ditch const

.bc-linter.yml

@@ -13,4 +13,3 @@ exclude:
   - "**/benchmarks/**"
   - "**/test_*.py"
   - "**/*_test.py"
-  - "tools/**"

.ci/aarch64_linux/README.md

@@ -0,0 +1,19 @@
+# Aarch64 (ARM/Graviton) Support Scripts
+Scripts for building aarch64 PyTorch PIP Wheels. These scripts build the following wheels:
+* torch
+* torchvision
+* torchaudio
+* torchtext
+* torchdata
+## Aarch64_ci_build.sh
+This script is design to support CD operations within PyPi manylinux aarch64 container, and be executed in the container. It prepares the container and then executes __aarch64_wheel_ci_build.py__ to build the wheels. The script "assumes" the PyTorch repo is located at: ```/pytorch``` and will put the wheels into ```/artifacts```.
+### Usage
+```DESIRED_PYTHON=<PythonVersion> aarch64_ci_build.sh```
+
+__NOTE:__ CI build is currently __EXPERMINTAL__
+
+## Build_aarch64_wheel.py
+This app allows a person to build using AWS EC3 resources and requires AWS-CLI and Boto3 with AWS credentials to support building EC2 instances for the wheel builds. Can be used in a codebuild CD or from a local system.
+
+### Usage
+```build_aarch64_wheel.py --key-name <YourPemKey> --use-docker --python 3.8 --branch <RCtag>```

.ci/aarch64_linux/aarch64_ci_build.sh

@@ -0,0 +1,40 @@
+#!/bin/bash
+set -eux -o pipefail
+
+GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
+
+if [[ "$GPU_ARCH_VERSION" == *"12.9"* ]]; then
+    export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;12.0"
+fi
+
+if [[ "$GPU_ARCH_VERSION" == *"13.0"* ]]; then
+    export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;11.0;12.0"
+fi
+
+# Compress the fatbin with -compress-mode=size for CUDA 13
+if [[ "$DESIRED_CUDA" == *"13"* ]]; then
+    export TORCH_NVCC_FLAGS="-compress-mode=size"
+fi
+
+SCRIPTPATH="$( cd -- "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P )"
+source $SCRIPTPATH/aarch64_ci_setup.sh
+
+###############################################################################
+# Run aarch64 builder python
+###############################################################################
+cd /
+# adding safe directory for git as the permissions will be
+# on the mounted pytorch repo
+git config --global --add safe.directory /pytorch
+pip install -r /pytorch/requirements.txt
+pip install auditwheel==6.2.0
+if [ "$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
+    USE_PRIORITIZED_TEXT_FOR_LD=1 python /pytorch/.ci/aarch64_linux/aarch64_wheel_ci_build.py --enable-mkldnn
+else
+    echo "BASE_CUDA_VERSION is set to: $DESIRED_CUDA"
+    export USE_SYSTEM_NCCL=1
+    #USE_PRIORITIZED_TEXT_FOR_LD for enable linker script optimization https://github.com/pytorch/pytorch/pull/121975/files
+    USE_PRIORITIZED_TEXT_FOR_LD=1 python /pytorch/.ci/aarch64_linux/aarch64_wheel_ci_build.py --enable-mkldnn --enable-cuda
+fi

.ci/aarch64_linux/aarch64_ci_setup.sh

@@ -0,0 +1,21 @@
+#!/bin/bash
+set -eux -o pipefail
+
+# This script is used to prepare the Docker container for aarch64_ci_wheel_build.py python script
+# By creating symlinks from desired /opt/python to /usr/local/bin/
+
+NUMPY_VERSION=2.0.2
+if [[ "$DESIRED_PYTHON"  == "3.13" || "$DESIRED_PYTHON" == "3.13t" ]]; then
+    NUMPY_VERSION=2.1.2
+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
+
+for tool in python python3 pip pip3 ninja scons patchelf; do
+    ln -sf ${DESIRED_PYTHON_BIN_DIR}/${tool} /usr/local/bin;
+done
+
+python --version

.ci/aarch64_linux/aarch64_wheel_ci_build.py

@@ -0,0 +1,282 @@
+#!/usr/bin/env python3
+# encoding: UTF-8
+
+import os
+import shutil
+from subprocess import check_call, check_output
+
+
+def list_dir(path: str) -> list[str]:
+    """'
+    Helper for getting paths for Python
+    """
+    return check_output(["ls", "-1", path]).decode().split("\n")
+
+
+def build_ArmComputeLibrary() -> None:
+    """
+    Using ArmComputeLibrary for aarch64 PyTorch
+    """
+    print("Building Arm Compute Library")
+    acl_build_flags = [
+        "debug=0",
+        "neon=1",
+        "opencl=0",
+        "os=linux",
+        "openmp=1",
+        "cppthreads=0",
+        "arch=armv8a",
+        "multi_isa=1",
+        "fixed_format_kernels=1",
+        "build=native",
+    ]
+    acl_install_dir = "/acl"
+    acl_checkout_dir = os.getenv("ACL_SOURCE_DIR", "ComputeLibrary")
+    if os.path.isdir(acl_install_dir):
+        shutil.rmtree(acl_install_dir)
+    if not os.path.isdir(acl_checkout_dir) or not len(os.listdir(acl_checkout_dir)):
+        check_call(
+            [
+                "git",
+                "clone",
+                "https://github.com/ARM-software/ComputeLibrary.git",
+                "-b",
+                "v25.02",
+                "--depth",
+                "1",
+                "--shallow-submodules",
+            ]
+        )
+
+    check_call(
+        ["scons", "Werror=1", f"-j{os.cpu_count()}"] + acl_build_flags,
+        cwd=acl_checkout_dir,
+    )
+    for d in ["arm_compute", "include", "utils", "support", "src", "build"]:
+        shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
+
+
+def replace_tag(filename) -> None:
+    with open(filename) as f:
+        lines = f.readlines()
+    for i, line in enumerate(lines):
+        if line.startswith("Tag:"):
+            lines[i] = line.replace("-linux_", "-manylinux_2_28_")
+            print(f"Updated tag from {line} to {lines[i]}")
+            break
+
+    with open(filename, "w") as f:
+        f.writelines(lines)
+
+
+def package_cuda_wheel(wheel_path, desired_cuda) -> None:
+    """
+    Package the cuda wheel libraries
+    """
+    folder = os.path.dirname(wheel_path)
+    wheelname = os.path.basename(wheel_path)
+    os.mkdir(f"{folder}/tmp")
+    os.system(f"unzip {wheel_path} -d {folder}/tmp")
+    # Common libraries for all CUDA versions
+    common_libs = [
+        # Non-NVIDIA system libraries
+        "/lib64/libgomp.so.1",
+        "/usr/lib64/libgfortran.so.5",
+        "/acl/build/libarm_compute.so",
+        "/acl/build/libarm_compute_graph.so",
+        # Common CUDA libraries (same for all versions)
+        "/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
+        "/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
+        "/usr/local/lib/libnvpl_lapack_core.so.0",
+        "/usr/local/lib/libnvpl_blas_core.so.0",
+        "/usr/local/cuda/extras/CUPTI/lib64/libnvperf_host.so",
+        "/usr/local/cuda/lib64/libcudnn.so.9",
+        "/usr/local/cuda/lib64/libcusparseLt.so.0",
+        "/usr/local/cuda/lib64/libcurand.so.10",
+        "/usr/local/cuda/lib64/libnccl.so.2",
+        "/usr/local/cuda/lib64/libnvshmem_host.so.3",
+        "/usr/local/cuda/lib64/libcudnn_adv.so.9",
+        "/usr/local/cuda/lib64/libcudnn_cnn.so.9",
+        "/usr/local/cuda/lib64/libcudnn_graph.so.9",
+        "/usr/local/cuda/lib64/libcudnn_ops.so.9",
+        "/usr/local/cuda/lib64/libcudnn_engines_runtime_compiled.so.9",
+        "/usr/local/cuda/lib64/libcudnn_engines_precompiled.so.9",
+        "/usr/local/cuda/lib64/libcudnn_heuristic.so.9",
+        "/usr/local/cuda/lib64/libcufile.so.0",
+        "/usr/local/cuda/lib64/libcufile_rdma.so.1",
+        "/usr/local/cuda/lib64/libcusparse.so.12",
+    ]
+
+    # CUDA version-specific libraries
+    if "130" in desired_cuda:
+        version_specific_libs = [
+            "/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.13",
+            "/usr/local/cuda/lib64/libcublas.so.13",
+            "/usr/local/cuda/lib64/libcublasLt.so.13",
+            "/usr/local/cuda/lib64/libcudart.so.13",
+            "/usr/local/cuda/lib64/libcufft.so.12",
+            "/usr/local/cuda/lib64/libcusolver.so.12",
+            "/usr/local/cuda/lib64/libnvJitLink.so.13",
+            "/usr/local/cuda/lib64/libnvrtc.so.13",
+            "/usr/local/cuda/lib64/libnvrtc-builtins.so.13.0",
+        ]
+    elif "12" in desired_cuda:
+        # Get the last character for libnvrtc-builtins version (e.g., "129" -> "9")
+        minor_version = desired_cuda[-1]
+        version_specific_libs = [
+            "/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12",
+            "/usr/local/cuda/lib64/libcublas.so.12",
+            "/usr/local/cuda/lib64/libcublasLt.so.12",
+            "/usr/local/cuda/lib64/libcudart.so.12",
+            "/usr/local/cuda/lib64/libcufft.so.11",
+            "/usr/local/cuda/lib64/libcusolver.so.11",
+            "/usr/local/cuda/lib64/libnvJitLink.so.12",
+            "/usr/local/cuda/lib64/libnvrtc.so.12",
+            f"/usr/local/cuda/lib64/libnvrtc-builtins.so.12.{minor_version}",
+        ]
+
+    # Combine all libraries
+    libs_to_copy = common_libs + version_specific_libs
+
+    # Copy libraries to unzipped_folder/a/lib
+    for lib_path in libs_to_copy:
+        lib_name = os.path.basename(lib_path)
+        shutil.copy2(lib_path, f"{folder}/tmp/torch/lib/{lib_name}")
+        os.system(
+            f"cd {folder}/tmp/torch/lib/; "
+            f"patchelf --set-rpath '$ORIGIN' --force-rpath {folder}/tmp/torch/lib/{lib_name}"
+        )
+
+    # Make sure the wheel is tagged with manylinux_2_28
+    for f in os.scandir(f"{folder}/tmp/"):
+        if f.is_dir() and f.name.endswith(".dist-info"):
+            replace_tag(f"{f.path}/WHEEL")
+            break
+
+    os.mkdir(f"{folder}/cuda_wheel")
+    os.system(f"cd {folder}/tmp/; zip -r {folder}/cuda_wheel/{wheelname} *")
+    shutil.move(
+        f"{folder}/cuda_wheel/{wheelname}",
+        f"{folder}/{wheelname}",
+        copy_function=shutil.copy2,
+    )
+    os.system(f"rm -rf {folder}/tmp/ {folder}/cuda_wheel/")
+
+
+def complete_wheel(folder: str) -> str:
+    """
+    Complete wheel build and put in artifact location
+    """
+    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)
+        repaired_wheel_name = list_dir(f"/{folder}/wheelhouse")[0]
+
+        print(f"Moving {repaired_wheel_name} wheel to /{folder}/dist")
+        os.rename(
+            f"/{folder}/wheelhouse/{repaired_wheel_name}",
+            f"/{folder}/dist/{repaired_wheel_name}",
+        )
+    else:
+        repaired_wheel_name = wheel_name.replace(
+            "linux_aarch64", "manylinux_2_28_aarch64"
+        )
+        print(f"Renaming {wheel_name} wheel to {repaired_wheel_name}")
+        os.rename(
+            f"/{folder}/dist/{wheel_name}",
+            f"/{folder}/dist/{repaired_wheel_name}",
+        )
+
+    print(f"Copying {repaired_wheel_name} to artifacts")
+    shutil.copy2(
+        f"/{folder}/dist/{repaired_wheel_name}", f"/artifacts/{repaired_wheel_name}"
+    )
+
+    return repaired_wheel_name
+
+
+def parse_arguments():
+    """
+    Parse inline arguments
+    """
+    from argparse import ArgumentParser
+
+    parser = ArgumentParser("AARCH64 wheels python CD")
+    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("--enable-mkldnn", action="store_true")
+    parser.add_argument("--enable-cuda", action="store_true")
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    """
+    Entry Point
+    """
+    args = parse_arguments()
+    enable_mkldnn = args.enable_mkldnn
+    enable_cuda = args.enable_cuda
+    branch = check_output(
+        ["git", "rev-parse", "--abbrev-ref", "HEAD"], cwd="/pytorch"
+    ).decode()
+
+    print("Building PyTorch wheel")
+    build_vars = "CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000 "
+    # MAX_JOB=5 is not required for CPU backend (see commit 465d98b)
+    if enable_cuda:
+        build_vars += "MAX_JOBS=5 "
+
+    override_package_version = os.getenv("OVERRIDE_PACKAGE_VERSION")
+    desired_cuda = os.getenv("DESIRED_CUDA")
+    if override_package_version is not None:
+        version = override_package_version
+        build_vars += (
+            f"BUILD_TEST=0 PYTORCH_BUILD_VERSION={version} PYTORCH_BUILD_NUMBER=1 "
+        )
+    elif branch in ["nightly", "main"]:
+        build_date = (
+            check_output(["git", "log", "--pretty=format:%cs", "-1"], cwd="/pytorch")
+            .decode()
+            .replace("-", "")
+        )
+        version = (
+            check_output(["cat", "version.txt"], cwd="/pytorch").decode().strip()[:-2]
+        )
+        if enable_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 "
+
+    if enable_mkldnn:
+        build_ArmComputeLibrary()
+        print("build pytorch with mkldnn+acl backend")
+        build_vars += (
+            "USE_MKLDNN=ON USE_MKLDNN_ACL=ON "
+            "ACL_ROOT_DIR=/acl "
+            "LD_LIBRARY_PATH=/pytorch/build/lib:/acl/build:$LD_LIBRARY_PATH "
+            "ACL_INCLUDE_DIR=/acl/build "
+            "ACL_LIBRARY=/acl/build "
+        )
+        if enable_cuda:
+            build_vars += "BLAS=NVPL "
+        else:
+            build_vars += "BLAS=OpenBLAS OpenBLAS_HOME=/OpenBLAS "
+    else:
+        print("build pytorch without mkldnn backend")
+
+    os.system(f"cd /pytorch; {build_vars} python3 setup.py bdist_wheel")
+    if enable_cuda:
+        print("Updating Cuda Dependency")
+        filename = os.listdir("/pytorch/dist/")
+        wheel_path = f"/pytorch/dist/{filename[0]}"
+        package_cuda_wheel(wheel_path, desired_cuda)
+    pytorch_wheel_name = complete_wheel("/pytorch/")
+    print(f"Build Complete. Created {pytorch_wheel_name}..")

.ci/aarch64_linux/embed_library.py

@@ -0,0 +1,87 @@
+#!/usr/bin/env python3
+
+import os
+import shutil
+import sys
+from subprocess import check_call
+from tempfile import TemporaryDirectory
+
+from auditwheel.elfutils import elf_file_filter
+from auditwheel.lddtree import lddtree
+from auditwheel.patcher import Patchelf
+from auditwheel.repair import copylib
+from auditwheel.wheeltools import InWheelCtx
+
+
+def replace_tag(filename):
+    with open(filename) as f:
+        lines = f.read().split("\\n")
+    for i, line in enumerate(lines):
+        if not line.startswith("Tag: "):
+            continue
+        lines[i] = line.replace("-linux_", "-manylinux2014_")
+        print(f"Updated tag from {line} to {lines[i]}")
+
+    with open(filename, "w") as f:
+        f.write("\\n".join(lines))
+
+
+class AlignedPatchelf(Patchelf):
+    def set_soname(self, file_name: str, new_soname: str) -> None:
+        check_call(
+            ["patchelf", "--page-size", "65536", "--set-soname", new_soname, file_name]
+        )
+
+    def replace_needed(self, file_name: str, soname: str, new_soname: str) -> None:
+        check_call(
+            [
+                "patchelf",
+                "--page-size",
+                "65536",
+                "--replace-needed",
+                soname,
+                new_soname,
+                file_name,
+            ]
+        )
+
+
+def embed_library(whl_path, lib_soname, update_tag=False):
+    patcher = AlignedPatchelf()
+    out_dir = TemporaryDirectory()
+    whl_name = os.path.basename(whl_path)
+    tmp_whl_name = os.path.join(out_dir.name, whl_name)
+    with InWheelCtx(whl_path) as ctx:
+        torchlib_path = os.path.join(ctx._tmpdir.name, "torch", "lib")
+        ctx.out_wheel = tmp_whl_name
+        new_lib_path, new_lib_soname = None, None
+        for filename, _ in elf_file_filter(ctx.iter_files()):
+            if not filename.startswith("torch/lib"):
+                continue
+            libtree = lddtree(filename)
+            if lib_soname not in libtree["needed"]:
+                continue
+            lib_path = libtree["libs"][lib_soname]["path"]
+            if lib_path is None:
+                print(f"Can't embed {lib_soname} as it could not be found")
+                break
+            if lib_path.startswith(torchlib_path):
+                continue
+
+            if new_lib_path is None:
+                new_lib_soname, new_lib_path = copylib(lib_path, torchlib_path, patcher)
+            patcher.replace_needed(filename, lib_soname, new_lib_soname)
+            print(f"Replacing {lib_soname} with {new_lib_soname} for {filename}")
+        if update_tag:
+            # Add manylinux2014 tag
+            for filename in ctx.iter_files():
+                if os.path.basename(filename) != "WHEEL":
+                    continue
+                replace_tag(filename)
+    shutil.move(tmp_whl_name, whl_path)
+
+
+if __name__ == "__main__":
+    embed_library(
+        sys.argv[1], "libgomp.so.1", len(sys.argv) > 2 and sys.argv[2] == "--update-tag"
+    )

.ci/docker/almalinux/Dockerfile

@@ -7,13 +7,13 @@ ENV LC_ALL en_US.UTF-8
 ENV LANG en_US.UTF-8
 ENV LANGUAGE en_US.UTF-8
 
-ARG DEVTOOLSET_VERSION=13
+ARG DEVTOOLSET_VERSION=11
 
 RUN yum -y update
 RUN yum -y install epel-release
 # install glibc-langpack-en make sure en_US.UTF-8 locale is available
 RUN yum -y install glibc-langpack-en
-RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel openssl-devel yum-utils autoconf automake make gcc-toolset-${DEVTOOLSET_VERSION}-gcc gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran gcc-toolset-${DEVTOOLSET_VERSION}-gdb
+RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel openssl-devel yum-utils autoconf automake make gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
 # Just add everything as a safe.directory for git since these will be used in multiple places with git
 RUN git config --global --add safe.directory '*'
 ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
@@ -41,7 +41,6 @@ RUN bash ./install_conda.sh && rm install_conda.sh
 # Install CUDA
 FROM base as cuda
 ARG CUDA_VERSION=12.6
-ARG DEVTOOLSET_VERSION=13
 RUN rm -rf /usr/local/cuda-*
 ADD ./common/install_cuda.sh install_cuda.sh
 COPY ./common/install_nccl.sh install_nccl.sh
@@ -51,8 +50,7 @@ ENV CUDA_HOME=/usr/local/cuda-${CUDA_VERSION}
 # Preserve CUDA_VERSION for the builds
 ENV CUDA_VERSION=${CUDA_VERSION}
 # Make things in our path by default
-ENV PATH=/usr/local/cuda-${CUDA_VERSION}/bin:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
-
+ENV PATH=/usr/local/cuda-${CUDA_VERSION}/bin:$PATH
 
 FROM cuda as cuda12.6
 RUN bash ./install_cuda.sh 12.6
@@ -70,23 +68,8 @@ FROM cuda as cuda13.0
 RUN bash ./install_cuda.sh 13.0
 ENV DESIRED_CUDA=13.0
 
-FROM ${ROCM_IMAGE} as rocm_base
-ARG DEVTOOLSET_VERSION=13
-ENV LC_ALL en_US.UTF-8
-ENV LANG en_US.UTF-8
-ENV LANGUAGE en_US.UTF-8
-# Install devtoolset on ROCm base image
-RUN yum -y update && \
-    yum -y install epel-release && \
-    yum -y install glibc-langpack-en && \
-    yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel openssl-devel yum-utils autoconf automake make gcc-toolset-${DEVTOOLSET_VERSION}-gcc gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran gcc-toolset-${DEVTOOLSET_VERSION}-gdb
-RUN git config --global --add safe.directory '*'
-ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
-
-FROM rocm_base as rocm
-ARG PYTORCH_ROCM_ARCH
-ARG DEVTOOLSET_VERSION=13
-ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
+FROM ${ROCM_IMAGE} as rocm
+ENV PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
 ADD ./common/install_mkl.sh install_mkl.sh
 RUN bash ./install_mkl.sh && rm install_mkl.sh
 ENV MKLROOT /opt/intel
@@ -104,7 +87,6 @@ COPY --from=cuda13.0  /usr/local/cuda-13.0 /usr/local/cuda-13.0
 
 # Final step
 FROM ${BASE_TARGET} as final
-ARG DEVTOOLSET_VERSION=13
 COPY --from=openssl            /opt/openssl           /opt/openssl
 COPY --from=patchelf           /patchelf              /usr/local/bin/patchelf
 COPY --from=conda              /opt/conda             /opt/conda

.ci/docker/almalinux/build.sh

@@ -36,8 +36,6 @@ case ${DOCKER_TAG_PREFIX} in
     ;;
   rocm*)
     BASE_TARGET=rocm
-    PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201;gfx950;gfx1150;gfx1151"
-    EXTRA_BUILD_ARGS="${EXTRA_BUILD_ARGS} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}"
     ;;
   *)
     echo "ERROR: Unknown docker tag ${DOCKER_TAG_PREFIX}"
@@ -59,7 +57,7 @@ docker build \
   --target final \
   --progress plain \
   --build-arg "BASE_TARGET=${BASE_TARGET}" \
-  --build-arg "DEVTOOLSET_VERSION=13" \
+  --build-arg "DEVTOOLSET_VERSION=11" \
   ${EXTRA_BUILD_ARGS} \
   -t ${tmp_tag} \
   $@ \

