[MKLDNN] Check that strides are positive (#153092)

[MKLDNN] Check that strides are positive (#151848)

For pooling ops. Prevents division-by-zero when argument is wrong

Fixes https://github.com/pytorch/pytorch/issues/149274

Pull Request resolved: https://github.com/pytorch/pytorch/pull/151848
Approved by: https://github.com/atalman

(cherry picked from commit 6f327128a99debfb2312ee256523ad6b62f763d6)

Co-authored-by: Nikita Shulga <nshulga@meta.com>

.ci/aarch64_linux/aarch64_ci_build.sh

@@ -3,8 +3,11 @@ set -eux -o pipefail
 
 GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
 
-# cuda arm build for Grace Hopper solely
-export TORCH_CUDA_ARCH_LIST="9.0"
+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 $SCRIPTPATH/aarch64_ci_setup.sh
@@ -17,7 +20,7 @@ cd /
 # on the mounted pytorch repo
 git config --global --add safe.directory /pytorch
 pip install -r /pytorch/requirements.txt
-pip install auditwheel
+pip install auditwheel==6.2.0
 if [ "$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

@@ -5,16 +5,14 @@ set -eux -o pipefail
 # By creating symlinks from desired /opt/python to /usr/local/bin/
 
 NUMPY_VERSION=2.0.2
-PYGIT2_VERSION=1.15.1
-if [[ "$DESIRED_PYTHON"  == "3.13" ]]; then
+if [[ "$DESIRED_PYTHON"  == "3.13" || "$DESIRED_PYTHON" == "3.13t" ]]; 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==${NUMPY_VERSION} pyyaml==6.0.2 scons==4.7.0 ninja==1.11.1 patchelf==0.17.2 pygit2==${PYGIT2_VERSION}
+pip install -q numpy==${NUMPY_VERSION} pyyaml==6.0.2 scons==4.7.0 ninja==1.11.1 patchelf==0.17.2
 
 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

@@ -4,12 +4,9 @@
 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
     """
@@ -42,7 +39,7 @@ def build_ArmComputeLibrary() -> None:
             "clone",
             "https://github.com/ARM-software/ComputeLibrary.git",
             "-b",
-            "v24.09",
+            "v25.02",
             "--depth",
             "1",
             "--shallow-submodules",
@@ -58,7 +55,7 @@ def build_ArmComputeLibrary() -> None:
         shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
 
 
-def update_wheel(wheel_path) -> None:
+def update_wheel(wheel_path, desired_cuda) -> None:
     """
     Update the cuda wheel libraries
     """
@@ -80,7 +77,6 @@ def update_wheel(wheel_path) -> 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",
@@ -100,6 +96,18 @@ def update_wheel(wheel_path) -> 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",
@@ -128,6 +136,9 @@ 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)
@@ -139,7 +150,14 @@ def complete_wheel(folder: str) -> str:
             f"/{folder}/dist/{repaired_wheel_name}",
         )
     else:
-        repaired_wheel_name = wheel_name
+        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}",
+        )
 
     print(f"Copying {repaired_wheel_name} to artifacts")
     shutil.copy2(
@@ -171,22 +189,22 @@ if __name__ == "__main__":
     args = parse_arguments()
     enable_mkldnn = args.enable_mkldnn
     enable_cuda = args.enable_cuda
-    repo = Repository("/pytorch")
-    branch = repo.head.name
-    if branch == "HEAD":
-        branch = "master"
+    branch = check_output(
+        ["git", "rev-parse", "--abbrev-ref", "HEAD"], cwd="/pytorch"
+    ).decode()
 
     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", "master"]:
+    elif branch in ["nightly", "main"]:
         build_date = (
             check_output(["git", "log", "--pretty=format:%cs", "-1"], cwd="/pytorch")
             .decode()
@@ -196,12 +214,11 @@ 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()
@@ -225,6 +242,6 @@ if __name__ == "__main__":
         print("Updating Cuda Dependency")
         filename = os.listdir("/pytorch/dist/")
         wheel_path = f"/pytorch/dist/{filename[0]}"
-        update_wheel(wheel_path)
+        update_wheel(wheel_path, desired_cuda)
     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 Dict, List, Optional, Tuple, Union
+from typing import Optional, Union
 
 import boto3
 
@@ -24,10 +24,12 @@ 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:
@@ -57,7 +59,7 @@ def ec2_instances_by_id(instance_id):
 
 
 def start_instance(
-    key_name, ami=ubuntu18_04_ami, instance_type="t4g.2xlarge", ebs_size: int = 50
+    key_name, ami=ubuntu20_04_ami, instance_type="t4g.2xlarge", ebs_size: int = 50
 ):
     inst = ec2.create_instances(
         ImageId=ami,
@@ -96,7 +98,7 @@ class RemoteHost:
         self.keyfile_path = keyfile_path
         self.login_name = login_name
 
-    def _gen_ssh_prefix(self) -> List[str]:
+    def _gen_ssh_prefix(self) -> list[str]:
         return [
             "ssh",
             "-o",
@@ -108,13 +110,13 @@ class RemoteHost:
         ]
 
     @staticmethod
-    def _split_cmd(args: Union[str, List[str]]) -> List[str]:
+    def _split_cmd(args: Union[str, list[str]]) -> list[str]:
         return args.split() if isinstance(args, str) else args
 
-    def run_ssh_cmd(self, args: Union[str, List[str]]) -> None:
+    def run_ssh_cmd(self, args: Union[str, list[str]]) -> None:
         subprocess.check_call(self._gen_ssh_prefix() + self._split_cmd(args))
 
-    def check_ssh_output(self, args: Union[str, List[str]]) -> str:
+    def check_ssh_output(self, args: Union[str, list[str]]) -> str:
         return subprocess.check_output(
             self._gen_ssh_prefix() + self._split_cmd(args)
         ).decode("utf-8")
@@ -157,7 +159,7 @@ class RemoteHost:
     def using_docker(self) -> bool:
         return self.container_id is not None
 
-    def run_cmd(self, args: Union[str, List[str]]) -> None:
+    def run_cmd(self, args: Union[str, list[str]]) -> None:
         if not self.using_docker():
             return self.run_ssh_cmd(args)
         assert self.container_id is not None
@@ -178,7 +180,7 @@ class RemoteHost:
         if rc != 0:
             raise subprocess.CalledProcessError(rc, docker_cmd)
 
-    def check_output(self, args: Union[str, List[str]]) -> str:
+    def check_output(self, args: Union[str, list[str]]) -> str:
         if not self.using_docker():
             return self.check_ssh_output(args)
         assert self.container_id is not None
@@ -230,7 +232,7 @@ class RemoteHost:
             )
         self.download_file(remote_file, local_file)
 
-    def list_dir(self, path: str) -> List[str]:
+    def list_dir(self, path: str) -> list[str]:
         return self.check_output(["ls", "-1", path]).split("\n")
 
