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
     export VC_YEAR=2022
     export USE_SCCACHE=0
     export XPU_VERSION=2025.0
-    export XPU_ENABLE_KINETO=1
 fi
 
 echo "Free space on filesystem before build:"

.clang-tidy

@@ -1,9 +1,8 @@
 ---
 # NOTE there must be no spaces before the '-', so put the comma last.
-# The check bugprone-unchecked-optional-access is also turned on.
-# Note that it can cause clang-tidy to hang randomly. The tracking issue
+# The check bugprone-unchecked-optional-access is also turned off atm
+# because it causes clang-tidy to hang randomly. The tracking issue
 # can be found at https://github.com/llvm/llvm-project/issues/69369.
-# When that happens, we can disable it on the problematic code by NOLINT.
 InheritParentConfig: true
 Checks: '
 bugprone-*,
@@ -12,8 +11,8 @@ bugprone-*,
 -bugprone-macro-parentheses,
 -bugprone-lambda-function-name,
 -bugprone-reserved-identifier,
--bugprone-return-const-ref-from-parameter,
 -bugprone-swapped-arguments,
+-bugprone-unchecked-optional-access,
 clang-analyzer-core.*,
 clang-analyzer-cplusplus.*,
 clang-analyzer-nullability.*,
@@ -25,7 +24,6 @@ cppcoreguidelines-*,
 -cppcoreguidelines-avoid-non-const-global-variables,
 -cppcoreguidelines-interfaces-global-init,
 -cppcoreguidelines-macro-usage,
--cppcoreguidelines-macro-to-enum,
 -cppcoreguidelines-owning-memory,
 -cppcoreguidelines-pro-bounds-array-to-pointer-decay,
 -cppcoreguidelines-pro-bounds-constant-array-index,
@@ -48,7 +46,6 @@ misc-*,
 -misc-no-recursion,
 -misc-non-private-member-variables-in-classes,
 -misc-unused-using-decls,
--misc-use-internal-linkage,
 modernize-*,
 -modernize-macro-to-enum,
 -modernize-return-braced-init-list,
@@ -58,7 +55,6 @@ modernize-*,
 -modernize-use-trailing-return-type,
 -modernize-use-nodiscard,
 performance-*,
--performance-enum-size,
 readability-container-size-empty,
 readability-delete-null-pointer,
 readability-duplicate-include