.ci/docker/build.sh

@@ -84,8 +84,8 @@ fi
 _UCX_COMMIT=7836b165abdbe468a2f607e7254011c07d788152
 _UCC_COMMIT=430e241bf5d38cbc73fc7a6b89155397232e3f96
 if [[ "$image" == *rocm* ]]; then
-  _UCX_COMMIT=29831d319e6be55cb8c768ca61de335c934ca39e
-  _UCC_COMMIT=9f4b242cbbd8b1462cbc732eb29316cdfa124b77
+  _UCX_COMMIT=cc312eaa4655c0cc5c2bcd796db938f90563bcf6
+  _UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d
 fi
 
 tag=$(echo $image | awk -F':' '{print $2}')
@@ -113,7 +113,6 @@ case "$tag" in
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
     TRITON=yes
-    INSTALL_MINGW=yes
     ;;
   pytorch-linux-jammy-cuda13.0-cudnn9-py3-gcc11)
     CUDA_VERSION=13.0.0
@@ -168,18 +167,6 @@ case "$tag" in
     VISION=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-py3.11-clang12)
-    ANACONDA_PYTHON_VERSION=3.11
-    CLANG_VERSION=12
-    VISION=no
-    TRITON=no
-    ;;
-  pytorch-linux-jammy-py3.12-clang12)
-    ANACONDA_PYTHON_VERSION=3.12
-    CLANG_VERSION=12
-    VISION=no
-    TRITON=no
-    ;;
   pytorch-linux-jammy-rocm-n-py3 | pytorch-linux-jammy-rocm-n-py3-benchmarks | pytorch-linux-noble-rocm-n-py3)
     if [[ $tag =~ "jammy" ]]; then
       ANACONDA_PYTHON_VERSION=3.10
@@ -188,16 +175,27 @@ case "$tag" in
     fi
     GCC_VERSION=11
     VISION=yes
+    ROCM_VERSION=6.4
+    NINJA_VERSION=1.9.0
+    TRITON=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    if [[ $tag =~ "benchmarks" ]]; then
+      INDUCTOR_BENCHMARKS=yes
+    fi
+    ;;
+  pytorch-linux-noble-rocm-alpha-py3)
+    ANACONDA_PYTHON_VERSION=3.12
+    GCC_VERSION=11
+    VISION=yes
     ROCM_VERSION=7.0
     NINJA_VERSION=1.9.0
     TRITON=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
-    PYTORCH_ROCM_ARCH="gfx90a;gfx942;gfx950;gfx1100"
-    if [[ $tag =~ "benchmarks" ]]; then
-      INDUCTOR_BENCHMARKS=yes
-    fi
+    PYTORCH_ROCM_ARCH="gfx90a;gfx942;gfx950"
     ;;
   pytorch-linux-jammy-xpu-n-1-py3)
     ANACONDA_PYTHON_VERSION=3.10
@@ -207,19 +205,17 @@ case "$tag" in
     NINJA_VERSION=1.9.0
     TRITON=yes
     ;;
-  pytorch-linux-noble-xpu-n-py3 | pytorch-linux-noble-xpu-n-py3-inductor-benchmarks)
+  pytorch-linux-jammy-xpu-n-py3)
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=13
+    GCC_VERSION=11
     VISION=yes
     XPU_VERSION=2025.2
     NINJA_VERSION=1.9.0
     TRITON=yes
-    if [[ $tag =~ "benchmarks" ]]; then
-      INDUCTOR_BENCHMARKS=yes
-    fi
     ;;
   pytorch-linux-jammy-py3-gcc11-inductor-benchmarks)
-    ANACONDA_PYTHON_VERSION=3.10
+    # TODO (huydhn): Upgrade this to Python >= 3.10
+    ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
     VISION=yes
     KATEX=yes
@@ -260,12 +256,6 @@ case "$tag" in
     HALIDE=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-cuda12.8-py3.12-pallas)
-    CUDA_VERSION=12.8.1
-    ANACONDA_PYTHON_VERSION=3.12
-    GCC_VERSION=11
-    PALLAS=yes
-    ;;
   pytorch-linux-jammy-py3.12-triton-cpu)
     CUDA_VERSION=12.6
     ANACONDA_PYTHON_VERSION=3.12
@@ -273,15 +263,18 @@ case "$tag" in
     TRITON_CPU=yes
     ;;
   pytorch-linux-jammy-linter)
-    PYTHON_VERSION=3.10
+    # TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
+    # We will need to update mypy version eventually, but that's for another day. The task
+    # would be to upgrade mypy to 1.0.0 with Python 3.11
+    PYTHON_VERSION=3.9
     ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3.10-linter)
-    PYTHON_VERSION=3.10
+  pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-linter)
+    PYTHON_VERSION=3.9
     CUDA_VERSION=12.8.1
     ;;
-  pytorch-linux-jammy-aarch64-py3.10-gcc13)
+  pytorch-linux-jammy-aarch64-py3.10-gcc11)
     ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=13
+    GCC_VERSION=11
     ACL=yes
     VISION=yes
     OPENBLAS=yes
@@ -289,19 +282,9 @@ case "$tag" in
     # from pytorch/llvm:9.0.1 is x86 specific
     SKIP_LLVM_SRC_BUILD_INSTALL=yes
     ;;
-  pytorch-linux-jammy-aarch64-py3.10-clang21)
+  pytorch-linux-jammy-aarch64-py3.10-gcc11-inductor-benchmarks)
     ANACONDA_PYTHON_VERSION=3.10
-    CLANG_VERSION=21
-    ACL=yes
-    VISION=yes
-    OPENBLAS=yes
-    # snadampal: skipping llvm src build install because the current version
-    # from pytorch/llvm:9.0.1 is x86 specific
-    SKIP_LLVM_SRC_BUILD_INSTALL=yes
-    ;;
-  pytorch-linux-jammy-aarch64-py3.10-gcc13-inductor-benchmarks)
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=13
+    GCC_VERSION=11
     ACL=yes
     VISION=yes
     OPENBLAS=yes
@@ -376,7 +359,7 @@ docker build \
        --build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
        --build-arg "KATEX=${KATEX:-}" \
        --build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
-       --build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}" \
+       --build-arg "PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH:-gfx90a;gfx942}" \
        --build-arg "IMAGE_NAME=${IMAGE_NAME}" \
        --build-arg "UCX_COMMIT=${UCX_COMMIT}" \
        --build-arg "UCC_COMMIT=${UCC_COMMIT}" \
@@ -387,14 +370,12 @@ docker build \
        --build-arg "INDUCTOR_BENCHMARKS=${INDUCTOR_BENCHMARKS}" \
        --build-arg "EXECUTORCH=${EXECUTORCH}" \
        --build-arg "HALIDE=${HALIDE}" \
-       --build-arg "PALLAS=${PALLAS}" \
        --build-arg "XPU_VERSION=${XPU_VERSION}" \
        --build-arg "UNINSTALL_DILL=${UNINSTALL_DILL}" \
        --build-arg "ACL=${ACL:-}" \
        --build-arg "OPENBLAS=${OPENBLAS:-}" \
        --build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
        --build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
-       --build-arg "INSTALL_MINGW=${INSTALL_MINGW:-}" \
        -f $(dirname ${DOCKERFILE})/Dockerfile \
        -t "$tmp_tag" \
        "$@" \
@@ -475,3 +456,12 @@ elif [ "$HAS_TRITON" = "yes" ]; then
   echo "expecting triton to not be installed, but it is"
   exit 1
 fi
+
+# Sanity check cmake version.  Executorch reinstalls cmake and I'm not sure if
+# they support 4.0.0 yet, so exclude them from this check.
+CMAKE_VERSION=$(drun cmake --version)
+if [[ "$EXECUTORCH" != *yes* && "$CMAKE_VERSION" != *4.* ]]; then
+  echo "CMake version is not 4.0.0:"
+  drun cmake --version
+  exit 1
+fi

.ci/docker/centos-rocm/Dockerfile

@@ -56,13 +56,9 @@ ENV INSTALLED_VISION ${VISION}
 
 # Install rocm
 ARG ROCM_VERSION
-RUN mkdir ci_commit_pins
-COPY ./common/common_utils.sh common_utils.sh
-COPY ./ci_commit_pins/rocm-composable-kernel.txt ci_commit_pins/rocm-composable-kernel.txt
 COPY ./common/install_rocm.sh install_rocm.sh
 RUN bash ./install_rocm.sh
-RUN rm install_rocm.sh common_utils.sh
-RUN rm -r ci_commit_pins
+RUN rm install_rocm.sh
 COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
 RUN bash ./install_rocm_magma.sh ${ROCM_VERSION}
 RUN rm install_rocm_magma.sh

.ci/docker/ci_commit_pins/executorch.txt

@@ -1 +1 @@
-deb42f2a8e48f5032b4a98ee781a15fa87a157cf
+56392aa978594cc155fa8af48cd949f5b5f1823a

.ci/docker/ci_commit_pins/huggingface-requirements.txt

@@ -1,2 +1,2 @@
-transformers==4.56.0
+transformers==4.54.0
 soxr==0.5.0

.ci/docker/ci_commit_pins/jax.txt

@@ -1 +0,0 @@
-0.8.0

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

@@ -1 +1 @@
-v2.27.5-1
+v2.27.5-1

.ci/docker/ci_commit_pins/rocm-composable-kernel.txt

@@ -1 +0,0 @@
-7fe50dc3da2069d6645d9deb8c017a876472a977

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

@@ -1 +1 @@
-1b0418a9a454b2b93ab8d71f40e59d2297157fae
+d0e80f39c562c70986fc548fa6e5852ad86e16e7

.ci/docker/ci_commit_pins/triton.txt

@@ -1 +1 @@
-bfeb066872bc1e8b2d2bc0a3b295b99dd77206e7
+f7888497a1eb9e98d4c07537f0d0bcfe180d1363

.ci/docker/common/install_acl.sh

@@ -1,27 +1,16 @@
-#!/bin/bash
-# Script used only in CD pipeline
+set -euo pipefail
 
-set -eux
-
-ACL_VERSION=${ACL_VERSION:-"v52.6.0"}
-ACL_INSTALL_DIR="/acl"
+readonly version=v25.02
+readonly src_host=https://github.com/ARM-software
+readonly src_repo=ComputeLibrary
 
 # Clone ACL
-git clone https://github.com/ARM-software/ComputeLibrary.git -b "${ACL_VERSION}" --depth 1 --shallow-submodules
+[[ ! -d ${src_repo} ]] && git clone ${src_host}/${src_repo}.git
+cd ${src_repo}
+
+git checkout $version
 
-ACL_CHECKOUT_DIR="ComputeLibrary"
 # Build with scons
-pushd $ACL_CHECKOUT_DIR
 scons -j8  Werror=0 debug=0 neon=1 opencl=0 embed_kernels=0 \
   os=linux arch=armv8a build=native multi_isa=1 \
   fixed_format_kernels=1 openmp=1 cppthreads=0
-popd
-
-# Install ACL
-sudo mkdir -p ${ACL_INSTALL_DIR}
-for d in arm_compute include utils support src build
-do
-  sudo cp -r ${ACL_CHECKOUT_DIR}/${d} ${ACL_INSTALL_DIR}/${d}
-done
-
-rm -rf $ACL_CHECKOUT_DIR

.ci/docker/common/install_clang.sh

@@ -8,8 +8,8 @@ if [ -n "$CLANG_VERSION" ]; then
     # work around ubuntu apt-get conflicts
     sudo apt-get -y -f install
     wget --no-check-certificate -O - https://apt.llvm.org/llvm-snapshot.gpg.key | sudo apt-key add -
-    if [[ $CLANG_VERSION -ge 18 ]]; then
-      apt-add-repository "deb http://apt.llvm.org/jammy/ llvm-toolchain-jammy-${CLANG_VERSION} main"
+    if [[ $CLANG_VERSION == 18 ]]; then
+      apt-add-repository "deb http://apt.llvm.org/jammy/ llvm-toolchain-jammy-18 main"
     fi
   fi
 

.ci/docker/common/install_conda.sh

@@ -49,20 +49,12 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
     export SYSROOT_DEP="sysroot_linux-64=2.17"
   fi
 
-# Install correct Python version
-# Also ensure sysroot is using a modern GLIBC to match system compilers
-if [ "$ANACONDA_PYTHON_VERSION" = "3.14" ]; then
-  as_jenkins conda create -n py_$ANACONDA_PYTHON_VERSION -y\
-             python="3.14.0" \
-             ${SYSROOT_DEP} \
-             -c conda-forge
-else
   # Install correct Python version
   # Also ensure sysroot is using a modern GLIBC to match system compilers
   as_jenkins conda create -n py_$ANACONDA_PYTHON_VERSION -y\
              python="$ANACONDA_PYTHON_VERSION" \
              ${SYSROOT_DEP}
-fi
+
   # libstdcxx from conda default channels are too old, we need GLIBCXX_3.4.30
   # which is provided in libstdcxx 12 and up.
   conda_install libstdcxx-ng=12.3.0 --update-deps -c conda-forge

.ci/docker/common/install_cpython.sh

@@ -83,6 +83,10 @@ function build_cpython {
         py_suffix=${py_ver::-1}
         py_folder=$py_suffix
     fi
+    # Update to rc2 due to https://github.com/python/cpython/commit/c72699086fe4
+    if [ "$py_suffix" == "3.14.0" ]; then
+        py_suffix="3.14.0rc2"
+    fi
     wget -q $PYTHON_DOWNLOAD_URL/$py_folder/Python-$py_suffix.tgz -O Python-$py_ver.tgz
     do_cpython_build $py_ver Python-$py_suffix
 

.ci/docker/common/install_cuda.sh

@@ -10,7 +10,7 @@ else
   arch_path='sbsa'
 fi
 
-NVSHMEM_VERSION=3.4.5
+NVSHMEM_VERSION=3.3.24
 
 function install_cuda {
   version=$1
@@ -147,10 +147,10 @@ function install_128 {
 }
 
 function install_130 {
-  CUDNN_VERSION=9.13.0.50
+  CUDNN_VERSION=9.12.0.46
   echo "Installing CUDA 13.0 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
   # install CUDA 13.0 in the same container
-  install_cuda 13.0.2 cuda_13.0.2_580.95.05_linux
+  install_cuda 13.0.0 cuda_13.0.0_580.65.06_linux
 
   # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
   install_cudnn 13 $CUDNN_VERSION

.ci/docker/common/install_executorch.sh

@@ -42,27 +42,22 @@ install_pip_dependencies() {
   # 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
-  # Yaspin is needed for running CI test (get_benchmark_analysis_data.py)
-  pip_install yaspin==3.1.0
 
   popd
 }
 
 setup_executorch() {
+  pushd executorch
+
   export PYTHON_EXECUTABLE=python
-  export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON -DEXECUTORCH_BUILD_TESTS=ON"
+  export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
 
   as_jenkins .ci/scripts/setup-linux.sh --build-tool cmake || true
+  popd
 }
 
-if [ $# -eq 0 ]; then
-  clone_executorch
-  install_buck2
-  install_conda_dependencies
-  install_pip_dependencies
-  pushd executorch
-  setup_executorch
-  popd
-else
-  "$@"
-fi
+clone_executorch
+install_buck2
+install_conda_dependencies
+install_pip_dependencies
+setup_executorch

.ci/docker/common/install_gcc.sh

@@ -7,11 +7,11 @@ if [ -n "$GCC_VERSION" ]; then
   # Need the official toolchain repo to get alternate packages
   add-apt-repository ppa:ubuntu-toolchain-r/test
   apt-get update
-  apt-get install -y g++-$GCC_VERSION gfortran-$GCC_VERSION
+  apt-get install -y g++-$GCC_VERSION
   update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-"$GCC_VERSION" 50
   update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-"$GCC_VERSION" 50
   update-alternatives --install /usr/bin/gcov gcov /usr/bin/gcov-"$GCC_VERSION" 50
-  update-alternatives --install /usr/bin/gfortran gfortran /usr/bin/gfortran-"$GCC_VERSION" 50
+
 
   # Cleanup package manager
   apt-get autoclean && apt-get clean

.ci/docker/common/install_jax.sh

@@ -1,40 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
-
-# Get the pinned JAX version (same for all CUDA versions)
-JAX_VERSION=$(get_pinned_commit /ci_commit_pins/jax)
-
-function install_jax_12() {
-  echo "Installing JAX ${JAX_VERSION} with CUDA 12 support"
-  pip_install "jax[cuda12]==${JAX_VERSION}" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
-
-  # Verify installation
-  python -c "import jax"  # check for errors
-  echo "JAX ${JAX_VERSION} installation completed successfully for CUDA 12"
-}
-
-function install_jax_13() {
-  echo "Installing JAX ${JAX_VERSION} with CUDA 13 support"
-  pip_install "jax[cuda13]==${JAX_VERSION}" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
-
-  # Verify installation
-  python -c "import jax"  # check for errors
-  echo "JAX ${JAX_VERSION} installation completed successfully for CUDA 13"
-}
-
-# idiomatic parameter and option handling in sh
-while test $# -gt 0
-do
-    case "$1" in
-    12.4|12.6|12.6.*|12.8|12.8.*|12.9|12.9.*) install_jax_12;
-        ;;
-    13.0|13.0.*) install_jax_13;
-        ;;
-    *) echo "bad argument $1"; exit 1
-        ;;
-    esac
-    shift
-done

.ci/docker/common/install_libgomp.sh

@@ -1,56 +0,0 @@
-#!/bin/bash
-# Script used only in CD pipeline
-
-set -ex
-
-# install dependencies
-dnf -y install gmp-devel libmpc-devel texinfo flex bison
-
-cd /usr/local/src
-# fetch source for gcc 13
-git clone --depth 1 --single-branch -b releases/gcc-13.3.0 https://github.com/gcc-mirror/gcc.git gcc-13.3.0
-
-mkdir -p gcc-13.3.0/build-gomp
-cd gcc-13.3.0/build-gomp
-
-# configure gcc build
-# I got these flags by:
-# 1. downloading the source rpm for gcc-11 on AlmaLinux 8 container
-#    dnf install -y dnf-plugins-core rpmdevtools
-#   dnf download --source libgomp
-# 2. extracting the gcc.spec from the source.
-#    rpmdev-extract gcc-xx.src.rpm
-# 3. extracting optflags and ld_flags from gcc.spec:
-#    rpm --eval '%{optflags}'
-#    rpm --eval '%{build_ldflags}'
-#
-# I had to remove the following flags because they didn't compile for this version of libgomp:
-#   -Werror=format-security
-#   -specs=/usr/lib/rpm/redhat/redhat-hardened-cc1
-#   -specs=/usr/lib/rpm/redhat/redhat-annobin-cc1
-#
-# I added -march=armv8-a -mtune=generic to make them explicit. I don't think they're strictly needed.
-
-OPT_FLAGS='-O2 -march=armv8-a -mtune=generic'\
-' -fexceptions -g -grecord-gcc-switches -pipe -Wall'\
-' -Wp,-D_FORTIFY_SOURCE=2 -Wp,-D_GLIBCXX_ASSERTIONS'\
-' -fstack-protector-strong -fasynchronous-unwind-tables'\
-' -fstack-clash-protection'
-
-LDFLAGS='-Wl,-z,relro -Wl,--as-needed -Wl,-z,now'
-
-CFLAGS="$OPT_FLAGS" \
-CXXFLAGS="$OPT_FLAGS" \
-LDFLAGS="$LDFLAGS" \
-../configure \
-  --prefix=/usr \
-  --libdir=/usr/lib64 \
-  --enable-languages=c,c++ \
-  --disable-multilib \
-  --disable-bootstrap \
-  --enable-libgomp
-
-# only build libgomp
-make -j$(nproc) all-target-libgomp
-
-make install-target-libgomp

.ci/docker/common/install_mingw.sh

@@ -1,10 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-# Install MinGW-w64 for Windows cross-compilation
-apt-get update
-apt-get install -y g++-mingw-w64-x86-64-posix
-
-echo "MinGW-w64 installed successfully"
-x86_64-w64-mingw32-g++ --version

.ci/docker/common/install_onnx.sh

@@ -19,8 +19,8 @@ pip_install \
   transformers==4.36.2
 
 pip_install coloredlogs packaging
-pip_install onnxruntime==1.23.1
-pip_install onnxscript==0.5.4
+pip_install onnxruntime==1.22.1
+pip_install onnxscript==0.4.0
 
 # 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/

.ci/docker/common/install_openblas.sh

@@ -3,14 +3,11 @@
 
 set -ex
 
-OPENBLAS_VERSION=${OPENBLAS_VERSION:-"v0.3.30"}
-
-# Clone OpenBLAS
-git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION}" --depth 1 --shallow-submodules
+cd /
+git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION:-v0.3.30}" --depth 1 --shallow-submodules
 
 OPENBLAS_CHECKOUT_DIR="OpenBLAS"
 OPENBLAS_BUILD_FLAGS="
-CC=gcc
 NUM_THREADS=128
 USE_OPENMP=1
 NO_SHARED=0
@@ -20,7 +17,5 @@ CFLAGS=-O3
 BUILD_BFLOAT16=1
 "
 
-make -j8 ${OPENBLAS_BUILD_FLAGS} -C $OPENBLAS_CHECKOUT_DIR
-sudo make install -C $OPENBLAS_CHECKOUT_DIR
-
-rm -rf $OPENBLAS_CHECKOUT_DIR
+make -j8 ${OPENBLAS_BUILD_FLAGS} -C ${OPENBLAS_CHECKOUT_DIR}
+make -j8 ${OPENBLAS_BUILD_FLAGS} install -C ${OPENBLAS_CHECKOUT_DIR}

.ci/docker/common/install_rocm.sh

@@ -2,11 +2,6 @@
 
 set -ex
 
-# for pip_install function
-source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
-
-ROCM_COMPOSABLE_KERNEL_VERSION="$(cat $(dirname $0)/../ci_commit_pins/rocm-composable-kernel.txt)"
-
 ver() {
     printf "%3d%03d%03d%03d" $(echo "$1" | tr '.' ' ');
 }
@@ -40,7 +35,17 @@ EOF
 
     # Default url values
     rocm_baseurl="http://repo.radeon.com/rocm/apt/${ROCM_VERSION}"
+    amdgpu_baseurl="https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu"
+
+    # Special case for ROCM_VERSION == 7.0
+    if [[ $(ver "$ROCM_VERSION") -eq $(ver 7.0) ]]; then
+        rocm_baseurl="https://repo.radeon.com/rocm/apt/7.0_alpha2"
+        amdgpu_baseurl="https://repo.radeon.com/amdgpu/30.10_alpha2/ubuntu"
+    fi
+
+    # Add amdgpu repository
     UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
+    echo "deb [arch=amd64] ${amdgpu_baseurl} ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
 
     # Add rocm repository
     wget -qO - http://repo.radeon.com/rocm/rocm.gpg.key | apt-key add -
@@ -108,8 +113,6 @@ EOF
         rm -rf HIP clr
     fi
 
-    pip_install "git+https://github.com/rocm/composable_kernel@$ROCM_COMPOSABLE_KERNEL_VERSION"
-
     # Cleanup
     apt-get autoclean && apt-get clean
     rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
@@ -173,8 +176,6 @@ install_centos() {
       sqlite3 $kdb "PRAGMA journal_mode=off; PRAGMA VACUUM;"
   done
 
-  pip_install "git+https://github.com/rocm/composable_kernel@$ROCM_COMPOSABLE_KERNEL_VERSION"
-
   # Cleanup
   yum clean all
   rm -rf /var/cache/yum

.ci/docker/common/install_rocm_magma.sh

@@ -12,8 +12,8 @@ function do_install() {
 
     rocm_version_nodot=${rocm_version//./}
 
-    # post merge of https://github.com/icl-utk-edu/magma/pull/65
-    MAGMA_VERSION=c0792ae825fb36872784892ea643dd6f3456bc5f
+    # Version 2.7.2 + ROCm related updates
+    MAGMA_VERSION=a1625ff4d9bc362906bd01f805dbbe12612953f6
     magma_archive="magma-rocm${rocm_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
 
     rocm_dir="/opt/rocm"

.ci/docker/common/install_triton.sh

@@ -66,15 +66,15 @@ 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 conda_run python -m build --wheel --no-isolation
+  CXX=g++-9 conda_run python setup.py bdist_wheel
 elif [ -n "${UBUNTU_VERSION}" ] && [ -n "${CLANG_VERSION}" ]; then
   # Triton needs <filesystem> which surprisingly is not available with clang-9 toolchain
   add-apt-repository -y ppa:ubuntu-toolchain-r/test
   apt-get install -y g++-9
 
-  CXX=g++-9 conda_run python -m build --wheel --no-isolation
+  CXX=g++-9 conda_run python setup.py bdist_wheel
 else
-  conda_run python -m build --wheel --no-isolation
+  conda_run python setup.py bdist_wheel
 fi
 
 # Copy the wheel to /opt for multi stage docker builds

.ci/docker/common/install_xpu.sh

@@ -9,7 +9,7 @@ set -xe
 
 function install_ubuntu() {
     . /etc/os-release
-    if [[ ! " jammy noble " =~ " ${VERSION_CODENAME} " ]]; then
+    if [[ ! " jammy " =~ " ${VERSION_CODENAME} " ]]; then
         echo "Ubuntu version ${VERSION_CODENAME} not supported"
         exit
     fi
@@ -35,24 +35,25 @@ function install_ubuntu() {
     # The xpu-smi packages
     apt-get install -y flex bison xpu-smi
 