 
@@ -327,7 +329,7 @@ def build_ArmComputeLibrary(host: RemoteHost, git_clone_flags: str = "") -> None
         ]
     )
     host.run_cmd(
-        f"git clone https://github.com/ARM-software/ComputeLibrary.git -b v24.09 {git_clone_flags}"
+        f"git clone https://github.com/ARM-software/ComputeLibrary.git -b v25.02 {git_clone_flags}"
     )
 
     host.run_cmd(f"cd ComputeLibrary && scons Werror=1 -j8 {acl_build_flags}")
@@ -358,7 +360,7 @@ 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):
@@ -681,7 +683,7 @@ 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
     )
@@ -708,7 +710,7 @@ 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")
@@ -759,7 +761,7 @@ def start_build(
         version = host.check_output("cat pytorch/version.txt").strip()[:-2]
         build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version}.dev{build_date} PYTORCH_BUILD_NUMBER=1"
     if branch.startswith(("v1.", "v2.")):
-        build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1:branch.find('-')]} PYTORCH_BUILD_NUMBER=1"
+        build_vars += f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={branch[1 : branch.find('-')]} PYTORCH_BUILD_NUMBER=1"
     if host.using_docker():
         build_vars += " CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000"
     if enable_mkldnn:
@@ -932,9 +934,9 @@ 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)
-    parser.add_argument(
-        "--os", type=str, choices=list(os_amis.keys()), default="ubuntu20_04"
-    )
+    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(
         "--python-version",
         type=str,
@@ -964,7 +966,13 @@ def parse_arguments():
 
 if __name__ == "__main__":
     args = parse_arguments()
-    ami = os_amis[args.os]
+    ami = (
+        args.ami
+        if args.ami is not None
+        else os_amis[args.os]
+        if args.os is not None
+        else ubuntu20_04_ami
+    )
     keyfile_path, key_name = compute_keyfile_path(args.key_name)
 
     if args.list_instances:

.ci/docker/build.sh

@@ -1,4 +1,8 @@
 #!/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
 
@@ -86,30 +90,20 @@ 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 "$image" in
-  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.4.1
+  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc11)
+    CUDA_VERSION=12.6.3
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
-    PROTOBUF=yes
-    DB=yes
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    CONDA_CMAKE=yes
-    TRITON=yes
-    ;;
-  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.1.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
+    GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
     VISION=yes
@@ -134,36 +128,6 @@ case "$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
@@ -194,8 +158,8 @@ case "$image" in
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
-    CUDA_VERSION=11.8.0
+  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9)
+    CUDA_VERSION=12.6.3
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
@@ -208,8 +172,53 @@ case "$image" in
     CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-focal-cuda12.1-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.1.1
+  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
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
@@ -264,7 +273,7 @@ case "$image" in
     ;;
   pytorch-linux-focal-rocm-n-1-py3)
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=9
+    GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
     VISION=yes
@@ -272,10 +281,14 @@ case "$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=9
+    GCC_VERSION=11
     PROTOBUF=yes
     DB=yes
     VISION=yes
@@ -283,6 +296,10 @@ case "$image" in
     NINJA_VERSION=1.9.0
     CONDA_CMAKE=yes
     TRITON=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    INDUCTOR_BENCHMARKS=yes
     ;;
   pytorch-linux-jammy-xpu-2024.0-py3)
     ANACONDA_PYTHON_VERSION=3.9
@@ -368,7 +385,7 @@ case "$image" in
     EXECUTORCH=yes
     ;;
   pytorch-linux-jammy-py3.12-halide)
-    CUDA_VERSION=12.4
+    CUDA_VERSION=12.6
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
     CONDA_CMAKE=yes
@@ -376,7 +393,7 @@ case "$image" in
     TRITON=yes
     ;;
   pytorch-linux-jammy-py3.12-triton-cpu)
-    CUDA_VERSION=12.4
+    CUDA_VERSION=12.6
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
     CONDA_CMAKE=yes

.ci/docker/ci_commit_pins/executorch.txt

@@ -1 +1 @@
-a29b208a06ab378bb29ab1aa68932e412f8e09f1
+01a22b6f16d117454b7d21ebdc691b0785b84a7f

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

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

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

@@ -0,0 +1 @@
+v2.26.2-1

.ci/docker/ci_commit_pins/timm.txt

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

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

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

.ci/docker/ci_commit_pins/triton.txt

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

.ci/docker/common/install_acl.sh

@@ -1,6 +1,6 @@
 set -euo pipefail
 
-readonly version=v24.04
+readonly version=v25.02
 readonly src_host=https://github.com/ARM-software
 readonly src_repo=ComputeLibrary
 

.ci/docker/common/install_base.sh

@@ -32,8 +32,12 @@ 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 v0.9.0
+  git clone https://github.com/mozilla/sccache -b v0.9.1
   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==0.3.28=*openmp*"
+    conda_install "openblas==0.3.29=*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=v2.21.5-1
+NCCL_VERSION=v2.26.2-1
 CUDNN_VERSION=9.5.1.17
 
 function install_cusparselt_040 {
@@ -16,17 +16,6 @@ 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
@@ -51,6 +40,7 @@ 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
@@ -83,39 +73,6 @@ 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"
@@ -214,37 +171,6 @@ 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"
   #####################################################################################
@@ -313,18 +239,52 @@ 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

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

.ci/docker/common/install_cudnn.sh

@@ -4,7 +4,9 @@ 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} == "12.6" ]]; then
+    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
         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

@@ -5,7 +5,15 @@ set -ex
 # cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
 mkdir tmp_cusparselt && cd tmp_cusparselt
 
-if [[ ${CUDA_VERSION:0:4} =~ ^12\.[2-6]$ ]]; then
+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 [[ ${CUDA_VERSION:0:4} == "12.4" ]]; then
     arch_path='sbsa'
     export TARGETARCH=${TARGETARCH:-$(uname -m)}
     if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
@@ -13,17 +21,11 @@ if [[ ${CUDA_VERSION:0:4} =~ ^12\.[2-6]$ ]]; 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

@@ -37,7 +37,12 @@ install_conda_dependencies() {
 
 install_pip_dependencies() {
   pushd executorch
-  as_jenkins bash install_requirements.sh --pybind xnnpack
+  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
+
   popd
 }
 
@@ -48,7 +53,7 @@ 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 cmake || true
+  as_jenkins .ci/scripts/setup-linux.sh --build-tool cmake || true
   popd
 }
 

.ci/docker/common/install_ninja.sh

@@ -4,10 +4,15 @@ set -ex
 
 [ -n "$NINJA_VERSION" ]
 
-url="https://github.com/ninja-build/ninja/releases/download/v${NINJA_VERSION}/ninja-linux.zip"
+arch=$(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
 
 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==1.16.2
-pip_install onnxscript==0.1.0.dev20241124 --no-deps
+pip_install onnx==1.17.0
+pip_install onnxscript==0.2.2 --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.AutoModel.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoTokenizer.from_pretrained("sshleifer/tiny-gpt2"); transformers.AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3");' > "${IMPORT_SCRIPT_FILENAME}"
+as_jenkins echo 'import transformers; transformers.GPTJForCausalLM.from_pretrained("hf-internal-testing/tiny-random-gptj");' > "${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 v0.3.28 --depth 1 --shallow-submodules
+git clone https://github.com/OpenMathLib/OpenBLAS.git -b v0.3.29 --depth 1 --shallow-submodules
 
 
 OPENBLAS_BUILD_FLAGS="

.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 -e .
+  CXX=g++-9 pip_install .
 elif [ -n "${UBUNTU_VERSION}" ] && [ -n "${CLANG_VERSION}" ]; then
   # Triton needs <filesystem> which surprisingly is not available with clang-9 toolchain
   add-apt-repository -y ppa:ubuntu-toolchain-r/test
   apt-get install -y g++-9
 