.flake8

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

.git-blame-ignore-revs

@@ -24,10 +24,6 @@ e3900d2ba5c9f91a24a9ce34520794c8366d5c54
 2e26976ad3b06ce95dd6afccfdbe124802edf28f
 # 2021-06-07 Strictly typed everything in `.github` and `tools`
 737d920b21db9b4292d056ee1329945990656304
-# 2021-08-12 [codemod][lint][fbcode/c*] Enable BLACK by default
-b0043072529b81276a69df29e00555333117646c
-# 2021-08-25 Reformat run_test.py
-67d8e7b659b19e1ee68208b28bfa7dba73375dbc
 # 2022-06-09 Apply clang-format to ATen headers
 95b15c266baaf989ef7b6bbd7c23a2d90bacf687
 # 2022-06-11 [lint] autoformat test/cpp and torch/csrc
@@ -48,57 +44,3 @@ a53cda1ddc15336dc1ff0ce1eff2a49cdc5f882e
 d80939e5e9337e8078f11489afefec59fd42f93b
 # 2024-06-28 enable UFMT in `torch.utils.data`
 7cf0b90e49689d45be91aa539fdf54cf2ea8a9a3
-# 2024-07-03 Enable UFMT on test/test_public_bindings.py (#128389)
-fe5424d0f8604f6e66d827ae9f94b05cb7119d55
-# 2024-07-03 Enable UFMT on test/test_public_bindings.py (#128389)
-c686304277f7cd72331f685605325498cff94a0b
-# 2024-07-15 Enable UFMT on all of torch/sparse (#130545)
-535016967ae65a6027f83d6b935a985996223d49
-# 2024-07-15 [BE][Easy][1/19] enforce style for empty lines in import segments (#129752)
-a3abfa5cb57203b6a8ba7dff763f4057db8282a8
-# 2024-07-15 [BE][Easy][2/19] enforce style for empty lines in import segments in `.ci/` and `.github/` (#129753)
-ba48cf653541e9160dfdefa7bfea885c22e48608
-# 2024-07-16 [BE][Easy][5/19] enforce style for empty lines in import segments in `tools/` and `torchgen/` (#129756)
-f6838d521a243dbedc50ae96575720bf2cc8a8ad
-# 2024-07-17 [BE][Easy][9/19] enforce style for empty lines in import segments in `test/[e-h]*/` (#129760)
-76169cf69184bd462b9add40f893f57675f8a057
-# 2024-07-16 [BE][Easy][3/19] enforce style for empty lines in import segments in `benchmarks/` (#129754)
-c0ed38e644aed812d76b0ec85fae2f6019bf462b
-# 2024-07-16 [BE][Easy][4/19] enforce style for empty lines in import segments in `functorch/` (#129755)
-740fb229660f388feddc288c127ab12c82e67d36
-# 2024-07-17 [BE][Easy][12/19] enforce style for empty lines in import segments in `test/i*/` (#129763)
-aecc746fccc4495313167e3a7f94210daf457e1d
-# 2024-07-18 Revert "[BE][Easy][12/19] enforce style for empty lines in import segments in `test/i*/` (#129763)"
-b732b52f1e4378f8486ceb5e7026be3321c2651c
-# 2024-07-18 [BE][Easy][12/19] enforce style for empty lines in import segments in `test/i*/` (#129763)
-134bc4fc34bb02795aa694e66b132dcea5dde1e1
-# 2024-07-26 [BE][Easy][8/19] enforce style for empty lines in import segments in `test/[k-p]*/` (#129759)
-fbe6f42dcf1834213e0baa87b87529161df3c4d7
-# 2024-07-31 [BE][Easy][14/19] enforce style for empty lines in import segments in `torch/_[a-c]*/` and `torch/_[e-h]*/` and `torch/_[j-z]*/` (#129765)
-e7eeee473c6cb45942e87de5a616b0eb635513d6
-# 2024-07-31 Fix lint after PR #130572 (#132316)
-d72e863b3ecd3de4c8ea00518e110da964583f4f
-# 2024-07-31 [BE][Easy][15/19] enforce style for empty lines in import segments in `torch/_d*/` (#129767)
-e74ba1b34a476b46e76b4e32afe2d481f97e9a47
-# 2024-07-31 [BE][Easy][18/19] enforce style for empty lines in import segments in `torch/d*/` (#129770)
-b25ef91bf158ce459d8654e33c50c8e6ed8db716
-# 2024-07-20 [BE][Easy][13/19] enforce style for empty lines in import segments in `test/j*/` (#129764)
-6ff1e43a416c43cd82b210e22ac47384494c172e
-# 2024-11-01 [Lint] Clang-format all metal kernels (#139530)
-b3ad45733bd908b7358959ca1e1f8d026f4507eb
-# 2024-11-17 [BE][MPS] Apply clang-format to mps headers (#140906)
-99014a297c179862af38ee86bac2051434d3db41
-# 2024-11-27 Apply clang-format for ATen/core/boxing headers (#141105)
-19d01a1ef0c0d65768eb0a5c97a25328eec57fbd
-# 2024-12-05 fix the lint from D66795414 (#142122)
-65c2086d452ae6966ce9d7fb3cb2eef2fd0d2add
-# 2024-12-20 Apply clang-format for ATen/core/dispatch headers (#143620)
-cee06e74eeb54994b97000a02b715a4e63a97951
-# 2024-12-22 Better fix for f-strings in set_linter for py3.12 (#143725)
-eebc93d41eeffb936cbf20c9052e1e813d0cc052
-# 2025-01-04 [mps/BE] Fix linter warning/advice. (#144199)
-0dc1e6be192b260f1c072d70e1b06a3ac8e109fa
-# 2025-01-07 Fix lint in `test_provenance_tracing.py` (#144296)
-61c0a3d1cbaf6420e40ab0f9c9019daa21145e69
-# 2025-01-09 [BE] fix ruff rule E226: add missing whitespace around operator in f-strings (#144415)
-dcc3cf7066b4d8cab63ecb73daf1e36b01220a4e

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -5,7 +5,7 @@ body:
 - type: markdown
   attributes:
     value: >
-      #### Before submitting a bug, please make sure the issue hasn't been already addressed by searching through [the existing and past issues](https://github.com/pytorch/pytorch/issues?q=is%3Aissue+sort%3Acreated-desc+). Note: Please write your bug report in English to ensure it can be understood and addressed by the development team. If you are filing a bug for torch.compile, please use the [torch.compile issue template](https://github.com/pytorch/pytorch/issues/new?q=sort%3Aupdated-desc+is%3Aissue+is%3Aopen&template=pt2-bug-report.yml).
+      #### Before submitting a bug, please make sure the issue hasn't been already addressed by searching through [the existing and past issues](https://github.com/pytorch/pytorch/issues?q=is%3Aissue+sort%3Acreated-desc+).
 - type: textarea
   attributes:
     label: 🐛 Describe the bug

