Halves time spent in generating the key strings

.ci/aarch64_linux/aarch64_ci_build.sh

@@ -3,8 +3,10 @@ set -eux -o pipefail
 
 GPU_ARCH_VERSION=${GPU_ARCH_VERSION:-}
 
-if [[ "$GPU_ARCH_VERSION" == *"12.9"* ]]; then
-    export TORCH_CUDA_ARCH_LIST="8.0;9.0;10.0;12.0"
+if [[ "$GPU_ARCH_VERSION" == *"12.6"* ]]; then
+    export TORCH_CUDA_ARCH_LIST="9.0"
+elif [[ "$GPU_ARCH_VERSION" == *"12.8"* ]]; then
+    export TORCH_CUDA_ARCH_LIST="9.0;10.0;12.0"
 fi
 
 SCRIPTPATH="$( cd -- "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P )"
@@ -25,7 +27,6 @@ if [ "$DESIRED_CUDA" = "cpu" ]; then
     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_wheel_ci_build.py

@@ -31,47 +31,33 @@ def build_ArmComputeLibrary() -> None:
         "build=native",
     ]
     acl_install_dir = "/acl"
-    acl_checkout_dir = os.getenv("ACL_SOURCE_DIR", "ComputeLibrary")
-    if os.path.isdir(acl_install_dir):
-        shutil.rmtree(acl_install_dir)
-    if not os.path.isdir(acl_checkout_dir) or not len(os.listdir(acl_checkout_dir)):
-        check_call(
-            [
-                "git",
-                "clone",
-                "https://github.com/ARM-software/ComputeLibrary.git",
-                "-b",
-                "v25.02",
-                "--depth",
-                "1",
-                "--shallow-submodules",
-            ]
-        )
+    acl_checkout_dir = "ComputeLibrary"
+    os.makedirs(acl_install_dir)
+    check_call(
+        [
+            "git",
+            "clone",
+            "https://github.com/ARM-software/ComputeLibrary.git",
+            "-b",
+            "v25.02",
+            "--depth",
+            "1",
+            "--shallow-submodules",
+        ]
+    )
 
     check_call(
-        ["scons", "Werror=1", f"-j{os.cpu_count()}"] + acl_build_flags,
+        ["scons", "Werror=1", "-j8", f"build_dir=/{acl_install_dir}/build"]
+        + acl_build_flags,
         cwd=acl_checkout_dir,
     )
-    for d in ["arm_compute", "include", "utils", "support", "src", "build"]:
+    for d in ["arm_compute", "include", "utils", "support", "src"]:
         shutil.copytree(f"{acl_checkout_dir}/{d}", f"{acl_install_dir}/{d}")
 
 
-def replace_tag(filename) -> None:
-    with open(filename) as f:
-        lines = f.readlines()
-    for i, line in enumerate(lines):
-        if line.startswith("Tag:"):
-            lines[i] = line.replace("-linux_", "-manylinux_2_28_")
-            print(f"Updated tag from {line} to {lines[i]}")
-            break
-
-    with open(filename, "w") as f:
-        f.writelines(lines)
-
-
-def package_cuda_wheel(wheel_path, desired_cuda) -> None:
+def update_wheel(wheel_path, desired_cuda) -> None:
     """
-    Package the cuda wheel libraries
+    Update the cuda wheel libraries
     """
     folder = os.path.dirname(wheel_path)
     wheelname = os.path.basename(wheel_path)
@@ -79,7 +65,6 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
     os.system(f"unzip {wheel_path} -d {folder}/tmp")
     libs_to_copy = [
         "/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12",
-        "/usr/local/cuda/extras/CUPTI/lib64/libnvperf_host.so",
         "/usr/local/cuda/lib64/libcudnn.so.9",
         "/usr/local/cuda/lib64/libcublas.so.12",
         "/usr/local/cuda/lib64/libcublasLt.so.12",
@@ -89,7 +74,7 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
         "/usr/local/cuda/lib64/libcusparseLt.so.0",
         "/usr/local/cuda/lib64/libcusolver.so.11",
         "/usr/local/cuda/lib64/libcurand.so.10",
-        "/usr/local/cuda/lib64/libnccl.so.2",
+        "/usr/local/cuda/lib64/libnvToolsExt.so.1",
         "/usr/local/cuda/lib64/libnvJitLink.so.12",
         "/usr/local/cuda/lib64/libnvrtc.so.12",
         "/usr/local/cuda/lib64/libcudnn_adv.so.9",
@@ -103,19 +88,30 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
         "/usr/lib64/libgfortran.so.5",
         "/acl/build/libarm_compute.so",
         "/acl/build/libarm_compute_graph.so",
-        "/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
-        "/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
-        "/usr/local/lib/libnvpl_lapack_core.so.0",
-        "/usr/local/lib/libnvpl_blas_core.so.0",
     ]
-
-    if "129" in desired_cuda:
+    if enable_cuda:
         libs_to_copy += [
-            "/usr/local/cuda/lib64/libnvrtc-builtins.so.12.9",
-            "/usr/local/cuda/lib64/libcufile.so.0",
-            "/usr/local/cuda/lib64/libcufile_rdma.so.1",
+            "/usr/local/lib/libnvpl_lapack_lp64_gomp.so.0",
+            "/usr/local/lib/libnvpl_blas_lp64_gomp.so.0",
+            "/usr/local/lib/libnvpl_lapack_core.so.0",
+            "/usr/local/lib/libnvpl_blas_core.so.0",
+        ]
+        if "126" in desired_cuda:
+            libs_to_copy += [
+                "/usr/local/cuda/lib64/libnvrtc-builtins.so.12.6",
+                "/usr/local/cuda/lib64/libcufile.so.0",
+                "/usr/local/cuda/lib64/libcufile_rdma.so.1",
+            ]
+        elif "128" in desired_cuda:
+            libs_to_copy += [
+                "/usr/local/cuda/lib64/libnvrtc-builtins.so.12.8",
+                "/usr/local/cuda/lib64/libcufile.so.0",
+                "/usr/local/cuda/lib64/libcufile_rdma.so.1",
+            ]
+    else:
+        libs_to_copy += [
+            "/opt/OpenBLAS/lib/libopenblas.so.0",
         ]
-
     # Copy libraries to unzipped_folder/a/lib
     for lib_path in libs_to_copy:
         lib_name = os.path.basename(lib_path)
@@ -124,13 +120,6 @@ def package_cuda_wheel(wheel_path, desired_cuda) -> None:
             f"cd {folder}/tmp/torch/lib/; "
             f"patchelf --set-rpath '$ORIGIN' --force-rpath {folder}/tmp/torch/lib/{lib_name}"
         )
-
-    # Make sure the wheel is tagged with manylinux_2_28
-    for f in os.scandir(f"{folder}/tmp/"):
-        if f.is_dir() and f.name.endswith(".dist-info"):
-            replace_tag(f"{f.path}/WHEEL")
-            break
-
     os.mkdir(f"{folder}/cuda_wheel")
     os.system(f"cd {folder}/tmp/; zip -r {folder}/cuda_wheel/{wheelname} *")
     shutil.move(
@@ -205,10 +194,8 @@ if __name__ == "__main__":
     ).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 " + build_vars
+    build_vars = "MAX_JOBS=5 CMAKE_SHARED_LINKER_FLAGS=-Wl,-z,max-page-size=0x10000 "
+    os.system("cd /pytorch; python setup.py clean")
 
     override_package_version = os.getenv("OVERRIDE_PACKAGE_VERSION")
     desired_cuda = os.getenv("DESIRED_CUDA")
@@ -255,6 +242,6 @@ if __name__ == "__main__":
         print("Updating Cuda Dependency")
         filename = os.listdir("/pytorch/dist/")
         wheel_path = f"/pytorch/dist/{filename[0]}"
-        package_cuda_wheel(wheel_path, desired_cuda)
+        update_wheel(wheel_path, desired_cuda)
     pytorch_wheel_name = complete_wheel("/pytorch/")
     print(f"Build Complete. Created {pytorch_wheel_name}..")

.ci/caffe2/README.md

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

.ci/caffe2/test.sh

@@ -5,7 +5,7 @@ source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
 
 if [[ ${BUILD_ENVIRONMENT} == *onnx* ]]; then
   pip install click mock tabulate networkx==2.0
-  pip -q install "file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx"
+  pip -q install --user "file:///var/lib/jenkins/workspace/third_party/onnx#egg=onnx"
 fi
 
 # Skip tests in environments where they are not built/applicable
@@ -13,6 +13,10 @@ if [[ "${BUILD_ENVIRONMENT}" == *-android* ]]; then
   echo 'Skipping tests'
   exit 0
 fi
+if [[ "${BUILD_ENVIRONMENT}" == *-rocm* ]]; then
+  # temporary to locate some kernel issues on the CI nodes
+  export HSAKMT_DEBUG_LEVEL=4
+fi
 # These additional packages are needed for circleci ROCm builds.
 if [[ $BUILD_ENVIRONMENT == *rocm* ]]; then
     # Need networkx 2.0 because bellmand_ford was moved in 2.1 . Scikit-image by
@@ -147,8 +151,8 @@ export DNNL_MAX_CPU_ISA=AVX2
 if [[ "${SHARD_NUMBER:-1}" == "1" ]]; then
   # TODO(sdym@meta.com) remove this when the linked issue resolved.
   # py is temporary until https://github.com/Teemu/pytest-sugar/issues/241 is fixed
-  pip install py==1.11.0
-  pip install pytest-sugar
+  pip install --user py==1.11.0
+  pip install --user pytest-sugar
   # NB: Warnings are disabled because they make it harder to see what
   # the actual erroring test is
   "$PYTHON" \

.ci/docker/README.md

@@ -34,5 +34,5 @@ See `build.sh` for valid build environments (it's the giant switch).
 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
 