-  CXX=g++-9 pip_install -e .
+  CXX=g++-9 pip_install .
 else
-  pip_install -e .
+  pip_install .
 fi
 
 if [ -n "${CONDA_CMAKE}" ]; then

.ci/docker/common/install_ucc.sh

@@ -8,6 +8,12 @@ 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
@@ -19,6 +25,7 @@ function install_ucx() {
   ./configure --prefix=$UCX_HOME      \
       --enable-mt                     \
       --with-cuda=$with_cuda          \
+      --with-rocm=$with_rocm          \
       --enable-profiling              \
       --enable-stats
   time make -j
@@ -36,12 +43,29 @@ 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="${NVCC_GENCODE}"
+    --with-nvcc-gencode="${NVCC_GENCODE}" \
+    --with-rocm=$with_rocm                \
+    --with-rocm-arch="${HIP_OFFLOAD}"
   time make -j
   sudo make install
 

.ci/docker/common/install_xpu.sh

@@ -47,6 +47,9 @@ 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
@@ -82,6 +85,9 @@ 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

@@ -56,11 +56,6 @@ 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
@@ -71,6 +66,11 @@ 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}

.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:${GPU_ARCH_VERSION}-complete
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx1030;gfx1100;gfx1101;gfx942"
+        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
         DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}"
         ;;
     *)

.ci/docker/manywheel/Dockerfile_2014

@@ -1,153 +0,0 @@
-# syntax = docker/dockerfile:experimental
-ARG ROCM_VERSION=3.7
-ARG BASE_CUDA_VERSION=10.2
-ARG GPU_IMAGE=nvidia/cuda:${BASE_CUDA_VERSION}-devel-centos7
-FROM quay.io/pypa/manylinux2014_x86_64 as base
-
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-
-RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
-RUN yum install -y wget curl perl util-linux xz bzip2 git patch which perl zlib-devel
-RUN yum install -y yum-utils centos-release-scl sudo
-RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
-RUN yum install -y devtoolset-7-gcc devtoolset-7-gcc-c++ devtoolset-7-gcc-gfortran devtoolset-7-binutils
-ENV PATH=/opt/rh/devtoolset-7/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-7/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib:$LD_LIBRARY_PATH
-
-# cmake
-RUN yum install -y cmake3 && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-FROM base as openssl
-# Install openssl (this must precede `build python` step)
-# (In order to have a proper SSL module, Python is compiled
-# against a recent openssl [see env vars above], which is linked
-# statically. We delete openssl afterwards.)
-ADD ./common/install_openssl.sh install_openssl.sh
-RUN bash ./install_openssl.sh && rm install_openssl.sh
-
-
-
-# remove unncessary python versions
-RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
-RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
-RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
-RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
-
-FROM base as cuda
-ARG BASE_CUDA_VERSION=10.2
-# Install CUDA
-ADD ./common/install_cuda.sh install_cuda.sh
-RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh
-
-FROM base as intel
-# MKL
-ADD ./common/install_mkl.sh install_mkl.sh
-RUN bash ./install_mkl.sh && rm install_mkl.sh
-
-FROM base as magma
-ARG BASE_CUDA_VERSION=10.2
-# Install magma
-ADD ./common/install_magma.sh install_magma.sh
-RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
-
-FROM base as jni
-# Install java jni header
-ADD ./common/install_jni.sh install_jni.sh
-ADD ./java/jni.h jni.h
-RUN bash ./install_jni.sh && rm install_jni.sh
-
-FROM base as libpng
-# Install libpng
-ADD ./common/install_libpng.sh install_libpng.sh
-RUN bash ./install_libpng.sh && rm install_libpng.sh
-
-FROM ${GPU_IMAGE} as common
-RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
-RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-RUN yum install -y \
-        aclocal \
-        autoconf \
-        automake \
-        bison \
-        bzip2 \
-        curl \
-        diffutils \
-        file \
-        git \
-        make \
-        patch \
-        perl \
-        unzip \
-        util-linux \
-        wget \
-        which \
-        xz \
-        yasm
-RUN yum install -y \
-    https://repo.ius.io/ius-release-el7.rpm \
-    https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
-
-RUN yum swap -y git git236-core
-# git236+ would refuse to run git commands in repos owned by other users
-# Which causes version check to fail, as pytorch repo is bind-mounted into the image
-# Override this behaviour by treating every folder as safe
-# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
-RUN git config --global --add safe.directory "*"
-
-ENV SSL_CERT_FILE=/opt/_internal/certs.pem
-# Install LLVM version
-COPY --from=openssl            /opt/openssl                          /opt/openssl
-COPY --from=base               /opt/python                           /opt/python
-COPY --from=base               /opt/_internal                        /opt/_internal
-COPY --from=base               /usr/local/bin/auditwheel             /usr/local/bin/auditwheel
-COPY --from=intel              /opt/intel                            /opt/intel
-COPY --from=base               /usr/local/bin/patchelf               /usr/local/bin/patchelf
-COPY --from=libpng             /usr/local/bin/png*                   /usr/local/bin/
-COPY --from=libpng             /usr/local/bin/libpng*                /usr/local/bin/
-COPY --from=libpng             /usr/local/include/png*               /usr/local/include/
-COPY --from=libpng             /usr/local/include/libpng*            /usr/local/include/
-COPY --from=libpng             /usr/local/lib/libpng*                /usr/local/lib/
-COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/lib/pkgconfig
-COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
-
-FROM common as cpu_final
-ARG BASE_CUDA_VERSION=10.2
-RUN yum install -y yum-utils centos-release-scl
-RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
-RUN yum install -y devtoolset-7-gcc devtoolset-7-gcc-c++ devtoolset-7-gcc-gfortran devtoolset-7-binutils
-ENV PATH=/opt/rh/devtoolset-7/root/usr/bin:$PATH
-ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-7/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib:$LD_LIBRARY_PATH
-
-# cmake
-RUN yum install -y cmake3 && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-
-# ninja
-RUN yum install -y http://repo.okay.com.mx/centos/7/x86_64/release/okay-release-1-1.noarch.rpm
-RUN yum install -y ninja-build
-
-FROM cpu_final as cuda_final
-RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=cuda     /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
-COPY --from=magma    /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
-
-FROM common as rocm_final
-ARG ROCM_VERSION=3.7
-# Install ROCm
-ADD ./common/install_rocm.sh install_rocm.sh
-RUN bash ./install_rocm.sh ${ROCM_VERSION} && rm install_rocm.sh
-# cmake is already installed inside the rocm base image, but both 2 and 3 exist
-# cmake3 is needed for the later MIOpen custom build, so that step is last.
-RUN yum install -y cmake3 && \
-    rm -f /usr/bin/cmake && \
-    ln -s /usr/bin/cmake3 /usr/bin/cmake
-ADD ./common/install_miopen.sh install_miopen.sh
-RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh

.ci/docker/manywheel/Dockerfile_2_28_aarch64

@@ -38,6 +38,12 @@ 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"
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11 --build-arg NINJA_VERSION=1.12.1"
         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"
+        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
         DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
         ;;
     xpu)
@@ -121,7 +121,8 @@ fi
 (
     set -x
 
-    if [ "$(uname -m)" != "s390x" ]; then
+    # Only activate this if in CI
+    if [ "$(uname -m)" != "s390x" ] && [ -v CI ]; then
         # TODO: Remove LimitNOFILE=1048576 patch once https://github.com/pytorch/test-infra/issues/5712
         # is resolved. This patch is required in order to fix timing out of Docker build on Amazon Linux 2023.
         sudo sed -i s/LimitNOFILE=infinity/LimitNOFILE=1048576/ /usr/lib/systemd/system/docker.service
@@ -139,7 +140,7 @@ fi
         "${TOPDIR}/.ci/docker/"
 )
 