.github/ISSUE_TEMPLATE/documentation.yml

@@ -2,10 +2,6 @@ name: 📚 Documentation
 description: Report an issue related to https://pytorch.org/docs/stable/index.html
 
 body:
-- type: markdown
-  attributes:
-    value: >
-      #### Note: Please report your documentation issue in English to ensure it can be understood and addressed by the development team.
 - type: textarea
   attributes:
     label: 📚 The doc issue

.github/ISSUE_TEMPLATE/feature-request.yml

@@ -2,10 +2,6 @@ name: 🚀 Feature request
 description: Submit a proposal/request for a new PyTorch feature
 
 body:
-- type: markdown
-  attributes:
-    value: >
-      #### Note: Please write your feature request in English to ensure it can be understood and addressed by the development team.
 - type: textarea
   attributes:
     label: 🚀 The feature, motivation and pitch

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

@@ -3,10 +3,6 @@ description: Create a report to help us reproduce and fix the bug
 labels: ["oncall: pt2"]
 
 body:
-  - type: markdown
-    attributes:
-      value: >
-        #### Note: Please write your bug report in English to ensure it can be understood and addressed by the development team.
   - type: markdown
     attributes:
       value: >
@@ -22,8 +18,6 @@ body:
 
         - If comparing eager and torch.compile at fp16/bf16, you should use fp32 as baseline
 
-        - Ensure rng state used to compare results is equivalent. Use `torch._inductor.config.fallback_random=True` and reset the torch rng seed between comparisons
-
         If the above requirements are met, add the label "topic: fuzzer" to your issue.
 
   - type: textarea

.github/actionlint.yaml

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

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

@@ -40,11 +40,6 @@ runs:
         fi
         mkdir "${GITHUB_WORKSPACE}"
 
-        # Use all available CPUs for fetching
-        cd "${GITHUB_WORKSPACE}"
-        git config --global fetch.parallel 0
-        git config --global submodule.fetchJobs 0
-
     - name: Checkout PyTorch
       uses: actions/checkout@v4
       with:

.github/actions/diskspace-cleanup/action.yml

@@ -17,10 +17,6 @@ runs:
         set -ex
         diskspace_cutoff=${{ inputs.diskspace-cutoff }}
         docker_root_dir=$(docker info -f '{{.DockerRootDir}}')
-        if [ ! -d "$docker_root_dir" ]; then
-            echo "Docker root directory ($docker_root_dir) does not exist. Skipping disk space check."
-            exit 0
-        fi
         diskspace=$(df -H --output=pcent ${docker_root_dir} | sed -n 2p | sed 's/%//' | sed 's/ //')
         msg="Please file an issue on pytorch/pytorch reporting the faulty runner. Include a link to the runner logs so the runner can be identified"
         if [[ "$diskspace" -ge "$diskspace_cutoff" ]] ; then

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

@@ -5,6 +5,20 @@ description: Set up ROCm host for CI
 runs:
   using: composite
   steps:
+    - name: Set DOCKER_HOST
+      shell: bash
+      run: echo "DOCKER_HOST=unix:///run/user/$(id -u)/docker.sock" >> "${GITHUB_ENV}"
+
+    - name: Remove leftover Docker config file
+      shell: bash
+      continue-on-error: true
+      run: |
+        set -ex
+
+        cat ~/.docker/config.json || true
+        # https://stackoverflow.com/questions/64455468/error-when-logging-into-ecr-with-docker-login-error-saving-credentials-not
+        rm -f ~/.docker/config.json
+
     - name: Stop all running docker containers
       if: always()
       shell: bash
@@ -97,16 +111,8 @@ runs:
       shell: bash
       run: |
         # All GPUs are visible to the runner; visibility, if needed, will be set by run_test.py.
-        # Add render group for container creation.
-        render_gid=`cat /etc/group | grep render | cut -d: -f3`
-        # Ensure GPU isolation if pod is part of kubernetes setup with DEVICE_FLAG.
-        if [ -f "/etc/podinfo/gha-render-devices" ]; then
-          DEVICE_FLAG=$(cat /etc/podinfo/gha-render-devices)
-        else
-          DEVICE_FLAG="--device /dev/dri"
-        fi
         # The --group-add daemon and --group-add bin are needed in the Ubuntu 24.04 and Almalinux OSs respectively.
         # This is due to the device files (/dev/kfd & /dev/dri) being owned by video group on bare metal.
         # This video group ID maps to subgid 1 inside the docker image due to the /etc/subgid entries.
         # The group name corresponding to group ID 1 can change depending on the OS, so both are necessary.
-        echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd $DEVICE_FLAG --group-add video --group-add $render_gid --group-add daemon --group-add bin --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --network=host" >> "${GITHUB_ENV}"
+        echo "GPU_FLAG=--device=/dev/mem --device=/dev/kfd --device=/dev/dri --group-add video --group-add daemon --group-add bin" >> "${GITHUB_ENV}"