 # Set flags (see build.sh) and build image
-sudo bash -c 'TRITON=1 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
+sudo bash -c 'PROTOBUF=1 ./build.sh pytorch-linux-bionic-py3.8-gcc9 -t myimage:latest
 ```

.ci/docker/almalinux/Dockerfile

@@ -1,7 +1,6 @@
-ARG CUDA_VERSION=12.6
+ARG CUDA_VERSION=12.4
 ARG BASE_TARGET=cuda${CUDA_VERSION}
-ARG ROCM_IMAGE=rocm/dev-almalinux-8:6.3-complete
-FROM amd64/almalinux:8.10-20250519 as base
+FROM amd64/almalinux:8 as base
 
 ENV LC_ALL en_US.UTF-8
 ENV LANG en_US.UTF-8
@@ -9,10 +8,12 @@ ENV LANGUAGE en_US.UTF-8
 
 ARG DEVTOOLSET_VERSION=11
 
+ENV LC_ALL en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US.UTF-8
+
 RUN yum -y update
 RUN yum -y install epel-release
-# install glibc-langpack-en make sure en_US.UTF-8 locale is available
-RUN yum -y install glibc-langpack-en
 RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel openssl-devel yum-utils autoconf automake make gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
 # Just add everything as a safe.directory for git since these will be used in multiple places with git
 RUN git config --global --add safe.directory '*'
@@ -40,36 +41,33 @@ RUN bash ./install_conda.sh && rm install_conda.sh
 
 # Install CUDA
 FROM base as cuda
-ARG CUDA_VERSION=12.6
+ARG CUDA_VERSION=12.4
 RUN rm -rf /usr/local/cuda-*
 ADD ./common/install_cuda.sh install_cuda.sh
 COPY ./common/install_nccl.sh install_nccl.sh
 COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
 ENV CUDA_HOME=/usr/local/cuda-${CUDA_VERSION}
 # Preserve CUDA_VERSION for the builds
 ENV CUDA_VERSION=${CUDA_VERSION}
 # Make things in our path by default
 ENV PATH=/usr/local/cuda-${CUDA_VERSION}/bin:$PATH
 
+FROM cuda as cuda11.8
+RUN bash ./install_cuda.sh 11.8
+ENV DESIRED_CUDA=11.8
+
+FROM cuda as cuda12.1
+RUN bash ./install_cuda.sh 12.1
+ENV DESIRED_CUDA=12.1
+
+FROM cuda as cuda12.4
+RUN bash ./install_cuda.sh 12.4
+ENV DESIRED_CUDA=12.4
+
 FROM cuda as cuda12.6
 RUN bash ./install_cuda.sh 12.6
 ENV DESIRED_CUDA=12.6
 
-FROM cuda as cuda12.8
-RUN bash ./install_cuda.sh 12.8
-ENV DESIRED_CUDA=12.8
-
-FROM cuda as cuda12.9
-RUN bash ./install_cuda.sh 12.9
-ENV DESIRED_CUDA=12.9
-
-FROM ${ROCM_IMAGE} as rocm
-ENV PYTORCH_ROCM_ARCH="gfx900;gfx906;gfx908;gfx90a;gfx942;gfx1030;gfx1100;gfx1101;gfx1102;gfx1200;gfx1201"
-ADD ./common/install_mkl.sh install_mkl.sh
-RUN bash ./install_mkl.sh && rm install_mkl.sh
-ENV MKLROOT /opt/intel
-
 # Install MNIST test data
 FROM base as mnist
 ADD ./common/install_mnist.sh install_mnist.sh
@@ -77,9 +75,9 @@ RUN bash ./install_mnist.sh
 
 FROM base as all_cuda
 COPY --from=cuda11.8  /usr/local/cuda-11.8 /usr/local/cuda-11.8
+COPY --from=cuda12.1  /usr/local/cuda-12.1 /usr/local/cuda-12.1
+COPY --from=cuda12.4  /usr/local/cuda-12.4 /usr/local/cuda-12.4
 COPY --from=cuda12.6  /usr/local/cuda-12.6 /usr/local/cuda-12.6
-COPY --from=cuda12.8  /usr/local/cuda-12.8 /usr/local/cuda-12.8
-COPY --from=cuda12.9  /usr/local/cuda-12.9 /usr/local/cuda-12.9
 
 # Final step
 FROM ${BASE_TARGET} as final

.ci/docker/almalinux/build.sh

@@ -15,16 +15,9 @@ fi
 DOCKER_TAG_PREFIX=$(echo "${image}" | awk -F':' '{print $2}')
 
 CUDA_VERSION=""
-ROCM_VERSION=""
-EXTRA_BUILD_ARGS=""
 if [[ "${DOCKER_TAG_PREFIX}" == cuda* ]]; then
     # extract cuda version from image name and tag.  e.g. manylinux2_28-builder:cuda12.8 returns 12.8
     CUDA_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'cuda' '{print $2}')
-    EXTRA_BUILD_ARGS="--build-arg CUDA_VERSION=${CUDA_VERSION}"
-elif [[ "${DOCKER_TAG_PREFIX}" == rocm* ]]; then
-    # extract rocm version from image name and tag.  e.g. manylinux2_28-builder:rocm6.2.4 returns 6.2.4
-    ROCM_VERSION=$(echo "${DOCKER_TAG_PREFIX}" | awk -F'rocm' '{print $2}')
-    EXTRA_BUILD_ARGS="--build-arg ROCM_IMAGE=rocm/dev-almalinux-8:${ROCM_VERSION}-complete"
 fi
 
 case ${DOCKER_TAG_PREFIX} in
@@ -34,9 +27,6 @@ case ${DOCKER_TAG_PREFIX} in
   cuda*)
     BASE_TARGET=cuda${CUDA_VERSION}
     ;;
-  rocm*)
-    BASE_TARGET=rocm
-    ;;
   *)
     echo "ERROR: Unknown docker tag ${DOCKER_TAG_PREFIX}"
     exit 1
@@ -57,8 +47,8 @@ docker build \
   --target final \
   --progress plain \
   --build-arg "BASE_TARGET=${BASE_TARGET}" \
+  --build-arg "CUDA_VERSION=${CUDA_VERSION}" \
   --build-arg "DEVTOOLSET_VERSION=11" \
-  ${EXTRA_BUILD_ARGS} \
   -t ${tmp_tag} \
   $@ \
   -f "${TOPDIR}/.ci/docker/almalinux/Dockerfile" \

.ci/docker/build.sh

@@ -50,23 +50,30 @@ if [[ "$image" == *xla* ]]; then
   exit 0
 fi
 
-if [[ "$image" == *-jammy* ]]; then
+if [[ "$image" == *-focal* ]]; then
+  UBUNTU_VERSION=20.04
+elif [[ "$image" == *-jammy* ]]; then
   UBUNTU_VERSION=22.04
-elif [[ "$image" == *-noble* ]]; then
-  UBUNTU_VERSION=24.04
 elif [[ "$image" == *ubuntu* ]]; then
   extract_version_from_image_name ubuntu UBUNTU_VERSION
+elif [[ "$image" == *centos* ]]; then
+  extract_version_from_image_name centos CENTOS_VERSION
 fi
 
 if [ -n "${UBUNTU_VERSION}" ]; then
   OS="ubuntu"
+elif [ -n "${CENTOS_VERSION}" ]; then
+  OS="centos"
 else
   echo "Unable to derive operating system base..."
   exit 1
 fi
 
 DOCKERFILE="${OS}/Dockerfile"
-if [[ "$image" == *rocm* ]]; then
+# When using ubuntu - 22.04, start from Ubuntu docker image, instead of nvidia/cuda docker image.
+if [[ "$image" == *cuda* && "$UBUNTU_VERSION" != "22.04" ]]; then
+  DOCKERFILE="${OS}-cuda/Dockerfile"
+elif [[ "$image" == *rocm* ]]; then
   DOCKERFILE="${OS}-rocm/Dockerfile"
 elif [[ "$image" == *xpu* ]]; then
   DOCKERFILE="${OS}-xpu/Dockerfile"
@@ -78,6 +85,9 @@ elif [[ "$image" == *linter* ]]; then
   DOCKERFILE="linter/Dockerfile"
 fi
 
+# CMake 3.18 is needed to support CUDA17 language variant
+CMAKE_VERSION=3.18.5
+
 _UCX_COMMIT=7bb2722ff2187a0cad557ae4a6afa090569f83fb
 _UCC_COMMIT=20eae37090a4ce1b32bcce6144ccad0b49943e0b
 if [[ "$image" == *rocm* ]]; then
@@ -85,223 +95,260 @@ if [[ "$image" == *rocm* ]]; then
   _UCC_COMMIT=0c0fc21559835044ab107199e334f7157d6a0d3d
 fi
 
-tag=$(echo $image | awk -F':' '{print $2}')
-
 # It's annoying to rename jobs every time you want to rewrite a
 # configuration, so we hardcode everything here rather than do it
 # from scratch
-case "$tag" in
-  pytorch-linux-jammy-cuda12.4-cudnn9-py3-gcc11)
-    CUDA_VERSION=12.4
+case "$image" in
+  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc11)
+    CUDA_VERSION=12.6.3
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=11
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc11)
-    CUDA_VERSION=12.8.1
-    CUDNN_VERSION=9
-    ANACONDA_PYTHON_VERSION=3.10
-    GCC_VERSION=11
-    VISION=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    TRITON=yes
-    ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.8.1
+  pytorch-linux-focal-cuda12.4-cudnn9-py3-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.4.1
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.8.1
+  pytorch-linux-focal-cuda12.4-cudnn9-py3.12-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.4.1
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3.13-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.8.1
+  pytorch-linux-focal-cuda12.4-cudnn9-py3.13-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.4.1
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.13
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc9)
+  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9)
     CUDA_VERSION=12.6.3
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6
+  pytorch-linux-focal-cuda12.6-cudnn9-py3-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.6.3
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6
+  pytorch-linux-focal-cuda12.6-cudnn9-py3.12-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.6.3
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
-    CUDA_VERSION=12.6
+  pytorch-linux-focal-cuda12.6-cudnn9-py3.13-gcc9-inductor-benchmarks)
+    CUDA_VERSION=12.6.3
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.13
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3-gcc9)
-    CUDA_VERSION=12.8.1
+  pytorch-linux-focal-cuda11.8-cudnn9-py3-gcc9)
+    CUDA_VERSION=11.8.0
     CUDNN_VERSION=9
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-py3-clang12-onnx)
+  pytorch-linux-focal-py3-clang10-onnx)
     ANACONDA_PYTHON_VERSION=3.9
-    CLANG_VERSION=12
+    CLANG_VERSION=10
+    PROTOBUF=yes
     VISION=yes
+    CONDA_CMAKE=yes
     ONNX=yes
     ;;
-  pytorch-linux-jammy-py3.9-clang12)
+  pytorch-linux-focal-py3.9-clang10)
     ANACONDA_PYTHON_VERSION=3.9
-    CLANG_VERSION=12
+    CLANG_VERSION=10
+    PROTOBUF=yes
     VISION=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-py3.11-clang12)
+  pytorch-linux-focal-py3.11-clang10)
     ANACONDA_PYTHON_VERSION=3.11
-    CLANG_VERSION=12
+    CLANG_VERSION=10
+    PROTOBUF=yes
     VISION=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-py3.9-gcc9)
+  pytorch-linux-focal-py3.9-gcc9)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=9
+    PROTOBUF=yes
     VISION=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
-  pytorch-linux-jammy-rocm-n-1-py3)
+  pytorch-linux-focal-rocm-n-1-py3)
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=11
+    PROTOBUF=yes
+    VISION=yes
+    ROCM_VERSION=6.2.4
+    NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
+    TRITON=yes
+    KATEX=yes
+    UCX_COMMIT=${_UCX_COMMIT}
+    UCC_COMMIT=${_UCC_COMMIT}
+    INDUCTOR_BENCHMARKS=yes
+    ;;
+  pytorch-linux-focal-rocm-n-py3)
+    ANACONDA_PYTHON_VERSION=3.10
+    GCC_VERSION=11
+    PROTOBUF=yes
     VISION=yes
     ROCM_VERSION=6.3
     NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
     TRITON=yes
     KATEX=yes
     UCX_COMMIT=${_UCX_COMMIT}
     UCC_COMMIT=${_UCC_COMMIT}
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-rocm-n-py3 | pytorch-linux-noble-rocm-n-py3)
-    if [[ $tag =~ "jammy" ]]; then
-      ANACONDA_PYTHON_VERSION=3.10
-    else
-      ANACONDA_PYTHON_VERSION=3.12
-    fi
+  pytorch-linux-jammy-xpu-2024.0-py3)
+    ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
     VISION=yes
-    ROCM_VERSION=6.4
+    XPU_VERSION=0.5
     NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
     TRITON=yes
-    KATEX=yes
-    UCX_COMMIT=${_UCX_COMMIT}
-    UCC_COMMIT=${_UCC_COMMIT}
-    INDUCTOR_BENCHMARKS=yes
     ;;
   pytorch-linux-jammy-xpu-2025.0-py3)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
     VISION=yes
     XPU_VERSION=2025.0
     NINJA_VERSION=1.9.0
-    TRITON=yes
-    ;;
-  pytorch-linux-jammy-xpu-2025.1-py3)
-    ANACONDA_PYTHON_VERSION=3.9
-    GCC_VERSION=11
-    VISION=yes
-    XPU_VERSION=2025.1
-    NINJA_VERSION=1.9.0
+    CONDA_CMAKE=yes
     TRITON=yes
     ;;
     pytorch-linux-jammy-py3.9-gcc11-inductor-benchmarks)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     DOCS=yes
     INDUCTOR_BENCHMARKS=yes
     ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-clang12)
+  pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-clang12)
     ANACONDA_PYTHON_VERSION=3.9
-    CUDA_VERSION=12.8.1
+    CUDA_VERSION=11.8
     CUDNN_VERSION=9
     CLANG_VERSION=12
+    PROTOBUF=yes
     VISION=yes
     TRITON=yes
     ;;
+  pytorch-linux-jammy-py3-clang12-asan)
+    ANACONDA_PYTHON_VERSION=3.9
+    CLANG_VERSION=12
+    PROTOBUF=yes
+    VISION=yes
+    CONDA_CMAKE=yes
+    TRITON=yes
+    ;;
+  pytorch-linux-jammy-py3-clang15-asan)
+    ANACONDA_PYTHON_VERSION=3.10
+    CLANG_VERSION=15
+    CONDA_CMAKE=yes
+    VISION=yes
+    ;;
   pytorch-linux-jammy-py3-clang18-asan)
     ANACONDA_PYTHON_VERSION=3.10
     CLANG_VERSION=18
+    CONDA_CMAKE=yes
     VISION=yes
     ;;
   pytorch-linux-jammy-py3.9-gcc11)
     ANACONDA_PYTHON_VERSION=3.9
     GCC_VERSION=11
+    PROTOBUF=yes
     VISION=yes
     KATEX=yes
+    CONDA_CMAKE=yes
     TRITON=yes
     DOCS=yes
     UNINSTALL_DILL=yes
@@ -309,12 +356,14 @@ case "$tag" in
   pytorch-linux-jammy-py3-clang12-executorch)
     ANACONDA_PYTHON_VERSION=3.10
     CLANG_VERSION=12
+    CONDA_CMAKE=yes
     EXECUTORCH=yes
     ;;
   pytorch-linux-jammy-py3.12-halide)
     CUDA_VERSION=12.6
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
+    CONDA_CMAKE=yes
     HALIDE=yes
     TRITON=yes
     ;;
@@ -322,25 +371,28 @@ case "$tag" in
     CUDA_VERSION=12.6
     ANACONDA_PYTHON_VERSION=3.12
     GCC_VERSION=11
+    CONDA_CMAKE=yes
     TRITON_CPU=yes
     ;;
-  pytorch-linux-jammy-linter)
+  pytorch-linux-focal-linter)
     # TODO: Use 3.9 here because of this issue https://github.com/python/mypy/issues/13627.
     # We will need to update mypy version eventually, but that's for another day. The task
     # would be to upgrade mypy to 1.0.0 with Python 3.11
     PYTHON_VERSION=3.9
+    PIP_CMAKE=yes
     ;;
-  pytorch-linux-jammy-cuda12.8-cudnn9-py3.9-linter)
+  pytorch-linux-jammy-cuda11.8-cudnn9-py3.9-linter)
     PYTHON_VERSION=3.9
-    CUDA_VERSION=12.8.1
+    CUDA_VERSION=11.8
+    PIP_CMAKE=yes
     ;;
   pytorch-linux-jammy-aarch64-py3.10-gcc11)
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=11
     ACL=yes
+    PROTOBUF=yes
     VISION=yes
     CONDA_CMAKE=yes
-    OPENBLAS=yes
     # snadampal: skipping llvm src build install because the current version
     # from pytorch/llvm:9.0.1 is x86 specific
     SKIP_LLVM_SRC_BUILD_INSTALL=yes
@@ -349,9 +401,9 @@ case "$tag" in
     ANACONDA_PYTHON_VERSION=3.10
     GCC_VERSION=11
     ACL=yes
+    PROTOBUF=yes
     VISION=yes
     CONDA_CMAKE=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
@@ -359,6 +411,7 @@ case "$tag" in
     ;;
   *)
     # Catch-all for builds that are not hardcoded.
+    PROTOBUF=yes
     VISION=yes
     echo "image '$image' did not match an existing build configuration"
     if [[ "$image" == *py* ]]; then
@@ -374,7 +427,8 @@ case "$tag" in
       TRITON=yes
       # To ensure that any ROCm config will build using conda cmake
       # and thus have LAPACK/MKL enabled
-      fi
+      CONDA_CMAKE=yes
+    fi
     if [[ "$image" == *centos7* ]]; then
       NINJA_VERSION=1.10.2
     fi
@@ -390,11 +444,22 @@ case "$tag" in
     if [[ "$image" == *glibc* ]]; then
       extract_version_from_image_name glibc GLIBC_VERSION
     fi
+    if [[ "$image" == *cmake* ]]; then
+      extract_version_from_image_name cmake CMAKE_VERSION
+    fi
   ;;
 esac
 
 tmp_tag=$(basename "$(mktemp -u)" | tr '[:upper:]' '[:lower:]')
 
+#when using cudnn version 8 install it separately from cuda
+if [[ "$image" == *cuda*  && ${OS} == "ubuntu" ]]; then
+  IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-cudnn${CUDNN_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
+  if [[ ${CUDNN_VERSION} == 9 ]]; then
+    IMAGE_NAME="nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}"
+  fi
+fi
+
 no_cache_flag=""
 progress_flag=""
 # Do not use cache and progress=plain when in CI
@@ -408,9 +473,11 @@ docker build \
        ${no_cache_flag} \
        ${progress_flag} \
        --build-arg "BUILD_ENVIRONMENT=${image}" \
+       --build-arg "PROTOBUF=${PROTOBUF:-}" \
        --build-arg "LLVMDEV=${LLVMDEV:-}" \
        --build-arg "VISION=${VISION:-}" \
        --build-arg "UBUNTU_VERSION=${UBUNTU_VERSION}" \
+       --build-arg "CENTOS_VERSION=${CENTOS_VERSION}" \
        --build-arg "DEVTOOLSET_VERSION=${DEVTOOLSET_VERSION}" \
        --build-arg "GLIBC_VERSION=${GLIBC_VERSION}" \
        --build-arg "CLANG_VERSION=${CLANG_VERSION}" \
@@ -421,6 +488,7 @@ docker build \
        --build-arg "CUDNN_VERSION=${CUDNN_VERSION}" \
        --build-arg "TENSORRT_VERSION=${TENSORRT_VERSION}" \
        --build-arg "GRADLE_VERSION=${GRADLE_VERSION}" \
+       --build-arg "CMAKE_VERSION=${CMAKE_VERSION:-}" \
        --build-arg "NINJA_VERSION=${NINJA_VERSION:-}" \
        --build-arg "KATEX=${KATEX:-}" \
        --build-arg "ROCM_VERSION=${ROCM_VERSION:-}" \
@@ -428,6 +496,8 @@ docker build \
        --build-arg "IMAGE_NAME=${IMAGE_NAME}" \
        --build-arg "UCX_COMMIT=${UCX_COMMIT}" \
        --build-arg "UCC_COMMIT=${UCC_COMMIT}" \
+       --build-arg "CONDA_CMAKE=${CONDA_CMAKE}" \
+       --build-arg "PIP_CMAKE=${PIP_CMAKE}" \
        --build-arg "TRITON=${TRITON}" \
        --build-arg "TRITON_CPU=${TRITON_CPU}" \
        --build-arg "ONNX=${ONNX}" \
@@ -436,9 +506,7 @@ docker build \