-    # Compute and Media Runtimes
-    if [[ " ${VERSION_CODENAME} " =~ " noble " ]]; then
+    if [[ "${XPU_DRIVER_TYPE,,}" == "lts" ]]; then
+        # Compute and Media Runtimes
         apt-get install -y \
-            intel-opencl-icd libze-intel-gpu1 libze1 \
-            intel-media-va-driver-non-free libmfx-gen1 libvpl2 \
-            libegl-mesa0 libegl1-mesa-dev libgbm1 libgl1-mesa-dev libgl1-mesa-dri \
+            intel-opencl-icd intel-level-zero-gpu level-zero \
+            intel-media-va-driver-non-free libmfx1 libmfxgen1 libvpl2 \
+            libegl-mesa0 libegl1-mesa libegl1-mesa-dev libgbm1 libgl1-mesa-dev libgl1-mesa-dri \
             libglapi-mesa libgles2-mesa-dev libglx-mesa0 libigdgmm12 libxatracker2 mesa-va-drivers \
-            mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo intel-ocloc
-    else # jammy
+            mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo
+        # Development Packages
+        apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev level-zero-dev
+    else # rolling driver
         apt-get install -y \
             intel-opencl-icd libze-intel-gpu1 libze1 \
             intel-media-va-driver-non-free libmfx-gen1 libvpl2 \
             libegl-mesa0 libegl1-mesa libegl1-mesa-dev libgbm1 libgl1-mesa-dev libgl1-mesa-dri \
             libglapi-mesa libglx-mesa0 libigdgmm12 libxatracker2 mesa-va-drivers \
             mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo intel-ocloc
+        apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev libze-dev
     fi
-    # Development Packages
-    apt-get install -y libigc-dev intel-igc-cm libigdfcl-dev libigfxcmrt-dev libze-dev
 
     # Install Intel Support Packages
     apt-get install -y ${XPU_PACKAGES}
@@ -65,7 +66,7 @@ function install_ubuntu() {
 function install_rhel() {
     . /etc/os-release
     if [[ "${ID}" == "rhel" ]]; then
-        if [[ ! " 8.8 8.10 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
+        if [[ ! " 8.8 8.9 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
             echo "RHEL version ${VERSION_ID} not supported"
             exit
         fi
@@ -146,7 +147,7 @@ function install_sles() {
 XPU_DRIVER_VERSION=""
 if [[ "${XPU_DRIVER_TYPE,,}" == "lts" ]]; then
     # Use GPU driver LTS releases
-    XPU_DRIVER_VERSION="/lts/2523"
+    XPU_DRIVER_VERSION="/lts/2350"
 fi
 
 # Default use Intel® oneAPI Deep Learning Essentials 2025.1

.ci/docker/common/patch_libstdc.sh

@@ -1,9 +0,0 @@
-#!/bin/bash
-set -xe
-# Script used in Linux x86 and aarch64 CD pipeline
-
-# Workaround for exposing statically linked libstdc++ CXX11 ABI symbols.
-# see: https://github.com/pytorch/pytorch/issues/133437
-LIBNONSHARED=$(gcc -print-file-name=libstdc++_nonshared.a)
-nm -g $LIBNONSHARED | grep " T " | grep recursive_directory_iterator | cut -c 20-  > weaken-symbols.txt
-objcopy --weaken-symbols weaken-symbols.txt $LIBNONSHARED $LIBNONSHARED

.ci/docker/libtorch/Dockerfile

@@ -74,14 +74,6 @@ RUN bash ./install_cuda.sh 13.0
 RUN bash ./install_magma.sh 13.0
 RUN ln -sf /usr/local/cuda-13.0 /usr/local/cuda
 
-# Install libibverbs for libtorch and copy to CUDA directory
-RUN apt-get update -y && \
-    apt-get install -y libibverbs-dev librdmacm-dev && \
-    cp /usr/lib/x86_64-linux-gnu/libmlx5.so* /usr/local/cuda/lib64/ && \
-    cp /usr/lib/x86_64-linux-gnu/librdmacm.so* /usr/local/cuda/lib64/ && \
-    cp /usr/lib/x86_64-linux-gnu/libibverbs.so* /usr/local/cuda/lib64/ && \
-    cp /usr/lib/x86_64-linux-gnu/libnl* /usr/local/cuda/lib64/
-
 FROM cpu as rocm
 ARG ROCM_VERSION
 ARG PYTORCH_ROCM_ARCH

.ci/docker/libtorch/build.sh

@@ -39,17 +39,13 @@ case ${DOCKER_TAG_PREFIX} in
         DOCKER_GPU_BUILD_ARG=""
         ;;
     rocm*)
-        # we want the patch version of 7.0 instead
-        if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
-            GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
-        fi
         # we want the patch version of 6.4 instead
-        if [[ "$GPU_ARCH_VERSION" == *"6.4"* ]]; then
-            GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.4"
+        if [[ $(ver $GPU_ARCH_VERSION) -eq $(ver 6.4) ]]; then
+            GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
         fi
         BASE_TARGET=rocm
         GPU_IMAGE=rocm/dev-ubuntu-22.04:${GPU_ARCH_VERSION}-complete
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201;gfx950;gfx1150;gfx1151"
+        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
         DOCKER_GPU_BUILD_ARG="--build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg ROCM_VERSION=${GPU_ARCH_VERSION}"
         ;;
     *)

.ci/docker/manywheel/Dockerfile_2_28

@@ -130,8 +130,7 @@ ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/op
 RUN for cpython_version in "cp312-cp312" "cp313-cp313" "cp313-cp313t"; do \
     /opt/python/${cpython_version}/bin/python -m pip install setuptools wheel; \
     done;
-ADD ./common/patch_libstdc.sh patch_libstdc.sh
-RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
+
 
 # cmake-3.18.4 from pip; force in case cmake3 already exists
 RUN yum install -y python3-pip && \
@@ -149,7 +148,7 @@ FROM cpu_final as rocm_final
 ARG ROCM_VERSION=6.0
 ARG PYTORCH_ROCM_ARCH
 ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
-ARG DEVTOOLSET_VERSION=13
+ARG DEVTOOLSET_VERSION=11
 ENV LDFLAGS="-Wl,-rpath=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64 -Wl,-rpath=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib"
 # Somewhere in ROCm stack, we still use non-existing /opt/rocm/hip path,
 # below workaround helps avoid error

.ci/docker/manywheel/Dockerfile_2_28_aarch64

@@ -50,10 +50,6 @@ RUN rm install_ninja.sh
 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
 
-# Build a newer version of libgomp than that supported in in Almalinux 8.
-COPY ./common/install_libgomp.sh install_libgomp.sh
-RUN bash ./install_libgomp.sh && rm install_libgomp.sh
-
 # 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
@@ -66,13 +62,6 @@ ARG OPENBLAS_VERSION
 ADD ./common/install_openblas.sh install_openblas.sh
 RUN bash ./install_openblas.sh && rm install_openblas.sh
 
-# Install Arm Compute Library
-FROM base as arm_compute
-# use python3.9 to install scons
-RUN python3.9 -m pip install scons==4.7.0
-RUN ln -sf /opt/python/cp39-cp39/bin/scons /usr/local/bin
-COPY ./common/install_acl.sh install_acl.sh
-RUN bash ./install_acl.sh && rm install_acl.sh
 FROM base as final
 
 # remove unnecessary python versions
@@ -81,7 +70,4 @@ RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
 RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
 RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
 COPY --from=openblas     /opt/OpenBLAS/  /opt/OpenBLAS/
-COPY --from=arm_compute /acl /acl
-ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:/acl/build/:$LD_LIBRARY_PATH
-ADD ./common/patch_libstdc.sh patch_libstdc.sh
-RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
+ENV LD_LIBRARY_PATH=/opt/OpenBLAS/lib:$LD_LIBRARY_PATH

.ci/docker/manywheel/Dockerfile_cuda_aarch64

@@ -86,15 +86,6 @@ FROM base as nvpl
 ADD ./common/install_nvpl.sh install_nvpl.sh
 RUN bash ./install_nvpl.sh && rm install_nvpl.sh
 
-# Install Arm Compute Library
-FROM base as arm_compute
-# use python3.9 to install scons
-RUN python3.9 -m pip install scons==4.7.0
-RUN ln -sf /opt/python/cp39-cp39/bin/scons /usr/local/bin
-COPY ./common/install_acl.sh install_acl.sh
-RUN bash ./install_acl.sh && rm install_acl.sh
-FROM base as final
-
 FROM final as cuda_final
 ARG BASE_CUDA_VERSION
 RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
@@ -102,9 +93,5 @@ COPY --from=cuda     /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BAS
 COPY --from=magma    /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
 COPY --from=nvpl /opt/nvpl/lib/  /usr/local/lib/
 COPY --from=nvpl /opt/nvpl/include/  /usr/local/include/
-COPY --from=arm_compute /acl /acl
 RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
 ENV PATH=/usr/local/cuda/bin:$PATH
-ENV LD_LIBRARY_PATH=/acl/build/:$LD_LIBRARY_PATH
-ADD ./common/patch_libstdc.sh patch_libstdc.sh
-RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh

.ci/docker/manywheel/Dockerfile_cxx11-abi

@@ -0,0 +1,71 @@
+FROM centos:8 as base
+
+ENV LC_ALL en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US.UTF-8
+ENV PATH /opt/rh/gcc-toolset-11/root/bin/:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
+
+# change to a valid repo
+RUN sed -i 's|#baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-Linux-*.repo
+# enable to install ninja-build
+RUN sed -i 's|enabled=0|enabled=1|g' /etc/yum.repos.d/CentOS-Linux-PowerTools.repo
+
+RUN yum -y update
+RUN yum install -y wget curl perl util-linux xz bzip2 git patch which zlib-devel sudo
+RUN yum install -y autoconf automake make cmake gdb gcc-toolset-11-gcc-c++
+
+
+FROM base as openssl
+ADD ./common/install_openssl.sh install_openssl.sh
+RUN bash ./install_openssl.sh && rm install_openssl.sh
+
+# Install python
+FROM base as python
+RUN yum install -y openssl-devel zlib-devel bzip2-devel ncurses-devel sqlite-devel readline-devel tk-devel gdbm-devel libpcap-devel xz-devel libffi-devel
+ADD common/install_cpython.sh install_cpython.sh
+RUN bash ./install_cpython.sh && rm install_cpython.sh
+
+FROM base as conda
+ADD ./common/install_conda_docker.sh install_conda.sh
+RUN bash ./install_conda.sh && rm install_conda.sh
+RUN /opt/conda/bin/conda install -y cmake
+
+FROM base as intel
+# Install MKL
+COPY --from=python             /opt/python                           /opt/python
+COPY --from=python             /opt/_internal                        /opt/_internal
+COPY --from=conda              /opt/conda                            /opt/conda
+ENV PATH=/opt/conda/bin:$PATH
+ADD ./common/install_mkl.sh install_mkl.sh
+RUN bash ./install_mkl.sh && rm install_mkl.sh
+
+FROM base as patchelf
+ADD ./common/install_patchelf.sh install_patchelf.sh
+RUN bash ./install_patchelf.sh && rm install_patchelf.sh
+RUN cp $(which patchelf) /patchelf
+
+FROM base as jni
+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
+ADD ./common/install_libpng.sh install_libpng.sh
+RUN bash ./install_libpng.sh && rm install_libpng.sh
+
+FROM base as final
+COPY --from=openssl            /opt/openssl                          /opt/openssl
+COPY --from=python             /opt/python                           /opt/python
+COPY --from=python             /opt/_internal                        /opt/_internal
+COPY --from=intel              /opt/intel                            /opt/intel
+COPY --from=conda              /opt/conda                            /opt/conda
+COPY --from=patchelf           /usr/local/bin/patchelf               /usr/local/bin/patchelf
+COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
+COPY --from=libpng             /usr/local/bin/png*                   /usr/local/bin/
+COPY --from=libpng             /usr/local/bin/libpng*                /usr/local/bin/
+COPY --from=libpng             /usr/local/include/png*               /usr/local/include/
+COPY --from=libpng             /usr/local/include/libpng*            /usr/local/include/
+COPY --from=libpng             /usr/local/lib/libpng*                /usr/local/lib/
+COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/lib/pkgconfig
+
+RUN yum install -y ninja-build

.ci/docker/manywheel/Dockerfile_s390x

@@ -115,9 +115,6 @@ RUN env GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=True pip3 install grpcio
 # cmake-3.28.0 from pip for onnxruntime
 RUN python3 -mpip install cmake==3.28.0
 
-ADD ./common/patch_libstdc.sh patch_libstdc.sh
-RUN bash ./patch_libstdc.sh && rm patch_libstdc.sh
-
 # build onnxruntime 1.21.0 from sources.
 # it is not possible to build it from sources using pip,
 # so just build it from upstream repository.

.ci/docker/manywheel/build.sh

@@ -28,7 +28,6 @@ fi
 MANY_LINUX_VERSION=${MANY_LINUX_VERSION:-}
 DOCKERFILE_SUFFIX=${DOCKERFILE_SUFFIX:-}
 OPENBLAS_VERSION=${OPENBLAS_VERSION:-}
-ACL_VERSION=${ACL_VERSION:-}
 
 case ${image} in
     manylinux2_28-builder:cpu)
@@ -42,6 +41,13 @@ case ${image} in
         GPU_IMAGE=arm64v8/almalinux:8
         DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13 --build-arg NINJA_VERSION=1.12.1"
         MANY_LINUX_VERSION="2_28_aarch64"
+        OPENBLAS_VERSION="v0.3.30"
+        ;;
+    manylinuxcxx11-abi-builder:cpu-cxx11-abi)
+        TARGET=final
+        GPU_IMAGE=""
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=9"
+        MANY_LINUX_VERSION="cxx11-abi"
         ;;
     manylinuxs390x-builder:cpu-s390x)
         TARGET=final
@@ -75,25 +81,21 @@ case ${image} in
         DOCKERFILE_SUFFIX="_cuda_aarch64"
         ;;
     manylinux2_28-builder:rocm*)
-        # we want the patch version of 7.0 instead
-        if [[ "$GPU_ARCH_VERSION" == *"7.0"* ]]; then
-            GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
-        fi
         # we want the patch version of 6.4 instead
-        if [[ "$GPU_ARCH_VERSION" == *"6.4"* ]]; then
-            GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.4"
+        if [[ $(ver $GPU_ARCH_VERSION) -eq $(ver 6.4) ]]; then
+            GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.2"
         fi
         TARGET=rocm_final
         MANY_LINUX_VERSION="2_28"
         DEVTOOLSET_VERSION="11"
         GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
-        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201;gfx950;gfx1150;gfx1151"
+        PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
         DOCKER_GPU_BUILD_ARG="--build-arg ROCM_VERSION=${GPU_ARCH_VERSION} --build-arg PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} --build-arg DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}"
         ;;
     manylinux2_28-builder:xpu)
         TARGET=xpu_final
         GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13"
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28"
         ;;
     *)
@@ -119,8 +121,7 @@ tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
 DOCKER_BUILDKIT=1 docker build  \
     ${DOCKER_GPU_BUILD_ARG} \
     --build-arg "GPU_IMAGE=${GPU_IMAGE}" \
-    --build-arg "OPENBLAS_VERSION=${OPENBLAS_VERSION:-}" \
-    --build-arg "ACL_VERSION=${ACL_VERSION:-}" \
+    --build-arg "OPENBLAS_VERSION=${OPENBLAS_VERSION}" \
     --target "${TARGET}" \
     -t "${tmp_tag}" \
     $@ \

.ci/docker/manywheel/build_scripts/ssl-check.py

@@ -10,6 +10,11 @@ BAD_SSL = "https://self-signed.badssl.com"
 
 print("Testing SSL certificate checking for Python:", sys.version)
 
+if sys.version_info[:2] < (2, 7) or sys.version_info[:2] < (3, 4):
+    print("This version never checks SSL certs; skipping tests")
+    sys.exit(0)
+
+
 EXC = OSError
 
 print(f"Connecting to {GOOD_SSL} should work")

.ci/docker/requirements-ci.txt

@@ -10,11 +10,6 @@ boto3==1.35.42
 #Pinned versions: 1.19.12, 1.16.34
 #test that import:
 
-build==1.3.0
-#Description: A simple, correct Python build frontend.
-#Pinned versions: 1.3.0
-#test that import:
-
 click
 #Description: Command Line Interface Creation Kit
 #Pinned versions:
@@ -52,10 +47,10 @@ flatbuffers==24.12.23
 #Pinned versions: 24.12.23
 #test that import:
 
-hypothesis==6.56.4
+hypothesis==5.35.1
 # Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
 #Description: advanced library for generating parametrized tests
-#Pinned versions: 6.56.4
+#Pinned versions: 5.35.1
 #test that import: test_xnnpack_integration.py, test_pruning_op.py, test_nn.py
 
 junitparser==2.1.1
@@ -98,9 +93,8 @@ librosa==0.10.2 ; python_version == "3.12" and platform_machine != "s390x"
 #Pinned versions:
 #test that import:
 
-mypy==1.16.0 ; platform_system == "Linux"
+mypy==1.16.0
 # Pin MyPy version because new errors are likely to appear with each release
-# Skip on Windows as lots of type annotations are POSIX specific
 #Description: linter
 #Pinned versions: 1.16.0
 #test that import: test_typing.py, test_type_hints.py
@@ -111,17 +105,20 @@ networkx==2.8.8
 #Pinned versions: 2.8.8
 #test that import: functorch
 
-ninja==1.11.1.4
+ninja==1.11.1.3
 #Description: build system. Used in some tests. Used in build to generate build
 #time tracing information
-#Pinned versions: 1.11.1.4
+#Pinned versions: 1.11.1.3
 #test that import: run_test.py, test_cpp_extensions_aot.py,test_determination.py
 
+numba==0.49.0 ; python_version < "3.9" and platform_machine != "s390x"
+numba==0.55.2 ; python_version == "3.9" and platform_machine != "s390x"
 numba==0.55.2 ; python_version == "3.10" and platform_machine != "s390x"
 numba==0.60.0 ; python_version == "3.12" and platform_machine != "s390x"
 #Description: Just-In-Time Compiler for Numerical Functions
-#Pinned versions: 0.55.2, 0.60.0
+#Pinned versions: 0.54.1, 0.49.0, <=0.49.1
 #test that import: test_numba_integration.py
+#For numba issue see https://github.com/pytorch/pytorch/issues/51511
 #Need release > 0.61.2 for s390x due to https://github.com/numba/numba/pull/10073
 
 #numpy
@@ -136,14 +133,12 @@ numba==0.60.0 ; python_version == "3.12" and platform_machine != "s390x"
 #test_nn.py, test_namedtensor.py, test_linalg.py, test_jit_cuda_fuser.py,
 #test_jit.py, test_indexing.py, test_datapipe.py, test_dataloader.py,
 #test_binary_ufuncs.py
-numpy==1.22.4; python_version == "3.10"
+numpy==1.22.4; python_version == "3.9" or python_version == "3.10"
 numpy==1.26.2; python_version == "3.11" or python_version == "3.12"
-numpy==2.1.2; python_version >= "3.13" and python_version < "3.14"
-numpy==2.3.4; python_version >= "3.14"
+numpy==2.1.2; python_version >= "3.13"
 
 pandas==2.0.3; python_version < "3.13"
-pandas==2.2.3; python_version >= "3.13" and python_version < "3.14"
-pandas==2.3.3; python_version >= "3.14"
+pandas==2.2.3; python_version >= "3.13"
 
 #onnxruntime
 #Description: scoring engine for Open Neural Network Exchange (ONNX) models
@@ -155,8 +150,7 @@ opt-einsum==3.3
 #Pinned versions: 3.3
 #test that import: test_linalg.py
 
-optree==0.13.0 ; python_version < "3.14"
-optree==0.17.0 ; python_version >= "3.14"
+optree==0.13.0
 #Description: A library for tree manipulation
 #Pinned versions: 0.13.0
 #test that import: test_vmap.py, test_aotdispatch.py, test_dynamic_shapes.py,
@@ -171,12 +165,12 @@ optree==0.17.0 ; python_version >= "3.14"
 
 pillow==11.0.0
 #Description:  Python Imaging Library fork
-#Pinned versions: 11.0.0
+#Pinned versions: 10.3.0
 #test that import:
 
-protobuf==5.29.5
+protobuf==5.29.4
 #Description:  Google's data interchange format
-#Pinned versions: 5.29.5
+#Pinned versions: 5.29.4
 #test that import: test_tensorboard.py, test/onnx/*
 
 psutil
@@ -219,7 +213,7 @@ pytest-subtests==0.13.1
 #Pinned versions:
 #test that import:
 
-xdoctest==1.3.0
+xdoctest==1.1.0
 #Description: runs doctests in pytest
 #Pinned versions: 1.1.0
 #test that import:
@@ -244,9 +238,10 @@ pygments==2.15.0
 #Pinned versions: 14.1.0
 #test that import:
 
-scikit-image==0.22.0
+scikit-image==0.19.3 ; python_version < "3.10"
+scikit-image==0.22.0 ; python_version >= "3.10"
 #Description: image processing routines
-#Pinned versions: 0.22.0
+#Pinned versions:
 #test that import: test_nn.py
 
 #scikit-learn
@@ -255,8 +250,7 @@ scikit-image==0.22.0
 #test that import:
 
 scipy==1.10.1 ; python_version <= "3.11"
-scipy==1.14.1 ; python_version > "3.11" and python_version < "3.14"
-scipy==1.16.2 ; python_version >= "3.14"
+scipy==1.14.1 ; python_version >= "3.12"
 # Pin SciPy because of failing distribution tests (see #60347)
 #Description: scientific python
 #Pinned versions: 1.10.1
@@ -270,7 +264,7 @@ scipy==1.16.2 ; python_version >= "3.14"
 #test that import:
 
 # needed by torchgen utils
-typing-extensions==4.12.2
+typing-extensions>=4.10.0
 #Description: type hints for python
 #Pinned versions:
 #test that import:
@@ -328,10 +322,11 @@ pywavelets==1.7.0 ; python_version >= "3.12"
 #Pinned versions: 1.4.1
 #test that import:
 
-lxml==5.3.0 ; python_version < "3.14"
-lxml==6.0.2 ; python_version >= "3.14"
+lxml==5.3.0
 #Description: This is a requirement of unittest-xml-reporting
 
+# Python-3.9 binaries
+
 PyGithub==2.3.0
 
 sympy==1.13.3
@@ -339,14 +334,12 @@ sympy==1.13.3
 #Pinned versions:
 #test that import:
 
-onnx==1.19.1 ; python_version < "3.14"
-# Unpin once Python 3.14 is supported. See  onnxruntime issue 26309.
-onnx==1.18.0 ; python_version == "3.14"
+onnx==1.18.0
 #Description: Required by onnx tests, and mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
 
-onnxscript==0.5.4
+onnxscript==0.4.0
 #Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
@@ -366,10 +359,9 @@ pwlf==2.2.1
 #test that import: test_sac_estimator.py
 
 # To build PyTorch itself
-pyyaml==6.0.3
+pyyaml
 pyzstd
-setuptools==78.1.1
-packaging==23.1
+setuptools>=70.1.0
 six
 
 scons==4.5.2 ; platform_machine == "aarch64"
@@ -384,16 +376,13 @@ dataclasses_json==0.6.7
 #Pinned versions: 0.6.7
 #test that import:
 
-cmake==3.31.6
+cmake==4.0.0
 #Description: required for building
 
 tlparse==0.4.0
 #Description: required for log parsing
 
-filelock==3.18.0
-#Description: required for inductor testing
-
-cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x" and platform_system != "Darwin"
+cuda-bindings>=12.0,<13.0 ; platform_machine != "s390x"
 #Description: required for testing CUDAGraph::raw_cuda_graph(). See https://nvidia.github.io/cuda-python/cuda-bindings/latest/support.html for how this version was chosen. Note "Any fix in the latest bindings would be backported to the prior major version" means that only the newest version of cuda-bindings will get fixes. Depending on the latest version of 12.x is okay because all 12.y versions will be supported via "CUDA minor version compatibility". Pytorch builds against 13.z versions of cuda toolkit work with 12.x versions of cuda-bindings as well because newer drivers work with old toolkits.
 #test that import: test_cuda.py
 

.ci/docker/requirements-docs.txt

@@ -1,10 +1,7 @@
-sphinx==7.2.6
+sphinx==5.3.0
 #Description: This is used to generate PyTorch docs
-#Pinned versions: 7.2.6
-
-pytorch_sphinx_theme2==0.2.0
-#Description: This is needed to generate PyTorch docs
-#Pinned versions: 0.2.0
+#Pinned versions: 5.3.0
+-e git+https://github.com/pytorch/pytorch_sphinx_theme.git@1657ad2fc1acdc98aa719eebecbb0128a7c13ce4#egg=pytorch_sphinx_theme2
 