-GITHUB_REF=${GITHUB_REF:-$(git symbolic-ref -q HEAD || git describe --tags --exact-match)}
+GITHUB_REF=${GITHUB_REF:-"dev")}
 GIT_BRANCH_NAME=${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.askapache.com/download
+CURL_DOWNLOAD_URL=https://curl.se/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==1.13.0
+mypy==1.14.0
 # Pin MyPy version because new errors are likely to appear with each release
 #Description: linter
-#Pinned versions: 1.10.0
+#Pinned versions: 1.14.0
 #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==3.1.5
+jinja2==3.1.6
 #Description: jinja2 template engine
 #Pinned versions: 3.1.4
 #test that import:
@@ -329,7 +329,7 @@ lxml==5.3.0
 
 PyGithub==2.3.0
 
-sympy==1.13.1 ; python_version >= "3.9"
+sympy==1.13.3
 #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==0.1.0.dev20240817
+onnxscript==0.2.2
 #Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
@@ -362,6 +362,7 @@ pwlf==2.2.1 ; python_version >= "3.8"
 # To build PyTorch itself
 astunparse
 PyYAML
+pyzstd
 setuptools
 
 ninja==1.11.1 ; platform_machine == "aarch64"
@@ -371,3 +372,8 @@ 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 @@
-3.2.0
+3.3.0

.ci/docker/ubuntu-rocm/Dockerfile

@@ -14,21 +14,20 @@ 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
@@ -39,6 +38,11 @@ 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
@@ -85,6 +89,32 @@ 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 "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
+RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
+
 # (optional) Install non-default CMake version
 ARG CMAKE_VERSION
 COPY ./common/install_cmake.sh install_cmake.sh
@@ -107,17 +137,17 @@ COPY triton_version.txt triton_version.txt
 RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
 RUN rm install_triton.sh common_utils.sh triton.txt triton_version.txt
 
-# 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="${CUDA_ARCH_LIST}" \
-	"pytorch/manylinux-builder:cuda${DESIRED_CUDA}-main" \
+	"pytorch/manylinux2_28-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:
@@ -26,6 +26,12 @@ 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:
@@ -36,11 +42,6 @@ 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

@@ -14,6 +14,7 @@ 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 "$CMAKE_ARGS" ]]; then
@@ -52,8 +53,12 @@ cuda_version_nodot=$(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+PTX"
+        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
         EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
     12.4)
@@ -114,7 +119,16 @@ if [[ $USE_CUSPARSELT == "1" && $CUDA_VERSION == "11.8" ]]; then
         )
 fi
 
-if [[ $CUDA_VERSION == "12.4" || $CUDA_VERSION == "12.6" ]]; then
+
+# 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
     export USE_STATIC_CUDNN=0
     # Try parallelizing nvcc as well
     export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"
@@ -155,6 +169,16 @@ if [[ $CUDA_VERSION == "12.4" || $CUDA_VERSION == "12.6" ]]; 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=(
@@ -171,6 +195,11 @@ if [[ $CUDA_VERSION == "12.4" || $CUDA_VERSION == "12.6" ]]; then
             '$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/pytorch/build.sh

@@ -173,6 +173,7 @@ 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
@@ -191,7 +192,7 @@ 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) ]]; then
+if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ 1 -eq $(echo "${TORCH_CUDA_ARCH_LIST} >= 8.0" | bc) ]] && [ -z "$MAX_JOBS_OVERRIDE" ]; then
   echo "WARNING: FlashAttention files require large amounts of memory to build and will OOM"
   echo "Setting MAX_JOBS=(nproc-2)/3 to reduce memory usage"
   export MAX_JOBS="$(( $(nproc --ignore=2) / 3 ))"
@@ -377,8 +378,10 @@ else
     # This is an attempt to mitigate flaky libtorch build OOM error. By default, the build parallelization
     # is set to be the number of CPU minus 2. So, let's try a more conservative value here. A 4xlarge has
     # 16 CPUs
-    MAX_JOBS=$(nproc --ignore=4)
-    export MAX_JOBS
+    if [ -z "$MAX_JOBS_OVERRIDE" ]; then
+      MAX_JOBS=$(nproc --ignore=4)
+      export MAX_JOBS
+    fi
 
     # 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" == 'conda' || "$PACKAGE_TYPE" == 'manywheel')]]; then
+if [[ "$(uname)" == 'Linux' &&  "$PACKAGE_TYPE" == 'manywheel' ]]; then
   pushd /tmp
   python -c "import torch; exit(0 if torch.compiled_with_cxx11_abi() else (0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi1011' else 1))"
   popd

.ci/pytorch/common_utils.sh

@@ -169,30 +169,40 @@ 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
 
-  # 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 [[ "$IS_A100_RUNNER" == "1" ]]; then
-    unset CMAKE_CUDA_COMPILER_LAUNCHER
-    sudo mv /opt/cache/bin /opt/cache/bin-backup
-  fi
+  if [[ "$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
 
-  # 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 [[ "$IS_A100_RUNNER" == "1" ]]; then
-    export CMAKE_CUDA_COMPILER_LAUNCHER=/opt/cache/bin/sccache
-    sudo mv /opt/cache/bin-backup /opt/cache/bin
+    pip_install tabulate  # needed for newer fbgemm
+    pip_install patchelf  # needed for rocm fbgemm
+    git clone --recursive https://github.com/pytorch/fbgemm
+    pushd fbgemm/fbgemm_gpu
+    git checkout "${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}"
   fi
 }
 
 function clone_pytorch_xla() {
   if [[ ! -d ./xla ]]; then
-    git clone --recursive --quiet https://github.com/pytorch/xla.git
+    git clone --recursive -b r2.7 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)"
@@ -216,6 +226,11 @@ function checkout_install_torchbench() {
     # to install and test other models
     python install.py --continue_on_fail
   fi
+
+  # TODO (huydhn): transformers-4.44.2 added by https://github.com/pytorch/benchmark/pull/2488
+  # is regressing speedup metric. This needs to be investigated further
+  pip install transformers==4.38.1
+
   echo "Print all dependencies after TorchBench is installed"
   python -mpip freeze
   popd

.ci/pytorch/macos-test.sh

@@ -18,6 +18,9 @@ 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 'conda' or 'manywheel' or 'libtorch'"
+    echo "The env variable PACKAGE_TYPE must be set to 'manywheel' or 'libtorch'"
     echo "The env variable DESIRED_PYTHON must be set like '2.7mu' or '3.6m' etc"
     echo "The env variable DESIRED_CUDA must be set like 'cpu' or 'cu80' etc"
     exit 1

.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, List, Tuple
+from typing import Any
 
 
 # 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

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

.ci/pytorch/smoke_test/smoke_test.py

@@ -6,6 +6,7 @@ import re
 import subprocess
 import sys
 from pathlib import Path
+from tempfile import NamedTemporaryFile
 
 import torch
 import torch._dynamo
@@ -161,6 +162,36 @@ 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:
@@ -381,6 +412,7 @@ def main() -> None:
     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

@@ -46,6 +46,9 @@ BUILD_BIN_DIR="$BUILD_DIR"/bin
 SHARD_NUMBER="${SHARD_NUMBER:=1}"
 NUM_TEST_SHARDS="${NUM_TEST_SHARDS:=1}"
 