        --build-arg "EXECUTORCH=${EXECUTORCH}" \
        --build-arg "HALIDE=${HALIDE}" \
        --build-arg "XPU_VERSION=${XPU_VERSION}" \
-       --build-arg "UNINSTALL_DILL=${UNINSTALL_DILL}" \
        --build-arg "ACL=${ACL:-}" \
-       --build-arg "OPENBLAS=${OPENBLAS:-}" \
        --build-arg "SKIP_SCCACHE_INSTALL=${SKIP_SCCACHE_INSTALL:-}" \
        --build-arg "SKIP_LLVM_SRC_BUILD_INSTALL=${SKIP_LLVM_SRC_BUILD_INSTALL:-}" \
        -f $(dirname ${DOCKERFILE})/Dockerfile \
@@ -514,12 +582,3 @@ elif [ "$HAS_TRITON" = "yes" ]; then
   echo "expecting triton to not be installed, but it is"
   exit 1
 fi
-
-# Sanity check cmake version.  Executorch reinstalls cmake and I'm not sure if
-# they support 4.0.0 yet, so exclude them from this check.
-CMAKE_VERSION=$(drun cmake --version)
-if [[ "$EXECUTORCH" != *yes* && "$CMAKE_VERSION" != *4.* ]]; then
-  echo "CMake version is not 4.0.0:"
-  drun cmake --version
-  exit 1
-fi

.ci/docker/centos-rocm/Dockerfile

@@ -17,8 +17,9 @@ RUN bash ./install_base.sh && rm install_base.sh
 # Update CentOS git version
 RUN yum -y remove git
 RUN yum -y remove git-*
-RUN yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
-    sed -i 's/packages.endpoint/packages.endpointdev/' /etc/yum.repos.d/endpoint.repo
+RUN yum -y install https://packages.endpoint.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm || \
+    (yum -y install https://packages.endpointdev.com/rhel/7/os/x86_64/endpoint-repo-1.9-1.x86_64.rpm && \
+    sed -i "s/packages.endpoint/packages.endpointdev/" /etc/yum.repos.d/endpoint.repo)
 RUN yum install -y git
 
 # Install devtoolset
@@ -39,7 +40,7 @@ RUN bash ./install_user.sh && rm install_user.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
 ARG ANACONDA_PYTHON_VERSION
-ARG BUILD_ENVIRONMENT
+ARG CONDA_CMAKE
 ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
 ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
 COPY requirements-ci.txt /opt/conda/requirements-ci.txt
@@ -47,6 +48,13 @@ COPY ./common/install_conda.sh install_conda.sh
 COPY ./common/common_utils.sh common_utils.sh
 RUN bash ./install_conda.sh && rm install_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
 
+# (optional) Install protobuf for ONNX
+ARG PROTOBUF
+COPY ./common/install_protobuf.sh install_protobuf.sh
+RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
+RUN rm install_protobuf.sh
+ENV INSTALLED_PROTOBUF ${PROTOBUF}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -74,6 +82,12 @@ ENV MAGMA_HOME /opt/rocm/magma
 ENV LANG en_US.utf8
 ENV LC_ALL en_US.utf8
 
+# (optional) Install non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
+
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
 COPY ./common/install_ninja.sh install_ninja.sh

.ci/docker/ci_commit_pins/executorch.txt

@@ -1 +1 @@
-56392aa978594cc155fa8af48cd949f5b5f1823a
+381ae5d57d35c165d98df728380b20fbde350392

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

@@ -1 +1 @@
-v2.27.5-1
+v2.26.2-1

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

@@ -1 +1 @@
-ae324eeac8e102a2b40370e341460f3791353398
+0bcc8265e677e5321606a3311bf71470f14456a8

.ci/docker/ci_commit_pins/triton.txt

@@ -1 +1 @@
-ae848267bebc65c6181e8cc5e64a6357d2679260
+96316ce50fade7e209553aba4898cd9b82aab83b

.ci/docker/common/common_utils.sh

@@ -23,10 +23,6 @@ conda_install() {
   as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y python="$ANACONDA_PYTHON_VERSION" $*
 }
 
-conda_install_through_forge() {
-  as_jenkins conda install -c conda-forge -q -n py_$ANACONDA_PYTHON_VERSION -y python="$ANACONDA_PYTHON_VERSION" $*
-}
-
 conda_run() {
   as_jenkins conda run -n py_$ANACONDA_PYTHON_VERSION --no-capture-output $*
 }

.ci/docker/common/install_base.sh

@@ -15,9 +15,6 @@ install_ubuntu() {
   elif [[ "$UBUNTU_VERSION" == "22.04"* ]]; then
     cmake3="cmake=3.22*"
     maybe_libiomp_dev=""
-  elif [[ "$UBUNTU_VERSION" == "24.04"* ]]; then
-    cmake3="cmake=3.28*"
-    maybe_libiomp_dev=""
   else
     cmake3="cmake=3.5*"
     maybe_libiomp_dev="libiomp-dev"
@@ -33,6 +30,18 @@ install_ubuntu() {
     maybe_libomp_dev=""
   fi
 
+  # HACK: UCC testing relies on libnccl library from NVIDIA repo, and version 2.16 crashes
+  # See https://github.com/pytorch/pytorch/pull/105260#issuecomment-1673399729
+  # TODO: Eliminate this hack, we should not relay on apt-get installation
+  # See https://github.com/pytorch/pytorch/issues/144768
+  if [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "11.8"* ]]; then
+    maybe_libnccl_dev="libnccl2=2.15.5-1+cuda11.8 libnccl-dev=2.15.5-1+cuda11.8 --allow-downgrades --allow-change-held-packages"
+  elif [[ "$UBUNTU_VERSION" == "20.04"* && "$CUDA_VERSION" == "12.4"* ]]; then
+    maybe_libnccl_dev="libnccl2=2.26.2-1+cuda12.4 libnccl-dev=2.26.2-1+cuda12.4 --allow-downgrades --allow-change-held-packages"
+  else
+    maybe_libnccl_dev=""
+  fi
+
   # Install common dependencies
   apt-get update
   # TODO: Some of these may not be necessary
@@ -61,6 +70,7 @@ install_ubuntu() {
     libasound2-dev \
     libsndfile-dev \
     ${maybe_libomp_dev} \
+    ${maybe_libnccl_dev} \
     software-properties-common \
     wget \
     sudo \
@@ -89,6 +99,9 @@ install_centos() {
 
   ccache_deps="asciidoc docbook-dtds docbook-style-xsl libxslt"
   numpy_deps="gcc-gfortran"
+  # Note: protobuf-c-{compiler,devel} on CentOS are too old to be used
+  # for Caffe2. That said, we still install them to make sure the build
+  # system opts to build/use protoc and libprotobuf from third-party.
   yum install -y \
     $ccache_deps \
     $numpy_deps \

.ci/docker/common/install_cache.sh

@@ -9,7 +9,7 @@ install_ubuntu() {
   # Instead use lib and headers from OpenSSL1.1 installed in `install_openssl.sh``
   apt-get install -y cargo
   echo "Checking out sccache repo"
-  git clone https://github.com/mozilla/sccache -b v0.10.0
+  git clone https://github.com/mozilla/sccache -b v0.9.1
   cd sccache
   echo "Building sccache"
   cargo build --release

.ci/docker/common/install_cmake.sh

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

.ci/docker/common/install_conda.sh

@@ -6,8 +6,8 @@ set -ex
 if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   BASE_URL="https://repo.anaconda.com/miniconda"
   CONDA_FILE="Miniconda3-latest-Linux-x86_64.sh"
-  if [[ $(uname -m) == "aarch64" ]] || [[ "$BUILD_ENVIRONMENT" == *xpu* ]] || [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
-    BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"  # @lint-ignore
+  if [[ $(uname -m) == "aarch64" ]] || [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
+    BASE_URL="https://github.com/conda-forge/miniforge/releases/latest/download"
     CONDA_FILE="Miniforge3-Linux-$(uname -m).sh"
   fi
 
@@ -64,31 +64,30 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
   # which is provided in libstdcxx 12 and up.
   conda_install libstdcxx-ng=12.3.0 --update-deps -c conda-forge
 
-  # Miniforge installer doesn't install sqlite by default
-  if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
-    conda_install sqlite
-  fi
-
   # Install PyTorch conda deps, as per https://github.com/pytorch/pytorch README
-  if [[ $(uname -m) != "aarch64" ]]; then
-    pip_install mkl==2024.2.0
-    pip_install mkl-static==2024.2.0
-    pip_install mkl-include==2024.2.0
+  if [[ $(uname -m) == "aarch64" ]]; then
+    conda_install "openblas==0.3.29=*openmp*"
+  else
+    conda_install "mkl=2021.4.0 mkl-include=2021.4.0"
   fi
 
   # Install llvm-8 as it is required to compile llvmlite-0.30.0 from source
   # and libpython-static for torch deploy
   conda_install llvmdev=8.0.0 "libpython-static=${ANACONDA_PYTHON_VERSION}"
 
+  # Use conda cmake in some cases. Conda cmake will be newer than our supported
+  # min version (3.5 for xenial and 3.10 for bionic), so we only do it in those
+  # following builds that we know should use conda. Specifically, Ubuntu bionic
+  # and focal cannot find conda mkl with stock cmake, so we need a cmake from conda
+  if [ -n "${CONDA_CMAKE}" ]; then
+    conda_install cmake
+  fi
+
   # Magma package names are concatenation of CUDA major and minor ignoring revision
   # I.e. magma-cuda102 package corresponds to CUDA_VERSION=10.2 and CUDA_VERSION=10.2.89
   # Magma is installed from a tarball in the ossci-linux bucket into the conda env
   if [ -n "$CUDA_VERSION" ]; then
-    conda_run ${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION})
-  fi
-
-  if [[ "$UBUNTU_VERSION" == "24.04"* ]] ; then
-    conda_install_through_forge libstdcxx-ng=14
+    ${SCRIPT_FOLDER}/install_magma_conda.sh $(cut -f1-2 -d'.' <<< ${CUDA_VERSION}) ${ANACONDA_PYTHON_VERSION}
   fi
 
   # Install some other packages, including those needed for Python test reporting

.ci/docker/common/install_cpython.sh

@@ -3,10 +3,11 @@
 set -uex -o pipefail
 
 PYTHON_DOWNLOAD_URL=https://www.python.org/ftp/python
+PYTHON_DOWNLOAD_GITHUB_BRANCH=https://github.com/python/cpython/archive/refs/heads
 GET_PIP_URL=https://bootstrap.pypa.io/get-pip.py
 
 # Python versions to be installed in /opt/$VERSION_NO
-CPYTHON_VERSIONS=${CPYTHON_VERSIONS:-"3.9.0 3.10.1 3.11.0 3.12.0 3.13.0 3.13.0t 3.14.0 3.14.0t"}
+CPYTHON_VERSIONS=${CPYTHON_VERSIONS:-"3.9.0 3.10.1 3.11.0 3.12.0 3.13.0 3.13.0t"}
 
 function check_var {
     if [ -z "$1" ]; then
@@ -23,8 +24,9 @@ function do_cpython_build {
     tar -xzf Python-$py_ver.tgz
 
     local additional_flags=""
-    if [[ "$py_ver" == *"t" ]]; then
+    if [ "$py_ver" == "3.13.0t" ]; then
         additional_flags=" --disable-gil"
+        mv cpython-3.13/ cpython-3.13t/
     fi
 
     pushd $py_folder
@@ -66,7 +68,7 @@ function do_cpython_build {
         ln -s pip3 ${prefix}/bin/pip
     fi
     # install setuptools since python 3.12 is required to use distutils
-    ${prefix}/bin/pip install wheel==0.45.1 setuptools==80.9.0
+    ${prefix}/bin/pip install wheel==0.34.2 setuptools==68.2.2
     local abi_tag=$(${prefix}/bin/python -c "from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag; print('{0}{1}-{2}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag()))")
     ln -sf ${prefix} /opt/python/${abi_tag}
 }
@@ -74,20 +76,24 @@ function do_cpython_build {
 function build_cpython {
     local py_ver=$1
     check_var $py_ver
-    local py_suffix=$py_ver
-    local py_folder=$py_ver
+    check_var $PYTHON_DOWNLOAD_URL
+    local py_ver_folder=$py_ver
 
-    # Special handling for nogil
-    if [[ "${py_ver}" == *"t" ]]; then
-        py_suffix=${py_ver::-1}
-        py_folder=$py_suffix
+    if [ "$py_ver" = "3.13.0t" ]; then
+        PY_VER_SHORT="3.13"
+        PYT_VER_SHORT="3.13t"
+        check_var $PYTHON_DOWNLOAD_GITHUB_BRANCH
+        wget $PYTHON_DOWNLOAD_GITHUB_BRANCH/$PY_VER_SHORT.tar.gz -O Python-$py_ver.tgz
+        do_cpython_build $py_ver cpython-$PYT_VER_SHORT
+    elif [ "$py_ver" = "3.13.0" ]; then
+        PY_VER_SHORT="3.13"
+        check_var $PYTHON_DOWNLOAD_GITHUB_BRANCH
+        wget $PYTHON_DOWNLOAD_GITHUB_BRANCH/$PY_VER_SHORT.tar.gz -O Python-$py_ver.tgz
+        do_cpython_build $py_ver cpython-$PY_VER_SHORT
+    else
+        wget -q $PYTHON_DOWNLOAD_URL/$py_ver_folder/Python-$py_ver.tgz
+        do_cpython_build $py_ver Python-$py_ver
     fi
-    # Only b3 is available now
-    if [ "$py_suffix" == "3.14.0" ]; then
-        py_suffix="3.14.0b3"
-    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
 
     rm -f Python-$py_ver.tgz
 }

.ci/docker/common/install_cuda.sh

@@ -2,128 +2,150 @@
 
 set -ex
 
-arch_path=''
-targetarch=${TARGETARCH:-$(uname -m)}
-if [ ${targetarch} = 'amd64' ] || [ "${targetarch}" = 'x86_64' ]; then
-  arch_path='x86_64'
-else
-  arch_path='sbsa'
-fi
+CUDNN_VERSION=9.5.1.17
 
-NVSHMEM_VERSION=3.3.9
-
-function install_cuda {
-  version=$1
-  runfile=$2
-  major_minor=${version%.*}
-  rm -rf /usr/local/cuda-${major_minor} /usr/local/cuda
-  if [[ ${arch_path} == 'sbsa' ]]; then
-      runfile="${runfile}_sbsa"
-  fi
-  runfile="${runfile}.run"
-  wget -q https://developer.download.nvidia.com/compute/cuda/${version}/local_installers/${runfile} -O ${runfile}
-  chmod +x ${runfile}
-  ./${runfile} --toolkit --silent
-  rm -f ${runfile}
-  rm -f /usr/local/cuda && ln -s /usr/local/cuda-${major_minor} /usr/local/cuda
+function install_cusparselt_040 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.4.0.7-archive.tar.xz
+    tar xf libcusparse_lt-linux-x86_64-0.4.0.7-archive.tar.xz
+    cp -a libcusparse_lt-linux-x86_64-0.4.0.7-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-x86_64-0.4.0.7-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
 }
 
-function install_cudnn {
-  cuda_major_version=$1
-  cudnn_version=$2
-  mkdir tmp_cudnn && cd tmp_cudnn
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  filepath="cudnn-linux-${arch_path}-${cudnn_version}_cuda${cuda_major_version}-archive"
-  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-${arch_path}/${filepath}.tar.xz
-  tar xf ${filepath}.tar.xz
-  cp -a ${filepath}/include/* /usr/local/cuda/include/
-  cp -a ${filepath}/lib/* /usr/local/cuda/lib64/
-  cd ..
-  rm -rf tmp_cudnn
+function install_cusparselt_062 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
+    tar xf libcusparse_lt-linux-x86_64-0.6.2.3-archive.tar.xz
+    cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-x86_64-0.6.2.3-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
 }
 
-function install_nvshmem {
-  cuda_major_version=$1      # e.g. "12"
-  nvshmem_version=$2         # e.g. "3.3.9"
+function install_cusparselt_063 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/libcusparse_lt-linux-x86_64-0.6.3.2-archive.tar.xz
+    tar xf libcusparse_lt-linux-x86_64-0.6.3.2-archive.tar.xz
+    cp -a libcusparse_lt-linux-x86_64-0.6.3.2-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-x86_64-0.6.3.2-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
 
-  case "${arch_path}" in
-    sbsa)
-      dl_arch="aarch64"
-      ;;
-    x86_64)
-      dl_arch="x64"
-      ;;
-    *)
-      dl_arch="${arch}"
-      ;;
-  esac
+function install_118 {
+    CUDNN_VERSION=9.1.0.70
+    echo "Installing CUDA 11.8 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.4.0"
+    rm -rf /usr/local/cuda-11.8 /usr/local/cuda
+    # install CUDA 11.8.0 in the same container
+    wget -q https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
+    chmod +x cuda_11.8.0_520.61.05_linux.run
+    ./cuda_11.8.0_520.61.05_linux.run --toolkit --silent
+    rm -f cuda_11.8.0_520.61.05_linux.run
+    rm -f /usr/local/cuda && ln -s /usr/local/cuda-11.8 /usr/local/cuda
 
-  tmpdir="tmp_nvshmem"
-  mkdir -p "${tmpdir}" && cd "${tmpdir}"
+    # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+    mkdir tmp_cudnn && cd tmp_cudnn
+    wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
+    tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive.tar.xz
+    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/include/* /usr/local/cuda/include/
+    cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda11-archive/lib/* /usr/local/cuda/lib64/
+    cd ..
+    rm -rf tmp_cudnn
 
-  # nvSHMEM license: https://docs.nvidia.com/nvshmem/api/sla.html
-  filename="libnvshmem_cuda${cuda_major_version}-linux-${arch_path}-${nvshmem_version}"
-  url="https://developer.download.nvidia.com/compute/redist/nvshmem/${nvshmem_version}/builds/cuda${cuda_major_version}/txz/agnostic/${dl_arch}/${filename}.tar.gz"
+    CUDA_VERSION=11.8 bash install_nccl.sh
 
-  # download, unpack, install
-  wget -q "${url}"
-  tar xf "${filename}.tar.gz"
-  cp -a "libnvshmem/include/"* /usr/local/include/
-  cp -a "libnvshmem/lib/"*     /usr/local/lib/
+    install_cusparselt_040
 
-  # cleanup
-  cd ..
-  rm -rf "${tmpdir}"
-
-  echo "nvSHMEM ${nvshmem_version} for CUDA ${cuda_major_version} (${arch_path}) installed."
+    ldconfig
 }
 
 function install_124 {
   CUDNN_VERSION=9.1.0.70
   echo "Installing CUDA 12.4.1 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.2"
-  install_cuda 12.4.1 cuda_12.4.1_550.54.15_linux
+  rm -rf /usr/local/cuda-12.4 /usr/local/cuda
+  # install CUDA 12.4.1 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.4.1/local_installers/cuda_12.4.1_550.54.15_linux.run