 # TODO: sphinxcontrib.katex 0.9.0 adds a local KaTeX server to speed up pre-rendering
 # but it doesn't seem to work and hangs around idly. The initial thought that it is probably
@@ -32,17 +29,17 @@ tensorboard==2.18.0 ; python_version >= "3.13"
 #Description: This is used to generate PyTorch docs
 #Pinned versions: 2.13.0
 
-breathe==4.36.0
+breathe==4.34.0
 #Description: This is used to generate PyTorch C++ docs
-#Pinned versions: 4.36.0
+#Pinned versions: 4.34.0
 
-exhale==0.3.7
+exhale==0.2.3
 #Description: This is used to generate PyTorch C++ docs
-#Pinned versions: 0.3.7
+#Pinned versions: 0.2.3
 
-docutils==0.20
+docutils==0.16
 #Description: This is used to generate PyTorch C++ docs
-#Pinned versions: 0.20
+#Pinned versions: 0.16
 
 bs4==0.0.1
 #Description: This is used to generate PyTorch C++ docs
@@ -52,13 +49,13 @@ IPython==8.12.0
 #Description: This is used to generate PyTorch functorch docs
 #Pinned versions: 8.12.0
 
-myst-nb==1.3.0
+myst-nb==0.17.2
 #Description: This is used to generate PyTorch functorch and torch.compile docs.
-#Pinned versions: 1.3.0
+#Pinned versions: 0.17.2
 
 # The following are required to build torch.distributed.elastic.rendezvous.etcd* docs
 python-etcd==0.4.5
 sphinx-copybutton==0.5.0
-sphinx-design==0.6.1
+sphinx-design==0.4.0
 sphinxcontrib-mermaid==1.0.0
-myst-parser==4.0.1
+myst-parser==0.18.1

.ci/docker/triton_version.txt

@@ -1 +1 @@
-3.5.1
+3.4.0

.ci/docker/triton_xpu_version.txt

@@ -1 +1 @@
-3.5.0
+3.4.0

.ci/docker/ubuntu-rocm/Dockerfile

@@ -52,13 +52,9 @@ ENV INSTALLED_VISION ${VISION}
 
 # Install rocm
 ARG ROCM_VERSION
-RUN mkdir ci_commit_pins
-COPY ./common/common_utils.sh common_utils.sh
-COPY ./ci_commit_pins/rocm-composable-kernel.txt ci_commit_pins/rocm-composable-kernel.txt
 COPY ./common/install_rocm.sh install_rocm.sh
 RUN bash ./install_rocm.sh
-RUN rm install_rocm.sh common_utils.sh
-RUN rm -r ci_commit_pins
+RUN rm install_rocm.sh
 COPY ./common/install_rocm_magma.sh install_rocm_magma.sh
 RUN bash ./install_rocm_magma.sh ${ROCM_VERSION}
 RUN rm install_rocm_magma.sh

.ci/docker/ubuntu-xpu/Dockerfile

@@ -54,15 +54,12 @@ ENV OPENSSL_DIR /opt/openssl
 RUN rm install_openssl.sh
 
 ARG INDUCTOR_BENCHMARKS
-ARG ANACONDA_PYTHON_VERSION
-ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
 COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
 COPY ./common/common_utils.sh common_utils.sh
 COPY ci_commit_pins/huggingface-requirements.txt huggingface-requirements.txt
 COPY ci_commit_pins/timm.txt timm.txt
-COPY ci_commit_pins/torchbench.txt torchbench.txt
 RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
-RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface-requirements.txt torchbench.txt
+RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface-requirements.txt
 
 # Install XPU Dependencies
 ARG XPU_VERSION

.ci/docker/ubuntu/Dockerfile

@@ -100,16 +100,9 @@ COPY ./common/common_utils.sh common_utils.sh
 COPY ci_commit_pins/huggingface-requirements.txt huggingface-requirements.txt
 COPY ci_commit_pins/timm.txt timm.txt
 COPY ci_commit_pins/torchbench.txt torchbench.txt
-# Only build aoti cpp tests when INDUCTOR_BENCHMARKS is set to True
-ENV BUILD_AOT_INDUCTOR_TEST ${INDUCTOR_BENCHMARKS}
 RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
 RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface-requirements.txt torchbench.txt
 
-ARG INSTALL_MINGW
-COPY ./common/install_mingw.sh install_mingw.sh
-RUN if [ -n "${INSTALL_MINGW}" ]; then bash ./install_mingw.sh; fi
-RUN rm install_mingw.sh
-
 ARG TRITON
 ARG TRITON_CPU
 
@@ -143,15 +136,6 @@ COPY ci_commit_pins/halide.txt halide.txt
 RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
 RUN rm install_halide.sh common_utils.sh halide.txt
 
-ARG PALLAS
-ARG CUDA_VERSION
-# Install JAX with CUDA support (for Pallas)
-COPY ./common/install_jax.sh install_jax.sh
-COPY ./common/common_utils.sh common_utils.sh
-COPY ./ci_commit_pins/jax.txt /ci_commit_pins/jax.txt
-RUN if [ -n "${PALLAS}" ]; then bash ./install_jax.sh ${CUDA_VERSION}; fi
-RUN rm -f install_jax.sh common_utils.sh /ci_commit_pins/jax.txt
-
 ARG ONNX
 # Install ONNX dependencies
 COPY ./common/install_onnx.sh ./common/common_utils.sh ./

.ci/libtorch/build.sh

@@ -7,4 +7,4 @@ set -ex
 
 SCRIPTPATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
 
-USE_NVSHMEM=0 USE_CUSPARSELT=0 BUILD_PYTHONLESS=1 DESIRED_PYTHON="3.10" ${SCRIPTPATH}/../manywheel/build.sh
+USE_NVSHMEM=0 USE_CUSPARSELT=0 BUILD_PYTHONLESS=1 DESIRED_PYTHON="3.9" ${SCRIPTPATH}/../manywheel/build.sh

.ci/lumen_cli/cli/lib/common/cli_helper.py

@@ -8,11 +8,9 @@ from abc import ABC, abstractmethod
 
 
 try:
-    from collections.abc import Callable  # Python 3.11+
-    from typing import Any, Required, TypedDict
+    from typing import Any, Callable, Required, TypedDict  # Python 3.11+
 except ImportError:
-    from collections.abc import Callable
-    from typing import Any, TypedDict
+    from typing import Any, Callable, TypedDict
 
     from typing_extensions import Required  # Fallback for Python <3.11
 

.ci/lumen_cli/cli/lib/common/git_helper.py

@@ -57,8 +57,8 @@ def clone_external_repo(target: str, repo: str, dst: str = "", update_submodules
         logger.info("Successfully cloned %s", target)
         return r, commit
 
-    except GitCommandError:
-        logger.exception("Git operation failed")
+    except GitCommandError as e:
+        logger.error("Git operation failed: %s", e)
         raise
 
 

.ci/lumen_cli/cli/lib/core/vllm/lib.py

@@ -41,6 +41,7 @@ def sample_vllm_test_library():
                 "pytest -v -s basic_correctness/test_cumem.py",
                 "pytest -v -s basic_correctness/test_basic_correctness.py",
                 "pytest -v -s basic_correctness/test_cpu_offload.py",
+                "VLLM_TEST_ENABLE_ARTIFICIAL_PREEMPT=1 pytest -v -s basic_correctness/test_preemption.py",
             ],
         },
         "vllm_basic_models_test": {
@@ -67,12 +68,16 @@ def sample_vllm_test_library():
                         "-v",
                         "-s",
                         "entrypoints/llm",
+                        "--ignore=entrypoints/llm/test_lazy_outlines.py",
                         "--ignore=entrypoints/llm/test_generate.py",
+                        "--ignore=entrypoints/llm/test_generate_multiple_loras.py",
                         "--ignore=entrypoints/llm/test_collective_rpc.py",
                     ]
                 ),
-                "pytest -v -s entrypoints/llm/test_generate.py",
-                "pytest -v -s entrypoints/offline_mode",
+                "pytest -v -s entrypoints/llm/test_lazy_outlines.py",
+                "pytest -v -s entrypoints/llm/test_generate.py ",
+                "pytest -v -s entrypoints/llm/test_generate_multiple_loras.py",
+                "VLLM_USE_V1=0 pytest -v -s entrypoints/offline_mode",
             ],
         },
         "vllm_regression_test": {
@@ -92,24 +97,14 @@ def sample_vllm_test_library():
             "num_gpus": 4,
             "steps": [
                 "pytest -v -s -x lora/test_chatglm3_tp.py",
+                "echo $VLLM_WORKER_MULTIPROC_METHOD",
                 "pytest -v -s -x lora/test_llama_tp.py",
-                "pytest -v -s -x lora/test_llm_with_multi_loras.py",
+                "pytest -v -s -x lora/test_multi_loras_with_tp.py",
             ],
         },
-        "vllm_distributed_test_28_failure_test": {
-            "title": "Distributed Tests (2 GPUs) pytorch 2.8 release failure",
-            "id": "vllm_distributed_test_28_failure_test",
-            "env_vars": {
-                "VLLM_WORKER_MULTIPROC_METHOD": "spawn",
-            },
-            "num_gpus": 4,
-            "steps": [
-                "pytest -v -s distributed/test_sequence_parallel.py",
-            ],
-        },
-        "vllm_lora_28_failure_test": {
-            "title": "LoRA pytorch 2.8 failure test",
-            "id": "vllm_lora_28_failure_test",
+        "vllm_lora_280_failure_test": {
+            "title": "LoRA 280 failure test",
+            "id": "vllm_lora_280_failure_test",
             "steps": ["pytest -v lora/test_quant_model.py"],
         },
         "vllm_multi_model_processor_test": {
@@ -120,15 +115,6 @@ def sample_vllm_test_library():
                 "pytest -v -s models/multimodal/processing --ignore models/multimodal/processing/test_tensor_schema.py",
             ],
         },
-        "vllm_multi_model_test_28_failure_test": {
-            "title": "Multi-Model Test (Failed 2.8 release)",
-            "id": "vllm_multi_model_test_28_failure_test",
-            "package_install": ["git+https://github.com/TIGER-AI-Lab/Mantis.git"],
-            "steps": [
-                "pytest -v -s models/multimodal/generation/test_voxtral.py",
-                "pytest -v -s models/multimodal/pooling",
-            ],
-        },
         "vllm_pytorch_compilation_unit_tests": {
             "title": "PyTorch Compilation Unit Tests",
             "id": "vllm_pytorch_compilation_unit_tests",
@@ -143,28 +129,6 @@ def sample_vllm_test_library():
                 "pytest -v -s compile/test_decorator.py",
             ],
         },
-        "vllm_language_model_test_extended_generation_28_failure_test": {
-            "title": "Language Models Test (Extended Generation) 2.8 release failure",
-            "id": "vllm_languagde_model_test_extended_generation_28_failure_test",
-            "package_install": [
-                "--no-build-isolation",
-                "git+https://github.com/Dao-AILab/causal-conv1d@v1.5.0.post8",
-            ],
-            "steps": [
-                "pytest -v -s models/language/generation/test_mistral.py",
-            ],
-        },
-        "vllm_distributed_test_2_gpu_28_failure_test": {
-            "title": "Distributed Tests (2 GPUs) pytorch 2.8 release failure",
-            "id": "vllm_distributed_test_2_gpu_28_failure_test",
-            "env_vars": {
-                "VLLM_WORKER_MULTIPROC_METHOD": "spawn",
-            },
-            "num_gpus": 4,
-            "steps": [
-                "pytest -v -s distributed/test_sequence_parallel.py",
-            ],
-        },
         # TODO(elainewy):need to add g6 with 4 gpus to run this test
         "vllm_lora_test": {
             "title": "LoRA Test %N",

.ci/lumen_cli/cli/lib/core/vllm/vllm_build.py

@@ -63,12 +63,7 @@ class VllmBuildParameters:
     # DOCKERFILE_PATH: path to Dockerfile used when use_local_dockerfile is True"
     use_local_dockerfile: bool = env_bool_field("USE_LOCAL_DOCKERFILE", True)
     dockerfile_path: Path = env_path_field(
-        "DOCKERFILE_PATH", ".github/ci_configs/vllm/Dockerfile"
-    )
-
-    # the cleaning script to remove torch dependencies from pip
-    cleaning_script: Path = env_path_field(
-        "cleaning_script", ".github/ci_configs/vllm/use_existing_torch.py"
+        "DOCKERFILE_PATH", ".github/ci_configs/vllm/Dockerfile.tmp_vllm"
     )
 
     # OUTPUT_DIR: where docker buildx (local exporter) will write artifacts
@@ -165,7 +160,6 @@ class VllmBuildRunner(BaseRunner):
         logger.info("Running vllm build with inputs: %s", inputs)
         vllm_commit = clone_vllm()
 
-        self.cp_torch_cleaning_script(inputs)
         self.cp_dockerfile_if_exist(inputs)
         # cp torch wheels from root direct to vllm workspace if exist
         self.cp_torch_whls_if_exist(inputs)
@@ -211,11 +205,6 @@ class VllmBuildRunner(BaseRunner):
         copy(inputs.torch_whls_path, tmp_dir)
         return tmp_dir
 
-    def cp_torch_cleaning_script(self, inputs: VllmBuildParameters):
-        script = get_path(inputs.cleaning_script, resolve=True)
-        vllm_script = Path(f"./{self.work_directory}/use_existing_torch.py")
-        copy(script, vllm_script)
-
     def cp_dockerfile_if_exist(self, inputs: VllmBuildParameters):
         if not inputs.use_local_dockerfile:
             logger.info("using vllm default dockerfile.torch_nightly for build")

.ci/lumen_cli/cli/lib/core/vllm/vllm_test.py

@@ -11,7 +11,7 @@ from typing import Any
 
 from cli.lib.common.cli_helper import BaseRunner
 from cli.lib.common.envs_helper import env_path_field, env_str_field, get_env
-from cli.lib.common.path_helper import copy, get_path, remove_dir
+from cli.lib.common.path_helper import copy, remove_dir
 from cli.lib.common.pip_helper import (
     pip_install_first_match,
     pip_install_packages,
@@ -43,10 +43,6 @@ class VllmTestParameters:
 
     torch_cuda_arch_list: str = env_str_field("TORCH_CUDA_ARCH_LIST", "8.9")
 
-    cleaning_script: Path = env_path_field(
-        "cleaning_script", ".github/ci_configs/vllm/use_existing_torch.py"
-    )
-
     def __post_init__(self):
         if not self.torch_whls_path.exists():
             raise ValueError("missing torch_whls_path")
@@ -96,13 +92,11 @@ class VllmTestRunner(BaseRunner):
         self._set_envs(params)
 
         clone_vllm(dst=self.work_directory)
-        self.cp_torch_cleaning_script(params)
         with working_directory(self.work_directory):
             remove_dir(Path("vllm"))
             self._install_wheels(params)
             self._install_dependencies()
         # verify the torches are not overridden by test dependencies
-
         check_versions()
 
     def run(self):
@@ -110,31 +104,20 @@ class VllmTestRunner(BaseRunner):
         main function to run vllm test
         """
         self.prepare()
-        try:
-            with working_directory(self.work_directory):
-                if self.test_type == TestInpuType.TEST_PLAN:
-                    if self.num_shards > 1:
-                        run_test_plan(
-                            self.test_plan,
-                            "vllm",
-                            sample_vllm_test_library(),
-                            self.shard_id,
-                            self.num_shards,
-                        )
-                    else:
-                        run_test_plan(
-                            self.test_plan, "vllm", sample_vllm_test_library()
-                        )
+        with working_directory(self.work_directory):
+            if self.test_type == TestInpuType.TEST_PLAN:
+                if self.num_shards > 1:
+                    run_test_plan(
+                        self.test_plan,
+                        "vllm",
+                        sample_vllm_test_library(),
+                        self.shard_id,
+                        self.num_shards,
+                    )
                 else:
-                    raise ValueError(f"Unknown test type {self.test_type}")
-        finally:
-            # double check the torches are not overridden by other packages
-            check_versions()
-
-    def cp_torch_cleaning_script(self, params: VllmTestParameters):
-        script = get_path(params.cleaning_script, resolve=True)
-        vllm_script = Path(f"./{self.work_directory}/use_existing_torch.py")
-        copy(script, vllm_script)
+                    run_test_plan(self.test_plan, "vllm", sample_vllm_test_library())
+            else:
+                raise ValueError(f"Unknown test type {self.test_type}")
 
     def _install_wheels(self, params: VllmTestParameters):
         logger.info("Running vllm test with inputs: %s", params)

.ci/lumen_cli/pyproject.toml

@@ -6,7 +6,7 @@ dependencies = [
     "GitPython==3.1.45",
     "docker==7.1.0",
     "pytest==7.3.2",
-    "uv==0.9.6"
+    "uv==0.8.6"
 ]
 
 [tool.setuptools]

.ci/magma-rocm/Makefile

@@ -1,11 +1,11 @@
 SHELL=/usr/bin/env bash
 
 DOCKER_CMD ?= docker
-DESIRED_ROCM ?= 7.1
+DESIRED_ROCM ?= 6.4
 DESIRED_ROCM_SHORT = $(subst .,,$(DESIRED_ROCM))
 PACKAGE_NAME = magma-rocm
 # inherit this from underlying docker image, do not pass this env var to docker
-#PYTORCH_ROCM_ARCH ?= gfx900;gfx906;gfx908;gfx90a;gfx942;gfx950;gfx1030;gfx1100;gfx1101;gfx1102;gfx1150;gfx1151;gfx1200;gfx1201
+#PYTORCH_ROCM_ARCH ?= gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201
 
 DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
 	-v $(shell git rev-parse --show-toplevel)/.ci:/builder \
@@ -16,26 +16,20 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
 	magma-rocm/build_magma.sh
 
 .PHONY: all
-all: magma-rocm71
-all: magma-rocm70
 all: magma-rocm64
+all: magma-rocm63
 
 .PHONY:
 clean:
 	$(RM) -r magma-*
 	$(RM) -r output
 
-.PHONY: magma-rocm71
-magma-rocm71: DESIRED_ROCM := 7.1
-magma-rocm71:
-	$(DOCKER_RUN)
-
-.PHONY: magma-rocm70
-magma-rocm70: DESIRED_ROCM := 7.0
-magma-rocm70:
-	$(DOCKER_RUN)
-
 .PHONY: magma-rocm64
 magma-rocm64: DESIRED_ROCM := 6.4
 magma-rocm64:
 	$(DOCKER_RUN)
+
+.PHONY: magma-rocm63
+magma-rocm63: DESIRED_ROCM := 6.3
+magma-rocm63:
+	$(DOCKER_RUN)

.ci/magma-rocm/README.md

@@ -30,6 +30,7 @@ into a tarball, with the following structure:
 More specifically, `build_magma.sh` copies over the relevant files from the `package_files` directory depending on the ROCm version.
 Outputted binaries should be in the `output` folder.
 
+
 ## Pushing
 
 Packages can be uploaded to an S3 bucket using:

.ci/magma-rocm/build_magma.sh

@@ -6,8 +6,8 @@ set -eou pipefail
 # The script expects DESIRED_CUDA and PACKAGE_NAME to be set
 ROOT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
 
-# https://github.com/icl-utk-edu/magma/pull/65
-MAGMA_VERSION=d6e4117bc88e73f06d26c6c2e14f064e8fc3d1ec
+# Version 2.7.2 + ROCm related updates
+MAGMA_VERSION=a1625ff4d9bc362906bd01f805dbbe12612953f6
 
 # Folders for the build
 PACKAGE_FILES=${ROOT_DIR}/magma-rocm/package_files # metadata
@@ -20,7 +20,7 @@ mkdir -p ${PACKAGE_DIR} ${PACKAGE_OUTPUT}/linux-64 ${PACKAGE_BUILD} ${PACKAGE_RE
 
 # Fetch magma sources and verify checksum
 pushd ${PACKAGE_DIR}
-git clone https://github.com/jeffdaily/magma
+git clone https://bitbucket.org/icl/magma.git
 pushd magma
 git checkout ${MAGMA_VERSION}
 popd

.ci/manywheel/build.sh

@@ -4,17 +4,14 @@ set -ex
 
 SCRIPTPATH="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
 
-# Source the common build script for architecture-specific configurations (MKLDNN, ACL, etc.)
-source "${SCRIPTPATH}/../pytorch/build.sh" || true
-
 case "${GPU_ARCH_TYPE:-BLANK}" in
-    cuda | cuda-aarch64)
+    cuda)
         bash "${SCRIPTPATH}/build_cuda.sh"
         ;;
     rocm)
         bash "${SCRIPTPATH}/build_rocm.sh"
         ;;
-    cpu | cpu-cxx11-abi | cpu-aarch64 | cpu-s390x)
+    cpu | cpu-cxx11-abi | cpu-s390x)
         bash "${SCRIPTPATH}/build_cpu.sh"
         ;;
     xpu)

.ci/manywheel/build_common.sh

@@ -18,31 +18,12 @@ retry () {
     $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
 }
 
-# Detect architecture first
-ARCH=$(uname -m)
-echo "Detected architecture: $ARCH"
-
 PLATFORM=""
 # TODO move this into the Docker images
 OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
 if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
     retry yum install -q -y zip openssl
-    # Set platform based on architecture
-    case $ARCH in
-        x86_64)
-            PLATFORM="manylinux_2_28_x86_64"
-            ;;
-        aarch64)
-            PLATFORM="manylinux_2_28_aarch64"
-            ;;
-        s390x)
-            PLATFORM="manylinux_2_28_s390x"
-            ;;
-        *)
-            echo "Unsupported architecture: $ARCH"
-            exit 1
-            ;;
-    esac
+    PLATFORM="manylinux_2_28_x86_64"
 elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
     retry dnf install -q -y zip openssl
 elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
@@ -57,8 +38,6 @@ else
     exit 1
 fi
 
-echo "Platform set to: $PLATFORM"
-
 # We use the package name to test the package by passing this to 'pip install'
 # This is the env variable that setup.py uses to name the package. Note that
 # pip 'normalizes' the name first by changing all - to _
@@ -163,7 +142,7 @@ time CMAKE_ARGS=${CMAKE_ARGS[@]} \
     EXTRA_CAFFE2_CMAKE_FLAGS=${EXTRA_CAFFE2_CMAKE_FLAGS[@]} \
     BUILD_LIBTORCH_CPU_WITH_DEBUG=$BUILD_DEBUG_INFO \
     USE_NCCL=${USE_NCCL} USE_RCCL=${USE_RCCL} USE_KINETO=${USE_KINETO} \
-    python -m build --wheel --no-isolation --outdir /tmp/$WHEELHOUSE_DIR
+    python setup.py bdist_wheel -d /tmp/$WHEELHOUSE_DIR
 echo "Finished setup.py bdist at $(date)"
 
 # Build libtorch packages
@@ -320,8 +299,8 @@ for pkg in /$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/torch*linux*.w
             # ROCm workaround for roctracer dlopens
             if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
                 patchedpath=$(fname_without_so_number $destpath)
-            # Keep the so number for XPU dependencies, libgomp.so.1, ACL libraries, and NVPL libraries to avoid twice load
-            elif [[ "$DESIRED_CUDA" == *"xpu"* || "$filename" == "libgomp.so.1" || "$filename" == libarm_compute* || "$filename" == libnvpl* || "$filename" == "libgfortran.so.5" ]]; then
+            # Keep the so number for XPU dependencies and libgomp.so.1 to avoid twice load
+            elif [[ "$DESIRED_CUDA" == *"xpu"* || "$filename" == "libgomp.so.1" ]]; then
                 patchedpath=$destpath
             else
                 patchedpath=$(fname_with_sha256 $destpath)
@@ -367,22 +346,9 @@ for pkg in /$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/torch*linux*.w
     done
 
     # create Manylinux 2_28 tag this needs to happen before regenerate the RECORD
-    # Support all architectures (x86_64, aarch64, s390x)
-    if [[ "$IS_MANYLINUX2_28" == "1" && $GPU_ARCH_TYPE != "xpu" ]]; then
+    if [[ $PLATFORM == "manylinux_2_28_x86_64" && $GPU_ARCH_TYPE != "cpu-s390x" && $GPU_ARCH_TYPE != "xpu" ]]; then
         wheel_file=$(echo $(basename $pkg) | sed -e 's/-cp.*$/.dist-info\/WHEEL/g')
-        echo "Updating wheel tag for $ARCH architecture"
-        # Replace linux_* with manylinux_2_28_* based on architecture
-        case $ARCH in
-            x86_64)
-                sed -i -e 's#linux_x86_64#manylinux_2_28_x86_64#g' $wheel_file
-                ;;
-            aarch64)
-                sed -i -e 's#linux_aarch64#manylinux_2_28_aarch64#g' $wheel_file
-                ;;
-            s390x)
-                sed -i -e 's#linux_s390x#manylinux_2_28_s390x#g' $wheel_file
-                ;;
-        esac
+        sed -i -e s#linux_x86_64#"${PLATFORM}"# $wheel_file;
     fi
 