.github/actions/upload-utilization-stats/action.yml

@@ -1,56 +0,0 @@
-name: upload-utilization-stats
-
-description: Upload utilization stats to artifacts
-
-inputs:
-    workflow_run_id:
-      type: string
-      description: 'workflow (run) id of the workflow the test is running'
-      required: True
-    workflow_attempt:
-      type: string
-      description: 'the workflow (run) attempt'
-      required: True
-    workflow_name:
-      description: 'name of the workflow'
-      type: string
-      required: True
-    job_id:
-      type: string
-      description: 'the job (run) id for the test'
-      required: True
-    job_name:
-      type: string
-      description: 'the job name of the test'
-      required: True
-
-runs:
-  using: composite
-  steps:
-    - name: Print Inputs
-      shell: bash
-      run: |
-        echo "workflow_id: ${{inputs.workflow_run_id}}"
-        echo "workflow_attempt: ${{inputs.workflow_attempt}}"
-        echo "workflow_Name: ${{inputs.workflow_name}}"
-        echo "job_id: ${{inputs.job_id}}"
-        echo "job_name:  ${{inputs.job_name}}"
-    - uses: nick-fields/retry@v3.0.0
-      name: Setup dependencies
-      with:
-        shell: bash
-        timeout_minutes: 5
-        max_attempts: 5
-        retry_wait_seconds: 30
-        command: |
-          set -eu
-          python3 -m pip install python-dateutil==2.8.2 boto3==1.35.42 pandas==2.1.3
-    - name: Upload utilizatoin stats to s3
-      shell: bash
-      run: |
-        python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \
-          --workflow-run-id "${{inputs.workflow_run_id}}" \
-          --workflow-name "${{inputs.workflow_name}}" \
-          --workflow-run-attempt "${{inputs.workflow_attempt}}" \
-          --job-id "${{inputs.job_id}}" \
-          --job-name "${{inputs.job_name}}"

.github/ci_commit_pins/audio.txt

@@ -1 +1 @@
-c670ad81fda266b6598aeeef434583eb98197ae8
+b6d4675c7aedc53ba04f3f55786aac1de32be6b4

.github/ci_commit_pins/fbgemm_rocm.txt

@@ -1 +0,0 @@
-5fb5024118e9bb9decf96c2b0b1a8f0010bf56be

.github/ci_commit_pins/torchbench.txt

@@ -1 +1 @@
-373ffb19dc470f4423a3176a4133f8f4b3cdb5bd
+766a5e3a189384659fd35a68c3b17b88c761aaac

.github/ci_commit_pins/xla.txt

@@ -1 +1 @@
-r2.7
+b2b890e962f5fb6f481e5da2eb4a43bb990d0f1b

.github/labeler.yml

@@ -98,7 +98,7 @@
 - test/distributed/**
 - torch/testing/_internal/distributed/**
 
-"release notes: distributed (checkpoint)":
+"module: distributed_checkpoint":
 - torch/distributed/checkpoint/**
 - test/distributed/checkpoint/**
 
@@ -107,8 +107,3 @@
 - torch/csrc/dynamo/compiled_autograd.h
 - torch/_dynamo/compiled_autograd.py
 - torch/inductor/test_compiled_autograd.py
-
-"ciflow/xpu":
-- torch/csrc/inductor/aoti_include/xpu.h
-- torch/csrc/inductor/cpp_wrapper/device_internal/xpu.h
-- torch/csrc/inductor/cpp_wrapper/xpu.h