+  chmod +x cuda_12.4.1_550.54.15_linux.run
+  ./cuda_12.4.1_550.54.15_linux.run --toolkit --silent
+  rm -f cuda_12.4.1_550.54.15_linux.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.4 /usr/local/cuda
 
-  install_cudnn 12 $CUDNN_VERSION
+  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
 
   CUDA_VERSION=12.4 bash install_nccl.sh
 
-  CUDA_VERSION=12.4 bash install_cusparselt.sh
+  install_cusparselt_062
 
   ldconfig
 }
 
 function install_126 {
-  CUDNN_VERSION=9.10.2.21
-  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
-  install_cuda 12.6.3 cuda_12.6.3_560.35.05_linux
+  echo "Installing CUDA 12.6.3 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
+  rm -rf /usr/local/cuda-12.6 /usr/local/cuda
+  # install CUDA 12.6.3 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda_12.6.3_560.35.05_linux.run
+  chmod +x cuda_12.6.3_560.35.05_linux.run
+  ./cuda_12.6.3_560.35.05_linux.run --toolkit --silent
+  rm -f cuda_12.6.3_560.35.05_linux.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.6 /usr/local/cuda
 
-  install_cudnn 12 $CUDNN_VERSION
-
-  install_nvshmem 12 $NVSHMEM_VERSION
+  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
 
   CUDA_VERSION=12.6 bash install_nccl.sh
 
-  CUDA_VERSION=12.6 bash install_cusparselt.sh
+  install_cusparselt_063
 
   ldconfig
 }
 
-function install_129 {
-  CUDNN_VERSION=9.10.2.21
-  echo "Installing CUDA 12.9.1 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
-  # install CUDA 12.9.1 in the same container
-  install_cuda 12.9.1 cuda_12.9.1_575.57.08_linux
+function prune_118 {
+    echo "Pruning CUDA 11.8 and cuDNN"
+    #####################################################################################
+    # CUDA 11.8 prune static libs
+    #####################################################################################
+    export NVPRUNE="/usr/local/cuda-11.8/bin/nvprune"
+    export CUDA_LIB_DIR="/usr/local/cuda-11.8/lib64"
 
-  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  install_cudnn 12 $CUDNN_VERSION
+    export GENCODE="-gencode arch=compute_35,code=sm_35 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
+    export GENCODE_CUDNN="-gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90"
 
-  install_nvshmem 12 $NVSHMEM_VERSION
+    if [[ -n "$OVERRIDE_GENCODE" ]]; then
+        export GENCODE=$OVERRIDE_GENCODE
+    fi
 
-  CUDA_VERSION=12.9 bash install_nccl.sh
+    # all CUDA libs except CuDNN and CuBLAS (cudnn and cublas need arch 3.7 included)
+    ls $CUDA_LIB_DIR/ | grep "\.a" | grep -v "culibos" | grep -v "cudart" | grep -v "cudnn" | grep -v "cublas" | grep -v "metis"  \
+      | xargs -I {} bash -c \
+                "echo {} && $NVPRUNE $GENCODE $CUDA_LIB_DIR/{} -o $CUDA_LIB_DIR/{}"
 
-  CUDA_VERSION=12.9 bash install_cusparselt.sh
+    # prune CuDNN and CuBLAS
+    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublas_static.a -o $CUDA_LIB_DIR/libcublas_static.a
+    $NVPRUNE $GENCODE_CUDNN $CUDA_LIB_DIR/libcublasLt_static.a -o $CUDA_LIB_DIR/libcublasLt_static.a
 
-  ldconfig
+    #####################################################################################
+    # CUDA 11.8 prune visual tools
+    #####################################################################################
+    export CUDA_BASE="/usr/local/cuda-11.8/"
+    rm -rf $CUDA_BASE/libnvvp $CUDA_BASE/nsightee_plugins $CUDA_BASE/nsight-compute-2022.3.0 $CUDA_BASE/nsight-systems-2022.4.2/
 }
 
 function prune_124 {
@@ -196,18 +218,27 @@ function prune_126 {
 
 function install_128 {
   CUDNN_VERSION=9.8.0.87
-  echo "Installing CUDA 12.8.1 and cuDNN ${CUDNN_VERSION} and NVSHMEM and NCCL and cuSparseLt-0.7.1"
-  # install CUDA 12.8.1 in the same container
-  install_cuda 12.8.1 cuda_12.8.1_570.124.06_linux
+  echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
+  rm -rf /usr/local/cuda-12.8 /usr/local/cuda
+  # install CUDA 12.8.0 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux.run
+  chmod +x cuda_12.8.0_570.86.10_linux.run
+  ./cuda_12.8.0_570.86.10_linux.run --toolkit --silent
+  rm -f cuda_12.8.0_570.86.10_linux.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.8 /usr/local/cuda
 
   # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
-  install_cudnn 12 $CUDNN_VERSION
-
-  install_nvshmem 12 $NVSHMEM_VERSION
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-x86_64/cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-x86_64-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
 
   CUDA_VERSION=12.8 bash install_nccl.sh
 
-  CUDA_VERSION=12.8 bash install_cusparselt.sh
+  install_cusparselt_063
 
   ldconfig
 }
@@ -216,13 +247,13 @@ function install_128 {
 while test $# -gt 0
 do
     case "$1" in
+    11.8) install_118; prune_118
+        ;;
     12.4) install_124; prune_124
         ;;
-    12.6|12.6.*) install_126; prune_126
+    12.6) install_126; prune_126
         ;;
-    12.8|12.8.*) install_128;
-        ;;
-    12.9|12.9.*) install_129;
+    12.8) install_128;
         ;;
     *) echo "bad argument $1"; exit 1
         ;;

.ci/docker/common/install_cuda_aarch64.sh

@@ -0,0 +1,55 @@
+#!/bin/bash
+# Script used only in CD pipeline
+
+set -ex
+
+CUDNN_VERSION=9.8.0.87
+
+function install_cusparselt_063 {
+    # cuSparseLt license: https://docs.nvidia.com/cuda/cusparselt/license.html
+    mkdir tmp_cusparselt && pushd tmp_cusparselt
+    wget -q https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-sbsa/libcusparse_lt-linux-sbsa-0.6.3.2-archive.tar.xz
+    tar xf libcusparse_lt-linux-sbsa-0.6.3.2-archive.tar.xz
+    cp -a libcusparse_lt-linux-sbsa-0.6.3.2-archive/include/* /usr/local/cuda/include/
+    cp -a libcusparse_lt-linux-sbsa-0.6.3.2-archive/lib/* /usr/local/cuda/lib64/
+    popd
+    rm -rf tmp_cusparselt
+}
+
+function install_128 {
+  echo "Installing CUDA 12.8.0 and cuDNN ${CUDNN_VERSION} and NCCL and cuSparseLt-0.6.3"
+  rm -rf /usr/local/cuda-12.8 /usr/local/cuda
+  # install CUDA 12.8.0 in the same container
+  wget -q https://developer.download.nvidia.com/compute/cuda/12.8.0/local_installers/cuda_12.8.0_570.86.10_linux_sbsa.run
+  chmod +x cuda_12.8.0_570.86.10_linux_sbsa.run
+  ./cuda_12.8.0_570.86.10_linux_sbsa.run --toolkit --silent
+  rm -f cuda_12.8.0_570.86.10_linux_sbsa.run
+  rm -f /usr/local/cuda && ln -s /usr/local/cuda-12.8 /usr/local/cuda
+
+  # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
+  mkdir tmp_cudnn && cd tmp_cudnn
+  wget -q https://developer.download.nvidia.com/compute/cudnn/redist/cudnn/linux-sbsa/cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz -O cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  tar xf cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive.tar.xz
+  cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/include/* /usr/local/cuda/include/
+  cp -a cudnn-linux-sbsa-${CUDNN_VERSION}_cuda12-archive/lib/* /usr/local/cuda/lib64/
+  cd ..
+  rm -rf tmp_cudnn
+
+  CUDA_VERSION=12.8 bash install_nccl.sh
+
+  install_cusparselt_063
+
+  ldconfig
+}
+
+# idiomatic parameter and option handling in sh
+while test $# -gt 0
+do
+    case "$1" in
+    12.8) install_128;
+        ;;
+    *) echo "bad argument $1"; exit 1
+        ;;
+    esac
+    shift
+done

.ci/docker/common/install_cudnn.sh

@@ -4,12 +4,12 @@ if [[ -n "${CUDNN_VERSION}" ]]; then
     # cuDNN license: https://developer.nvidia.com/cudnn/license_agreement
     mkdir tmp_cudnn
     pushd tmp_cudnn
-    if [[ ${CUDA_VERSION:0:4} == "12.9" || ${CUDA_VERSION:0:4} == "12.8" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-9.10.2.21_cuda12-archive"
+    if [[ ${CUDA_VERSION:0:4} == "12.8" ]]; then
+        CUDNN_NAME="cudnn-linux-x86_64-9.8.0.87_cuda12-archive"
     elif [[ ${CUDA_VERSION:0:4} == "12.6" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-9.10.2.21_cuda12-archive"
-    elif [[ ${CUDA_VERSION:0:4} == "12.4" ]]; then
-        CUDNN_NAME="cudnn-linux-x86_64-9.10.2.21_cuda12-archive"
+        CUDNN_NAME="cudnn-linux-x86_64-9.5.1.17_cuda12-archive"
+    elif [[ ${CUDA_VERSION:0:2} == "12" ]]; then
+        CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda12-archive"
     elif [[ ${CUDA_VERSION:0:2} == "11" ]]; then
         CUDNN_NAME="cudnn-linux-x86_64-9.1.0.70_cuda11-archive"
     else

.ci/docker/common/install_cusparselt.sh

@@ -5,13 +5,13 @@ set -ex
 # cuSPARSELt license: https://docs.nvidia.com/cuda/cusparselt/license.html
 mkdir tmp_cusparselt && cd tmp_cusparselt
 
-if [[ ${CUDA_VERSION:0:4} =~ ^12\.[5-9]$ ]]; then
+if [[ ${CUDA_VERSION:0:4} =~ ^12\.[5-8]$ ]]; then
     arch_path='sbsa'
     export TARGETARCH=${TARGETARCH:-$(uname -m)}
     if [ ${TARGETARCH} = 'amd64' ] || [ "${TARGETARCH}" = 'x86_64' ]; then
         arch_path='x86_64'
     fi
-    CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.7.1.0-archive"
+    CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.3.2-archive"
     curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
 elif [[ ${CUDA_VERSION:0:4} == "12.4" ]]; then
     arch_path='sbsa'
@@ -21,6 +21,9 @@ elif [[ ${CUDA_VERSION:0:4} == "12.4" ]]; then
     fi
     CUSPARSELT_NAME="libcusparse_lt-linux-${arch_path}-0.6.2.3-archive"
     curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-${arch_path}/${CUSPARSELT_NAME}.tar.xz
+elif [[ ${CUDA_VERSION:0:4} == "11.8" ]]; then
+    CUSPARSELT_NAME="libcusparse_lt-linux-x86_64-0.4.0.7-archive"
+    curl --retry 3 -OLs https://developer.download.nvidia.com/compute/cusparselt/redist/libcusparse_lt/linux-x86_64/${CUSPARSELT_NAME}.tar.xz
 else
     echo "Not sure which libcusparselt version to install for this ${CUDA_VERSION}"
 fi

.ci/docker/common/install_executorch.sh

@@ -13,7 +13,7 @@ clone_executorch() {
   # and fetch the target commit
   pushd executorch
   git checkout "${EXECUTORCH_PINNED_COMMIT}"
-  git submodule update --init --recursive
+  git submodule update --init
   popd
 
   chown -R jenkins executorch

.ci/docker/common/install_halide.sh

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

.ci/docker/common/install_inductor_benchmark_deps.sh

@@ -14,9 +14,16 @@ function install_timm() {
   local commit
   commit=$(get_pinned_commit timm)
 
+  # TODO (huydhn): There is no torchvision release on 3.13 when I write this, so
+  # I'm using nightly here instead. We just need to package to be able to install
+  # TIMM. Removing this once vision has a release on 3.13
+  if [[ "${ANACONDA_PYTHON_VERSION}" == "3.13" ]]; then
+    pip_install --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu124
+  fi
+
   pip_install "git+https://github.com/huggingface/pytorch-image-models@${commit}"
   # Clean up
-  conda_run pip uninstall -y torch torchvision triton
+  conda_run pip uninstall -y cmake torch torchvision triton
 }
 
 # Pango is needed for weasyprint which is needed for doctr

.ci/docker/common/install_magma_conda.sh

@@ -1,23 +1,26 @@
 #!/usr/bin/env bash
-# Script that installs magma from tarball inside conda environment.
-# It replaces anaconda magma-cuda package which is no longer published.
-# Execute it inside active conda environment.
-# See issue: https://github.com/pytorch/pytorch/issues/138506
+# Script that replaces the magma install from a conda package
 
 set -eou pipefail
 
-cuda_version_nodot=${1/./}
-anaconda_dir=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
+function do_install() {
+    cuda_version_nodot=${1/./}
+    anaconda_python_version=$2
 
-MAGMA_VERSION="2.6.1"
-magma_archive="magma-cuda${cuda_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
-(
-    set -x
-    tmp_dir=$(mktemp -d)
-    pushd ${tmp_dir}
-    curl -OLs https://ossci-linux.s3.us-east-1.amazonaws.com/${magma_archive}
-    tar -xvf "${magma_archive}"
-    mv include/* "${anaconda_dir}/include/"
-    mv lib/* "${anaconda_dir}/lib"
-    popd
-)
+    MAGMA_VERSION="2.6.1"
+    magma_archive="magma-cuda${cuda_version_nodot}-${MAGMA_VERSION}-1.tar.bz2"
+
+    anaconda_dir="/opt/conda/envs/py_${anaconda_python_version}"
+    (
+        set -x
+        tmp_dir=$(mktemp -d)
+        pushd ${tmp_dir}
+        curl -OLs https://ossci-linux.s3.us-east-1.amazonaws.com/${magma_archive}
+        tar -xvf "${magma_archive}"
+        mv include/* "${anaconda_dir}/include/"
+        mv lib/* "${anaconda_dir}/lib"
+        popd
+    )
+}
+
+do_install $1 $2

.ci/docker/common/install_onnx.sh

@@ -8,6 +8,16 @@ retry () {
     "$@" || (sleep 10 && "$@") || (sleep 20 && "$@") || (sleep 40 && "$@")
 }
 
+# A bunch of custom pip dependencies for ONNX
+pip_install \
+  beartype==0.15.0 \
+  filelock==3.9.0 \
+  flatbuffers==2.0 \
+  mock==5.0.1 \
+  ninja==1.10.2 \
+  networkx==2.5 \
+  numpy==1.24.2
+
 # ONNXRuntime should be installed before installing
 # onnx-weekly. Otherwise, onnx-weekly could be
 # overwritten by onnx.
@@ -19,8 +29,12 @@ pip_install \
   transformers==4.36.2
 
 pip_install coloredlogs packaging
+
 pip_install onnxruntime==1.18.1
-pip_install onnxscript==0.3.1
+pip_install onnx==1.17.0
+pip_install onnxscript==0.2.2 --no-deps
+# required by onnxscript
+pip_install ml_dtypes
 
 # Cache the transformers model to be used later by ONNX tests. We need to run the transformers
 # package to download the model. By default, the model is cached at ~/.cache/huggingface/hub/

.ci/docker/common/install_openblas.sh

@@ -4,9 +4,9 @@
 set -ex
 
 cd /
-git clone https://github.com/OpenMathLib/OpenBLAS.git -b "${OPENBLAS_VERSION:-v0.3.30}" --depth 1 --shallow-submodules
+git clone https://github.com/OpenMathLib/OpenBLAS.git -b v0.3.29 --depth 1 --shallow-submodules
+
 
-OPENBLAS_CHECKOUT_DIR="OpenBLAS"
 OPENBLAS_BUILD_FLAGS="
 NUM_THREADS=128
 USE_OPENMP=1
@@ -14,8 +14,9 @@ NO_SHARED=0
 DYNAMIC_ARCH=1
 TARGET=ARMV8
 CFLAGS=-O3
-BUILD_BFLOAT16=1
 "
 
+OPENBLAS_CHECKOUT_DIR="OpenBLAS"
+
 make -j8 ${OPENBLAS_BUILD_FLAGS} -C ${OPENBLAS_CHECKOUT_DIR}
 make -j8 ${OPENBLAS_BUILD_FLAGS} install -C ${OPENBLAS_CHECKOUT_DIR}

.ci/docker/common/install_protobuf.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+
+set -ex
+
+pb_dir="/usr/temp_pb_install_dir"
+mkdir -p $pb_dir
+
+# On the nvidia/cuda:9-cudnn7-devel-centos7 image we need this symlink or
+# else it will fail with
+#   g++: error: ./../lib64/crti.o: No such file or directory
+ln -s /usr/lib64 "$pb_dir/lib64"
+
+curl -LO "https://github.com/protocolbuffers/protobuf/releases/download/v3.17.3/protobuf-all-3.17.3.tar.gz" --retry 3
+
+tar -xvz --no-same-owner -C "$pb_dir" --strip-components 1 -f protobuf-all-3.17.3.tar.gz
+NPROC=$[$(nproc) - 2]
+pushd "$pb_dir" && ./configure && make -j${NPROC} && make -j${NPROC} check && sudo make -j${NRPOC} install && sudo ldconfig
+popd
+rm -rf $pb_dir

.ci/docker/common/install_python.sh

@@ -13,3 +13,6 @@ source /var/lib/jenkins/ci_env/bin/activate
 
 python -mpip install --upgrade pip
 python -mpip install -r /opt/requirements-ci.txt
+if [ -n "${PIP_CMAKE}" ]; then
+  python -mpip install cmake==3.31.6
+fi

.ci/docker/common/install_rocm.sh

@@ -8,11 +8,9 @@ ver() {
 
 install_ubuntu() {
     apt-get update
-    # gpg-agent is not available by default
-    apt-get install -y --no-install-recommends gpg-agent
-    if [[ $(ver $UBUNTU_VERSION) -ge $(ver 22.04) ]]; then
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' \
-            | sudo tee /etc/apt/preferences.d/rocm-pin-600
+    if [[ $UBUNTU_VERSION == 20.04 ]]; then
+      # gpg-agent is not available by default on 20.04
+      apt-get install -y --no-install-recommends gpg-agent
     fi
     apt-get install -y kmod
     apt-get install -y wget
@@ -28,11 +26,6 @@ Pin: release o=repo.radeon.com
 Pin-Priority: 600
 EOF
 
-    # we want the patch version of 6.4 instead
-    if [[ $(ver $ROCM_VERSION) -eq $(ver 6.4) ]]; then
-        ROCM_VERSION="${ROCM_VERSION}.1"
-    fi
-
     # Add amdgpu repository
     UBUNTU_VERSION_NAME=`cat /etc/os-release | grep UBUNTU_CODENAME | awk -F= '{print $2}'`
     echo "deb [arch=amd64] https://repo.radeon.com/amdgpu/${ROCM_VERSION}/ubuntu ${UBUNTU_VERSION_NAME} main" > /etc/apt/sources.list.d/amdgpu.list
@@ -73,30 +66,17 @@ EOF
     done
 
     # ROCm 6.3 had a regression where initializing static code objects had significant overhead