     # regenerate the RECORD file with new hashes

.ci/manywheel/build_cpu.sh

@@ -15,10 +15,6 @@ if [[ -z "$EXTRA_CAFFE2_CMAKE_FLAGS" ]]; then
     EXTRA_CAFFE2_CMAKE_FLAGS=()
 fi
 
-# Detect architecture
-ARCH=$(uname -m)
-echo "Building CPU wheel for architecture: $ARCH"
-
 WHEELHOUSE_DIR="wheelhousecpu"
 LIBTORCH_HOUSE_DIR="libtorch_housecpu"
 if [[ -z "$PYTORCH_FINAL_PACKAGE_DIR" ]]; then
@@ -38,10 +34,8 @@ elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
 elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
     LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
 elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
-    if [[ "$ARCH" == "s390x" ]]; then
+    if [[ "$(uname -m)" == "s390x" ]]; then
         LIBGOMP_PATH="/usr/lib/s390x-linux-gnu/libgomp.so.1"
-    elif [[ "$ARCH" == "aarch64" ]]; then
-        LIBGOMP_PATH="/usr/lib/aarch64-linux-gnu/libgomp.so.1"
     else
         LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
     fi
@@ -55,32 +49,6 @@ DEPS_SONAME=(
     "libgomp.so.1"
 )
 
-# Add ARM-specific library dependencies for CPU builds
-if [[ "$ARCH" == "aarch64" ]]; then
-    echo "Adding ARM-specific CPU library dependencies"
-
-    # ARM Compute Library (if available)
-    if [[ -d "/acl/build" ]]; then
-        echo "Adding ARM Compute Library for CPU"
-        DEPS_LIST+=(
-            "/acl/build/libarm_compute.so"
-            "/acl/build/libarm_compute_graph.so"
-        )
-        DEPS_SONAME+=(
-            "libarm_compute.so"
-            "libarm_compute_graph.so"
-        )
-    fi
-
-    # ARM system libraries
-    DEPS_LIST+=(
-        "/usr/lib64/libgfortran.so.5"
-    )
-    DEPS_SONAME+=(
-        "libgfortran.so.5"
-    )
-fi
-
 rm -rf /usr/local/cuda*
 
 SOURCE_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null && pwd )"

.ci/manywheel/build_cuda.sh

@@ -29,10 +29,6 @@ if [[ -z "$EXTRA_CAFFE2_CMAKE_FLAGS" ]]; then
     EXTRA_CAFFE2_CMAKE_FLAGS=()
 fi
 
-# Detect architecture
-ARCH=$(uname -m)
-echo "Building for architecture: $ARCH"
-
 # Determine CUDA version and architectures to build for
 #
 # NOTE: We should first check `DESIRED_CUDA` when determining `CUDA_VERSION`,
@@ -57,60 +53,34 @@ fi
 cuda_version_nodot=$(echo $CUDA_VERSION | tr -d '.')
 EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
 
-# Function to remove architectures from a list
-remove_archs() {
-    local result="$1"
-    shift
-    for arch in "$@"; do
-        result="${result//${arch};/}"
-    done
-    echo "$result"
-}
-
-# Function to filter CUDA architectures for aarch64
-# aarch64 ARM GPUs only support certain compute capabilities
-# Keep: 8.0 (A100), 9.0+ (Hopper, Grace Hopper, newer)
-# Remove: < 8.0 (no ARM GPUs), 8.6 (x86_64 RTX 3090/A6000 only)
-filter_aarch64_archs() {
-    local arch_list="$1"
-    # Explicitly remove architectures not needed on aarch64
-    arch_list=$(remove_archs "$arch_list" "5.0" "6.0" "7.0" "7.5" "8.6")
-    echo "$arch_list"
-}
-
-# Base: Common architectures across all modern CUDA versions
-TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6;9.0"
-
 case ${CUDA_VERSION} in
-    12.6) TORCH_CUDA_ARCH_LIST="5.0;6.0;${TORCH_CUDA_ARCH_LIST}" ;;  # Only 12.6 includes Legacy Maxwell/Pascal that will be removed in future releases
-    12.8) TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};10.0;12.0" ;;  # +Hopper/Blackwell support
-    12.9) TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};10.0;12.0+PTX" # +Hopper/Blackwell support + PTX for forward compatibility
+    #removing sm_50-sm_60 as these architectures are deprecated in CUDA 12.8/9 and will be removed in future releases
+    #however we would like to keep sm_70 architecture see: https://github.com/pytorch/pytorch/issues/157517
+    12.8)
+        TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6;9.0;10.0;12.0"
+        ;;
+    12.9)
+        TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6;9.0;10.0;12.0+PTX"
+        # WAR to resolve the ld error in libtorch build with CUDA 12.9
         if [[ "$PACKAGE_TYPE" == "libtorch" ]]; then
-            TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST//7.0;/}"  # Remove 7.0 to resolve the ld error
-            TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST//8.6;/}"  # Remove 8.6 for libtorch
+            TORCH_CUDA_ARCH_LIST="7.5;8.0;9.0;10.0;12.0+PTX"
         fi
         ;;
     13.0)
-        TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;$([[ "$ARCH" == "aarch64" ]] && echo "11.0;" || echo "")12.0+PTX"
-        export TORCH_NVCC_FLAGS="-compress-mode=size"
-        export BUILD_BUNDLE_PTXAS=1
+        TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;12.0+PTX"
+        ;;
+    12.6)
+        TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;7.5;8.0;8.6;9.0"
+        ;;
+    *)
+        echo "unknown cuda version $CUDA_VERSION"
+        exit 1
         ;;
-    *) echo "unknown cuda version $CUDA_VERSION"; exit 1 ;;
 esac
 
-# Filter for aarch64: Remove < 8.0 and 8.6
-[[ "$ARCH" == "aarch64" ]] && TORCH_CUDA_ARCH_LIST=$(filter_aarch64_archs "$TORCH_CUDA_ARCH_LIST")
-
-echo "TORCH_CUDA_ARCH_LIST set to: $TORCH_CUDA_ARCH_LIST"
 export TORCH_CUDA_ARCH_LIST=${TORCH_CUDA_ARCH_LIST}
 echo "${TORCH_CUDA_ARCH_LIST}"
 
-# Disable MAGMA for aarch64 as pre-built libraries are x86-64 only
-if [[ "$ARCH" == "aarch64" ]]; then
-    echo "Disabling MAGMA for aarch64 architecture"
-    export USE_MAGMA=0
-fi
-
 # Package directories
 WHEELHOUSE_DIR="wheelhouse$cuda_version_nodot"
 LIBTORCH_HOUSE_DIR="libtorch_house$cuda_version_nodot"
@@ -154,7 +124,6 @@ if [[ $CUDA_VERSION == 12* || $CUDA_VERSION == 13* ]]; then
     fi
     if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
         echo "Bundling with cudnn and cublas."
-
         DEPS_LIST+=(
             "/usr/local/cuda/lib64/libcudnn_adv.so.9"
             "/usr/local/cuda/lib64/libcudnn_cnn.so.9"
@@ -164,11 +133,16 @@ if [[ $CUDA_VERSION == 12* || $CUDA_VERSION == 13* ]]; then
             "/usr/local/cuda/lib64/libcudnn_engines_precompiled.so.9"
             "/usr/local/cuda/lib64/libcudnn_heuristic.so.9"
             "/usr/local/cuda/lib64/libcudnn.so.9"
+            "/usr/local/cuda/lib64/libcublas.so.12"
+            "/usr/local/cuda/lib64/libcublasLt.so.12"
             "/usr/local/cuda/lib64/libcusparseLt.so.0"
+            "/usr/local/cuda/lib64/libcudart.so.12"
+            "/usr/local/cuda/lib64/libnvrtc.so.12"
             "/usr/local/cuda/lib64/libnvrtc-builtins.so"
             "/usr/local/cuda/lib64/libcufile.so.0"
             "/usr/local/cuda/lib64/libcufile_rdma.so.1"
             "/usr/local/cuda/lib64/libnvshmem_host.so.3"
+            "/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12"
             "/usr/local/cuda/extras/CUPTI/lib64/libnvperf_host.so"
         )
         DEPS_SONAME+=(
@@ -180,59 +154,22 @@ if [[ $CUDA_VERSION == 12* || $CUDA_VERSION == 13* ]]; then
             "libcudnn_engines_precompiled.so.9"
             "libcudnn_heuristic.so.9"
             "libcudnn.so.9"
+            "libcublas.so.12"
+            "libcublasLt.so.12"
             "libcusparseLt.so.0"
+            "libcudart.so.12"
+            "libnvrtc.so.12"
             "libnvrtc-builtins.so"
             "libnvshmem_host.so.3"
             "libcufile.so.0"
             "libcufile_rdma.so.1"
+            "libcupti.so.12"
             "libnvperf_host.so"
         )
         # Add libnvToolsExt only if CUDA version is not 12.9
-        if [[ $CUDA_VERSION == 13* ]]; then
-            DEPS_LIST+=(
-                "/usr/local/cuda/lib64/libcublas.so.13"
-                "/usr/local/cuda/lib64/libcublasLt.so.13"
-                "/usr/local/cuda/lib64/libcudart.so.13"
-                "/usr/local/cuda/lib64/libnvrtc.so.13"
-                "/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.13"
-                "/usr/local/cuda/lib64/libibverbs.so.1"
-                "/usr/local/cuda/lib64/librdmacm.so.1"
-                "/usr/local/cuda/lib64/libmlx5.so.1"
-                "/usr/local/cuda/lib64/libnl-3.so.200"
-                "/usr/local/cuda/lib64/libnl-route-3.so.200")
-            DEPS_SONAME+=(
-                "libcublas.so.13"
-                "libcublasLt.so.13"
-                "libcudart.so.13"
-                "libnvrtc.so.13"
-                "libcupti.so.13"
-                "libibverbs.so.1"
-                "librdmacm.so.1"
-                "libmlx5.so.1"
-                "libnl-3.so.200"
-                "libnl-route-3.so.200")
-            export USE_CUPTI_SO=1
-            export ATEN_STATIC_CUDA=0
-            export USE_CUDA_STATIC_LINK=0
-            export USE_CUFILE=0
-        else
-            DEPS_LIST+=(
-                "/usr/local/cuda/lib64/libcublas.so.12"
-                "/usr/local/cuda/lib64/libcublasLt.so.12"
-                "/usr/local/cuda/lib64/libcudart.so.12"
-                "/usr/local/cuda/lib64/libnvrtc.so.12"
-                "/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12")
-            DEPS_SONAME+=(
-                "libcublas.so.12"
-                "libcublasLt.so.12"
-                "libcudart.so.12"
-                "libnvrtc.so.12"
-                "libcupti.so.12")
-
-            if [[ $CUDA_VERSION != 12.9* ]]; then
-                DEPS_LIST+=("/usr/local/cuda/lib64/libnvToolsExt.so.1")
-                DEPS_SONAME+=("libnvToolsExt.so.1")
-            fi
+        if [[ $CUDA_VERSION != 12.9* ]]; then
+            DEPS_LIST+=("/usr/local/cuda/lib64/libnvToolsExt.so.1")
+            DEPS_SONAME+=("libnvToolsExt.so.1")
         fi
     else
         echo "Using nvidia libs from pypi."
@@ -274,51 +211,6 @@ else
     exit 1
 fi
 
-# Add ARM-specific library dependencies
-if [[ "$ARCH" == "aarch64" ]]; then
-    echo "Adding ARM-specific library dependencies"
-
-    # ARM Compute Library (if available)
-    if [[ -d "/acl/build" ]]; then
-        echo "Adding ARM Compute Library"
-        DEPS_LIST+=(
-            "/acl/build/libarm_compute.so"
-            "/acl/build/libarm_compute_graph.so"
-        )
-        DEPS_SONAME+=(
-            "libarm_compute.so"
-            "libarm_compute_graph.so"
-        )
-    fi
-
-    # ARM system libraries
-    DEPS_LIST+=(
-        "/lib64/libgomp.so.1"
-        "/usr/lib64/libgfortran.so.5"
-    )
-    DEPS_SONAME+=(
-        "libgomp.so.1"
-        "libgfortran.so.5"
-    )
-
-    # NVPL libraries (ARM optimized BLAS/LAPACK)
-    if [[ -d "/usr/local/lib" && -f "/usr/local/lib/libnvpl_blas_lp64_gomp.so.0" ]]; then
-        echo "Adding NVPL libraries for ARM"
-        DEPS_LIST+=(
-            "/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0"
-            "/usr/local/lib/libnvpl_blas_lp64_gomp.so.0"
-            "/usr/local/lib/libnvpl_lapack_core.so.0"
-            "/usr/local/lib/libnvpl_blas_core.so.0"
-        )
-        DEPS_SONAME+=(
-            "libnvpl_lapack_lp64_gomp.so.0"
-            "libnvpl_blas_lp64_gomp.so.0"
-            "libnvpl_lapack_core.so.0"
-            "libnvpl_blas_core.so.0"
-        )
-    fi
-fi
-
 # run_tests.sh requires DESIRED_CUDA to know what tests to exclude
 export DESIRED_CUDA="$cuda_version_nodot"
 
@@ -326,11 +218,9 @@ export DESIRED_CUDA="$cuda_version_nodot"
 rm -rf /usr/local/cuda || true
 ln -s "/usr/local/cuda-${CUDA_VERSION}" /usr/local/cuda
 
-# Switch `/usr/local/magma` to the desired CUDA version (skip for aarch64)
-if [[ "$ARCH" != "aarch64" ]]; then
-    rm -rf /usr/local/magma || true
-    ln -s /usr/local/cuda-${CUDA_VERSION}/magma /usr/local/magma
-fi
+# Switch `/usr/local/magma` to the desired CUDA version
+rm -rf /usr/local/magma || true
+ln -s /usr/local/cuda-${CUDA_VERSION}/magma /usr/local/magma
 
 export CUDA_VERSION=$(ls /usr/local/cuda/lib64/libcudart.so.*|sort|tac | head -1 | rev | cut -d"." -f -3 | rev) # 10.0.130
 export CUDA_VERSION_SHORT=$(ls /usr/local/cuda/lib64/libcudart.so.*|sort|tac | head -1 | rev | cut -d"." -f -3 | rev | cut -f1,2 -d".") # 10.0

.ci/manywheel/build_libtorch.sh

@@ -104,7 +104,7 @@ if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
     export ROCclr_DIR=/opt/rocm/rocclr/lib/cmake/rocclr
 fi
 
-echo "Calling -m pip install . -v --no-build-isolation at $(date)"
+echo "Calling 'python -m pip install .' at $(date)"
 
 if [[ $LIBTORCH_VARIANT = *"static"* ]]; then
     STATIC_CMAKE_FLAG="-DTORCH_STATIC=1"

.ci/manywheel/build_rocm.sh

@@ -107,10 +107,6 @@ if [[ $ROCM_INT -ge 60200 ]]; then
     ROCM_SO_FILES+=("librocm-core.so")
 fi
 
-if [[ $ROCM_INT -ge 70000 ]]; then
-    ROCM_SO_FILES+=("librocroller.so")
-fi
-
 OS_NAME=`awk -F= '/^NAME/{print $2}' /etc/os-release`
 if [[ "$OS_NAME" == *"CentOS Linux"* || "$OS_NAME" == *"AlmaLinux"* ]]; then
     LIBGOMP_PATH="/usr/lib64/libgomp.so.1"

.ci/pytorch/build.sh

@@ -86,20 +86,10 @@ else
   fi
 fi
 
-# Enable MKLDNN with ARM Compute Library for ARM builds
 if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
   export USE_MKLDNN=1
-
-  # ACL is required for aarch64 builds
-  if [[ ! -d "/acl" ]]; then
-    echo "ERROR: ARM Compute Library not found at /acl"
-    echo "ACL is required for aarch64 builds. Check Docker image setup."
-    exit 1
-  fi
-
   export USE_MKLDNN_ACL=1
-  export ACL_ROOT_DIR=/acl
-  echo "ARM Compute Library enabled for MKLDNN: ACL_ROOT_DIR=/acl"
+  export ACL_ROOT_DIR=/ComputeLibrary
 fi
 
 if [[ "$BUILD_ENVIRONMENT" == *riscv64* ]]; then
@@ -178,16 +168,14 @@ if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   # shellcheck disable=SC1091
   source /opt/intel/oneapi/compiler/latest/env/vars.sh
   # shellcheck disable=SC1091
-  source /opt/intel/oneapi/umf/latest/env/vars.sh
-  # shellcheck disable=SC1091
   source /opt/intel/oneapi/ccl/latest/env/vars.sh
   # shellcheck disable=SC1091
   source /opt/intel/oneapi/mpi/latest/env/vars.sh
-  # shellcheck disable=SC1091
-  source /opt/intel/oneapi/pti/latest/env/vars.sh
   # Enable XCCL build
   export USE_XCCL=1
   export USE_MPI=0
+  # 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
 
@@ -245,9 +233,7 @@ if [[ "${BUILD_ENVIRONMENT}" != *cuda* ]]; then
   export BUILD_STATIC_RUNTIME_BENCHMARK=ON
 fi
 
-if [[ "$BUILD_ENVIRONMENT" == *-full-debug* ]]; then
-  export CMAKE_BUILD_TYPE=Debug
-elif [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
+if [[ "$BUILD_ENVIRONMENT" == *-debug* ]]; then
   export CMAKE_BUILD_TYPE=RelWithAssert
 fi
 
@@ -304,20 +290,15 @@ else
 
       WERROR=1 python setup.py clean
 
-      WERROR=1 python -m build --wheel --no-isolation
+      WERROR=1 python setup.py bdist_wheel
     else
       python setup.py clean
       if [[ "$BUILD_ENVIRONMENT" == *xla* ]]; then
         source .ci/pytorch/install_cache_xla.sh
       fi
-      python -m build --wheel --no-isolation
+      python setup.py bdist_wheel
     fi
     pip_install_whl "$(echo dist/*.whl)"
-    if [[ "$BUILD_ENVIRONMENT" == *full-debug* ]]; then
-      # Regression test for https://github.com/pytorch/pytorch/issues/164297
-      # Torch should be importable and that's about it
-      pushd /; python -c "import torch;print(torch.__config__.show(), torch.randn(5) + 1.7)"; popd
-    fi
 
     if [[ "${BUILD_ADDITIONAL_PACKAGES:-}" == *vision* ]]; then
       install_torchvision
@@ -438,7 +419,7 @@ fi
 if [[ "$BUILD_ENVIRONMENT" != *libtorch* && "$BUILD_ENVIRONMENT" != *bazel* ]]; then
   # export test times so that potential sharded tests that'll branch off this build will use consistent data
   # don't do this for libtorch as libtorch is C++ only and thus won't have python tests run on its build
-  PYTHONPATH=. python tools/stats/export_test_times.py
+  python tools/stats/export_test_times.py
 fi
 # don't do this for bazel or s390x or riscv64 as they don't use sccache
 if [[ "$BUILD_ENVIRONMENT" != *s390x* && "$BUILD_ENVIRONMENT" != *riscv64* && "$BUILD_ENVIRONMENT" != *-bazel-* ]]; then

.ci/pytorch/common_utils.sh

@@ -96,6 +96,7 @@ function pip_build_and_install() {
     python3 -m pip wheel \
       --no-build-isolation \
       --no-deps \
+      --no-use-pep517 \
       -w "${wheel_dir}" \
       "${build_target}"
   fi
@@ -257,19 +258,11 @@ function install_torchrec_and_fbgemm() {
       git clone --recursive https://github.com/pytorch/fbgemm
       pushd fbgemm/fbgemm_gpu
       git checkout "${fbgemm_commit}" --recurse-submodules
-      # until the fbgemm_commit includes the tbb patch
-      patch <<'EOF'
---- a/FbgemmGpu.cmake
-+++ b/FbgemmGpu.cmake
-@@ -184,5 +184,6 @@ gpu_cpp_library(
-     fbgemm_gpu_tbe_cache
-     fbgemm_gpu_tbe_optimizers
-     fbgemm_gpu_tbe_utils
-+    tbb
-   DESTINATION
-     fbgemm_gpu)
-EOF
-      python setup.py bdist_wheel --build-variant=rocm
+      python setup.py bdist_wheel \
+        --build-variant=rocm \
+        -DHIP_ROOT_DIR="${ROCM_PATH}" \
+        -DCMAKE_C_FLAGS="-DTORCH_USE_HIP_DSA" \
+        -DCMAKE_CXX_FLAGS="-DTORCH_USE_HIP_DSA"
       popd
 
       # Save the wheel before cleaning up
@@ -307,28 +300,6 @@ function install_torchao() {
   pip_build_and_install "git+https://github.com/pytorch/ao.git@${commit}" dist/ao
 }
 
-function install_flash_attn_cute() {
-  echo "Installing FlashAttention CuTe from GitHub..."
-  # Grab latest main til we have a pinned commit
-  local flash_attn_commit
-  flash_attn_commit=$(git ls-remote https://github.com/Dao-AILab/flash-attention.git HEAD | cut -f1)
-
-  # Clone the repo to a temporary directory
-  rm -rf flash-attention-build
-  git clone --depth 1 --recursive https://github.com/Dao-AILab/flash-attention.git flash-attention-build
-
-  pushd flash-attention-build
-  git checkout "${flash_attn_commit}"
-
-  # Install only the 'cute' sub-directory
-  pip_install -e flash_attn/cute/
-  popd
-
-  # remove the local repo
-  rm -rf flash-attention-build
-  echo "FlashAttention CuTe installation complete."
-}
-
 function print_sccache_stats() {
   echo 'PyTorch Build Statistics'
   sccache --show-stats

.ci/pytorch/cpp_doc_push_script.sh

@@ -58,7 +58,7 @@ time python tools/setup_helpers/generate_code.py \
 
 # Build the docs
 pushd docs/cpp
-time make VERBOSE=1 html
+time make VERBOSE=1 html -j
 
 popd
 popd

.ci/pytorch/functorch_doc_push_script.sh

@@ -0,0 +1,40 @@
+#!/bin/bash
+
+# This is where the local pytorch install in the docker image is located
+pt_checkout="/var/lib/jenkins/workspace"
+source "$pt_checkout/.ci/pytorch/common_utils.sh"
+echo "functorch_doc_push_script.sh: Invoked with $*"
+
+set -ex -o pipefail
+
+version=${DOCS_VERSION:-nightly}
+echo "version: $version"
+
+# Build functorch docs
+pushd $pt_checkout/functorch/docs
+make html
+popd
+
+git clone https://github.com/pytorch/functorch -b gh-pages --depth 1 functorch_ghpages
+pushd functorch_ghpages
+
+if [ "$version" == "main" ]; then
+  version=nightly
+fi
+
+git rm -rf "$version" || true
+mv "$pt_checkout/functorch/docs/build/html" "$version"
+
+git add "$version" || true
+git status
+git config user.email "soumith+bot@pytorch.org"
+git config user.name "pytorchbot"
+# If there aren't changes, don't make a commit; push is no-op
+git commit -m "Generate Python docs from pytorch/pytorch@${GITHUB_SHA}" || true
+git status
+
+if [[ "${WITH_PUSH:-}" == true ]]; then
+  git push -u origin gh-pages
+fi
+
+popd