+# enable debug asserts in serialization
+export TORCH_SERIALIZATION_DEBUG=1
+
 export VALGRIND=ON
 # export TORCH_INDUCTOR_INSTALL_GXX=ON
 if [[ "$BUILD_ENVIRONMENT" == *clang9* || "$BUILD_ENVIRONMENT" == *xpu* ]]; then
@@ -174,6 +177,9 @@ 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
@@ -308,6 +314,13 @@ 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
@@ -411,7 +424,10 @@ 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 --verbose
+  python test/run_test.py \
+    --include inductor/test_torchinductor inductor/test_max_autotune inductor/test_cpu_repro \
+    --verbose
+  python test/run_test.py --inductor --include test_torch -k 'take' --verbose
 
   # Run inductor benchmark tests with cpp wrapper.
   # Skip benchmark tests if it's in rerun-disabled-mode.
@@ -424,7 +440,7 @@ 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/inductor_timm_training.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}inductor_timm_training.csv"
 
     python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
       --bfloat16 --inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
@@ -434,7 +450,7 @@ test_inductor_cpp_wrapper_shard() {
       --bfloat16 --inference --inductor --only moco --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
     python benchmarks/dynamo/check_accuracy.py \
       --actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/inductor_torchbench_inference.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}inductor_torchbench_inference.csv"
   fi
 }
 
@@ -467,6 +483,8 @@ 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
@@ -481,6 +499,59 @@ 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 "$TEST_REPORTS_DIR"
@@ -509,6 +580,10 @@ test_perf_for_dashboard() {
     test_inductor_set_cpu_affinity
   elif [[ "${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 "${modes[@]}"; do
@@ -625,16 +700,16 @@ test_single_dynamo_benchmark() {
       TEST_CONFIG=${TEST_CONFIG//_avx512/}
     fi
     python "benchmarks/dynamo/$suite.py" \
-      --ci --accuracy --timing --explain \
+      --ci --accuracy --timing --explain --print-compilation-time \
       "${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/${TEST_CONFIG}_${name}.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}${TEST_CONFIG}_${name}.csv"
     python benchmarks/dynamo/check_graph_breaks.py \
       --actual "$TEST_REPORTS_DIR/${name}_$suite.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/${TEST_CONFIG}_${name}.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}${TEST_CONFIG}_${name}.csv"
   fi
 }
 
@@ -657,7 +732,7 @@ test_inductor_halide() {
 }
 
 test_inductor_triton_cpu() {
-  python test/run_test.py --include inductor/test_triton_cpu_backend.py --verbose
+  python test/run_test.py --include inductor/test_triton_cpu_backend.py inductor/test_torchinductor_strided_blocks.py --verbose
   assert_git_not_dirty
 }
 
@@ -687,6 +762,8 @@ 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" "$shard_id" --training --amp "$@"
@@ -721,7 +798,7 @@ 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_$test.csv" \
-      --expected "benchmarks/dynamo/ci_expected_accuracy/inductor_huggingface_training.csv"
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}inductor_huggingface_training.csv"
   done
 }
 
@@ -1096,8 +1173,9 @@ 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_deps_pytorch_xla $XLA_DIR $USE_CACHE
+  retry install_pre_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
 }
 
@@ -1404,7 +1482,7 @@ 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 cmake
+  bash .ci/scripts/setup-linux.sh --build-tool cmake
 
   echo "Run ExecuTorch unit tests"
   pytest -v -n auto
@@ -1428,7 +1506,7 @@ 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_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
         --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 
   # Dynamo tests
@@ -1496,6 +1574,16 @@ 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 [[ "${TEST_CONFIG}" == *cpu* ]]; then
     install_torchaudio cpu
@@ -1551,6 +1639,7 @@ elif [[ "${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

@@ -0,0 +1,41 @@
+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

@@ -0,0 +1,13 @@
+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

@@ -18,6 +18,9 @@ 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

@@ -0,0 +1,31 @@
+@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

@@ -0,0 +1,41 @@
+@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

@@ -0,0 +1,37 @@
+:: 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

@@ -0,0 +1,33 @@
+@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

@@ -0,0 +1,46 @@
+@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

@@ -0,0 +1,44 @@
+@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

@@ -0,0 +1,33 @@
+@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

@@ -0,0 +1,33 @@
+@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

@@ -0,0 +1,22 @@
+:: 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

@@ -0,0 +1,101 @@
+@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

@@ -0,0 +1,60 @@
+@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

@@ -0,0 +1,49 @@
+@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

@@ -9,12 +9,13 @@ 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" == "3.8" 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
+    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
     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

@@ -0,0 +1,59 @@
+@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

@@ -9,7 +9,8 @@ if "%CUDA_VERSION%" == "xpu" (
     exit /b 0
 )
 
-set SRC_DIR=%NIGHTLIES_PYTORCH_ROOT%
+set SRC_DIR=%~dp0\..
+
 if not exist "%SRC_DIR%\temp_build" mkdir "%SRC_DIR%\temp_build"
 
 set /a CUDA_VER=%CUDA_VERSION%
@@ -23,9 +24,9 @@ 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
@@ -111,6 +112,33 @@ 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

@@ -27,7 +27,6 @@ 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"
@@ -37,6 +36,7 @@ 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"
@@ -47,6 +47,13 @@ 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
@@ -55,85 +62,39 @@ 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 TargetDir=%CD%\Python
+start /wait "" python-amd64.exe /quiet InstallAllUsers=1 PrependPath=0 Include_test=0 %ADDITIONAL_OPTIONS% TargetDir=%CD%\Python
 if errorlevel 1 exit /b 1
 
 set "PATH=%CD%\Python%PYTHON_VERSION%\Scripts;%CD%\Python;%PATH%"
-
-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 "%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 errorlevel 1 exit /b 1
 
-for /F "delims=" %%i in ('where /R "%PYTORCH_FINAL_PACKAGE_DIR:/=\%" *.whl') do pip install "%%i"
+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%
 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 -c "import torch"
+%PYTHON_EXEC% -c "import torch"
 if ERRORLEVEL 1 exit /b 1
 
 echo Checking that MKL is available
-python -c "import torch; exit(0 if torch.backends.mkl.is_available() else 1)"
+%PYTHON_EXEC% -c "import torch; exit(0 if torch.backends.mkl.is_available() else 1)"
 if ERRORLEVEL 1 exit /b 1
 
 if "%NVIDIA_GPU_EXISTS%" == "0" (
@@ -142,24 +103,24 @@ if "%NVIDIA_GPU_EXISTS%" == "0" (
 )
 
 echo Checking that CUDA archs are setup correctly
-python -c "import torch; torch.randn([3,5]).cuda()"
+%PYTHON_EXEC% -c "import torch; torch.randn([3,5]).cuda()"
 if ERRORLEVEL 1 exit /b 1
 
 echo Checking that magma is available
-python -c "import torch; torch.rand(1).cuda(); exit(0 if torch.cuda.has_magma else 1)"
+%PYTHON_EXEC% -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 -c "import torch; exit(0 if torch.backends.cudnn.is_available() else 1)"
+%PYTHON_EXEC% -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 %PYTORCH_ROOT%\.ci\pytorch\test_example_code\rnn_smoke.py
+%PYTHON_EXEC% %PYTORCH_ROOT%\.ci\pytorch\test_example_code\rnn_smoke.py
 
 if ERRORLEVEL 1 exit /b 1
 
 echo Checking that basic CNN works
-python %PYTORCH_ROOT%\.ci\pytorch\test_example_code\cnn_smoke.py
+%PYTHON_EXEC% %PYTORCH_ROOT%\.ci\pytorch\test_example_code\cnn_smoke.py
 if ERRORLEVEL 1 exit /b 1
 
 goto end
@@ -167,7 +128,6 @@ goto end
 :libtorch
 echo "install and test libtorch"
 