-    # ROCm 6.4 did not yet fix the regression, also HIP branch names are different
-    if [[ $(ver $ROCM_VERSION) -ge $(ver 6.3) ]] && [[ $(ver $ROCM_VERSION) -lt $(ver 7.0) ]]; then
-        if [[ $(ver $ROCM_VERSION) -eq $(ver 6.4.1) ]]; then
-            HIP_BRANCH=release/rocm-rel-6.4
-            VER_STR=6.4
-            VER_PATCH=.1
-        elif [[ $(ver $ROCM_VERSION) -eq $(ver 6.4) ]]; then
-            HIP_BRANCH=release/rocm-rel-6.4
-            VER_STR=6.4
-        elif [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]]; then
-            HIP_BRANCH=rocm-6.3.x
-            VER_STR=6.3
-        fi
+    if [[ $(ver $ROCM_VERSION) -eq $(ver 6.3) ]]; then
         # clr build needs CppHeaderParser but can only find it using conda's python
-        python -m pip install CppHeaderParser
-        git clone https://github.com/ROCm/HIP -b $HIP_BRANCH
+        /opt/conda/bin/python -m pip install CppHeaderParser
+        git clone https://github.com/ROCm/HIP -b rocm-6.3.x
         HIP_COMMON_DIR=$(readlink -f HIP)
-        git clone https://github.com/jeffdaily/clr -b release/rocm-rel-${VER_STR}${VER_PATCH}-statco-hotfix
+        git clone https://github.com/jeffdaily/clr -b release/rocm-rel-6.3-statco-hotfix
         mkdir -p clr/build
         pushd clr/build
-        # Need to point CMake to the correct python installation to find CppHeaderParser
-        cmake .. -DPython3_EXECUTABLE=/opt/conda/envs/py_${ANACONDA_PYTHON_VERSION}/bin/python3 -DCLR_BUILD_HIP=ON -DHIP_COMMON_DIR=$HIP_COMMON_DIR
+        cmake .. -DCLR_BUILD_HIP=ON -DHIP_COMMON_DIR=$HIP_COMMON_DIR
         make -j
-        cp hipamd/lib/libamdhip64.so.${VER_STR}.* /opt/rocm/lib/libamdhip64.so.${VER_STR}.*
+        cp hipamd/lib/libamdhip64.so.6.3.* /opt/rocm/lib/libamdhip64.so.6.3.*
         popd
         rm -rf HIP clr
     fi

.ci/docker/common/install_rocm_magma.sh

@@ -5,12 +5,7 @@ set -eou pipefail
 
 function do_install() {
     rocm_version=$1
-    if [[ ${rocm_version} =~ ^[0-9]+\.[0-9]+\.[0-9]+$ ]]; then
-        # chop off any patch version
-        rocm_version="${rocm_version%.*}"
-    fi
-
-    rocm_version_nodot=${rocm_version//./}
+    rocm_version_nodot=${1//./}
 
     # Version 2.7.2 + ROCm related updates
     MAGMA_VERSION=a1625ff4d9bc362906bd01f805dbbe12612953f6

.ci/docker/common/install_triton.sh

@@ -10,8 +10,12 @@ fi
 
 source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
 
-get_pip_version() {
-  conda_run pip list | grep -w $* | head -n 1 | awk '{print $2}'
+get_conda_version() {
+  as_jenkins conda list -n py_$ANACONDA_PYTHON_VERSION | grep -w $* | head -n 1 | awk '{print $2}'
+}
+
+conda_reinstall() {
+  as_jenkins conda install -q -n py_$ANACONDA_PYTHON_VERSION -y --force-reinstall $*
 }
 
 if [ -n "${XPU_VERSION}" ]; then
@@ -33,9 +37,11 @@ if [ -n "${UBUNTU_VERSION}" ];then
     apt-get install -y gpg-agent
 fi
 
-# Keep the current cmake and numpy version here, so we can reinstall them later
-CMAKE_VERSION=$(get_pip_version cmake)
-NUMPY_VERSION=$(get_pip_version numpy)
+if [ -n "${CONDA_CMAKE}" ]; then
+  # Keep the current cmake and numpy version here, so we can reinstall them later
+  CMAKE_VERSION=$(get_conda_version cmake)
+  NUMPY_VERSION=$(get_conda_version numpy)
+fi
 
 if [ -z "${MAX_JOBS}" ]; then
     export MAX_JOBS=$(nproc)
@@ -51,12 +57,7 @@ as_jenkins git clone --recursive ${TRITON_REPO} triton
 cd triton
 as_jenkins git checkout ${TRITON_PINNED_COMMIT}
 as_jenkins git submodule update --init --recursive
-
-# Old versions of python have setup.py in ./python; newer versions have it in ./
-if [ ! -f setup.py ]; then
-  cd python
-fi
-
+cd python
 pip_install pybind11==2.13.6
 
 # TODO: remove patch setup.py once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
@@ -82,26 +83,17 @@ cp dist/*.whl /opt/triton
 # Install the wheel for docker builds that don't use multi stage
 pip_install dist/*.whl
 
-# TODO: This is to make sure that the same cmake and numpy version from install conda
-# script is used. Without this step, the newer cmake version (3.25.2) downloaded by
-# triton build step via pip will fail to detect conda MKL. Once that issue is fixed,
-# this can be removed.
-#
-# The correct numpy version also needs to be set here because conda claims that it
-# causes inconsistent environment.  Without this, conda will attempt to install the
-# latest numpy version, which fails ASAN tests with the following import error: Numba
-# needs NumPy 1.20 or less.
-# Note that we install numpy with pip as conda might not have the version we want
-if [ -n "${CMAKE_VERSION}" ]; then
-  pip_install "cmake==${CMAKE_VERSION}"
-fi
-if [ -n "${NUMPY_VERSION}" ]; then
-  pip_install "numpy==${NUMPY_VERSION}"
-fi
-
-# IMPORTANT: helion needs to be installed without dependencies.
-# It depends on torch and triton. We don't want to install
-# triton and torch from production on Docker CI images
-if [[ "$ANACONDA_PYTHON_VERSION" != 3.9* ]]; then
-  pip_install helion --no-deps
+if [ -n "${CONDA_CMAKE}" ]; then
+  # TODO: This is to make sure that the same cmake and numpy version from install conda
+  # script is used. Without this step, the newer cmake version (3.25.2) downloaded by
+  # triton build step via pip will fail to detect conda MKL. Once that issue is fixed,
+  # this can be removed.
+  #
+  # The correct numpy version also needs to be set here because conda claims that it
+  # causes inconsistent environment.  Without this, conda will attempt to install the
+  # latest numpy version, which fails ASAN tests with the following import error: Numba
+  # needs NumPy 1.20 or less.
+  conda_reinstall cmake="${CMAKE_VERSION}"
+  # Note that we install numpy with pip as conda might not have the version we want
+  pip_install --force-reinstall numpy=="${NUMPY_VERSION}"
 fi

.ci/docker/common/install_xpu.sh

@@ -26,7 +26,7 @@ function install_ubuntu() {
     wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB \
         | gpg --dearmor > /usr/share/keyrings/oneapi-archive-keyring.gpg.gpg
     echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg.gpg] \
-        https://apt.repos.intel.com/oneapi all main" \
+        https://apt.repos.intel.com/${XPU_REPO_NAME} all main" \
         | tee /etc/apt/sources.list.d/oneAPI.list
 
     # Update the packages list and repository index
@@ -56,10 +56,14 @@ function install_ubuntu() {
 
 function install_rhel() {
     . /etc/os-release
-
-    if [[ ! " 8.8 8.10 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
-        echo "RHEL version ${VERSION_ID} not supported"
-        exit
+    if [[ "${ID}" == "rhel" ]]; then
+        if [[ ! " 8.8 8.9 9.0 9.2 9.3 " =~ " ${VERSION_ID} " ]]; then
+            echo "RHEL version ${VERSION_ID} not supported"
+            exit
+        fi
+    elif [[ "${ID}" == "almalinux" ]]; then
+        # Workaround for almalinux8 which used by quay.io/pypa/manylinux_2_28_x86_64
+        VERSION_ID="8.8"
     fi
 
     dnf install -y 'dnf-command(config-manager)'
@@ -70,7 +74,7 @@ function install_rhel() {
     tee > /etc/yum.repos.d/oneAPI.repo << EOF
 [oneAPI]
 name=Intel for Pytorch GPU dev repository
-baseurl=https://yum.repos.intel.com/oneapi
+baseurl=https://yum.repos.intel.com/${XPU_REPO_NAME}
 enabled=1
 gpgcheck=1
 repo_gpgcheck=1
@@ -114,7 +118,7 @@ function install_sles() {
         https://repositories.intel.com/gpu/sles/${VERSION_SP}${XPU_DRIVER_VERSION}/unified/intel-gpu-${VERSION_SP}.repo
     rpm --import https://repositories.intel.com/gpu/intel-graphics.key
     # To add the online network network package repository for the Intel Support Packages
-    zypper addrepo https://yum.repos.intel.com/oneapi oneAPI
+    zypper addrepo https://yum.repos.intel.com/${XPU_REPO_NAME} oneAPI
     rpm --import https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
 
     # The xpu-smi packages
@@ -137,10 +141,10 @@ if [[ "${XPU_DRIVER_TYPE,,}" == "rolling" ]]; then
     XPU_DRIVER_VERSION=""
 fi
 
-# Default use Intel® oneAPI Deep Learning Essentials 2025.0
-if [[ "$XPU_VERSION" == "2025.1" ]]; then
-    XPU_PACKAGES="intel-deep-learning-essentials-2025.1"
-else
+XPU_REPO_NAME="intel-for-pytorch-gpu-dev"
+XPU_PACKAGES="intel-for-pytorch-gpu-dev-0.5 intel-pti-dev-0.9"
+if [[ "$XPU_VERSION" == "2025.0" ]]; then
+    XPU_REPO_NAME="oneapi"
     XPU_PACKAGES="intel-deep-learning-essentials-2025.0"
 fi
 

.ci/docker/libtorch/Dockerfile

@@ -51,9 +51,18 @@ ADD ./common/install_cuda.sh install_cuda.sh
 ADD ./common/install_magma.sh install_magma.sh
 COPY ./common/install_nccl.sh install_nccl.sh
 COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
 ENV CUDA_HOME /usr/local/cuda
 
+FROM cuda as cuda11.8
+RUN bash ./install_cuda.sh 11.8
+RUN bash ./install_magma.sh 11.8
+RUN ln -sf /usr/local/cuda-11.8 /usr/local/cuda
+
+FROM cuda as cuda12.4
+RUN bash ./install_cuda.sh 12.4
+RUN bash ./install_magma.sh 12.4
+RUN ln -sf /usr/local/cuda-12.4 /usr/local/cuda
+
 FROM cuda as cuda12.6
 RUN bash ./install_cuda.sh 12.6
 RUN bash ./install_magma.sh 12.6
@@ -64,11 +73,6 @@ RUN bash ./install_cuda.sh 12.8
 RUN bash ./install_magma.sh 12.8
 RUN ln -sf /usr/local/cuda-12.8 /usr/local/cuda
 
-FROM cuda as cuda12.9
-RUN bash ./install_cuda.sh 12.9
-RUN bash ./install_magma.sh 12.9
-RUN ln -sf /usr/local/cuda-12.9 /usr/local/cuda
-
 FROM cpu as rocm
 ARG ROCM_VERSION
 ARG PYTORCH_ROCM_ARCH

.ci/docker/libtorch/build.sh

@@ -39,10 +39,6 @@ case ${DOCKER_TAG_PREFIX} in
         DOCKER_GPU_BUILD_ARG=""
         ;;
     rocm*)
-        # we want the patch version of 6.4 instead
-        if [[ $(ver $GPU_ARCH_VERSION) -eq $(ver 6.4) ]]; then
-            GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.1"
-        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"

.ci/docker/linter-cuda/Dockerfile

@@ -32,8 +32,7 @@ ARG CUDA_VERSION
 COPY ./common/install_cuda.sh install_cuda.sh
 COPY ./common/install_nccl.sh install_nccl.sh
 COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
-RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu*
 ENV DESIRED_CUDA ${CUDA_VERSION}
 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH
 

.ci/docker/linter/Dockerfile

@@ -16,6 +16,7 @@ RUN bash ./install_user.sh && rm install_user.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
 ARG PYTHON_VERSION
+ARG PIP_CMAKE
 ENV PATH /var/lib/jenkins/ci_env/bin:$PATH
 ENV VIRTUAL_ENV /var/lib/jenkins/ci_env
 COPY requirements-ci.txt /opt/requirements-ci.txt
@@ -27,7 +28,5 @@ COPY ./common/install_linter.sh install_linter.sh
 RUN bash ./install_linter.sh
 RUN rm install_linter.sh
 
-RUN chown -R jenkins:jenkins /var/lib/jenkins/ci_env
-
 USER jenkins
 CMD ["bash"]

.ci/docker/manywheel/Dockerfile

@@ -0,0 +1,202 @@
+# syntax = docker/dockerfile:experimental
+ARG ROCM_VERSION=3.7
+ARG BASE_CUDA_VERSION=11.8
+
+ARG GPU_IMAGE=centos:7
+FROM centos:7 as base
+
+ENV LC_ALL en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US.UTF-8
+
+ARG DEVTOOLSET_VERSION=9
+
+# Note: This is required patch since CentOS have reached EOL
+# otherwise any yum install setp will fail
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+RUN yum install -y wget curl perl util-linux xz bzip2 git patch which perl zlib-devel
+# Just add everything as a safe.directory for git since these will be used in multiple places with git
+RUN git config --global --add safe.directory '*'
+RUN yum install -y yum-utils centos-release-scl
+RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
+# Note: After running yum-config-manager --enable rhel-server-rhscl-7-rpms
+# patch is required once again. Somehow this steps adds mirror.centos.org
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
+ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
+ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
+
+RUN yum --enablerepo=extras install -y epel-release
+
+# cmake-3.18.4 from pip
+RUN yum install -y python3-pip && \
+    python3 -mpip install cmake==3.18.4 && \
+    ln -s /usr/local/bin/cmake /usr/bin/cmake
+
+RUN yum install -y autoconf aclocal automake make sudo
+
+FROM base as openssl
+# Install openssl (this must precede `build python` step)
+# (In order to have a proper SSL module, Python is compiled
+# against a recent openssl [see env vars above], which is linked
+# statically. We delete openssl afterwards.)
+ADD ./common/install_openssl.sh install_openssl.sh
+RUN bash ./install_openssl.sh && rm install_openssl.sh
+
+# EPEL for cmake
+FROM base as patchelf
+# Install patchelf
+ADD ./common/install_patchelf.sh install_patchelf.sh
+RUN bash ./install_patchelf.sh && rm install_patchelf.sh
+RUN cp $(which patchelf) /patchelf
+
+FROM patchelf as python
+# build python
+COPY manywheel/build_scripts /build_scripts
+ADD ./common/install_cpython.sh /build_scripts/install_cpython.sh
+RUN bash build_scripts/build.sh && rm -r build_scripts
+
+FROM base as cuda
+ARG BASE_CUDA_VERSION=10.2
+# Install CUDA
+ADD ./common/install_cuda.sh install_cuda.sh
+COPY ./common/install_nccl.sh install_nccl.sh
+COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
+RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu*
+
+FROM base as intel
+# MKL
+ADD ./common/install_mkl.sh install_mkl.sh
+RUN bash ./install_mkl.sh && rm install_mkl.sh
+
+FROM base as magma
+ARG BASE_CUDA_VERSION=10.2
+# Install magma
+ADD ./common/install_magma.sh install_magma.sh
+RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
+
+FROM base as jni
+# Install java jni header
+ADD ./common/install_jni.sh install_jni.sh
+ADD ./java/jni.h jni.h
+RUN bash ./install_jni.sh && rm install_jni.sh
+
+FROM base as libpng
+# Install libpng
+ADD ./common/install_libpng.sh install_libpng.sh
+RUN bash ./install_libpng.sh && rm install_libpng.sh
+
+FROM ${GPU_IMAGE} as common
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+ENV LC_ALL en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US.UTF-8
+RUN yum install -y \
+        aclocal \
+        autoconf \
+        automake \
+        bison \
+        bzip2 \
+        curl \
+        diffutils \
+        file \
+        git \
+        make \
+        patch \
+        perl \
+        unzip \
+        util-linux \
+        wget \
+        which \
+        xz \
+        yasm
+RUN yum install -y \
+    https://repo.ius.io/ius-release-el7.rpm \
+    https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
+
+RUN yum swap -y git git236-core
+# git236+ would refuse to run git commands in repos owned by other users
+# Which causes version check to fail, as pytorch repo is bind-mounted into the image
+# Override this behaviour by treating every folder as safe
+# For more details see https://github.com/pytorch/pytorch/issues/78659#issuecomment-1144107327
+RUN git config --global --add safe.directory "*"
+
+ENV SSL_CERT_FILE=/opt/_internal/certs.pem
+# Install LLVM version
+COPY --from=openssl            /opt/openssl                          /opt/openssl
+COPY --from=python             /opt/python                           /opt/python
+COPY --from=python             /opt/_internal                        /opt/_internal
+COPY --from=python             /opt/python/cp39-cp39/bin/auditwheel /usr/local/bin/auditwheel
+COPY --from=intel              /opt/intel                            /opt/intel
+COPY --from=patchelf           /usr/local/bin/patchelf               /usr/local/bin/patchelf
+COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
+COPY --from=libpng             /usr/local/bin/png*                   /usr/local/bin/
+COPY --from=libpng             /usr/local/bin/libpng*                /usr/local/bin/
+COPY --from=libpng             /usr/local/include/png*               /usr/local/include/
+COPY --from=libpng             /usr/local/include/libpng*            /usr/local/include/
+COPY --from=libpng             /usr/local/lib/libpng*                /usr/local/lib/
+COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/lib/pkgconfig
+
+FROM common as cpu_final
+ARG BASE_CUDA_VERSION=10.1
+ARG DEVTOOLSET_VERSION=9
+# Install Anaconda
+ADD ./common/install_conda_docker.sh install_conda.sh
+RUN bash ./install_conda.sh && rm install_conda.sh
+ENV PATH /opt/conda/bin:$PATH
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+
+RUN yum install -y yum-utils centos-release-scl