.ci/pytorch/macos-build.sh

@@ -35,12 +35,11 @@ fi
 
 print_cmake_info
 if [[ ${BUILD_ENVIRONMENT} == *"distributed"* ]]; then
-  # Needed for inductor benchmarks, as lots of HF networks make `torch.distribtued` calls
-  USE_DISTRIBUTED=1 USE_OPENMP=1 WERROR=1 python -m build --wheel --no-isolation
+  USE_OPENMP=1 WERROR=1 python setup.py bdist_wheel
 else
-  # Explicitly set USE_DISTRIBUTED=0 to align with the default build config on mac. This also serves as the sole CI config that tests
-  # that building with USE_DISTRIBUTED=0 works at all. See https://github.com/pytorch/pytorch/issues/86448
-  USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python -m build --wheel --no-isolation -C--build-option=--plat-name=macosx_11_0_arm64
+  # NB: we always build with distributed; USE_DISTRIBUTED turns off all
+  # backends (specifically the gloo backend), so test that this case works too
+  USE_DISTRIBUTED=0 USE_OPENMP=1 MACOSX_DEPLOYMENT_TARGET=11.0 WERROR=1 BUILD_TEST=OFF USE_PYTORCH_METAL=1 python setup.py bdist_wheel --plat-name macosx_11_0_arm64
 fi
 if which sccache > /dev/null; then
   print_sccache_stats

.ci/pytorch/macos-test.sh

@@ -13,9 +13,13 @@ if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available(
 fi
 popd
 
+python -mpip install -r requirements.txt
+
 # enable debug asserts in serialization
 export TORCH_SERIALIZATION_DEBUG=1
 
+python -mpip install --no-input -r requirements.txt
+
 setup_test_python() {
   # The CircleCI worker hostname doesn't resolve to an address.
   # This environment variable makes ProcessGroupGloo default to
@@ -55,7 +59,7 @@ test_python_shard() {
 
   setup_test_python
 
-  time python test/run_test.py --verbose --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests --shard "$1" "$NUM_TEST_SHARDS"
+  time python test/run_test.py --verbose --exclude-jit-executor --exclude-distributed-tests --shard "$1" "$NUM_TEST_SHARDS"
 
   assert_git_not_dirty
 }
@@ -195,7 +199,7 @@ torchbench_setup_macos() {
   git checkout "$(cat ../.github/ci_commit_pins/vision.txt)"
   git submodule update --init --recursive
   python setup.py clean
-  python -m pip install -e . -v --no-build-isolation
+  python setup.py develop
   popd
 
   pushd torchaudio
@@ -204,7 +208,7 @@ torchbench_setup_macos() {
   git submodule update --init --recursive
   python setup.py clean
   #TODO: Remove me, when figure out how to make TorchAudio find brew installed openmp
-  USE_OPENMP=0 python -m pip install -e . -v --no-build-isolation
+  USE_OPENMP=0 python setup.py develop
   popd
 
   checkout_install_torchbench
@@ -256,7 +260,7 @@ test_torchbench_smoketest() {
   local device=mps
   local dtypes=(undefined float16 bfloat16 notset)
   local dtype=${dtypes[$1]}
-  local models=(llama BERT_pytorch dcgan yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor vgg16)
+  local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor timm_resnet timm_vovnet vgg16)
 
   for backend in eager inductor; do
 
@@ -319,7 +323,7 @@ test_aoti_torchbench_smoketest() {
   local device=mps
   local dtypes=(undefined float16 bfloat16 notset)
   local dtype=${dtypes[$1]}
-  local models=(llama BERT_pytorch dcgan yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor vgg16)
+  local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam sam_fast pytorch_unet stable_diffusion_text_encoder speech_transformer Super_SloMo doctr_det_predictor doctr_reco_predictor timm_resnet timm_vovnet vgg16)
 
   echo "Launching torchbench inference performance run for AOT Inductor and dtype ${dtype}"
   local dtype_arg="--${dtype}"

.ci/pytorch/multigpu-test.sh

@@ -26,7 +26,6 @@ if [[ "${SHARD_NUMBER:-2}" == "2" ]]; then
     time python test/run_test.py --verbose -i distributed/test_c10d_spawn_gloo
     time python test/run_test.py --verbose -i distributed/test_c10d_spawn_nccl
     time python test/run_test.py --verbose -i distributed/test_compute_comm_reordering
-    time python test/run_test.py --verbose -i distributed/test_aten_comm_compute_reordering
     time python test/run_test.py --verbose -i distributed/test_store
     time python test/run_test.py --verbose -i distributed/test_symmetric_memory
     time python test/run_test.py --verbose -i distributed/test_pg_wrapper

.ci/pytorch/numba-cuda-13.patch

@@ -1,25 +0,0 @@
-From 6e08c9d08e9de59c7af28b720289debbbd384764 Mon Sep 17 00:00:00 2001
-From: Michael Wang <13521008+isVoid@users.noreply.github.com>
-Date: Tue, 1 Apr 2025 17:28:05 -0700
-Subject: [PATCH] Avoid bumping certain driver API to avoid future breakage
- (#185)
-
-Co-authored-by: isVoid <isVoid@users.noreply.github.com>
----
- numba_cuda/numba/cuda/cudadrv/driver.py | 3 +++
- 1 file changed, 3 insertions(+)
-
-diff --git a/numba_cuda/numba/cuda/cudadrv/driver.py b/numba_cuda/numba/cuda/cudadrv/driver.py
-index 1641bf77..233e9ed7 100644
---- a/numba_cuda/numba/cuda/cudadrv/driver.py
-+++ b/numba_cuda/numba/cuda/cudadrv/driver.py
-@@ -365,6 +365,9 @@ def _find_api(self, fname):
-         else:
-             variants = ('_v2', '')
- 
-+        if fname in ("cuCtxGetDevice", "cuCtxSynchronize"):
-+            return getattr(self.lib, fname)
-+
-         for variant in variants:
-             try:
-                 return getattr(self.lib, f'{fname}{variant}')

.ci/pytorch/python_doc_push_script.sh

@@ -89,41 +89,23 @@ if [ "$is_main_doc" = true ]; then
 
   make coverage
   # Now we have the coverage report, we need to make sure it is empty.
-  # Sphinx 7.2.6+ format: python.txt contains a statistics table with a TOTAL row
-  # showing the undocumented count in the third column.
-  # Example: | TOTAL | 99.83% | 2 |
+  # Count the number of lines in the file and turn that number into a variable
+  # $lines. The `cut -f1 ...` is to only parse the number, not the filename
+  # Skip the report header by subtracting 2: the header will be output even if
+  # there are no undocumented items.
   #
   # Also: see docs/source/conf.py for "coverage_ignore*" items, which should
   # be documented then removed from there.
-
-  # Extract undocumented count from TOTAL row in Sphinx 7.2.6 statistics table
-  # The table format is: | Module | Coverage | Undocumented |
-  # Extract the third column (undocumented count) from the TOTAL row
-  undocumented=$(grep "| TOTAL" build/coverage/python.txt | awk -F'|' '{print $4}' | tr -d ' ')
-
-  if [ -z "$undocumented" ] || ! [[ "$undocumented" =~ ^[0-9]+$ ]]; then
+  lines=$(wc -l build/coverage/python.txt 2>/dev/null |cut -f1 -d' ')
+  undocumented=$((lines - 2))
+  if [ $undocumented -lt 0 ]; then
     echo coverage output not found
     exit 1
-  elif [ "$undocumented" -gt 0 ]; then
-    set +x  # Disable command echoing for cleaner output
-    echo ""
-    echo "====================="
-    echo "UNDOCUMENTED OBJECTS:"
-    echo "====================="
-    echo ""
-    # Find the line number of the TOTAL row and print only what comes after it
-    total_line=$(grep -n "| TOTAL" build/coverage/python.txt | cut -d: -f1)
-    if [ -n "$total_line" ]; then
-      # Print only the detailed list (skip the statistics table)
-      tail -n +$((total_line + 2)) build/coverage/python.txt
-    else
-      # Fallback to showing entire file if TOTAL line not found
-      cat build/coverage/python.txt
-    fi
-    echo ""
+  elif [ $undocumented -gt 0 ]; then
+    echo undocumented objects found:
+    cat build/coverage/python.txt
     echo "Make sure you've updated relevant .rsts in docs/source!"
-    echo "You can reproduce locally by running 'cd docs && make coverage && tail -n +\$((grep -n \"| TOTAL\" build/coverage/python.txt | cut -d: -f1) + 2)) build/coverage/python.txt'"
-    set -x  # Re-enable command echoing
+    echo "You can reproduce locally by running 'cd docs && make coverage && cat build/coverage/python.txt'"
     exit 1
   fi
 else

.ci/pytorch/smoke_test/check_binary_symbols.py

@@ -32,9 +32,6 @@ LIBTORCH_NAMESPACE_LIST = (
     "torch::",
 )
 
-# Patterns for detecting statically linked libstdc++ symbols
-STATICALLY_LINKED_CXX11_ABI = [re.compile(r".*recursive_directory_iterator.*")]
-
 
 def _apply_libtorch_symbols(symbols):
     return [
@@ -56,17 +53,12 @@ def get_symbols(lib: str) -> list[tuple[str, str, str]]:
     return [x.split(" ", 2) for x in lines.decode("latin1").split("\n")[:-1]]
 
 
-def grep_symbols(
-    lib: str, patterns: list[Any], symbol_type: str | None = None
-) -> 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]:
         rc = []
         for _s_addr, _s_type, s_name in symbols:
-            # Filter by symbol type if specified
-            if symbol_type and _s_type != symbol_type:
-                continue
             for pattern in patterns:
                 if pattern.match(s_name):
                     rc.append(s_name)
@@ -88,18 +80,6 @@ def grep_symbols(
         return functools.reduce(list.__add__, (x.result() for x in tasks), [])
 
 
-def check_lib_statically_linked_libstdc_cxx_abi_symbols(lib: str) -> None:
-    cxx11_statically_linked_symbols = grep_symbols(
-        lib, STATICALLY_LINKED_CXX11_ABI, symbol_type="T"
-    )
-    num_statically_linked_symbols = len(cxx11_statically_linked_symbols)
-    print(f"num_statically_linked_symbols (T): {num_statically_linked_symbols}")
-    if num_statically_linked_symbols > 0:
-        raise RuntimeError(
-            f"Found statically linked libstdc++ symbols (recursive_directory_iterator): {cxx11_statically_linked_symbols[:100]}"
-        )
-
-
 def check_lib_symbols_for_abi_correctness(lib: str) -> None:
     print(f"lib: {lib}")
     cxx11_symbols = grep_symbols(lib, LIBTORCH_CXX11_PATTERNS)
@@ -127,7 +107,6 @@ def main() -> None:
 
     libtorch_cpu_path = str(install_root / "lib" / "libtorch_cpu.so")
     check_lib_symbols_for_abi_correctness(libtorch_cpu_path)
-    check_lib_statically_linked_libstdc_cxx_abi_symbols(libtorch_cpu_path)
 
 
 if __name__ == "__main__":

.ci/pytorch/smoke_test/smoke_test.py

@@ -353,17 +353,6 @@ def test_linalg(device="cpu") -> None:
             torch.linalg.svd(A)
 
 
-def test_sdpa(device="cpu", dtype=torch.float16) -> None:
-    """Regression test for https://github.com/pytorch/pytorch/issues/167602
-    Without nvrtc_builtins on CuDNN-9.13 on CUDA-13 fails with ` No valid execution plans built.`
-    """
-    print(f"Testing SDPA on {device} using type {dtype}")
-    k, q, v = torch.rand(3, 1, 16, 77, 64, dtype=dtype, device=device).unbind(0)
-    attn = torch.rand(1, 1, 77, 77, dtype=dtype, device=device)
-    rc = torch.nn.functional.scaled_dot_product_attention(q, k, v, attn)
-    assert rc.isnan().any().item() is False
-
-
 def smoke_test_compile(device: str = "cpu") -> None:
     supported_dtypes = [torch.float16, torch.float32, torch.float64]
 
@@ -397,8 +386,8 @@ def smoke_test_compile(device: str = "cpu") -> None:
 
 
 def smoke_test_nvshmem() -> None:
-    if not torch.cuda.is_available() or target_os == "windows":
-        print("Windows platform or CUDA is not available, skipping NVSHMEM test")
+    if not torch.cuda.is_available():
+        print("CUDA is not available, skipping NVSHMEM test")
         return
 
     # Check if NVSHMEM is compiled in current build
@@ -407,9 +396,7 @@ def smoke_test_nvshmem() -> None:
     except ImportError:
         # Not built with NVSHMEM support.
         # torch is not compiled with NVSHMEM prior to 2.9
-        from torch.torch_version import TorchVersion
-
-        if TorchVersion(torch.__version__) < (2, 9):
+        if torch.__version__ < "2.9":
             return
         else:
             # After 2.9: NVSHMEM is expected to be compiled in current build
@@ -500,12 +487,10 @@ def main() -> None:
     smoke_test_conv2d()
     test_linalg()
     test_numpy()
-    test_sdpa()
 
     if is_cuda_system:
         test_linalg("cuda")
         test_cuda_gds_errors_captured()
-        test_sdpa("cuda")
 
     if options.package == "all":
         smoke_test_modules()

.ci/pytorch/test.sh

@@ -32,18 +32,6 @@ if [[ "$BUILD_ENVIRONMENT" != *rocm* && "$BUILD_ENVIRONMENT" != *s390x* && -d /v
   git config --global --add safe.directory /var/lib/jenkins/workspace
 fi
 
-
-# Patch numba to avoid CUDA-13 crash, see https://github.com/pytorch/pytorch/issues/162878
-if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
-  NUMBA_CUDA_DIR=$(python -c "import os;import numba.cuda; print(os.path.dirname(numba.cuda.__file__))" 2>/dev/null || true)
-  if [ -n "$NUMBA_CUDA_DIR" ]; then
-    NUMBA_PATCH="$(dirname "$(realpath "${BASH_SOURCE[0]}")")/numba-cuda-13.patch"
-    pushd "$NUMBA_CUDA_DIR"
-    patch -p4 <"$NUMBA_PATCH"
-    popd
-  fi
-fi
-
 echo "Environment variables:"
 env
 
@@ -208,8 +196,6 @@ if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   source /opt/intel/oneapi/ccl/latest/env/vars.sh
   # shellcheck disable=SC1091
   source /opt/intel/oneapi/mpi/latest/env/vars.sh
-  # shellcheck disable=SC1091
-  source /opt/intel/oneapi/pti/latest/env/vars.sh
   # Check XPU status before testing
   timeout 30 xpu-smi discovery || true
 fi
@@ -326,36 +312,20 @@ test_python_shard() {
 
   # modify LD_LIBRARY_PATH to ensure it has the conda env.
   # This set of tests has been shown to be buggy without it for the split-build
-  time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
+  time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --shard "$1" "$NUM_TEST_SHARDS" --verbose $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
 
   assert_git_not_dirty
 }
 
 test_python() {
   # shellcheck disable=SC2086
-  time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests $INCLUDE_CLAUSE --verbose $PYTHON_TEST_EXTRA_OPTION
+  time python test/run_test.py --exclude-jit-executor --exclude-distributed-tests $INCLUDE_CLAUSE --verbose $PYTHON_TEST_EXTRA_OPTION
   assert_git_not_dirty
 }
 
 test_python_smoke() {
-  # Smoke tests for H100/B200
-  time python test/run_test.py --include test_matmul_cuda test_scaled_matmul_cuda inductor/test_fp8 inductor/test_max_autotune inductor/test_cutedsl_grouped_mm $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
-  assert_git_not_dirty
-}
-
-test_python_smoke_b200() {
-  # Targeted smoke tests for B200 including FlashAttention CuTe coverage
-  install_flash_attn_cute
-  time python test/run_test.py \
-    --include \
-      test_matmul_cuda \
-      test_scaled_matmul_cuda \
-      inductor/test_fp8 \
-      nn/attention/test_fa4 \
-      nn/attention/test_open_registry \
-      inductor/test_flex_flash \
-    $PYTHON_TEST_EXTRA_OPTION \
-    --upload-artifacts-while-running
+  # Smoke tests for H100
+  time python test/run_test.py --include test_matmul_cuda inductor/test_fp8 inductor/test_max_autotune $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
   assert_git_not_dirty
 }
 
@@ -404,7 +374,6 @@ test_dynamo_wrapped_shard() {
     --exclude-distributed-tests \
     --exclude-torch-export-tests \
     --exclude-aot-dispatch-tests \
-    --exclude-quantization-tests \
     --shard "$1" "$NUM_TEST_SHARDS" \
     --verbose \
     --upload-artifacts-while-running
@@ -449,7 +418,7 @@ test_inductor_distributed() {
 
   # this runs on both single-gpu and multi-gpu instance. It should be smart about skipping tests that aren't supported
   # with if required # gpus aren't available
-  python test/run_test.py --include distributed/test_dynamo_distributed distributed/test_inductor_collectives distributed/test_aten_comm_compute_reordering distributed/test_compute_comm_reordering --verbose
+  python test/run_test.py --include distributed/test_dynamo_distributed distributed/test_inductor_collectives distributed/test_compute_comm_reordering --verbose
   assert_git_not_dirty
 }
 
@@ -472,37 +441,31 @@ test_inductor_shard() {
     --verbose
 }
 
-test_inductor_aoti_cpp() {
+test_inductor_aoti() {
+  # docker build uses bdist_wheel which does not work with test_aot_inductor
+  # TODO: need a faster way to build
   if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
     # We need to hipify before building again
     python3 tools/amd_build/build_amd.py
   fi
   if [[ "$BUILD_ENVIRONMENT" == *sm86* ]]; then
+    BUILD_COMMAND=(TORCH_CUDA_ARCH_LIST=8.6 USE_FLASH_ATTENTION=OFF python -m pip install --no-build-isolation -v -e .)
     # TODO: Replace me completely, as one should not use conda libstdc++, nor need special path to TORCH_LIB
     TEST_ENVS=(CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="/opt/conda/envs/py_3.10/lib:${TORCH_LIB_DIR}:${LD_LIBRARY_PATH}")
   else
+    BUILD_COMMAND=(python -m pip install --no-build-isolation -v -e .)
     TEST_ENVS=(CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}")
   fi
 
+  # aoti cmake custom command requires `torch` to be installed
+  # initialize the cmake build cache and install torch
+  /usr/bin/env "${BUILD_COMMAND[@]}"
+  # rebuild with the build cache with `BUILD_AOT_INDUCTOR_TEST` enabled
+  /usr/bin/env CMAKE_FRESH=1 BUILD_AOT_INDUCTOR_TEST=1 "${BUILD_COMMAND[@]}"
+
   /usr/bin/env "${TEST_ENVS[@]}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference cpp/test_vec_half_AVX2 -dist=loadfile
 }
 
-test_inductor_aoti_cross_compile_for_windows() {
-
-  TEST_REPORTS_DIR=$(pwd)/test/test-reports
-  mkdir -p "$TEST_REPORTS_DIR"
-
-  # Set WINDOWS_CUDA_HOME environment variable
-  WINDOWS_CUDA_HOME="$(pwd)/win-torch-wheel-extracted"
-  export WINDOWS_CUDA_HOME
-
-  echo "WINDOWS_CUDA_HOME is set to: $WINDOWS_CUDA_HOME"
-  echo "Contents:"
-  ls -lah "$(pwd)/win-torch-wheel-extracted/lib/x64/" || true
-
-  python test/inductor/test_aoti_cross_compile_windows.py -k compile --package-dir "$TEST_REPORTS_DIR" --win-torch-lib-dir "$(pwd)/win-torch-wheel-extracted/torch/lib"
-}
-
 test_inductor_cpp_wrapper_shard() {
   if [[ -z "$NUM_TEST_SHARDS" ]]; then
     echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
@@ -584,8 +547,6 @@ fi
 
 if [[ "${TEST_CONFIG}" == *cpu* ]]; then
   DYNAMO_BENCHMARK_FLAGS+=(--device cpu)
-elif [[ "${TEST_CONFIG}" == *xpu* ]]; then
-  DYNAMO_BENCHMARK_FLAGS+=(--device xpu)
 else
   DYNAMO_BENCHMARK_FLAGS+=(--device cuda)
 fi
@@ -679,8 +640,6 @@ test_perf_for_dashboard() {
     device=cuda_b200
   elif [[ "${TEST_CONFIG}" == *rocm* ]]; then
     device=rocm
-  elif [[ "${TEST_CONFIG}" == *xpu* ]]; then
-    device=xpu
   fi
 
   for mode in "${modes[@]}"; do
@@ -836,11 +795,6 @@ test_inductor_halide() {
   assert_git_not_dirty
 }
 
-test_inductor_pallas() {
-  python test/run_test.py --include inductor/test_pallas.py --verbose
-  assert_git_not_dirty
-}
-
 test_inductor_triton_cpu() {
   python test/run_test.py --include inductor/test_triton_cpu_backend.py inductor/test_torchinductor_strided_blocks.py --verbose
   assert_git_not_dirty
@@ -865,7 +819,7 @@ test_dynamo_benchmark() {
       elif [[ "${suite}" == "timm_models" ]]; then
         export TORCHBENCH_ONLY_MODELS="inception_v3"
       elif [[ "${suite}" == "torchbench" ]]; then
-        export TORCHBENCH_ONLY_MODELS="BERT_pytorch"
+        export TORCHBENCH_ONLY_MODELS="hf_Bert"
       fi
     fi
     test_single_dynamo_benchmark "dashboard" "$suite" "$shard_id" "$@"
@@ -896,13 +850,13 @@ test_inductor_torchbench_smoketest_perf() {
   mkdir -p "$TEST_REPORTS_DIR"
 
   python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --float16 --training \
-    --batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only BERT_pytorch \
+    --batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" --only hf_Bert \
     --output "$TEST_REPORTS_DIR/inductor_training_smoketest.csv"
   # The threshold value needs to be actively maintained to make this check useful
   python benchmarks/dynamo/check_perf_csv.py -f "$TEST_REPORTS_DIR/inductor_training_smoketest.csv" -t 1.4
 
   # Check memory compression ratio for a few models
-  for test in BERT_pytorch yolov3; do
+  for test in hf_Albert timm_vision_transformer; do
     python benchmarks/dynamo/torchbench.py --device cuda --performance --backend inductor --amp --training \
       --disable-cudagraphs --batch-size-file "$(realpath benchmarks/dynamo/torchbench_models_list.txt)" \
       --only $test --output "$TEST_REPORTS_DIR/inductor_training_smoketest_$test.csv"
@@ -913,7 +867,7 @@ test_inductor_torchbench_smoketest_perf() {
   done
 
   # Perform some "warm-start" runs for a few huggingface models.
-  for test in AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
+  for test in AlbertForQuestionAnswering AllenaiLongformerBase DistilBertForMaskedLM DistillGPT2 GoogleFnet YituTechConvBert; do
     python benchmarks/dynamo/huggingface.py --accuracy --training --amp --inductor --device cuda --warm-start-latency \
       --only $test --output "$TEST_REPORTS_DIR/inductor_warm_start_smoketest_$test.csv"
     python benchmarks/dynamo/check_accuracy.py \
@@ -927,7 +881,7 @@ test_inductor_set_cpu_affinity(){
   export LD_PRELOAD="$JEMALLOC_LIB":"$LD_PRELOAD"
   export MALLOC_CONF="oversize_threshold:1,background_thread:true,metadata_thp:auto,dirty_decay_ms:-1,muzzy_decay_ms:-1"
 
-  if [[ "$(uname -m)" != "aarch64" ]]; then
+  if [[ "${TEST_CONFIG}" != *aarch64* ]]; then
     # Use Intel OpenMP for x86
     IOMP_LIB="$(dirname "$(which python)")/../lib/libiomp5.so"
     export LD_PRELOAD="$IOMP_LIB":"$LD_PRELOAD"
@@ -941,7 +895,7 @@ test_inductor_set_cpu_affinity(){
   cores=$((cpus / thread_per_core))
 
   # Set number of cores to 16 on aarch64 for performance runs
-  if [[ "$(uname -m)" == "aarch64" && $cores -gt 16 ]]; then
+  if [[ "${TEST_CONFIG}" == *aarch64* && $cores -gt 16 ]]; then
     cores=16
   fi
   export OMP_NUM_THREADS=$cores
@@ -1192,12 +1146,6 @@ test_distributed() {
   fi
 }
 
-test_quantization() {
-  echo "Testing quantization"
-
-  python test/test_quantization.py
-}
-
 test_rpc() {
   echo "Testing RPC C++ tests"
   # NB: the ending test_rpc must match the current function name for the current
@@ -1444,7 +1392,7 @@ EOF
   pip3 install -r requirements.txt
   # shellcheck source=./common-build.sh
   source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
-  python -m build --wheel --no-isolation -C--build-option=--bdist-dir="base_bdist_tmp" --outdir "base_dist"
+  python setup.py bdist_wheel --bdist-dir="base_bdist_tmp" --dist-dir="base_dist"
   python -mpip install base_dist/*.whl
   echo "::endgroup::"
 