-if "%VC_YEAR%" == "2019" powershell internal\vs2019_install.ps1
 if "%VC_YEAR%" == "2022" powershell internal\vs2022_install.ps1
 
 if ERRORLEVEL 1 exit /b 1
@@ -179,10 +139,6 @@ pushd tmp\libtorch
 
 set VC_VERSION_LOWER=17
 set VC_VERSION_UPPER=18
-IF "%VC_YEAR%" == "2019" (
-    set VC_VERSION_LOWER=16
-    set VC_VERSION_UPPER=17
-)
 
 for /f "usebackq tokens=*" %%i in (`"%ProgramFiles(x86)%\Microsoft Visual Studio\Installer\vswhere.exe" -legacy -products * -version [%VC_VERSION_LOWER%^,%VC_VERSION_UPPER%^) -property installationPath`) do (
     if exist "%%i" if exist "%%i\VC\Auxiliary\Build\vcvarsall.bat" (

.ci/pytorch/windows/internal/static_lib_test.bat

@@ -70,7 +70,6 @@ echo "install and test libtorch"
 pip install cmake
 echo "installing cmake"
 
-if "%VC_YEAR%" == "2019" powershell internal\vs2019_install.ps1
 if "%VC_YEAR%" == "2022" powershell internal\vs2022_install.ps1
 
 if ERRORLEVEL 1 exit /b 1
@@ -83,10 +82,6 @@ pushd tmp\libtorch
 
 set VC_VERSION_LOWER=17
 set VC_VERSION_UPPER=18
-IF "%VC_YEAR%" == "2019" (
-    set VC_VERSION_LOWER=16
-    set VC_VERSION_UPPER=17
-)
 
 for /f "usebackq tokens=*" %%i in (`"%ProgramFiles(x86)%\Microsoft Visual Studio\Installer\vswhere.exe" -legacy -products * -version [%VC_VERSION_LOWER%^,%VC_VERSION_UPPER%^) -property installationPath`) do (
     if exist "%%i" if exist "%%i\VC\Auxiliary\Build\vcvarsall.bat" (

.ci/pytorch/windows/internal/vc_install_helper.bat

@@ -1,12 +1,8 @@
-if "%VC_YEAR%" == "2019" powershell windows/internal/vs2019_install.ps1
 if "%VC_YEAR%" == "2022" powershell windows/internal/vs2022_install.ps1
 
 set VC_VERSION_LOWER=17
 set VC_VERSION_UPPER=18
-if "%VC_YEAR%" == "2019" (
-    set VC_VERSION_LOWER=16
-    set VC_VERSION_UPPER=17
-)
+
 
 for /f "usebackq tokens=*" %%i in (`"%ProgramFiles(x86)%\Microsoft Visual Studio\Installer\vswhere.exe"  -products Microsoft.VisualStudio.Product.BuildTools -version [%VC_VERSION_LOWER%^,%VC_VERSION_UPPER%^) -property installationPath`) do (
     if exist "%%i" if exist "%%i\VC\Auxiliary\Build\vcvarsall.bat" (

.ci/pytorch/windows/internal/vs2019_install.ps1

@@ -1,48 +0,0 @@
-# https://developercommunity.visualstudio.com/t/install-specific-version-of-vs-component/1142479
-# https://docs.microsoft.com/en-us/visualstudio/releases/2019/history#release-dates-and-build-numbers
-
-# 16.8.6 BuildTools
-$VS_DOWNLOAD_LINK = "https://ossci-windows.s3.us-east-1.amazonaws.com/vs16.8.6_BuildTools.exe"
-$COLLECT_DOWNLOAD_LINK = "https://aka.ms/vscollect.exe"
-$VS_INSTALL_ARGS = @("--nocache","--quiet","--wait", "--add Microsoft.VisualStudio.Workload.VCTools",
-                                                     "--add Microsoft.Component.MSBuild",
-                                                     "--add Microsoft.VisualStudio.Component.Roslyn.Compiler",
-                                                     "--add Microsoft.VisualStudio.Component.TextTemplating",
-                                                     "--add Microsoft.VisualStudio.Component.VC.CoreIde",
-                                                     "--add Microsoft.VisualStudio.Component.VC.Redist.14.Latest",
-                                                     "--add Microsoft.VisualStudio.ComponentGroup.NativeDesktop.Core",
-                                                     "--add Microsoft.VisualStudio.Component.VC.Tools.x86.x64",
-                                                     "--add Microsoft.VisualStudio.ComponentGroup.NativeDesktop.Win81")
-
-curl.exe --retry 3 -kL $VS_DOWNLOAD_LINK --output vs_installer.exe
-if ($LASTEXITCODE -ne 0) {
-    echo "Download of the VS 2019 Version 16.8.5 installer failed"
-    exit 1
-}
-
-if (Test-Path "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswhere.exe") {
-    $existingPath = & "${env:ProgramFiles(x86)}\Microsoft Visual Studio\Installer\vswhere.exe" -products "Microsoft.VisualStudio.Product.BuildTools" -version "[16, 17)" -property installationPath
-    if ($existingPath -ne $null) {
-        if (!${env:CIRCLECI}) {
-            echo "Found correctly versioned existing BuildTools installation in $existingPath"
-            exit 0
-        }
-        echo "Found existing BuildTools installation in $existingPath, keeping it"
-    }
-}
-
-$process = Start-Process "${PWD}\vs_installer.exe" -ArgumentList $VS_INSTALL_ARGS -NoNewWindow -Wait -PassThru
-Remove-Item -Path vs_installer.exe -Force
-$exitCode = $process.ExitCode
-if (($exitCode -ne 0) -and ($exitCode -ne 3010)) {
-    echo "VS 2019 installer exited with code $exitCode, which should be one of [0, 3010]."
-    curl.exe --retry 3 -kL $COLLECT_DOWNLOAD_LINK --output Collect.exe
-    if ($LASTEXITCODE -ne 0) {
-        echo "Download of the VS Collect tool failed."
-        exit 1
-    }
-    Start-Process "${PWD}\Collect.exe" -NoNewWindow -Wait -PassThru
-    New-Item -Path "C:\w\build-results" -ItemType "directory" -Force
-    Copy-Item -Path "C:\Users\${env:USERNAME}\AppData\Local\Temp\vslogs.zip" -Destination "C:\w\build-results\"
-    exit 1
-}

.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/efc86abd-cb77-452e-a03f-a741895b8ece/intel-deep-learning-essentials-2025.0.0.336_offline.exe
+    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_PRODUCT_NAME=intel.oneapi.win.deep-learning-essentials.product
-    set XPU_BUNDLE_VERSION=2025.0.0+335
+    set XPU_BUNDLE_VERSION=2025.0.1+20
     set XPU_BUNDLE_INSTALLED=0
     set XPU_BUNDLE_UNINSTALL=0
     set XPU_EXTRA_URL=NULL
@@ -104,14 +104,6 @@ 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
@@ -128,3 +120,14 @@ 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