+RUN yum-config-manager --enable rhel-server-rhscl-7-rpms
+RUN sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
+RUN sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
+RUN yum install -y devtoolset-${DEVTOOLSET_VERSION}-gcc devtoolset-${DEVTOOLSET_VERSION}-gcc-c++ devtoolset-${DEVTOOLSET_VERSION}-gcc-gfortran devtoolset-${DEVTOOLSET_VERSION}-binutils
+ENV PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
+ENV LD_LIBRARY_PATH=/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/devtoolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
+
+# cmake is already installed inside the rocm base image, so remove if present
+RUN rpm -e cmake || true
+# cmake-3.18.4 from pip
+RUN yum install -y python3-pip && \
+    python3 -mpip install cmake==3.18.4 && \
+    ln -s /usr/local/bin/cmake /usr/bin/cmake
+
+# ninja
+RUN yum install -y ninja-build
+
+FROM cpu_final as cuda_final
+RUN rm -rf /usr/local/cuda-${BASE_CUDA_VERSION}
+COPY --from=cuda     /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
+COPY --from=magma    /usr/local/cuda-${BASE_CUDA_VERSION}  /usr/local/cuda-${BASE_CUDA_VERSION}
+RUN ln -sf /usr/local/cuda-${BASE_CUDA_VERSION} /usr/local/cuda
+ENV PATH=/usr/local/cuda/bin:$PATH
+
+FROM cpu_final as rocm_final
+ARG ROCM_VERSION=3.7
+ARG PYTORCH_ROCM_ARCH
+ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}
+# Adding ROCM_PATH env var so that LoadHip.cmake (even with logic updated for ROCm6.0)
+# find HIP works for ROCm5.7. Not needed for ROCm6.0 and above.
+# Remove below when ROCm5.7 is not in support matrix anymore.
+ENV ROCM_PATH /opt/rocm
+ENV MKLROOT /opt/intel
+# No need to install ROCm as base docker image should have full ROCm install
+#ADD ./common/install_rocm.sh install_rocm.sh
+#RUN ROCM_VERSION=${ROCM_VERSION} bash ./install_rocm.sh && rm install_rocm.sh
+ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
+RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
+# cmake3 is needed for the MIOpen build
+RUN ln -sf /usr/local/bin/cmake /usr/bin/cmake3
+ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
+RUN bash ./install_rocm_magma.sh ${ROCM_VERSION} && rm install_rocm_magma.sh
+ADD ./common/install_miopen.sh install_miopen.sh
+RUN bash ./install_miopen.sh ${ROCM_VERSION} && rm install_miopen.sh

.ci/docker/manywheel/Dockerfile_2_28

@@ -7,8 +7,8 @@ ENV LC_ALL en_US.UTF-8
 ENV LANG en_US.UTF-8
 ENV LANGUAGE en_US.UTF-8
 
-ARG DEVTOOLSET_VERSION=13
-RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel yum-utils gcc-toolset-${DEVTOOLSET_VERSION}-gcc gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran gcc-toolset-${DEVTOOLSET_VERSION}-gdb
+ARG DEVTOOLSET_VERSION=11
+RUN yum install -y sudo wget curl perl util-linux xz bzip2 git patch which perl zlib-devel yum-utils gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
 ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
 ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
 
@@ -26,20 +26,19 @@ ADD ./common/install_openssl.sh install_openssl.sh
 RUN bash ./install_openssl.sh && rm install_openssl.sh
 
 
-# remove unnecessary python versions
+# remove unncessary python versions
 RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
 RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
 RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
 RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
 
 FROM base as cuda
-ARG BASE_CUDA_VERSION=12.6
+ARG BASE_CUDA_VERSION=11.8
 # Install CUDA
 ADD ./common/install_cuda.sh install_cuda.sh
 COPY ./common/install_nccl.sh install_nccl.sh
 COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
-RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh ci_commit_pins/nccl-cu*
 
 FROM base as intel
 # MKL
@@ -47,7 +46,7 @@ ADD ./common/install_mkl.sh install_mkl.sh
 RUN bash ./install_mkl.sh && rm install_mkl.sh
 
 FROM base as magma
-ARG BASE_CUDA_VERSION=12.6
+ARG BASE_CUDA_VERSION=10.2
 # Install magma
 ADD ./common/install_magma.sh install_magma.sh
 RUN bash ./install_magma.sh ${BASE_CUDA_VERSION} && rm install_magma.sh
@@ -64,7 +63,7 @@ ADD ./common/install_libpng.sh install_libpng.sh
 RUN bash ./install_libpng.sh && rm install_libpng.sh
 
 FROM ${GPU_IMAGE} as common
-ARG DEVTOOLSET_VERSION=13
+ARG DEVTOOLSET_VERSION=11
 ENV LC_ALL en_US.UTF-8
 ENV LANG en_US.UTF-8
 ENV LANGUAGE en_US.UTF-8
@@ -87,12 +86,13 @@ RUN yum install -y \
         wget \
         which \
         xz \
-        glibc-langpack-en \
-        gcc-toolset-${DEVTOOLSET_VERSION}-gcc \
-        gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ \
-        gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
-        gcc-toolset-${DEVTOOLSET_VERSION}-gdb
+        gcc-toolset-${DEVTOOLSET_VERSION}-toolchain \
+        glibc-langpack-en
+RUN yum install -y \
+    https://repo.ius.io/ius-release-el7.rpm \
+    https://ossci-linux.s3.amazonaws.com/epel-release-7-14.noarch.rpm
 
+RUN yum swap -y git git236-core
 # git236+ would refuse to run git commands in repos owned by other users
 # Which causes version check to fail, as pytorch repo is bind-mounted into the image
 # Override this behaviour by treating every folder as safe
@@ -103,7 +103,6 @@ ENV SSL_CERT_FILE=/opt/_internal/certs.pem
 # Install LLVM version
 COPY --from=openssl            /opt/openssl                          /opt/openssl
 COPY --from=base               /opt/python                           /opt/python
-COPY --from=base               /usr/local/lib/                       /usr/local/lib/
 COPY --from=base               /opt/_internal                        /opt/_internal
 COPY --from=base               /usr/local/bin/auditwheel             /usr/local/bin/auditwheel
 COPY --from=intel              /opt/intel                            /opt/intel
@@ -117,8 +116,8 @@ COPY --from=libpng             /usr/local/lib/pkgconfig              /usr/local/
 COPY --from=jni                /usr/local/include/jni.h              /usr/local/include/jni.h
 
 FROM common as cpu_final
-ARG BASE_CUDA_VERSION=12.6
-ARG DEVTOOLSET_VERSION=13
+ARG BASE_CUDA_VERSION=11.8
+ARG DEVTOOLSET_VERSION=11
 # Install Anaconda
 ADD ./common/install_conda_docker.sh install_conda.sh
 RUN bash ./install_conda.sh && rm install_conda.sh
@@ -157,11 +156,8 @@ ENV ROCM_PATH /opt/rocm
 # and avoid 3.21.0 cmake+ninja issues with ninja inserting "-Wl,--no-as-needed" in LINK_FLAGS for static linker
 RUN python3 -m pip install --upgrade pip && \
     python3 -mpip install cmake==3.28.4
-# replace the libdrm in /opt/amdgpu with custom amdgpu.ids lookup path
 ADD ./common/install_rocm_drm.sh install_rocm_drm.sh
 RUN bash ./install_rocm_drm.sh && rm install_rocm_drm.sh
-# ROCm 6.4 rocm-smi depends on system drm.h header
-RUN yum install -y libdrm-devel
 ENV MKLROOT /opt/intel
 ADD ./common/install_rocm_magma.sh install_rocm_magma.sh
 RUN bash ./install_rocm_magma.sh ${ROCM_VERSION} && rm install_rocm_magma.sh
@@ -175,6 +171,6 @@ ENV XPU_DRIVER_TYPE ROLLING
 RUN python3 -m pip install --upgrade pip && \
     python3 -mpip install cmake==3.28.4
 ADD ./common/install_xpu.sh install_xpu.sh
-ENV XPU_VERSION 2025.1
+ENV XPU_VERSION 2025.0
 RUN bash ./install_xpu.sh && rm install_xpu.sh
 RUN pushd /opt/_internal && tar -xJf static-libs-for-embedding-only.tar.xz && popd

.ci/docker/manywheel/Dockerfile_2_28_aarch64

@@ -1,8 +1,9 @@
 FROM quay.io/pypa/manylinux_2_28_aarch64 as base
 
-ARG GCCTOOLSET_VERSION=13
+# Graviton needs GCC 10 or above for the build. GCC12 is the default version in almalinux-8.
+ARG GCCTOOLSET_VERSION=11
 
-# Language variables
+# Language variabes
 ENV LC_ALL=en_US.UTF-8
 ENV LANG=en_US.UTF-8
 ENV LANGUAGE=en_US.UTF-8
@@ -35,10 +36,7 @@ RUN yum install -y \
   yasm \
   zstd \
   sudo \
-  gcc-toolset-${GCCTOOLSET_VERSION}-gcc \
-  gcc-toolset-${GCCTOOLSET_VERSION}-gcc-c++ \
-  gcc-toolset-${GCCTOOLSET_VERSION}-gcc-gfortran \
-  gcc-toolset-${GCCTOOLSET_VERSION}-gdb
+  gcc-toolset-${GCCTOOLSET_VERSION}-toolchain
 
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
@@ -58,13 +56,12 @@ RUN git config --global --add safe.directory "*"
 
 FROM base as openblas
 # Install openblas
-ARG OPENBLAS_VERSION
 ADD ./common/install_openblas.sh install_openblas.sh
 RUN bash ./install_openblas.sh && rm install_openblas.sh
 
 FROM base as final
 
-# remove unnecessary python versions
+# remove unncessary python versions
 RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
 RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
 RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6

.ci/docker/manywheel/Dockerfile_aarch64

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

.ci/docker/manywheel/Dockerfile_cuda_aarch64

@@ -1,7 +1,7 @@
 FROM quay.io/pypa/manylinux_2_28_aarch64 as base
 
 # Cuda ARM build needs gcc 11
-ARG DEVTOOLSET_VERSION=13
+ARG DEVTOOLSET_VERSION=11
 
 # Language variables
 ENV LC_ALL=en_US.UTF-8
@@ -34,10 +34,7 @@ RUN yum install -y \
   zstd \
   libgomp \
   sudo \
-  gcc-toolset-${DEVTOOLSET_VERSION}-gcc \
-  gcc-toolset-${DEVTOOLSET_VERSION}-gcc-c++ \
-  gcc-toolset-${DEVTOOLSET_VERSION}-gcc-gfortran \
-  gcc-toolset-${DEVTOOLSET_VERSION}-gdb
+  gcc-toolset-${DEVTOOLSET_VERSION}-toolchain
 
 # Ensure the expected devtoolset is used
 ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
@@ -60,7 +57,7 @@ RUN bash ./install_openssl.sh && rm install_openssl.sh
 ENV SSL_CERT_FILE=/opt/_internal/certs.pem
 
 FROM openssl as final
-# remove unnecessary python versions
+# remove unncessary python versions
 RUN rm -rf /opt/python/cp26-cp26m /opt/_internal/cpython-2.6.9-ucs2
 RUN rm -rf /opt/python/cp26-cp26mu /opt/_internal/cpython-2.6.9-ucs4
 RUN rm -rf /opt/python/cp33-cp33m /opt/_internal/cpython-3.3.6
@@ -69,11 +66,10 @@ RUN rm -rf /opt/python/cp34-cp34m /opt/_internal/cpython-3.4.6
 FROM base as cuda
 ARG BASE_CUDA_VERSION
 # Install CUDA
-ADD ./common/install_cuda.sh install_cuda.sh
+ADD ./common/install_cuda_aarch64.sh install_cuda_aarch64.sh
 COPY ./common/install_nccl.sh install_nccl.sh
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
 COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-RUN bash ./install_cuda.sh ${BASE_CUDA_VERSION} && rm install_cuda.sh install_nccl.sh ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda_aarch64.sh ${BASE_CUDA_VERSION} && rm install_cuda_aarch64.sh install_nccl.sh ci_commit_pins/nccl-cu*
 
 FROM base as magma
 ARG BASE_CUDA_VERSION

.ci/docker/manywheel/Dockerfile_s390x

@@ -5,9 +5,7 @@ ENV LC_ALL=C.UTF-8
 ENV LANG=C.UTF-8
 ENV LANGUAGE=C.UTF-8
 
-# there is a bugfix in gcc >= 14 for precompiled headers and s390x vectorization interaction.
-# with earlier gcc versions test/inductor/test_cpu_cpp_wrapper.py will fail.
-ARG DEVTOOLSET_VERSION=14
+ARG DEVTOOLSET_VERSION=13
 # Installed needed OS packages. This is to support all
 # the binary builds (torch, vision, audio, text, data)
 RUN yum -y install epel-release
@@ -60,8 +58,7 @@ RUN yum install -y \
   libxslt-devel \
   libxml2-devel \
   openssl-devel \
-  valgrind \
-  ninja-build
+  valgrind
 
 ENV PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/bin:$PATH
 ENV LD_LIBRARY_PATH=/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib64:/opt/rh/gcc-toolset-${DEVTOOLSET_VERSION}/root/usr/lib:$LD_LIBRARY_PATH
@@ -106,6 +103,9 @@ CMD ["/bin/bash"]
 # install test dependencies:
 # - grpcio requires system openssl, bundled crypto fails to build
 RUN dnf install -y \
+  protobuf-devel \
+  protobuf-c-devel \
+  protobuf-lite-devel \
   hdf5-devel \
   python3-h5py \
   git
@@ -120,22 +120,15 @@ RUN python3 -mpip install cmake==3.28.0
 # so just build it from upstream repository.
 # h5py is dependency of onnxruntime_training.
 # h5py==3.11.0 builds with hdf5-devel 1.10.5 from repository.
-# h5py 3.11.0 doesn't build with numpy >= 2.3.0.
 # install newest flatbuffers version first:
 # for some reason old version is getting pulled in otherwise.
 # packaging package is required for onnxruntime wheel build.
 RUN pip3 install flatbuffers && \
-  pip3 install cython 'pkgconfig>=1.5.5' 'setuptools>=77' 'numpy<2.3.0' && \
-  pip3 install --no-build-isolation h5py==3.11.0 && \
+  pip3 install h5py==3.11.0 && \
   pip3 install packaging && \
   git clone https://github.com/microsoft/onnxruntime && \
   cd onnxruntime && git checkout v1.21.0 && \
   git submodule update --init --recursive && \
-  wget https://github.com/microsoft/onnxruntime/commit/f57db79743c4d1a3553aa05cf95bcd10966030e6.patch && \
-  patch -p1 < f57db79743c4d1a3553aa05cf95bcd10966030e6.patch && \
-  ./build.sh --config Release --parallel 0 --enable_pybind \
-  --build_wheel --enable_training --enable_training_apis \
-  --enable_training_ops --skip_tests --allow_running_as_root \
-  --compile_no_warning_as_error && \
+  ./build.sh --config Release --parallel 0 --enable_pybind --build_wheel --enable_training --enable_training_apis --enable_training_ops --skip_tests --allow_running_as_root && \
   pip3 install ./build/Linux/Release/dist/onnxruntime_training-*.whl && \
   cd .. && /bin/rm -rf ./onnxruntime

.ci/docker/manywheel/build.sh

@@ -27,21 +27,25 @@ fi
 
 MANY_LINUX_VERSION=${MANY_LINUX_VERSION:-}
 DOCKERFILE_SUFFIX=${DOCKERFILE_SUFFIX:-}
-OPENBLAS_VERSION=${OPENBLAS_VERSION:-}
 
 case ${image} in
     manylinux2_28-builder:cpu)
         TARGET=cpu_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"
         ;;
+    manylinuxaarch64-builder:cpu-aarch64)
+        TARGET=final
+        GPU_IMAGE=arm64v8/centos:7
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=10"
+        MANY_LINUX_VERSION="aarch64"
+        ;;
     manylinux2_28_aarch64-builder:cpu-aarch64)
         TARGET=final
         GPU_IMAGE=arm64v8/almalinux:8
-        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=13 --build-arg NINJA_VERSION=1.12.1"
+        DOCKER_GPU_BUILD_ARG=" --build-arg DEVTOOLSET_VERSION=11 --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
@@ -55,31 +59,23 @@ case ${image} in
         DOCKER_GPU_BUILD_ARG=""
         MANY_LINUX_VERSION="s390x"
         ;;
-    manylinux2_28-builder:cuda11*)
+    manylinux2_28-builder:cuda*)
         TARGET=cuda_final
         GPU_IMAGE=amd64/almalinux:8
         DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="2_28"
         ;;
-    manylinux2_28-builder:cuda12*)
-        TARGET=cuda_final
-        GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=13"
-        MANY_LINUX_VERSION="2_28"
-        ;;
     manylinuxaarch64-builder:cuda*)
         TARGET=cuda_final
-        GPU_IMAGE=amd64/almalinux:8
-        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=13"
+        GPU_IMAGE=arm64v8/centos:7
+        DOCKER_GPU_BUILD_ARG="--build-arg BASE_CUDA_VERSION=${GPU_ARCH_VERSION} --build-arg DEVTOOLSET_VERSION=11"
         MANY_LINUX_VERSION="aarch64"
         DOCKERFILE_SUFFIX="_cuda_aarch64"
         ;;
     manylinux2_28-builder:rocm*)
-        # we want the patch version of 6.4 instead
-        if [[ $(ver $GPU_ARCH_VERSION) -eq $(ver 6.4) ]]; then
-            GPU_ARCH_VERSION="${GPU_ARCH_VERSION}.1"
-        fi
         TARGET=rocm_final
+        GPU_IMAGE=rocm/dev-centos-7:${GPU_ARCH_VERSION}-complete
+        DEVTOOLSET_VERSION="9"
         MANY_LINUX_VERSION="2_28"
         DEVTOOLSET_VERSION="11"
         GPU_IMAGE=rocm/dev-almalinux-8:${GPU_ARCH_VERSION}-complete
@@ -115,7 +111,6 @@ 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=${OPENBLAS_VERSION}" \
     --target "${TARGET}" \
     -t "${tmp_tag}" \
     $@ \

.ci/docker/manywheel/build_scripts/build.sh

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

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

@@ -2,7 +2,7 @@
 # Helper utilities for build
 # Script used only in CD pipeline
 
-OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/  # @lint-ignore
+OPENSSL_DOWNLOAD_URL=https://www.openssl.org/source/old/1.1.1/
 CURL_DOWNLOAD_URL=https://curl.se/download
 
 AUTOCONF_DOWNLOAD_URL=https://ftp.gnu.org/gnu/autoconf

.ci/docker/requirements-ci.txt

@@ -16,7 +16,6 @@ click
 #test that import:
 
 coremltools==5.0b5 ; python_version < "3.12"
-coremltools==8.3 ; python_version == "3.12"
 #Description: Apple framework for ML integration
 #Pinned versions: 5.0b5
 #test that import:
@@ -42,11 +41,14 @@ fbscribelogger==0.1.7
 #Pinned versions: 0.1.6
 #test that import:
 
-flatbuffers==24.12.23
+flatbuffers==2.0 ; platform_machine != "s390x"
 #Description: cross platform serialization library
-#Pinned versions: 24.12.23
+#Pinned versions: 2.0
 #test that import:
 
+flatbuffers ; platform_machine == "s390x"
+#Description: cross platform serialization library; Newer version is required on s390x for new python version
+
 hypothesis==5.35.1
 # Pin hypothesis to avoid flakiness: https://github.com/pytorch/pytorch/issues/31136
 #Description: advanced library for generating parametrized tests
@@ -64,7 +66,6 @@ lark==0.12.0
 #test that import:
 
 librosa>=0.6.2 ; python_version < "3.11"
-librosa==0.10.2 ; python_version == "3.12"
 #Description: A python package for music and audio analysis
 #Pinned versions: >=0.6.2
 #test that import: test_spectral_ops.py
@@ -92,10 +93,10 @@ librosa==0.10.2 ; python_version == "3.12"
 #Pinned versions:
 #test that import:
 
-mypy==1.16.0
+mypy==1.14.0
 # Pin MyPy version because new errors are likely to appear with each release
 #Description: linter
-#Pinned versions: 1.16.0
+#Pinned versions: 1.14.0
 #test that import: test_typing.py, test_type_hints.py
 
 networkx==2.8.8
@@ -113,7 +114,6 @@ ninja==1.11.1.3
 numba==0.49.0 ; python_version < "3.9"
 numba==0.55.2 ; python_version == "3.9"
 numba==0.55.2 ; python_version == "3.10"
-numba==0.60.0 ; python_version == "3.12"
 #Description: Just-In-Time Compiler for Numerical Functions
 #Pinned versions: 0.54.1, 0.49.0, <=0.49.1
 #test that import: test_numba_integration.py
@@ -166,10 +166,10 @@ pillow==11.0.0
 #Pinned versions: 10.3.0
 #test that import:
 
-protobuf==5.29.4
-#Description:  Google's data interchange format
-#Pinned versions: 5.29.4
-#test that import: test_tensorboard.py, test/onnx/*
+protobuf==3.20.2
+#Description:  Google’s data interchange format
+#Pinned versions: 3.20.1
+#test that import: test_tensorboard.py
 
 psutil
 #Description: information on running processes and system utilization
@@ -337,12 +337,12 @@ sympy==1.13.3
 #Pinned versions:
 #test that import:
 
-onnx==1.18.0
-#Description: Required by onnx tests, and mypy and test_public_bindings.py when checking torch.onnx._internal
+onnx==1.17.0
+#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
 
-onnxscript==0.3.1
+onnxscript==0.2.2
 #Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
 #Pinned versions:
 #test that import:
@@ -363,10 +363,10 @@ pwlf==2.2.1
 
 
 # To build PyTorch itself
-pyyaml
+astunparse
+PyYAML
 pyzstd
-setuptools>=70.1.0
-six
+setuptools
 
 scons==4.5.2 ; platform_machine == "aarch64"
 
@@ -379,13 +379,3 @@ dataclasses_json==0.6.7
 #Description: required for data pipeline and scripts under tools/stats
 #Pinned versions: 0.6.7
 #test that import:
-
-cmake==4.0.0
-#Description: required for building
-
-tlparse==0.3.30
-#Description: required for log parsing
-
-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

@@ -1,11 +1,11 @@
 sphinx==5.3.0
 #Description: This is used to generate PyTorch docs
 #Pinned versions: 5.3.0
--e git+https://github.com/pytorch/pytorch_sphinx_theme.git@pytorch_sphinx_theme2#egg=pytorch_sphinx_theme2
+-e git+https://github.com/pytorch/pytorch_sphinx_theme.git@a98ffecb792d50df495be401becbf5c414421423#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 is probably
-# something related to Docker setup. We can investigate this later.
+# something related to Docker setup. We can investigate this later
 
 sphinxcontrib.katex==0.8.6
 #Description: This is used to generate PyTorch docs
@@ -15,14 +15,9 @@ sphinxext-opengraph==0.9.1
 #Description: This is used to generate PyTorch docs
 #Pinned versions: 0.9.1
 
-sphinx_sitemap==2.6.0
-#Description: This is used to generate sitemap for PyTorch docs
-#Pinned versions: 2.6.0
-
-matplotlib==3.5.3 ; python_version < "3.13"
-matplotlib==3.6.3 ; python_version >= "3.13"
+matplotlib==3.5.3
 #Description: This is used to generate PyTorch docs
-#Pinned versions: 3.6.3 if python > 3.12. Otherwise 3.5.3.
+#Pinned versions: 3.5.3
 
 tensorboard==2.13.0 ; python_version < "3.13"
 tensorboard==2.18.0 ; python_version >= "3.13"

.ci/docker/triton_version.txt

@@ -1 +1 @@
-3.4.0
+3.3.0

.ci/docker/triton_xpu_version.txt

@@ -1 +0,0 @@
-3.4.0

.ci/docker/ubuntu-cuda/Dockerfile

@@ -0,0 +1,184 @@
+ARG UBUNTU_VERSION
+ARG CUDA_VERSION
+ARG IMAGE_NAME
+
+FROM ${IMAGE_NAME} as base
+
+ARG UBUNTU_VERSION
+ARG CUDA_VERSION
+
+ENV DEBIAN_FRONTEND noninteractive
+
+# Install common dependencies (so that this step can be cached separately)
+COPY ./common/install_base.sh install_base.sh
+RUN bash ./install_base.sh && rm install_base.sh
+
+# Install user
+COPY ./common/install_user.sh install_user.sh
+RUN bash ./install_user.sh && rm install_user.sh
+
+# Install katex
+ARG KATEX
+COPY ./common/install_docs_reqs.sh install_docs_reqs.sh
+RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
+
+# Install conda and other packages (e.g., numpy, pytest)
+ARG ANACONDA_PYTHON_VERSION
+ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
+ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
+ARG CONDA_CMAKE
+COPY requirements-ci.txt /opt/conda/requirements-ci.txt
+COPY ./common/install_conda.sh install_conda.sh
+COPY ./common/common_utils.sh common_utils.sh
+COPY ./common/install_magma_conda.sh install_magma_conda.sh
+RUN bash ./install_conda.sh && rm install_conda.sh install_magma_conda.sh common_utils.sh /opt/conda/requirements-ci.txt
+
+# Install gcc
+ARG GCC_VERSION
+COPY ./common/install_gcc.sh install_gcc.sh
+RUN bash ./install_gcc.sh && rm install_gcc.sh
+
+# Install clang
+ARG CLANG_VERSION
+COPY ./common/install_clang.sh install_clang.sh
+RUN bash ./install_clang.sh && rm install_clang.sh
+
+# (optional) Install protobuf for ONNX
+ARG PROTOBUF
+COPY ./common/install_protobuf.sh install_protobuf.sh
+RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
+RUN rm install_protobuf.sh
+ENV INSTALLED_PROTOBUF ${PROTOBUF}
+
+# (optional) Install vision packages like OpenCV
+ARG VISION
+COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
+RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
+RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
+ENV INSTALLED_VISION ${VISION}
+
+# (optional) Install UCC
+ARG UCX_COMMIT
+ARG UCC_COMMIT
+ENV UCX_COMMIT $UCX_COMMIT
+ENV UCC_COMMIT $UCC_COMMIT
+ENV UCX_HOME /usr
+ENV UCC_HOME /usr
+ADD ./common/install_ucc.sh install_ucc.sh
+RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
+RUN rm install_ucc.sh
+
+COPY ./common/install_openssl.sh install_openssl.sh
+ENV OPENSSL_ROOT_DIR /opt/openssl
+RUN bash ./install_openssl.sh
+ENV OPENSSL_DIR /opt/openssl
+
+ARG INDUCTOR_BENCHMARKS
+ARG ANACONDA_PYTHON_VERSION
+ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
+COPY ./common/install_inductor_benchmark_deps.sh install_inductor_benchmark_deps.sh
+COPY ./common/common_utils.sh common_utils.sh
+COPY ci_commit_pins/huggingface.txt huggingface.txt
+COPY ci_commit_pins/timm.txt timm.txt
+RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
+RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
+
+# (optional) Install non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
+
+ARG TRITON
+
+FROM base as triton-builder
+# Install triton, this needs to be done before sccache because the latter will
+# try to reach out to S3, which docker build runners don't have access
+COPY ./common/install_triton.sh install_triton.sh
+COPY ./common/common_utils.sh common_utils.sh
+COPY ci_commit_pins/triton.txt triton.txt
+COPY triton_version.txt triton_version.txt
+RUN bash ./install_triton.sh
+
+FROM base as final
+COPY --from=triton-builder /opt/triton /opt/triton
+RUN if [ -n "${TRITON}" ]; then pip install /opt/triton/*.whl; chown -R jenkins:jenkins /opt/conda; fi
+RUN rm -rf /opt/triton
+
+ARG HALIDE
+# Build and install halide
+COPY ./common/install_halide.sh install_halide.sh
+COPY ./common/common_utils.sh common_utils.sh
+COPY ci_commit_pins/halide.txt halide.txt
+RUN if [ -n "${HALIDE}" ]; then bash ./install_halide.sh; fi
+RUN rm install_halide.sh common_utils.sh halide.txt
+
+# Install ccache/sccache (do this last, so we get priority in PATH)
+COPY ./common/install_cache.sh install_cache.sh
+ENV PATH /opt/cache/bin:$PATH
+# See https://github.com/pytorch/pytorch/issues/82174
+# TODO(sdym@fb.com):
+# check if this is needed after full off Xenial migration
+ENV CARGO_NET_GIT_FETCH_WITH_CLI true
+RUN bash ./install_cache.sh && rm install_cache.sh
+ENV CMAKE_CUDA_COMPILER_LAUNCHER=/opt/cache/bin/sccache
+
+# Add jni.h for java host build
+COPY ./common/install_jni.sh install_jni.sh
+COPY ./java/jni.h jni.h
+RUN bash ./install_jni.sh && rm install_jni.sh
+
+# Install Open MPI for CUDA
+COPY ./common/install_openmpi.sh install_openmpi.sh
+RUN if [ -n "${CUDA_VERSION}" ]; then bash install_openmpi.sh; fi
+RUN rm install_openmpi.sh
+
+# Include BUILD_ENVIRONMENT environment variable in image
+ARG BUILD_ENVIRONMENT
+ENV BUILD_ENVIRONMENT ${BUILD_ENVIRONMENT}
+
+# AWS specific CUDA build guidance
+ENV TORCH_CUDA_ARCH_LIST Maxwell
+ENV TORCH_NVCC_FLAGS "-Xfatbin -compress-all"
+ENV CUDA_PATH /usr/local/cuda
+
+# Install LLVM dev version (Defined in the pytorch/builder github repository)
+COPY --from=pytorch/llvm:9.0.1 /opt/llvm /opt/llvm
+
+# Install CUDNN
+ARG CUDNN_VERSION
+ARG CUDA_VERSION
+COPY ./common/install_cudnn.sh install_cudnn.sh
+RUN if [ -n "${CUDNN_VERSION}" ]; then bash install_cudnn.sh; fi
+RUN rm install_cudnn.sh
+
+# Install CUSPARSELT
+ARG CUDA_VERSION
+COPY ./common/install_cusparselt.sh install_cusparselt.sh
+RUN bash install_cusparselt.sh
+RUN rm install_cusparselt.sh
+
+# Install NCCL
+ARG CUDA_VERSION
+COPY ./common/install_nccl.sh install_nccl.sh
+COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
+RUN bash install_nccl.sh
+RUN rm install_nccl.sh /ci_commit_pins/nccl-cu*
+ENV USE_SYSTEM_NCCL=1
+ENV NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
+ENV NCCL_LIB_DIR="/usr/local/cuda/lib64/"
+
+# Install CUDSS
+ARG CUDA_VERSION
+COPY ./common/install_cudss.sh install_cudss.sh
+RUN bash install_cudss.sh
+RUN rm install_cudss.sh
+
+# Delete /usr/local/cuda-11.X/cuda-11.X symlinks
+RUN if [ -h /usr/local/cuda-11.6/cuda-11.6 ]; then rm /usr/local/cuda-11.6/cuda-11.6; fi
+RUN if [ -h /usr/local/cuda-11.7/cuda-11.7 ]; then rm /usr/local/cuda-11.7/cuda-11.7; fi
+RUN if [ -h /usr/local/cuda-12.1/cuda-12.1 ]; then rm /usr/local/cuda-12.1/cuda-12.1; fi
+RUN if [ -h /usr/local/cuda-12.4/cuda-12.4 ]; then rm /usr/local/cuda-12.4/cuda-12.4; fi
+
+USER jenkins
+CMD ["bash"]

.ci/docker/ubuntu-rocm/Dockerfile

@@ -25,9 +25,9 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
 ARG ANACONDA_PYTHON_VERSION
-ARG BUILD_ENVIRONMENT
 ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
 ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
+ARG CONDA_CMAKE
 COPY requirements-ci.txt /opt/conda/requirements-ci.txt
 COPY ./common/install_conda.sh install_conda.sh
 COPY ./common/common_utils.sh common_utils.sh
@@ -43,6 +43,13 @@ ARG CLANG_VERSION
 COPY ./common/install_clang.sh install_clang.sh
 RUN bash ./install_clang.sh && rm install_clang.sh
 
+# (optional) Install protobuf for ONNX
+ARG PROTOBUF
+COPY ./common/install_protobuf.sh install_protobuf.sh
+RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
+RUN rm install_protobuf.sh
+ENV INSTALLED_PROTOBUF ${PROTOBUF}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -101,6 +108,12 @@ COPY ci_commit_pins/timm.txt timm.txt
 RUN if [ -n "${INDUCTOR_BENCHMARKS}" ]; then bash ./install_inductor_benchmark_deps.sh; fi
 RUN rm install_inductor_benchmark_deps.sh common_utils.sh timm.txt huggingface.txt
 
+# (optional) Install non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
+
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
 COPY ./common/install_ninja.sh install_ninja.sh

.ci/docker/ubuntu-xpu/Dockerfile

@@ -28,6 +28,7 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
 ARG ANACONDA_PYTHON_VERSION
+ARG CONDA_CMAKE
 ARG DOCS
 ARG BUILD_ENVIRONMENT
 ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
@@ -72,7 +73,7 @@ ARG TRITON
 COPY ./common/install_triton.sh install_triton.sh
 COPY ./common/common_utils.sh common_utils.sh
 COPY ci_commit_pins/triton-xpu.txt triton-xpu.txt
-COPY triton_xpu_version.txt triton_version.txt
+COPY triton_version.txt triton_version.txt
 RUN if [ -n "${TRITON}" ]; then bash ./install_triton.sh; fi
 RUN rm install_triton.sh common_utils.sh triton-xpu.txt triton_version.txt
 
@@ -83,6 +84,12 @@ RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
 RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
 ENV INSTALLED_VISION ${VISION}
 
+# (optional) Install non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
+
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
 COPY ./common/install_ninja.sh install_ninja.sh

.ci/docker/ubuntu/Dockerfile

@@ -28,6 +28,7 @@ RUN bash ./install_docs_reqs.sh && rm install_docs_reqs.sh
 
 # Install conda and other packages (e.g., numpy, pytest)
 ARG ANACONDA_PYTHON_VERSION
+ARG CONDA_CMAKE
 ARG DOCS
 ENV ANACONDA_PYTHON_VERSION=$ANACONDA_PYTHON_VERSION
 ENV PATH /opt/conda/envs/py_$ANACONDA_PYTHON_VERSION/bin:/opt/conda/bin:$PATH
@@ -53,8 +54,7 @@ ARG CUDA_VERSION
 COPY ./common/install_cuda.sh install_cuda.sh
 COPY ./common/install_nccl.sh install_nccl.sh
 COPY ./ci_commit_pins/nccl-cu* /ci_commit_pins/
-COPY ./common/install_cusparselt.sh install_cusparselt.sh
-RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu* install_cusparselt.sh
+RUN bash ./install_cuda.sh ${CUDA_VERSION} && rm install_cuda.sh install_nccl.sh /ci_commit_pins/nccl-cu*
 ENV DESIRED_CUDA ${CUDA_VERSION}
 ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:$PATH
 # No effect if cuda not installed
@@ -74,6 +74,13 @@ ADD ./common/install_ucc.sh install_ucc.sh
 RUN if [ -n "${UCX_COMMIT}" ] && [ -n "${UCC_COMMIT}" ]; then bash ./install_ucc.sh; fi
 RUN rm install_ucc.sh
 
+# (optional) Install protobuf for ONNX
+ARG PROTOBUF
+COPY ./common/install_protobuf.sh install_protobuf.sh
+RUN if [ -n "${PROTOBUF}" ]; then bash ./install_protobuf.sh; fi
+RUN rm install_protobuf.sh
+ENV INSTALLED_PROTOBUF ${PROTOBUF}
+
 # (optional) Install vision packages like OpenCV
 ARG VISION
 COPY ./common/install_vision.sh ./common/cache_vision_models.sh ./common/common_utils.sh ./
@@ -81,6 +88,12 @@ RUN if [ -n "${VISION}" ]; then bash ./install_vision.sh; fi
 RUN rm install_vision.sh cache_vision_models.sh common_utils.sh
 ENV INSTALLED_VISION ${VISION}
 
+# (optional) Install non-default CMake version
+ARG CMAKE_VERSION
+COPY ./common/install_cmake.sh install_cmake.sh
+RUN if [ -n "${CMAKE_VERSION}" ]; then bash ./install_cmake.sh; fi
+RUN rm install_cmake.sh
+
 # (optional) Install non-default Ninja version
 ARG NINJA_VERSION
 COPY ./common/install_ninja.sh install_ninja.sh
@@ -147,12 +160,6 @@ RUN if [ -n "${ACL}" ]; then bash ./install_acl.sh; fi
 RUN rm install_acl.sh
 ENV INSTALLED_ACL ${ACL}
 
-ARG OPENBLAS
-COPY ./common/install_openblas.sh install_openblas.sh
-RUN if [ -n "${OPENBLAS}" ]; then bash ./install_openblas.sh; fi
-RUN rm install_openblas.sh
-ENV INSTALLED_OPENBLAS ${OPENBLAS}
-
 # Install ccache/sccache (do this last, so we get priority in PATH)
 ARG SKIP_SCCACHE_INSTALL
 COPY ./common/install_cache.sh install_cache.sh

.ci/magma-rocm/Makefile

@@ -12,12 +12,13 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
 	-w /builder \
 	-e PACKAGE_NAME=${PACKAGE_NAME}${DESIRED_ROCM_SHORT} \
 	-e DESIRED_ROCM=${DESIRED_ROCM} \
-	"pytorch/almalinux-builder:rocm${DESIRED_ROCM}" \
+	"pytorch/manylinux2_28-builder:rocm${DESIRED_ROCM}-main" \
 	magma-rocm/build_magma.sh
 
 .PHONY: all
 all: magma-rocm64
 all: magma-rocm63
+all: magma-rocm624
 
 .PHONY:
 clean:
@@ -33,3 +34,8 @@ magma-rocm64:
 magma-rocm63: DESIRED_ROCM := 6.3
 magma-rocm63:
 	$(DOCKER_RUN)
+
+.PHONY: magma-rocm624
+magma-rocm624: DESIRED_ROCM := 6.2.4
+magma-rocm624:
+	$(DOCKER_RUN)

.ci/magma/Makefile

@@ -1,7 +1,7 @@
 SHELL=/usr/bin/env bash
 
 DOCKER_CMD ?= docker
-DESIRED_CUDA ?= 12.8
+DESIRED_CUDA ?= 11.8
 DESIRED_CUDA_SHORT = $(subst .,,$(DESIRED_CUDA))
 PACKAGE_NAME = magma-cuda