@@ -1592,10 +1540,14 @@ test_executorch() {
   install_torchvision
   install_torchaudio
 
-  INSTALL_SCRIPT="$(pwd)/.ci/docker/common/install_executorch.sh"
-
   pushd /executorch
-  "${INSTALL_SCRIPT}" setup_executorch
+
+  export PYTHON_EXECUTABLE=python
+  export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
+
+  # NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
+  # from the PR
+  bash .ci/scripts/setup-linux.sh --build-tool cmake
 
   echo "Run ExecuTorch unit tests"
   pytest -v -n auto
@@ -1609,14 +1561,17 @@ test_executorch() {
 
   popd
 
+  # Test torchgen generated code for Executorch.
+  echo "Testing ExecuTorch op registration"
+  "$BUILD_BIN_DIR"/test_edge_op_registration
+
   assert_git_not_dirty
 }
 
 test_linux_aarch64() {
   python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
         test_transformers test_multiprocessing test_numpy_interop test_autograd test_binary_ufuncs test_complex test_spectral_ops \
-        test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops profiler/test_memory_profiler \
-        distributed/elastic/timer/api_test distributed/elastic/timer/local_timer_example distributed/elastic/timer/local_timer_test \
+        test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
         --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 
   # Dynamo tests
@@ -1642,12 +1597,11 @@ test_operator_benchmark() {
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
   TEST_DIR=$(pwd)
-  ARCH=$(uname -m)
 
   test_inductor_set_cpu_affinity
 
   cd benchmarks/operator_benchmark/pt_extension
-  python -m pip install . -v --no-build-isolation
+  python -m pip install .
 
   cd "${TEST_DIR}"/benchmarks/operator_benchmark
   $TASKSET python -m benchmark_all_test --device "$1" --tag-filter "$2" \
@@ -1657,44 +1611,9 @@ test_operator_benchmark() {
   pip_install pandas
   python check_perf_csv.py \
       --actual "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.csv" \
-      --expected "${ARCH}_expected_ci_operator_benchmark_eager_float32_cpu.csv"
+      --expected "expected_ci_operator_benchmark_eager_float32_cpu.csv"
 }
 
-test_operator_microbenchmark() {
-  TEST_REPORTS_DIR=$(pwd)/test/test-reports
-  mkdir -p "$TEST_REPORTS_DIR"
-  TEST_DIR=$(pwd)
-
-  cd benchmarks/operator_benchmark/pt_extension
-  python -m pip install .
-
-  cd "${TEST_DIR}"/benchmarks/operator_benchmark
-
-  for OP_BENCHMARK_TESTS in matmul mm addmm bmm conv; do
-    $TASKSET python -m pt.${OP_BENCHMARK_TESTS}_test --tag-filter long \
-      --output-json-for-dashboard "${TEST_REPORTS_DIR}/operator_microbenchmark_${OP_BENCHMARK_TESTS}_compile.json" \
-      --benchmark-name "PyTorch operator microbenchmark" --use-compile
-    $TASKSET python -m pt.${OP_BENCHMARK_TESTS}_test --tag-filter long \
-      --output-json-for-dashboard "${TEST_REPORTS_DIR}/operator_microbenchmark_${OP_BENCHMARK_TESTS}.json" \
-      --benchmark-name "PyTorch operator microbenchmark"
-  done
-}
-
-test_attention_microbenchmark() {
-  TEST_REPORTS_DIR=$(pwd)/test/test-reports
-  mkdir -p "$TEST_REPORTS_DIR"
-  TEST_DIR=$(pwd)
-
-  # Install attention-gym dependency
-  echo "Installing attention-gym..."
-  python -m pip install git+https://github.com/meta-pytorch/attention-gym.git@main
-  pip show triton
-
-  cd "${TEST_DIR}"/benchmarks/transformer
-
-  $TASKSET python score_mod.py --config configs/config_basic.yaml \
-    --output-json-for-dashboard "${TEST_REPORTS_DIR}/attention_microbenchmark.json"
-}
 
 if ! [[ "${BUILD_ENVIRONMENT}" == *libtorch* || "${BUILD_ENVIRONMENT}" == *-bazel-* ]]; then
   (cd test && python -c "import torch; print(torch.__config__.show())")
@@ -1710,7 +1629,7 @@ if [[ "${TEST_CONFIG}" == *numpy_2* ]]; then
     python -m pip install --pre numpy==2.0.2 scipy==1.13.1 numba==0.60.0
   fi
   python test/run_test.py --include dynamo/test_functions.py dynamo/test_unspec.py test_binary_ufuncs.py test_fake_tensor.py test_linalg.py test_numpy_interop.py test_tensor_creation_ops.py test_torch.py torch_np/test_basic.py
-elif [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" == 'default' ]]; then
+elif [[ "${BUILD_ENVIRONMENT}" == *aarch64* && "${TEST_CONFIG}" != *perf_cpu_aarch64* ]]; then
   test_linux_aarch64
 elif [[ "${TEST_CONFIG}" == *backward* ]]; then
   test_forward_backward_compatibility
@@ -1727,8 +1646,6 @@ elif [[ "${TEST_CONFIG}" == *executorch* ]]; then
   test_executorch
 elif [[ "$TEST_CONFIG" == 'jit_legacy' ]]; then
   test_python_legacy_jit
-elif [[ "$TEST_CONFIG" == 'quantization' ]]; then
-  test_quantization
 elif [[ "${BUILD_ENVIRONMENT}" == *libtorch* ]]; then
   # TODO: run some C++ tests
   echo "no-op at the moment"
@@ -1751,22 +1668,14 @@ elif [[ "${TEST_CONFIG}" == *operator_benchmark* ]]; then
     test_operator_benchmark cpu ${TEST_MODE}
 
   fi
-elif [[ "${TEST_CONFIG}" == *operator_microbenchmark* ]]; then
-  test_operator_microbenchmark
-elif [[ "${TEST_CONFIG}" == *attention_microbenchmark* ]]; then
-  test_attention_microbenchmark
 elif [[ "${TEST_CONFIG}" == *inductor_distributed* ]]; then
   test_inductor_distributed
 elif [[ "${TEST_CONFIG}" == *inductor-halide* ]]; then
   test_inductor_halide
-elif [[ "${TEST_CONFIG}" == *inductor-pallas* ]]; then
-  test_inductor_pallas
 elif [[ "${TEST_CONFIG}" == *inductor-triton-cpu* ]]; then
   test_inductor_triton_cpu
 elif [[ "${TEST_CONFIG}" == *inductor-micro-benchmark* ]]; then
   test_inductor_micro_benchmark
-elif [[ "${TEST_CONFIG}" == *aoti_cross_compile_for_windows* ]]; then
-  test_inductor_aoti_cross_compile_for_windows
 elif [[ "${TEST_CONFIG}" == *huggingface* ]]; then
   install_torchvision
   id=$((SHARD_NUMBER-1))
@@ -1798,7 +1707,7 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
   else
     # Do this after checkout_install_torchbench to ensure we clobber any
     # nightlies that torchbench may pull in
-    if [[ "${TEST_CONFIG}" != *cpu* && "${TEST_CONFIG}" != *xpu* ]]; then
+    if [[ "${TEST_CONFIG}" != *cpu* ]]; then
       install_torchrec_and_fbgemm
     fi
     PYTHONPATH=/torchbench test_dynamo_benchmark torchbench "$id"
@@ -1807,11 +1716,16 @@ elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper* ]]; then
   install_torchvision
   PYTHONPATH=/torchbench test_inductor_cpp_wrapper_shard "$SHARD_NUMBER"
   if [[ "$SHARD_NUMBER" -eq "1" ]]; then
-    test_inductor_aoti_cpp
+    test_inductor_aoti
   fi
 elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
   install_torchvision
   test_inductor_shard "${SHARD_NUMBER}"
+  if [[ "${SHARD_NUMBER}" == 1 ]]; then
+    if [[ "${BUILD_ENVIRONMENT}" != linux-jammy-py3.9-gcc11-build ]]; then
+      test_inductor_distributed
+    fi
+  fi
 elif [[ "${TEST_CONFIG}" == *einops* ]]; then
   test_einops
 elif [[ "${TEST_CONFIG}" == *dynamo_wrapped* ]]; then
@@ -1861,14 +1775,10 @@ elif [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
   test_xpu_bin
 elif [[ "${TEST_CONFIG}" == smoke ]]; then
   test_python_smoke
-elif [[ "${TEST_CONFIG}" == smoke_b200 ]]; then
-  test_python_smoke_b200
 elif [[ "${TEST_CONFIG}" == h100_distributed ]]; then
   test_h100_distributed
 elif [[ "${TEST_CONFIG}" == "h100-symm-mem" ]]; then
   test_h100_symm_mem
-elif [[ "${TEST_CONFIG}" == "b200-symm-mem" ]]; then
-  test_h100_symm_mem
 elif [[ "${TEST_CONFIG}" == h100_cutlass_backend ]]; then
   test_h100_cutlass_backend
 else

.ci/pytorch/test_fa3_abi_stable.sh

@@ -1,32 +0,0 @@
-#!/bin/bash
-
-set -ex -o pipefail
-
-# Suppress ANSI color escape sequences
-export TERM=vt100
-
-# shellcheck source=./common.sh
-source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
-# shellcheck source=./common-build.sh
-source "$(dirname "${BASH_SOURCE[0]}")/common-build.sh"
-
-echo "Environment variables"
-env
-
-echo "Testing FA3 stable wheel still works with currently built torch"
-
-echo "Installing ABI Stable FA3 wheel"
-# The wheel was built on https://github.com/Dao-AILab/flash-attention/commit/b3846b059bf6b143d1cd56879933be30a9f78c81
-# on torch nightly torch==2.9.0.dev20250830+cu129
-$MAYBE_SUDO pip -q install https://s3.amazonaws.com/ossci-linux/wheels/flash_attn_3-3.0.0b1-cp39-abi3-linux_x86_64.whl
-
-pushd flash-attention/hopper
-export PYTHONPATH=$PWD
-pytest -v -s \
-  "test_flash_attn.py::test_flash_attn_output[1-1-192-False-False-False-0.0-False-False-mha-dtype0]" \
-  "test_flash_attn.py::test_flash_attn_varlen_output[511-1-64-True-False-False-0.0-False-False-gqa-dtype2]" \
-  "test_flash_attn.py::test_flash_attn_kvcache[1-128-128-False-False-True-None-0.0-False-False-True-False-True-False-gqa-dtype0]" \
-  "test_flash_attn.py::test_flash_attn_race_condition[97-97-192-True-dtype0]" \
-  "test_flash_attn.py::test_flash_attn_combine[2-3-64-dtype1]" \
-  "test_flash_attn.py::test_flash3_bw_compatibility"
-popd

.ci/pytorch/win-test-helpers/arm64/build_pytorch.ps1

@@ -70,7 +70,7 @@ sccache --zero-stats
 sccache --show-stats
 
 # Build the wheel
-python -m build --wheel --no-isolation
+python setup.py bdist_wheel
 if ($LASTEXITCODE -ne 0) { exit 1 }
 
 # Install the wheel locally

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

@@ -38,12 +38,10 @@ if errorlevel 1 goto fail
 if not errorlevel 0 goto fail
 
 :: Update CMake
-:: TODO: Investigate why this helps MKL detection, even when CMake from choco is not used
 call choco upgrade -y cmake --no-progress --installargs 'ADD_CMAKE_TO_PATH=System' --apply-install-arguments-to-dependencies --version=3.27.9
 if errorlevel 1 goto fail
 if not errorlevel 0 goto fail
 
-:: TODO: Move to .ci/docker/requirements-ci.txt
 call pip install mkl==2024.2.0 mkl-static==2024.2.0 mkl-include==2024.2.0
 if errorlevel 1 goto fail
 if not errorlevel 0 goto fail
@@ -132,14 +130,14 @@ if "%USE_CUDA%"=="1" (
 :: Print all existing environment variable for debugging
 set
 
-python -m build --wheel --no-isolation
+python setup.py bdist_wheel
 if errorlevel 1 goto fail
 if not errorlevel 0 goto fail
 sccache --show-stats
 python -c "import os, glob; os.system('python -mpip install --no-index --no-deps ' + glob.glob('dist/*.whl')[0])"
 (
   if "%BUILD_ENVIRONMENT%"=="" (
-    echo NOTE: To run `import torch`, please make sure to activate the conda environment by running `call %CONDA_ROOT_DIR%\Scripts\activate.bat %CONDA_ROOT_DIR%\envs\py_tmp` in Command Prompt before running Git Bash.
+    echo NOTE: To run `import torch`, please make sure to activate the conda environment by running `call %CONDA_PARENT_DIR%\Miniconda3\Scripts\activate.bat %CONDA_PARENT_DIR%\Miniconda3` in Command Prompt before running Git Bash.
   ) else (
     copy /Y "dist\*.whl" "%PYTORCH_FINAL_PACKAGE_DIR%"
 

.ci/pytorch/win-test-helpers/installation-helpers/activate_miniconda3.bat

@@ -3,12 +3,12 @@ if "%BUILD_ENVIRONMENT%"=="" (
 ) else (
   set CONDA_PARENT_DIR=C:\Jenkins
 )
-set CONDA_ROOT_DIR=%CONDA_PARENT_DIR%\Miniconda3
+
 
 :: Be conservative here when rolling out the new AMI with conda. This will try
 :: to install conda as before if it couldn't find the conda installation. This
 :: can be removed eventually after we gain enough confidence in the AMI
-if not exist %CONDA_ROOT_DIR% (
+if not exist %CONDA_PARENT_DIR%\Miniconda3 (
   set INSTALL_FRESH_CONDA=1
 )
 
@@ -17,14 +17,10 @@ if "%INSTALL_FRESH_CONDA%"=="1" (
   if errorlevel 1 exit /b
   if not errorlevel 0 exit /b
 
-  %TMP_DIR_WIN%\Miniconda3-latest-Windows-x86_64.exe /InstallationType=JustMe /RegisterPython=0 /S /AddToPath=0 /D=%CONDA_ROOT_DIR%
+  %TMP_DIR_WIN%\Miniconda3-latest-Windows-x86_64.exe /InstallationType=JustMe /RegisterPython=0 /S /AddToPath=0 /D=%CONDA_PARENT_DIR%\Miniconda3
   if errorlevel 1 exit /b
   if not errorlevel 0 exit /b
 )
 
 :: Activate conda so that we can use its commands, i.e. conda, python, pip
-call %CONDA_ROOT_DIR%\Scripts\activate.bat %CONDA_ROOT_DIR%
-:: Activate conda so that we can use its commands, i.e. conda, python, pip
-call conda activate py_tmp
-
-call pip install -r .ci/docker/requirements-ci.txt
+call %CONDA_PARENT_DIR%\Miniconda3\Scripts\activate.bat %CONDA_PARENT_DIR%\Miniconda3

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

@@ -14,7 +14,7 @@ if not errorlevel 0 exit /b
 :: build\torch. Rather than changing all these references, making a copy of torch folder
 :: from conda to the current workspace is easier. The workspace will be cleaned up after
 :: the job anyway
-xcopy /s %CONDA_ROOT_DIR%\envs\py_tmp\Lib\site-packages\torch %TMP_DIR_WIN%\build\torch\
+xcopy /s %CONDA_PARENT_DIR%\Miniconda3\Lib\site-packages\torch %TMP_DIR_WIN%\build\torch\
 
 pushd .
 if "%VC_VERSION%" == "" (

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

@@ -15,35 +15,37 @@ if errorlevel 1 exit /b 1
 if not errorlevel 0 exit /b 1
 
 cd %TMP_DIR_WIN%\build\torch\test
-
-:: Enable delayed variable expansion to make the list
-setlocal enabledelayedexpansion
-set EXE_LIST=
 for /r "." %%a in (*.exe) do (
-  if "%%~na" == "c10_intrusive_ptr_benchmark" (
-    @REM NB: This is not a gtest executable file, thus couldn't be handled by
-    @REM pytest-cpp and is excluded from test discovery by run_test
-    call "%%~fa"
+    call :libtorch_check "%%~na" "%%~fa"
     if errorlevel 1 goto fail
-    if not errorlevel 0 goto fail
-  ) else (
-    if "%%~na" == "verify_api_visibility" (
-      @REM Skip verify_api_visibility as it is a compile-level test
-    ) else (
-      set EXE_LIST=!EXE_LIST! cpp/%%~na
-    )
-  )
 )
 
+goto :eof
+
+:libtorch_check
+
 cd %CWD%
 set CPP_TESTS_DIR=%TMP_DIR_WIN%\build\torch\test
 
-:: Run python test\run_test.py on the list
-set NO_TD=True && python test\run_test.py --cpp --verbose -i !EXE_LIST!
-if errorlevel 1 goto fail
-if not errorlevel 0 goto fail
+:: Skip verify_api_visibility as it a compile level test
+if "%~1" == "verify_api_visibility" goto :eof
 
-goto :eof
+echo Running "%~2"
+if "%~1" == "c10_intrusive_ptr_benchmark" (
+  :: NB: This is not a gtest executable file, thus couldn't be handled by pytest-cpp
+  call "%~2"
+  goto :eof
+)
+
+python test\run_test.py --cpp --verbose -i "cpp/%~1"
+if errorlevel 1 (
+  echo %1 failed with exit code %errorlevel%
+  goto fail
+)
+if not errorlevel 0 (
+  echo %1 failed with exit code %errorlevel%
+  goto fail
+)
 
 :eof
 exit /b 0

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

@@ -25,7 +25,7 @@ echo Copying over test times file
 robocopy /E "%PYTORCH_FINAL_PACKAGE_DIR_WIN%\.additional_ci_files" "%PROJECT_DIR_WIN%\.additional_ci_files"
 
 echo Run nn tests
-python run_test.py --exclude-jit-executor --exclude-distributed-tests --exclude-quantization-tests --shard "%SHARD_NUMBER%" "%NUM_TEST_SHARDS%" --verbose
+python run_test.py --exclude-jit-executor --exclude-distributed-tests --shard "%SHARD_NUMBER%" "%NUM_TEST_SHARDS%" --verbose
 if ERRORLEVEL 1 goto fail
 
 popd

.ci/pytorch/win-test.sh

@@ -37,8 +37,23 @@ if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
   export PYTORCH_TESTING_DEVICE_ONLY_FOR="cuda"
 fi
 
-# TODO: Move this to .ci/docker/requirements-ci.txt
-python -m pip install "psutil==5.9.1" nvidia-ml-py "pytest-shard==0.1.2"
+# TODO: Move both of them to Windows AMI
+python -m pip install pytest-rerunfailures==10.3 pytest-cpp==2.3.0 tensorboard==2.13.0 protobuf==5.29.4 pytest-subtests==0.13.1
+
+# Install Z3 optional dependency for Windows builds.
+python -m pip install z3-solver==4.15.1.0
+
+# Install tlparse for test\dynamo\test_structured_trace.py UTs.
+python -m pip install tlparse==0.4.0
+
+# Install parameterized
+python -m pip install parameterized==0.8.1
+
+# Install pulp for testing ilps under torch\distributed\_tools
+python -m pip install pulp==2.9.0
+
+# Install expecttest to merge https://github.com/pytorch/pytorch/pull/155308
+python -m pip install expecttest==0.3.0
 
 run_tests() {
     # Run nvidia-smi if available

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

@@ -48,7 +48,7 @@ sccache --zero-stats
 sccache --show-stats
 
 :: Call PyTorch build script
-python -m build --wheel --no-isolation --outdir "%PYTORCH_FINAL_PACKAGE_DIR%"
+python setup.py bdist_wheel -d "%PYTORCH_FINAL_PACKAGE_DIR%"
 
 :: show sccache stats
 sccache --show-stats

.ci/pytorch/windows/cuda128.bat

@@ -37,10 +37,10 @@ IF "%CUDA_PATH_V128%"=="" (
 )
 
 IF "%BUILD_VISION%" == "" (
-    set TORCH_CUDA_ARCH_LIST=7.0;7.5;8.0;8.6;9.0;10.0;12.0
+    set TORCH_CUDA_ARCH_LIST=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_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 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%"

.ci/pytorch/windows/internal/copy.bat

@@ -1,20 +1,12 @@
-
-if %CUDA_VERSION% geq 130 (
-    set "dll_path=bin\x64"
-) else (
-    set "dll_path=bin"
-)
-
-copy "%CUDA_PATH%\%dll_path%\cusparse*64_*.dll*" pytorch\torch\lib
-copy "%CUDA_PATH%\%dll_path%\cublas*64_*.dll*" pytorch\torch\lib
-copy "%CUDA_PATH%\%dll_path%\cudart*64_*.dll*" pytorch\torch\lib
-copy "%CUDA_PATH%\%dll_path%\curand*64_*.dll*" pytorch\torch\lib
-copy "%CUDA_PATH%\%dll_path%\cufft*64_*.dll*" pytorch\torch\lib
-copy "%CUDA_PATH%\%dll_path%\cusolver*64_*.dll*" pytorch\torch\lib
-copy "%CUDA_PATH%\%dll_path%\nvrtc*64_*.dll*" pytorch\torch\lib
-copy "%CUDA_PATH%\%dll_path%\nvJitLink_*.dll*"  pytorch\torch\lib
+copy "%CUDA_PATH%\bin\cusparse*64_*.dll*" pytorch\torch\lib
+copy "%CUDA_PATH%\bin\cublas*64_*.dll*" pytorch\torch\lib
+copy "%CUDA_PATH%\bin\cudart*64_*.dll*" pytorch\torch\lib
+copy "%CUDA_PATH%\bin\curand*64_*.dll*" pytorch\torch\lib
+copy "%CUDA_PATH%\bin\cufft*64_*.dll*" pytorch\torch\lib
+copy "%CUDA_PATH%\bin\cusolver*64_*.dll*" pytorch\torch\lib
 
 copy "%CUDA_PATH%\bin\cudnn*64_*.dll*" pytorch\torch\lib
+copy "%CUDA_PATH%\bin\nvrtc*64_*.dll*" pytorch\torch\lib
 copy "%CUDA_PATH%\extras\CUPTI\lib64\cupti64_*.dll*" pytorch\torch\lib
 copy "%CUDA_PATH%\extras\CUPTI\lib64\nvperf_host*.dll*" pytorch\torch\lib
 
@@ -28,3 +20,8 @@ copy "%libuv_ROOT%\bin\uv.dll" pytorch\torch\lib
 if exist "C:\Windows\System32\zlibwapi.dll" (
     copy "C:\Windows\System32\zlibwapi.dll"  pytorch\torch\lib
 )
+
+::copy nvJitLink dll is requires for cuda 12+
+if exist "%CUDA_PATH%\bin\nvJitLink_*.dll*" (
+    copy "%CUDA_PATH%\bin\nvJitLink_*.dll*"  pytorch\torch\lib
+)

.ci/pytorch/windows/internal/driver_update.bat

@@ -1,9 +1,9 @@
-set WIN_DRIVER_VN=580.88
-set "DRIVER_DOWNLOAD_LINK=https://ossci-windows.s3.amazonaws.com/%WIN_DRIVER_VN%-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe" & REM @lint-ignore
-curl --retry 3 -kL %DRIVER_DOWNLOAD_LINK% --output %WIN_DRIVER_VN%-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe
+set WIN_DRIVER_VN=528.89
+set "DRIVER_DOWNLOAD_LINK=https://ossci-windows.s3.amazonaws.com/%WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe" & REM @lint-ignore
+curl --retry 3 -kL %DRIVER_DOWNLOAD_LINK% --output %WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe
 if errorlevel 1 exit /b 1
 
-start /wait %WIN_DRIVER_VN%-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe -s -noreboot
+start /wait %WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe -s -noreboot
 if errorlevel 1 exit /b 1
 
-del %WIN_DRIVER_VN%-data-center-tesla-desktop-win10-win11-64bit-dch-international.exe || ver > NUL
+del %WIN_DRIVER_VN%-data-center-tesla-desktop-winserver-2016-2019-2022-dch-international.exe || ver > NUL