@@ -28,11 +28,6 @@ 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

@@ -130,7 +130,19 @@ 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"
@@ -169,18 +181,15 @@ 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 create ${EXTRA_CONDA_INSTALL_FLAGS} -yn "$tmp_env_name" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS}
 source activate "$tmp_env_name"
 
-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
+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
 
-# For USE_DISTRIBUTED=1 on macOS, need libuv and pkg-config to find libuv.
+# For USE_DISTRIBUTED=1 on macOS, need libuv, which is build as part of tensorpipe submodule
 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
@@ -222,10 +231,13 @@ 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 "$BUILD_PYTHONLESS" ]]; then
+if [[ -z "$BUILD_PYTHONLESS" && $RENAME_WHEEL == true  ]]; 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

@@ -30,12 +30,10 @@ fi
 # Pick docker image
 export DOCKER_IMAGE=${DOCKER_IMAGE:-}
 if [[ -z "$DOCKER_IMAGE" ]]; then
-  if [[ "$PACKAGE_TYPE" == conda ]]; then
-    export DOCKER_IMAGE="pytorch/conda-cuda"
-  elif [[ "$DESIRED_CUDA" == cpu ]]; then
-    export DOCKER_IMAGE="pytorch/manylinux:cpu"
+  if [[ "$DESIRED_CUDA" == cpu ]]; then
+    export DOCKER_IMAGE="pytorch/manylinux2_28:cpu"
   else
-    export DOCKER_IMAGE="pytorch/manylinux-builder:${DESIRED_CUDA:2}"
+    export DOCKER_IMAGE="pytorch/manylinux2_28-builder:${DESIRED_CUDA:2}"
   fi
 fi
 
@@ -63,7 +61,7 @@ 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 [[ "$(uname)" == 'Darwin' ]] || [[ "$PACKAGE_TYPE" == conda ]]; then
+if [[ "$(uname)" == 'Darwin' ]]; then
   export PYTORCH_BUILD_VERSION="${BASE_BUILD_VERSION}"
 else
   export PYTORCH_BUILD_VERSION="${BASE_BUILD_VERSION}+$DESIRED_CUDA"
@@ -76,6 +74,12 @@ 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" && "$PYTORCH_BUILD_VERSION" =~ .*dev.* ]]; then
@@ -100,11 +104,11 @@ if [[ "$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.* && $(uname) == "Linux" ]]; then
-    TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}; ${TRITON_CONSTRAINT}"
+if [[ "$PACKAGE_TYPE" =~ .*wheel.* && -n "$PYTORCH_BUILD_VERSION" && "$PYTORCH_BUILD_VERSION" =~ .*xpu.* ]]; then
+    TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}"
     if [[ -n "$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}; ${TRITON_CONSTRAINT}"
+        TRITON_REQUIREMENT="pytorch-triton-xpu==${TRITON_VERSION}+git${TRITON_SHORTHASH}"
     fi
     if [[ -z "${PYTORCH_EXTRA_INSTALL_REQUIREMENTS:-}" ]]; then
         export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${TRITON_REQUIREMENT}"
@@ -149,8 +153,6 @@ export PYTORCH_EXTRA_INSTALL_REQUIREMENTS="${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=${PACKAGE_TYPE:-conda}
+PACKAGE_TYPE=${PACKAGE_TYPE:-wheel}
 
 PKG_DIR=${PKG_DIR:-/tmp/workspace/final_pkgs}
 
@@ -18,10 +18,8 @@ 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
 
@@ -34,10 +32,6 @@ 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
@@ -49,72 +43,33 @@ 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="$2"
-  s3_key_prefix="${pkg_type}/${UPLOAD_CHANNEL}"
+  s3_root_dir="${UPLOAD_BUCKET}/${pkg_type}/${UPLOAD_CHANNEL}"
   if [[ -z ${UPLOAD_SUBFOLDER:-} ]]; then
-    s3_upload_dir="${UPLOAD_BUCKET}/${s3_key_prefix}/"
+    s3_upload_dir="${s3_root_dir}/"
   else
-    s3_key_prefix="${s3_key_prefix}/${UPLOAD_SUBFOLDER}"
-    s3_upload_dir="${UPLOAD_BUCKET}/${s3_key_prefix}/"
+    s3_upload_dir="${s3_root_dir}/${UPLOAD_SUBFOLDER}/"
   fi
   (
     for pkg in ${PKG_DIR}/*.${extension}; do
       (
         set -x
-        ${AWS_S3_CP} --no-progress --acl public-read "${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}" \
-            ${dry_run_arg}
-        fi
+        shm_id=$(sha256sum "${pkg}" | awk '{print $1}')
+        ${AWS_S3_CP} --no-progress --acl public-read "${pkg}" "${s3_upload_dir}" \
+          --metadata "checksum-sha256=${shm_id}"
       )
     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

@@ -0,0 +1,22 @@
+#!/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

@@ -0,0 +1,6 @@
+#!/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

@@ -8,12 +8,12 @@ export CUDA_VERSION="${DESIRED_CUDA/cu/}"
 export USE_SCCACHE=1
 export SCCACHE_BUCKET=ossci-compiler-cache
 export SCCACHE_IGNORE_SERVER_IO_ERROR=1
-export VC_YEAR=2019
+export VC_YEAR=2022
 
 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:"

.circleci/scripts/binary_windows_test.sh

@@ -4,10 +4,9 @@ set -eux -o pipefail
 source "${BINARY_ENV_FILE:-/c/w/env}"
 
 export CUDA_VERSION="${DESIRED_CUDA/cu/}"
-export VC_YEAR=2019
+export VC_YEAR=2022
 
 if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
-    export VC_YEAR=2022
     export XPU_VERSION=2025.0
 fi
 

.clang-tidy

@@ -12,6 +12,7 @@ bugprone-*,
 -bugprone-macro-parentheses,
 -bugprone-lambda-function-name,
 -bugprone-reserved-identifier,
+-bugprone-return-const-ref-from-parameter,
 -bugprone-swapped-arguments,
 clang-analyzer-core.*,
 clang-analyzer-cplusplus.*,
@@ -24,6 +25,7 @@ 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,
@@ -46,6 +48,7 @@ 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,
@@ -55,6 +58,7 @@ 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

@@ -38,6 +38,7 @@ 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

@@ -24,6 +24,10 @@ 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
@@ -44,3 +48,57 @@ 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.
+      #### 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).
 - type: textarea
   attributes:
     label: 🐛 Describe the bug

.github/ISSUE_TEMPLATE/disable-ci-jobs.md

@@ -5,7 +5,7 @@ title: "DISABLED [WORKFLOW_NAME] / [PLATFORM_NAME] / [JOB_NAME]"
 labels: "module: ci"
 ---
 
-> For example, DISABLED pull / win-vs2019-cpu-py3 / test (default). Once
+> For example, DISABLED pull / win-vs2022-cpu-py3 / test (default). Once
 > created, the job will be disabled within 15 minutes. You can check the
 > list of disabled jobs at https://ossci-metrics.s3.amazonaws.com/disabled-jobs.json
 

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

@@ -6,7 +6,7 @@ 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.
+        #### Note: Please write your bug report in English to ensure it can be understood and addressed by the development team.
   - type: markdown
     attributes:
       value: >
@@ -22,6 +22,8 @@ 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