.github/merge_rules.yaml

@@ -79,6 +79,7 @@
   - .ci/docker/ci_commit_pins/triton.txt
   approved_by:
   - pytorchbot
+  ignore_flaky_failures: false
   mandatory_checks_name:
   - EasyCLA
   - Lint
@@ -90,6 +91,7 @@
   - test/slow_tests.json
   approved_by:
   - pytorchbot
+  ignore_flaky_failures: false
   mandatory_checks_name:
   - EasyCLA
   - Lint
@@ -101,10 +103,12 @@
   - .ci/docker/ci_commit_pins/executorch.txt
   approved_by:
   - pytorchbot
+  ignore_flaky_failures: false
   mandatory_checks_name:
   - EasyCLA
   - Lint
-  - pull
+  - pull / linux-jammy-py3-clang12-executorch / build
+  - pull / linux-jammy-py3-clang12-executorch / test (executorch, 1, 1, linux.2xlarge)
 
 - name: OSS CI / pytorchbot / XLA
   patterns:
@@ -115,7 +119,8 @@
   mandatory_checks_name:
   - EasyCLA
   - Lint
-  - pull
+  - pull / linux-focal-py3_9-clang9-xla / build
+  - pull / linux-focal-py3_9-clang9-xla / test (xla, 1, 1, linux.12xlarge)
 
 - name: Documentation
   patterns:
@@ -242,6 +247,25 @@
   - Lint
   - pull
 
+- name: XPU ATen
+  patterns:
+  - aten/src/ATen/xpu/**
+  - c10/xpu/**
+  - torch/csrc/xpu/**
+  - torch/xpu/**
+  - test/xpu/**
+  - test/test_xpu.py
+  - third_party/xpu.txt
+  - .ci/docker/ci_commit_pins/triton-xpu.txt
+  approved_by:
+  - EikanWang
+  - jgong5
+  - gujinghui
+  mandatory_checks_name:
+  - EasyCLA
+  - Lint
+  - pull
+
 - name: Distributions
   patterns:
   - torch/distributions/**
@@ -334,7 +358,6 @@
   - XiaobingSuper
   - jgong5
   - mingfeima
-  - EikanWang
   mandatory_checks_name:
   - EasyCLA
   - Lint
@@ -367,7 +390,6 @@
   - jgong5
   - vfdev-5
   - leslie-fang-intel
-  - EikanWang
   mandatory_checks_name:
   - EasyCLA
   - Lint
@@ -381,7 +403,6 @@
   approved_by:
   - leslie-fang-intel
   - jgong5
-  - EikanWang
   mandatory_checks_name:
   - EasyCLA
   - Lint
@@ -498,19 +519,6 @@
   - Lint
   - pull
 
-- name: XPU
-  patterns:
-  - '**xpu**'
-  - '**sycl**'
-  approved_by:
-  - EikanWang
-  - jgong5
-  - gujinghui
-  mandatory_checks_name:
-  - EasyCLA
-  - Lint
-  - pull
-
 - name: superuser
   patterns:
   - '*'

.github/nitpicks.yml

@@ -3,10 +3,3 @@
     If you are adding a new function or defaulted argument to native_functions.yaml, you cannot use it from pre-existing Python frontend code until our FC window passes (two weeks).  Split your PR into two PRs, one which adds the new C++ functionality, and one that makes use of it from Python, and land them two weeks apart.  See https://github.com/pytorch/pytorch/wiki/PyTorch's-Python-Frontend-Backward-and-Forward-Compatibility-Policy#forwards-compatibility-fc for more info.
   pathFilter:
     - 'aten/src/ATen/native/native_functions.yaml'
-
-- markdown: |
-    ## Attention! PyTorch one of the C-stable API file was changed
-    You MUST NOT change existing function declarations in this, as this header defines a stable C ABI.  If you need to change the signature for a function, introduce a new v2 version of the function and modify code generation to target the new version of the function.
-  pathFilter:
-    - 'torch/csrc/inductor/aoti_torch/c/*'
-    - 'torch/csrc/inductor/aoti_torch/generated/*'

.github/pytorch-probot.yml

@@ -7,7 +7,6 @@ ciflow_push_tags:
 - ciflow/inductor
 - ciflow/inductor-periodic
 - ciflow/inductor-rocm
-- ciflow/inductor-perf-test-nightly-rocm
 - ciflow/inductor-perf-compare
 - ciflow/inductor-micro-benchmark
 - ciflow/inductor-micro-benchmark-cpu-x86
@@ -17,7 +16,6 @@ ciflow_push_tags:
 - ciflow/nightly
 - ciflow/periodic
 - ciflow/rocm
-- ciflow/rocm-mi300
 - ciflow/s390
 - ciflow/slow
 - ciflow/trunk