.ci/pytorch/windows/internal/install_python.bat

@@ -7,9 +7,12 @@ if "%DESIRED_PYTHON%" == "3.13t" (
     set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.13.0/python-3.13.0-amd64.exe"
     set ADDITIONAL_OPTIONS="Include_freethreaded=1"
     set PYTHON_EXEC="python3.13t"
+) else if "%DESIRED_PYTHON%"=="3.14" (
+    echo Python version is set to 3.14 or 3.14t
+    set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.14.0/python-3.14.0rc1-amd64.exe"
 ) else if "%DESIRED_PYTHON%"=="3.14t" (
     echo Python version is set to 3.14 or 3.14t
-    set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.14.0/python-3.14.0-amd64.exe"
+    set "PYTHON_INSTALLER_URL=https://www.python.org/ftp/python/3.14.0/python-3.14.0rc1-amd64.exe"
     set ADDITIONAL_OPTIONS="Include_freethreaded=1"
     set PYTHON_EXEC="python3.14t"
 ) else (
@@ -25,5 +28,5 @@ start /wait "" python-amd64.exe /quiet InstallAllUsers=1 PrependPath=0 Include_t
 if errorlevel 1 exit /b 1
 
 set "PATH=%CD%\Python\Scripts;%CD%\Python;%PATH%"
-%PYTHON_EXEC% -m pip install --upgrade pip setuptools packaging wheel build
+%PYTHON_EXEC% -m pip install --upgrade pip setuptools packaging wheel
 if errorlevel 1 exit /b 1

.ci/pytorch/windows/internal/setup.bat

@@ -86,7 +86,7 @@ copy /Y "%LIBTORCH_PREFIX%-%PYTORCH_BUILD_VERSION%.zip" "%PYTORCH_FINAL_PACKAGE_
 goto build_end
 
 :pytorch
-%PYTHON_EXEC% -m build --wheel --no-isolation --outdir "%PYTORCH_FINAL_PACKAGE_DIR%"
+%PYTHON_EXEC% setup.py bdist_wheel -d "%PYTORCH_FINAL_PACKAGE_DIR%"
 
 :build_end
 IF ERRORLEVEL 1 exit /b 1

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

@@ -63,7 +63,7 @@ if errorlevel 1 exit /b 1
 call %CONDA_HOME%\condabin\activate.bat testenv
 if errorlevel 1 exit /b 1
 
-call conda install  -y -q -c conda-forge libuv=1.51
+call conda install  -y -q -c conda-forge libuv=1.39
 call conda install -y -q intel-openmp
 
 echo "install and test libtorch"

.ci/pytorch/windows/setup_build.bat

@@ -18,7 +18,7 @@ if "%DESIRED_PYTHON%" == "3.9" %PYTHON_EXEC% -m pip install numpy==2.0.2 cmake
 
 %PYTHON_EXEC% -m pip install pyyaml
 %PYTHON_EXEC% -m pip install mkl-include mkl-static
-%PYTHON_EXEC% -m pip install boto3 requests ninja typing_extensions setuptools==72.1.0
+%PYTHON_EXEC% -m pip install boto3 ninja typing_extensions setuptools==72.1.0
 
 where cmake.exe
 

.ci/wheel/build_wheel.sh

@@ -85,7 +85,7 @@ mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
 # Create an isolated directory to store this builds pytorch checkout and conda
 # installation
 if [[ -z "$MAC_PACKAGE_WORK_DIR" ]]; then
-    MAC_PACKAGE_WORK_DIR="$(pwd)/tmp_wheel_${DESIRED_PYTHON}_$(date +%H%M%S)"
+    MAC_PACKAGE_WORK_DIR="$(pwd)/tmp_wheel_conda_${DESIRED_PYTHON}_$(date +%H%M%S)"
 fi
 mkdir -p "$MAC_PACKAGE_WORK_DIR" || true
 if [[ -n ${GITHUB_ACTIONS} ]]; then
@@ -96,11 +96,11 @@ fi
 whl_tmp_dir="${MAC_PACKAGE_WORK_DIR}/dist"
 mkdir -p "$whl_tmp_dir"
 
-mac_version='macosx-11_0-arm64'
+mac_version='macosx_11_0_arm64'
 libtorch_arch='arm64'
 
 # Create a consistent wheel package name to rename the wheel to
-wheel_filename_new="${TORCH_PACKAGE_NAME}-${build_version}${build_number_prefix}-cp${python_nodot}-none-${mac_version//[-,]/_}.whl"
+wheel_filename_new="${TORCH_PACKAGE_NAME}-${build_version}${build_number_prefix}-cp${python_nodot}-none-${mac_version}.whl"
 
 ###########################################################
 
@@ -124,61 +124,97 @@ popd
 
 export TH_BINARY_BUILD=1
 export INSTALL_TEST=0 # dont install test binaries into site-packages
-export MACOSX_DEPLOYMENT_TARGET=11.0
+export MACOSX_DEPLOYMENT_TARGET=10.15
+export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
 
+SETUPTOOLS_PINNED_VERSION="==70.1.0"
+PYYAML_PINNED_VERSION="==5.3"
 EXTRA_CONDA_INSTALL_FLAGS=""
 CONDA_ENV_CREATE_FLAGS=""
 RENAME_WHEEL=true
 case $desired_python in
     3.14t)
         echo "Using 3.14 deps"
-        mac_version='macosx-11.0-arm64'
+        SETUPTOOLS_PINNED_VERSION=">=70.1.0"
+        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/label/python_rc -c conda-forge"
+        desired_python="3.14.0rc1"
         RENAME_WHEEL=false
         ;;
     3.14)
         echo "Using 3.14t deps"
-        mac_version='macosx-11.0-arm64'
+        SETUPTOOLS_PINNED_VERSION=">=70.1.0"
+        PYYAML_PINNED_VERSION=">=6.0.1"
         NUMPY_PINNED_VERSION="==2.1.0"
+        EXTRA_CONDA_INSTALL_FLAGS="-c conda-forge/label/python_rc -c conda-forge"
+        desired_python="3.14.0rc1"
         RENAME_WHEEL=false
         ;;
     3.13t)
-        echo "Using 3.13t deps"
-        mac_version='macosx-11.0-arm64'
+        echo "Using 3.13 deps"
+        SETUPTOOLS_PINNED_VERSION=">=70.1.0"
+        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=">=70.1.0"
+        PYYAML_PINNED_VERSION=">=6.0.1"
         NUMPY_PINNED_VERSION="==2.1.0"
         ;;
     3.12)
         echo "Using 3.12 deps"
+        SETUPTOOLS_PINNED_VERSION=">=70.1.0"
+        PYYAML_PINNED_VERSION=">=6.0.1"
         NUMPY_PINNED_VERSION="==2.0.2"
         ;;
     3.11)
         echo "Using 3.11 deps"
+        SETUPTOOLS_PINNED_VERSION=">=70.1.0"
+        PYYAML_PINNED_VERSION=">=5.3"
         NUMPY_PINNED_VERSION="==2.0.2"
         ;;
     3.10)
         echo "Using 3.10 deps"
+        SETUPTOOLS_PINNED_VERSION=">=70.1.0"
+        PYYAML_PINNED_VERSION=">=5.3"
+        NUMPY_PINNED_VERSION="==2.0.2"
+        ;;
+    3.9)
+        echo "Using 3.9 deps"
+        SETUPTOOLS_PINNED_VERSION=">=70.1.0"
+        PYYAML_PINNED_VERSION=">=5.3"
         NUMPY_PINNED_VERSION="==2.0.2"
         ;;
     *)
-        echo "Unsupported version $desired_python"
-        exit 1
+        echo "Using default deps"
+        NUMPY_PINNED_VERSION="==1.11.3"
         ;;
 esac
 
+# Install into a fresh env
+tmp_env_name="wheel_py$python_nodot"
+conda create ${EXTRA_CONDA_INSTALL_FLAGS} -yn "$tmp_env_name" python="$desired_python" ${CONDA_ENV_CREATE_FLAGS}
+source activate "$tmp_env_name"
+
 PINNED_PACKAGES=(
+    "setuptools${SETUPTOOLS_PINNED_VERSION}"
+    "pyyaml${PYYAML_PINNED_VERSION}"
     "numpy${NUMPY_PINNED_VERSION}"
 )
-python -mvenv ~/${desired_python}-build
-source ~/${desired_python}-build/bin/activate
-retry pip install "${PINNED_PACKAGES[@]}" -r "${pytorch_rootdir}/requirements.txt"
+retry pip install "${PINNED_PACKAGES[@]}" -r "${pytorch_rootdir}/requirements-build.txt"
+pip install requests ninja typing-extensions
+retry pip install -r "${pytorch_rootdir}/requirements.txt" || true
 retry brew install libomp
 
-# For USE_DISTRIBUTED=1 on macOS, need libuv, which is build as part of tensorpipe submodule
+# For USE_DISTRIBUTED=1 on macOS, this enables gloo, which needs libuv, which
+# is build as part of tensorpipe submodule
 export USE_DISTRIBUTED=1
 
 export USE_MKLDNN=OFF
@@ -186,11 +222,11 @@ export USE_QNNPACK=OFF
 export BUILD_TEST=OFF
 
 pushd "$pytorch_rootdir"
-echo "Calling -m build --wheel --no-isolation at $(date)"
+echo "Calling setup.py bdist_wheel at $(date)"
 
-_PYTHON_HOST_PLATFORM=${mac_version} ARCHFLAGS="-arch arm64" python -m build --wheel --no-isolation --outdir "$whl_tmp_dir" -C--plat-name="${mac_version//[-.]/_}"
+python setup.py bdist_wheel -d "$whl_tmp_dir"
 
-echo "Finished -m build --wheel --no-isolation at $(date)"
+echo "Finished setup.py bdist_wheel at $(date)"
 
 if [[ $package_type != 'libtorch' ]]; then
     echo "delocating wheel dependencies"

.circleci/scripts/binary_populate_env.sh

@@ -71,7 +71,14 @@ export PYTORCH_BUILD_NUMBER=1
 
 # Set triton version as part of PYTORCH_EXTRA_INSTALL_REQUIREMENTS
 TRITON_VERSION=$(cat $PYTORCH_ROOT/.ci/docker/triton_version.txt)
-TRITON_CONSTRAINT="platform_system == 'Linux'"
+
+# Here PYTORCH_EXTRA_INSTALL_REQUIREMENTS is already set for the all the wheel builds hence append TRITON_CONSTRAINT
+TRITON_CONSTRAINT="platform_system == 'Linux' and platform_machine == 'x86_64'"
+
+# CUDA 12.9/13.0 builds have triton for Linux and Linux aarch64 binaries.
+if [[ "$DESIRED_CUDA" == "cu129" ]] || [[ "$DESIRED_CUDA" == "cu130" ]]; 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}; ${TRITON_CONSTRAINT}"
@@ -163,13 +170,8 @@ if [[ "$(uname)" != Darwin ]]; then
   MEMORY_LIMIT_MAX_JOBS=12
   NUM_CPUS=$(( $(nproc) - 2 ))
 
-  if [[ "$(uname)" == Linux ]]; then
-    # Defaults here for **binary** linux builds so they can be changed in one place
-    export MAX_JOBS=${MAX_JOBS:-$(( ${NUM_CPUS} > ${MEMORY_LIMIT_MAX_JOBS} ? ${MEMORY_LIMIT_MAX_JOBS} : ${NUM_CPUS} ))}
-  else
-    # For other builds
-    export MAX_JOBS=${NUM_CPUS}
-  fi
+  # Defaults here for **binary** linux builds so they can be changed in one place
+  export MAX_JOBS=${MAX_JOBS:-$(( ${NUM_CPUS} > ${MEMORY_LIMIT_MAX_JOBS} ? ${MEMORY_LIMIT_MAX_JOBS} : ${NUM_CPUS} ))}
 
   cat >>"$envfile" <<EOL
   export MAX_JOBS="${MAX_JOBS}"

.circleci/scripts/functorch_doc_push_script.sh

@@ -0,0 +1,47 @@
+#!/bin/bash
+# =================== The following code **should** be executed inside Docker container ===================
+
+# Install dependencies
+sudo apt-get -y update
+sudo apt-get -y install expect-dev
+
+# This is where the local pytorch install in the docker image is located
+pt_checkout="/var/lib/jenkins/workspace"
+source "$pt_checkout/.ci/pytorch/common_utils.sh"
+echo "functorch_doc_push_script.sh: Invoked with $*"
+
+set -ex
+
+version=${DOCS_VERSION:-nightly}
+echo "version: $version"
+
+# Build functorch docs
+pushd $pt_checkout/functorch/docs
+pip -q install -r requirements.txt
+make html
+popd
+
+git clone https://github.com/pytorch/functorch -b gh-pages --depth 1 functorch_ghpages
+pushd functorch_ghpages
+
+if [ $version == "main" ]; then
+  version=nightly
+fi
+
+git rm -rf "$version" || true
+mv "$pt_checkout/functorch/docs/build/html" "$version"
+
+git add "$version" || true
+git status
+git config user.email "soumith+bot@pytorch.org"
+git config user.name "pytorchbot"
+# If there aren't changes, don't make a commit; push is no-op
+git commit -m "Generate Python docs from pytorch/pytorch@${GITHUB_SHA}" || true
+git status
+
+if [[ "${WITH_PUSH:-}" == true ]]; then
+  git push -u origin gh-pages
+fi
+
+popd
+# =================== The above code **should** be executed inside Docker container ===================

.clang-tidy

@@ -59,21 +59,16 @@ performance-*,
 -performance-enum-size,
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-readability-duplicate-include,
-readability-named-parameter,
+readability-duplicate-include
 readability-misplaced-array-index,
-readability-redundant*,
+readability-redundant*
 readability-simplify-subscript-expr,
-readability-static-definition-in-anonymous-namespace
 readability-string-compare,
 -readability-redundant-access-specifiers,
 -readability-redundant-control-flow,
--readability-redundant-inline-specifier,
 '
 HeaderFilterRegex: '^(aten/|c10/|torch/).*$'
 WarningsAsErrors: '*'
-LineFilter:
-  - name: '/usr/include/.*'
 CheckOptions:
   cppcoreguidelines-special-member-functions.AllowSoleDefaultDtor: true
   cppcoreguidelines-special-member-functions.AllowImplicitlyDeletedCopyOrMove: true

.claude/skills/add-uint-support/SKILL.md

@@ -1,319 +0,0 @@
----
-name: add-uint-support
-description: Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
----
-
-# Add Unsigned Integer (uint) Support to Operators
-
-This skill helps add support for unsigned integer types (uint16, uint32, uint64) to PyTorch operators by updating their AT_DISPATCH macros.
-
-## When to use this skill
-
-Use this skill when:
-- Adding uint16, uint32, or uint64 support to an operator
-- User mentions "unsigned types", "uint support", "barebones unsigned types"
-- Enabling support for kUInt16, kUInt32, kUInt64 in kernels
-- Working with operator implementations that need expanded type coverage
-
-## Quick reference
-
-**Add unsigned types to existing dispatch:**
-```cpp
-// Before
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_ALL_TYPES));
-
-// After (method 1: add unsigned types explicitly)
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES));
-
-// After (method 2: use V2 integral types if AT_INTEGRAL_TYPES present)
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES));
-```
-
-## Type group reference
-
-**Unsigned type groups:**
-- `AT_BAREBONES_UNSIGNED_TYPES`: kUInt16, kUInt32, kUInt64
-- `AT_INTEGRAL_TYPES_V2`: AT_INTEGRAL_TYPES + AT_BAREBONES_UNSIGNED_TYPES
-
-**Relationship:**
-```cpp
-AT_INTEGRAL_TYPES          // kByte, kChar, kInt, kLong, kShort
-AT_BAREBONES_UNSIGNED_TYPES  // kUInt16, kUInt32, kUInt64
-AT_INTEGRAL_TYPES_V2       // INTEGRAL_TYPES + BAREBONES_UNSIGNED_TYPES
-```
-
-## Instructions
-
-### Step 1: Determine if conversion to V2 is needed
-
-Check if the file uses AT_DISPATCH_V2:
-
-**If using old AT_DISPATCH:**
-- First convert to AT_DISPATCH_V2 using the at-dispatch-v2 skill
-- Then proceed with adding uint support
-
-**If already using AT_DISPATCH_V2:**
-- Proceed directly to Step 2
-
-### Step 2: Analyze the current dispatch macro
-
-Identify what type groups are currently in use:
-
-```cpp
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  // body
-}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);
-    ^^^^^^^^^^^^^^^^^^^^^^^^^
-    Current type coverage
-```
-
-Common patterns:
-- `AT_EXPAND(AT_ALL_TYPES)` → includes AT_INTEGRAL_TYPES + AT_FLOATING_TYPES
-- `AT_EXPAND(AT_INTEGRAL_TYPES)` → signed integers only
-- `AT_EXPAND(AT_FLOATING_TYPES)` → floating point types
-
-### Step 3: Choose the uint addition method
-
-Two approaches:
-
-**Method 1: Add AT_BAREBONES_UNSIGNED_TYPES explicitly**
-- Use when: You want to be explicit about adding uint support
-- Add `AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES)` to the type list
-
-**Method 2: Substitute AT_INTEGRAL_TYPES with AT_INTEGRAL_TYPES_V2**
-- Use when: The dispatch already uses `AT_EXPAND(AT_INTEGRAL_TYPES)`
-- More concise: replaces one type group with its superset
-- Only applicable if AT_INTEGRAL_TYPES is present
-
-### Step 4: Apply the transformation
-
-**Method 1 example:**
-```cpp
-// Before
-AT_DISPATCH_V2(
-    dtype,
-    "min_values_cuda",
-    AT_WRAP([&]() {
-      kernel_impl<scalar_t>(iter);
-    }),
-    AT_EXPAND(AT_ALL_TYPES),
-    kBFloat16, kHalf, kBool
-);
-
-// After (add unsigned types)
-AT_DISPATCH_V2(
-    dtype,
-    "min_values_cuda",
-    AT_WRAP([&]() {
-      kernel_impl<scalar_t>(iter);
-    }),
-    AT_EXPAND(AT_ALL_TYPES),
-    AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES),
-    kBFloat16, kHalf, kBool
-);
-```
-
-**Method 2 example:**
-```cpp
-// Before
-AT_DISPATCH_V2(
-    dtype,
-    "integral_op",
-    AT_WRAP([&]() {
-      kernel<scalar_t>();
-    }),
-    AT_EXPAND(AT_INTEGRAL_TYPES)
-);
-
-// After (substitute with V2)
-AT_DISPATCH_V2(
-    dtype,
-    "integral_op",
-    AT_WRAP([&]() {
-      kernel<scalar_t>();
-    }),
-    AT_EXPAND(AT_INTEGRAL_TYPES_V2)
-);
-```
-
-### Step 5: Handle AT_ALL_TYPES vs individual type groups
-
-If the dispatch uses `AT_EXPAND(AT_ALL_TYPES)`:
-- `AT_ALL_TYPES` = `AT_INTEGRAL_TYPES` + `AT_FLOATING_TYPES`
-- To add uint: add `AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES)` to the list
-
-If the dispatch separately lists INTEGRAL and FLOATING:
-```cpp
-// Before
-AT_EXPAND(AT_INTEGRAL_TYPES), AT_EXPAND(AT_FLOATING_TYPES)
-
-// After (Method 2 preferred)
-AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES)
-```
-
-### Step 6: Verify all dispatch sites
-
-Check the file for ALL dispatch macros that need uint support:
-- Some operators have multiple dispatch sites (CPU, CUDA, different functions)
-- Apply the transformation consistently across all sites
-- Ensure each gets the same type coverage updates
-
-### Step 7: Validate the changes
-
-Check that:
-- [ ] AT_DISPATCH_V2 format is used (not old AT_DISPATCH)
-- [ ] Unsigned types are added via one of the two methods
-- [ ] All relevant dispatch sites in the file are updated
-- [ ] Type groups use `AT_EXPAND()`
-- [ ] Arguments are properly formatted and comma-separated
-
-## Common patterns
-
-### Pattern 1: AT_ALL_TYPES + extras
-
-```cpp
-// Before
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);
-
-// After
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kHalf, kBFloat16);
-```
-
-### Pattern 2: Separate INTEGRAL + FLOATING
-
-```cpp
-// Before
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_INTEGRAL_TYPES), AT_EXPAND(AT_FLOATING_TYPES));
-
-// After
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_INTEGRAL_TYPES_V2), AT_EXPAND(AT_FLOATING_TYPES));
-```
-
-### Pattern 3: Old dispatch needs conversion first
-
-```cpp
-// Before (needs v2 conversion first)
-AT_DISPATCH_ALL_TYPES_AND2(kHalf, kBFloat16, dtype, "op", [&]() {
-  kernel<scalar_t>();
-});
-
-// After v2 conversion
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_ALL_TYPES), kHalf, kBFloat16);
-
-// After adding uint support
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kHalf, kBFloat16);
-```
-
-## Multiple dispatch sites example
-
-For a file with multiple functions:
-
-```cpp
-void min_values_kernel_cuda(TensorIterator& iter) {
-  AT_DISPATCH_V2(iter.dtype(), "min_values_cuda", AT_WRAP([&]() {
-    impl<scalar_t>(iter);
-  }), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kBFloat16, kHalf);
-  //                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  //                           Added uint support
-}
-
-void min_launch_kernel(TensorIterator &iter) {
-  AT_DISPATCH_V2(iter.input_dtype(), "min_cuda", AT_WRAP([&]() {
-    gpu_reduce_kernel<scalar_t>(iter);
-  }), AT_EXPAND(AT_ALL_TYPES), AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES), kBFloat16, kHalf);
-  //                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  //                           Added uint support here too
-}
-```
-
-## Decision tree
-
-Use this decision tree to determine the approach:
-
-```
-Is the file using AT_DISPATCH_V2?
-├─ No → Use at-dispatch-v2 skill first, then continue
-└─ Yes
-   └─ Does it use AT_EXPAND(AT_INTEGRAL_TYPES)?
-      ├─ Yes → Replace with AT_EXPAND(AT_INTEGRAL_TYPES_V2)
-      └─ No → Add AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES) to type list
-```
-
-## Edge cases
-
-### Case 1: Dispatch with only floating types
-
-If the operator only supports floating point types, don't add uint support:
-
-```cpp
-// Leave as-is - floating point only operator
-AT_DISPATCH_V2(dtype, "float_op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_FLOATING_TYPES), kHalf);
-```
-
-### Case 2: Complex types present
-
-Unsigned types work alongside complex types:
-
-```cpp
-AT_DISPATCH_V2(dtype, "op", AT_WRAP([&]() {
-  kernel<scalar_t>();
-}), AT_EXPAND(AT_ALL_TYPES),
-    AT_EXPAND(AT_BAREBONES_UNSIGNED_TYPES),
-    AT_EXPAND(AT_COMPLEX_TYPES),
-    kHalf, kBFloat16);
-```
-
-### Case 3: Already has uint support
-
-Check if uint types are already present:
-- If `AT_INTEGRAL_TYPES_V2` is used → already has uint support
-- If `AT_BAREBONES_UNSIGNED_TYPES` is already in list → already has uint support
-- Skip the file if uint support is already present
-
-## Workflow
-
-When asked to add uint support:
-
-1. Read the target file
-2. Check if using AT_DISPATCH_V2:
-   - If not → use at-dispatch-v2 skill first
-3. Identify all dispatch macro sites
-4. For each dispatch:
-   - Analyze current type groups
-   - Choose method (add BAREBONES_UNSIGNED or upgrade to V2)
-   - Apply transformation with Edit tool
-5. Show the user the changes
-6. Explain what was modified
-
-## Important notes
-
-- Always check if v2 conversion is needed first
-- Apply changes consistently across all dispatch sites in the file
-- Method 2 (AT_INTEGRAL_TYPES_V2) is cleaner when applicable
-- Method 1 (explicit AT_BAREBONES_UNSIGNED_TYPES) is more explicit
-- Unsigned types are: kUInt16, kUInt32, kUInt64 (not kByte which is uint8)
-- Some operators may not semantically support unsigned types - use judgment
-
-## Testing
-
-After adding uint support, the operator should accept uint16, uint32, and uint64 tensors. The user is responsible for functional testing.