@@ -1,8 +1,10 @@
 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.20_04.4x
-    - linux.20_04.16x
+    - linux.24_04.4x
+    - linux.24_04.16x
     # Organization-wide AWS Linux Runners
     - linux.large
     - linux.2xlarge
@@ -10,7 +12,6 @@ self-hosted-runner:
     - linux.9xlarge.ephemeral
     - am2.linux.9xlarge.ephemeral
     - linux.12xlarge
-    - linux.12xlarge.ephemeral
     - linux.24xlarge
     - linux.24xlarge.ephemeral
     - linux.arm64.2xlarge
@@ -42,6 +43,8 @@ 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

@@ -40,6 +40,11 @@ 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/setup-rocm/action.yml

@@ -99,8 +99,14 @@ runs:
         # 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 /dev/dri --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_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}"

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

@@ -0,0 +1,56 @@
+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 @@
-b6d4675c7aedc53ba04f3f55786aac1de32be6b4
+c670ad81fda266b6598aeeef434583eb98197ae8

.github/ci_commit_pins/fbgemm_rocm.txt

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

.github/ci_commit_pins/torchbench.txt

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

.github/ci_commit_pins/xla.txt

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

.github/labeler.yml

@@ -98,7 +98,7 @@
 - test/distributed/**
 - torch/testing/_internal/distributed/**
 
-"module: distributed_checkpoint":
+"release notes: distributed (checkpoint)":
 - torch/distributed/checkpoint/**
 - test/distributed/checkpoint/**
 
@@ -107,3 +107,8 @@
 - 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

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

.github/nitpicks.yml

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

@@ -7,6 +7,7 @@ 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
@@ -16,6 +17,7 @@ ciflow_push_tags:
 - ciflow/nightly
 - ciflow/periodic
 - ciflow/rocm
+- ciflow/rocm-mi300
 - ciflow/s390
 - ciflow/slow
 - ciflow/trunk

.github/requirements-gha-cache.txt

@@ -5,7 +5,7 @@
 #   functorch/docs/requirements.txt
 #   .ci/docker/requirements-ci.txt
 boto3==1.35.42
-jinja2==3.1.5
+jinja2==3.1.6
 lintrunner==0.10.7
 ninja==1.10.0.post1
 nvidia-ml-py==11.525.84

.github/requirements/pip-requirements-macOS.txt

@@ -19,8 +19,7 @@ pytest-rerunfailures==10.3
 pytest-flakefinder==1.1.0
 pytest-subtests==0.13.1
 scipy==1.10.1
-sympy==1.12.1 ; python_version == "3.8"
-sympy==1.13.1 ; python_version >= "3.9"
+sympy==1.13.3
 unittest-xml-reporting<=3.2.0,>=2.0.0
 xdoctest==1.1.0
 filelock==3.6.0

.github/scripts/build_triton_wheel.py

@@ -52,7 +52,6 @@ def build_triton(
     *,
     version: str,
     commit_hash: str,
-    build_conda: bool = False,
     device: str = "cuda",
     py_version: Optional[str] = None,
     release: bool = False,
@@ -83,55 +82,6 @@ def build_triton(
         else:
             check_call(["git", "checkout", commit_hash], cwd=triton_basedir)
 
-        if build_conda:
-            with open(triton_basedir / "meta.yaml", "w") as meta:
-                print(
-                    f"package:\n  name: torchtriton\n  version: {version}\n",
-                    file=meta,
-                )
-                print("source:\n  path: .\n", file=meta)
-                print(
-                    "build:\n  string: py{{py}}\n  number: 1\n  script: cd python; "
-                    "python setup.py install --record=record.txt\n",
-                    " script_env:\n   - MAX_JOBS\n",
-                    file=meta,
-                )
-                print(
-                    "requirements:\n  host:\n    - python\n    - setuptools\n    - pybind11\n"
-                    "  run:\n    - python\n    - filelock\n    - pytorch\n",
-                    file=meta,
-                )
-                print(
-                    "about:\n  home: https://github.com/openai/triton\n  license: MIT\n  summary:"
-                    " 'A language and compiler for custom Deep Learning operation'",
-                    file=meta,
-                )
-
-            patch_init_py(
-                triton_pythondir / "triton" / "__init__.py",
-                version=f"{version}",
-            )
-            if py_version is None:
-                py_version = f"{sys.version_info.major}.{sys.version_info.minor}"
-            check_call(
-                [
-                    "conda",
-                    "build",
-                    "--python",
-                    py_version,
-                    "-c",
-                    "pytorch-nightly",
-                    "--output-folder",
-                    tmpdir,
-                    ".",
-                ],
-                cwd=triton_basedir,
-                env=env,
-            )
-            conda_path = next(iter(Path(tmpdir).glob("linux-64/torchtriton*.bz2")))
-            shutil.copy(conda_path, Path.cwd())
-            return Path.cwd() / conda_path.name
-
         # change built wheel name and version
         env["TRITON_WHEEL_NAME"] = triton_pkg_name
         if with_clang_ldd:
@@ -172,9 +122,8 @@ def main() -> None:
 
     parser = ArgumentParser("Build Triton binaries")
     parser.add_argument("--release", action="store_true")
-    parser.add_argument("--build-conda", action="store_true")
     parser.add_argument(
-        "--device", type=str, default="cuda", choices=["cuda", "rocm", "xpu"]
+        "--device", type=str, default="cuda", choices=["cuda", "rocm", "xpu", "aarch64"]
     )
     parser.add_argument("--py-version", type=str)
     parser.add_argument("--commit-hash", type=str)
@@ -188,7 +137,6 @@ def main() -> None:
             args.commit_hash if args.commit_hash else read_triton_pin(args.device)
         ),
         version=args.triton_version,
-        build_conda=args.build_conda,
         py_version=args.py_version,
         release=args.release,
         with_clang_ldd=args.with_clang_ldd,

.github/scripts/cherry_pick.py

@@ -3,7 +3,7 @@
 import json
 import os
 import re
-from typing import Any, cast, Dict, List, Optional
+from typing import Any, cast, Optional
 from urllib.error import HTTPError
 
 from github_utils import gh_fetch_url, gh_post_pr_comment, gh_query_issues_by_labels
@@ -67,7 +67,7 @@ def get_release_version(onto_branch: str) -> Optional[str]:
 
 def get_tracker_issues(
     org: str, project: str, onto_branch: str
-) -> List[Dict[str, Any]]:
+) -> list[dict[str, Any]]:
     """
     Find the tracker issue from the repo. The tracker issue needs to have the title
     like [VERSION] Release Tracker following the convention on PyTorch
@@ -117,7 +117,7 @@ def cherry_pick(
                 continue
 
             res = cast(
-                Dict[str, Any],
+                dict[str, Any],
                 post_tracker_issue_comment(
                     org,
                     project,
@@ -220,7 +220,7 @@ def submit_pr(
 
 def post_pr_comment(
     org: str, project: str, pr_num: int, msg: str, dry_run: bool = False
-) -> List[Dict[str, Any]]:
+) -> list[dict[str, Any]]:
     """
     Post a comment on the PR itself to point to the cherry picking PR when success
     or print the error when failure
@@ -255,7 +255,7 @@ def post_tracker_issue_comment(
     classification: str,
     fixes: str,
     dry_run: bool = False,
-) -> List[Dict[str, Any]]:
+) -> list[dict[str, Any]]:
     """
     Post a comment on the tracker issue (if any) to record the cherry pick
     """