 CUDA_ARCH_LIST ?= -gencode arch=compute_50,code=sm_50 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_90,code=sm_90
@@ -12,25 +12,20 @@ DOCKER_RUN = set -eou pipefail; ${DOCKER_CMD} run --rm -i \
 	-e PACKAGE_NAME=${PACKAGE_NAME}${DESIRED_CUDA_SHORT} \
 	-e DESIRED_CUDA=${DESIRED_CUDA} \
 	-e CUDA_ARCH_LIST="${CUDA_ARCH_LIST}" \
-	"pytorch/almalinux-builder:cuda${DESIRED_CUDA}-main" \
+	"pytorch/manylinux2_28-builder:cuda${DESIRED_CUDA}-main" \
 	magma/build_magma.sh
 
 .PHONY: all
-all: magma-cuda129
 all: magma-cuda128
 all: magma-cuda126
+all: magma-cuda124
+all: magma-cuda118
 
 .PHONY:
 clean:
 	$(RM) -r magma-*
 	$(RM) -r output
 
-.PHONY: magma-cuda129
-magma-cuda129: DESIRED_CUDA := 12.9
-magma-cuda129: CUDA_ARCH_LIST += -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120
-magma-cuda129:
-	$(DOCKER_RUN)
-
 .PHONY: magma-cuda128
 magma-cuda128: DESIRED_CUDA := 12.8
 magma-cuda128: CUDA_ARCH_LIST += -gencode arch=compute_100,code=sm_100 -gencode arch=compute_120,code=sm_120
@@ -41,3 +36,14 @@ magma-cuda128:
 magma-cuda126: DESIRED_CUDA := 12.6
 magma-cuda126:
 	$(DOCKER_RUN)
+
+.PHONY: magma-cuda124
+magma-cuda124: DESIRED_CUDA := 12.4
+magma-cuda124:
+	$(DOCKER_RUN)
+
+.PHONY: magma-cuda118
+magma-cuda118: DESIRED_CUDA := 11.8
+magma-cuda118: CUDA_ARCH_LIST += -gencode arch=compute_37,code=sm_37
+magma-cuda118:
+	$(DOCKER_RUN)

.ci/manywheel/build_common.sh

@@ -18,10 +18,12 @@ retry () {
     $*  || (sleep 1 && $*) || (sleep 2 && $*) || (sleep 4 && $*) || (sleep 8 && $*)
 }
 
-PLATFORM=""
+PLATFORM="manylinux2014_x86_64"
 # TODO move this into the Docker images
 OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
-if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
+if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
+    retry yum install -q -y zip openssl
+elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
     retry yum install -q -y zip openssl
     PLATFORM="manylinux_2_28_x86_64"
 elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
@@ -31,11 +33,9 @@ elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
     # Comment out nvidia repositories to prevent them from getting apt-get updated, see https://github.com/pytorch/pytorch/issues/74968
     # shellcheck disable=SC2046
     sed -i 's/.*nvidia.*/# &/' $(find /etc/apt/ -type f -name "*.list")
+
     retry apt-get update
     retry apt-get -y install zip openssl
-else
-    echo "Unknown OS: '$OS_NAME'"
-    exit 1
 fi
 
 # We use the package name to test the package by passing this to 'pip install'
@@ -79,6 +79,8 @@ if [[ -e /opt/openssl ]]; then
     export CMAKE_INCLUDE_PATH="/opt/openssl/include":$CMAKE_INCLUDE_PATH
 fi
 
+
+
 mkdir -p /tmp/$WHEELHOUSE_DIR
 
 export PATCHELF_BIN=/usr/local/bin/patchelf
@@ -97,8 +99,6 @@ if [[ -z "$PYTORCH_ROOT" ]]; then
     exit 1
 fi
 pushd "$PYTORCH_ROOT"
-retry pip install -q "setuptools>=70.1.0" packaging
-retry pip install -qU cmake ninja
 python setup.py clean
 retry pip install -qr requirements.txt
 case ${DESIRED_PYTHON} in
@@ -152,7 +152,7 @@ if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
     BUILD_LIBTORCH_WHL=0 BUILD_PYTHON_ONLY=1 \
     BUILD_LIBTORCH_CPU_WITH_DEBUG=$BUILD_DEBUG_INFO \
     USE_NCCL=${USE_NCCL} USE_RCCL=${USE_RCCL} USE_KINETO=${USE_KINETO} \
-    CMAKE_FRESH=1 python setup.py bdist_wheel -d /tmp/$WHEELHOUSE_DIR
+    python setup.py bdist_wheel -d /tmp/$WHEELHOUSE_DIR --cmake
     echo "Finished setup.py bdist_wheel for split build (BUILD_PYTHON_ONLY)"
 else
     time CMAKE_ARGS=${CMAKE_ARGS[@]} \
@@ -321,8 +321,8 @@ for pkg in /$WHEELHOUSE_DIR/torch_no_python*.whl /$WHEELHOUSE_DIR/torch*linux*.w
             # ROCm workaround for roctracer dlopens
             if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
                 patchedpath=$(fname_without_so_number $destpath)
-            # Keep the so number for XPU dependencies and libgomp.so.1 to avoid twice load
-            elif [[ "$DESIRED_CUDA" == *"xpu"* || "$filename" == "libgomp.so.1" ]]; then
+            # Keep the so number for XPU dependencies
+            elif [[ "$DESIRED_CUDA" == *"xpu"* ]]; then
                 patchedpath=$destpath
             else
                 patchedpath=$(fname_with_sha256 $destpath)

.ci/manywheel/build_cuda.sh

@@ -15,9 +15,6 @@ export INSTALL_TEST=0 # dont install test binaries into site-packages
 export USE_CUPTI_SO=0
 export USE_CUSPARSELT=${USE_CUSPARSELT:-1} # Enable if not disabled by libtorch build
 export USE_CUFILE=${USE_CUFILE:-1}
-export USE_SYSTEM_NCCL=1
-export NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
-export NCCL_LIB_DIR="/usr/local/cuda/lib64/"
 
 # Keep an array of cmake variables to add to
 if [[ -z "$CMAKE_ARGS" ]]; then
@@ -39,8 +36,10 @@ if [[ -n "$DESIRED_CUDA" ]]; then
     if [[ ${DESIRED_CUDA} =~ ^[0-9]+\.[0-9]+$ ]]; then
         CUDA_VERSION=${DESIRED_CUDA}
     else
-        # cu126, cu128 etc...
-        if [[ ${#DESIRED_CUDA} -eq 5 ]]; then
+        # cu90, cu92, cu100, cu101
+        if [[ ${#DESIRED_CUDA} -eq 4 ]]; then
+            CUDA_VERSION="${DESIRED_CUDA:2:1}.${DESIRED_CUDA:3:1}"
+        elif [[ ${#DESIRED_CUDA} -eq 5 ]]; then
             CUDA_VERSION="${DESIRED_CUDA:2:2}.${DESIRED_CUDA:4:1}"
         fi
     fi
@@ -51,23 +50,24 @@ else
 fi
 
 cuda_version_nodot=$(echo $CUDA_VERSION | tr -d '.')
-EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
 
+TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;7.5;8.0;8.6"
 case ${CUDA_VERSION} in
-    #removing sm_50-sm_60 as these architectures are deprecated in CUDA 12.8/9 and will be removed in future releases
-    #however we would like to keep sm_70 architecture see: https://github.com/pytorch/pytorch/issues/157517
     12.8)
-        TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6;9.0;10.0;12.0"
-        ;;
-    12.9)
-        TORCH_CUDA_ARCH_LIST="7.0;7.5;8.0;8.6;9.0;10.0;12.0+PTX"
-        # WAR to resolve the ld error in libtorch build with CUDA 12.9
-        if [[ "$PACKAGE_TYPE" == "libtorch" ]]; then
-            TORCH_CUDA_ARCH_LIST="7.5;8.0;9.0;10.0;12.0+PTX"
-        fi
+        TORCH_CUDA_ARCH_LIST="7.5;8.0;8.6;9.0;10.0;12.0+PTX" #removing sm_50-sm_70 as these architectures are deprecated in CUDA 12.8 and will be removed in future releases
+        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
     12.6)
-        TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;7.5;8.0;8.6;9.0"
+        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
+        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
+        ;;
+    12.4)
+        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};9.0"
+        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
+        ;;
+    11.8)
+        TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST};3.7;9.0"
+        EXTRA_CAFFE2_CMAKE_FLAGS+=("-DATEN_NO_TEST=ON")
         ;;
     *)
         echo "unknown cuda version $CUDA_VERSION"
@@ -91,15 +91,14 @@ fi
 mkdir -p "$PYTORCH_FINAL_PACKAGE_DIR" || true
 
 OS_NAME=$(awk -F= '/^NAME/{print $2}' /etc/os-release)
-if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
+if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
+    LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
+elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
     LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
 elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
     LIBGOMP_PATH="/usr/lib64/libgomp.so.1"
 elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
     LIBGOMP_PATH="/usr/lib/x86_64-linux-gnu/libgomp.so.1"
-else
-    echo "Unknown OS: '$OS_NAME'"
-    exit 1
 fi
 
 DEPS_LIST=(
@@ -109,12 +108,31 @@ DEPS_SONAME=(
     "libgomp.so.1"
 )
 
+# CUDA 11.8 have to ship the libcusparseLt.so.0 with the binary
+# since nvidia-cusparselt-cu11 is not available in PYPI
+if [[ $USE_CUSPARSELT == "1" && $CUDA_VERSION == "11.8" ]]; then
+        DEPS_SONAME+=(
+            "libcusparseLt.so.0"
+        )
+        DEPS_LIST+=(
+            "/usr/local/cuda/lib64/libcusparseLt.so.0"
+        )
+fi
 
-# CUDA_VERSION 12.6, 12.8, 12.9
+
+# Turn USE_CUFILE off for CUDA 11.8, 12.4 since nvidia-cufile-cu11 and 1.9.0.20 are
+# not available in PYPI
+if [[ $CUDA_VERSION == "11.8" || $CUDA_VERSION == "12.4" ]]; then
+    export USE_CUFILE=0
+fi
+
+
+# CUDA_VERSION 12.4, 12.6, 12.8
 if [[ $CUDA_VERSION == 12* ]]; then
     export USE_STATIC_CUDNN=0
     # Try parallelizing nvcc as well
     export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"
+
     if [[ -z "$PYTORCH_EXTRA_INSTALL_REQUIREMENTS" ]]; then
         echo "Bundling with cudnn and cublas."
         DEPS_LIST+=(
@@ -130,12 +148,9 @@ if [[ $CUDA_VERSION == 12* ]]; then
             "/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/libnvToolsExt.so.1"
             "/usr/local/cuda/lib64/libnvrtc.so.12"
             "/usr/local/cuda/lib64/libnvrtc-builtins.so"
-            "/usr/local/cuda/lib64/libcufile.so.0"
-            "/usr/local/cuda/lib64/libcufile_rdma.so.1"
-            "/usr/local/cuda/extras/CUPTI/lib64/libcupti.so.12"
-            "/usr/local/cuda/extras/CUPTI/lib64/libnvperf_host.so"
         )
         DEPS_SONAME+=(
             "libcudnn_adv.so.9"
@@ -150,17 +165,19 @@ if [[ $CUDA_VERSION == 12* ]]; then
             "libcublasLt.so.12"
             "libcusparseLt.so.0"
             "libcudart.so.12"
+            "libnvToolsExt.so.1"
             "libnvrtc.so.12"
             "libnvrtc-builtins.so"
-            "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 != 12.9* ]]; then
-            DEPS_LIST+=("/usr/local/cuda/lib64/libnvToolsExt.so.1")
-            DEPS_SONAME+=("libnvToolsExt.so.1")
+        if [[ $USE_CUFILE == 1 ]]; then
+            DEPS_LIST+=(
+                "/usr/local/cuda/lib64/libcufile.so.0"
+                "/usr/local/cuda/lib64/libcufile_rdma.so.1"
+            )
+            DEPS_SONAME+=(
+                "libcufile.so.0"
+                "libcufile_rdma.so.1"
+            )
         fi
     else
         echo "Using nvidia libs from pypi."
@@ -174,21 +191,94 @@ if [[ $CUDA_VERSION == 12* ]]; then
             '$ORIGIN/../../nvidia/curand/lib'
             '$ORIGIN/../../nvidia/cusolver/lib'
             '$ORIGIN/../../nvidia/cusparse/lib'
-            '$ORIGIN/../../nvidia/cusparselt/lib'
             '$ORIGIN/../../cusparselt/lib'
             '$ORIGIN/../../nvidia/nccl/lib'
-            '$ORIGIN/../../nvidia/nvshmem/lib'
             '$ORIGIN/../../nvidia/nvtx/lib'
-            '$ORIGIN/../../nvidia/cufile/lib'
+        )
+        if [[ $USE_CUFILE == 1 ]]; then
+            CUDA_RPATHS+=(
+                '$ORIGIN/../../nvidia/cufile/lib'
+            )
+        fi
+        CUDA_RPATHS=$(IFS=: ; echo "${CUDA_RPATHS[*]}")
+        export C_SO_RPATH=$CUDA_RPATHS':$ORIGIN:$ORIGIN/lib'
+        export LIB_SO_RPATH=$CUDA_RPATHS':$ORIGIN'
+        export FORCE_RPATH="--force-rpath"
+        export USE_STATIC_NCCL=0
+        export USE_SYSTEM_NCCL=1
+        export ATEN_STATIC_CUDA=0
+        export USE_CUDA_STATIC_LINK=0
+        export USE_CUPTI_SO=1
+        export NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
+        export NCCL_LIB_DIR="/usr/local/cuda/lib64/"
+    fi
+elif [[ $CUDA_VERSION == "11.8" ]]; then
+    export USE_STATIC_CUDNN=0
+    # Try parallelizing nvcc as well
+    export TORCH_NVCC_FLAGS="-Xfatbin -compress-all --threads 2"
+    # Bundle ptxas into the wheel, see https://github.com/pytorch/pytorch/pull/119750
+    export BUILD_BUNDLE_PTXAS=1
+
+    if [[ -z "$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"
+            "/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/libcudnn.so.9"
+            "/usr/local/cuda/lib64/libcublas.so.11"
+            "/usr/local/cuda/lib64/libcublasLt.so.11"
+            "/usr/local/cuda/lib64/libcudart.so.11.0"
+            "/usr/local/cuda/lib64/libnvToolsExt.so.1"
+            "/usr/local/cuda/lib64/libnvrtc.so.11.2"    # this is not a mistake, it links to more specific cuda version
+            "/usr/local/cuda/lib64/libnvrtc-builtins.so.11.8"
+        )
+        DEPS_SONAME+=(
+            "libcudnn_adv.so.9"
+            "libcudnn_cnn.so.9"
+            "libcudnn_graph.so.9"
+            "libcudnn_ops.so.9"
+            "libcudnn_engines_runtime_compiled.so.9"
+            "libcudnn_engines_precompiled.so.9"
+            "libcudnn_heuristic.so.9"
+            "libcudnn.so.9"
+            "libcublas.so.11"
+            "libcublasLt.so.11"
+            "libcudart.so.11.0"
+            "libnvToolsExt.so.1"
+            "libnvrtc.so.11.2"
+            "libnvrtc-builtins.so.11.8"
+        )
+    else
+        echo "Using nvidia libs from pypi."
+        CUDA_RPATHS=(
+            '$ORIGIN/../../nvidia/cublas/lib'
+            '$ORIGIN/../../nvidia/cuda_cupti/lib'
+            '$ORIGIN/../../nvidia/cuda_nvrtc/lib'
+            '$ORIGIN/../../nvidia/cuda_runtime/lib'
+            '$ORIGIN/../../nvidia/cudnn/lib'
+            '$ORIGIN/../../nvidia/cufft/lib'
+            '$ORIGIN/../../nvidia/curand/lib'
+            '$ORIGIN/../../nvidia/cusolver/lib'
+            '$ORIGIN/../../nvidia/cusparse/lib'
+            '$ORIGIN/../../nvidia/nccl/lib'
+            '$ORIGIN/../../nvidia/nvtx/lib'
         )
         CUDA_RPATHS=$(IFS=: ; echo "${CUDA_RPATHS[*]}")
         export C_SO_RPATH=$CUDA_RPATHS':$ORIGIN:$ORIGIN/lib'
         export LIB_SO_RPATH=$CUDA_RPATHS':$ORIGIN'
         export FORCE_RPATH="--force-rpath"
         export USE_STATIC_NCCL=0
+        export USE_SYSTEM_NCCL=1
         export ATEN_STATIC_CUDA=0
         export USE_CUDA_STATIC_LINK=0
         export USE_CUPTI_SO=1
+        export NCCL_INCLUDE_DIR="/usr/local/cuda/include/"
+        export NCCL_LIB_DIR="/usr/local/cuda/lib64/"
     fi
 else
     echo "Unknown cuda version $CUDA_VERSION"

.ci/manywheel/build_libtorch.sh

@@ -22,7 +22,9 @@ retry () {
 
 # TODO move this into the Docker images
 OS_NAME=`awk -F= '/^NAME/{print $2}' /etc/os-release`
-if [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
+if [[ "$OS_NAME" == *"CentOS Linux"* ]]; then
+    retry yum install -q -y zip openssl
+elif [[ "$OS_NAME" == *"AlmaLinux"* ]]; then
     retry yum install -q -y zip openssl
 elif [[ "$OS_NAME" == *"Red Hat Enterprise Linux"* ]]; then
     retry dnf install -q -y zip openssl
@@ -33,9 +35,6 @@ elif [[ "$OS_NAME" == *"Ubuntu"* ]]; then
     sed -i 's/.*nvidia.*/# &/' $(find /etc/apt/ -type f -name "*.list")
     retry apt-get update
     retry apt-get -y install zip openssl
-else
-    echo "Unknown OS: '$OS_NAME'"
-    exit 1
 fi
 
 # Version: setup.py uses $PYTORCH_BUILD_VERSION.post$PYTORCH_BUILD_NUMBER if
@@ -92,8 +91,6 @@ if [[ -z "$PYTORCH_ROOT" ]]; then
     exit 1
 fi
 pushd "$PYTORCH_ROOT"
-retry pip install -q "setuptools>=70.1.0" packaging
-retry pip install -qU cmake ninja
 python setup.py clean
 retry pip install -qr requirements.txt
 retry pip install -q numpy==2.0.1
@@ -105,7 +102,7 @@ if [[ "$DESIRED_CUDA" == *"rocm"* ]]; then
     export ROCclr_DIR=/opt/rocm/rocclr/lib/cmake/rocclr
 fi
 
-echo "Calling 'python -m pip install .' at $(date)"
+echo "Calling setup.py install at $(date)"
 
 if [[ $LIBTORCH_VARIANT = *"static"* ]]; then
     STATIC_CMAKE_FLAG="-DTORCH_STATIC=1"
@@ -121,7 +118,7 @@ fi
         # TODO: Remove this flag once https://github.com/pytorch/pytorch/issues/55952 is closed
         CFLAGS='-Wno-deprecated-declarations' \
         BUILD_LIBTORCH_CPU_WITH_DEBUG=1 \
-        python -m pip install --no-build-isolation -v .
+        python setup.py install
 
     mkdir -p libtorch/{lib,bin,include,share}
 

.ci/manywheel/build_rocm.sh

@@ -95,7 +95,6 @@ ROCM_SO_FILES=(
     "libroctracer64.so"
     "libroctx64.so"
     "libhipblaslt.so"
-    "libhipsparselt.so"
     "libhiprtc.so"
 )
 
@@ -187,28 +186,20 @@ do
     OS_SO_FILES[${#OS_SO_FILES[@]}]=$file_name # Append lib to array
 done
 
-ARCH=$(echo $PYTORCH_ROCM_ARCH | sed 's/;/|/g') # Replace ; separated arch list to bar for grep
-
 # rocBLAS library files
 ROCBLAS_LIB_SRC=$ROCM_HOME/lib/rocblas/library
 ROCBLAS_LIB_DST=lib/rocblas/library
-ROCBLAS_ARCH_SPECIFIC_FILES=$(ls $ROCBLAS_LIB_SRC | grep -E $ARCH)
-ROCBLAS_OTHER_FILES=$(ls $ROCBLAS_LIB_SRC | grep -v gfx)
-ROCBLAS_LIB_FILES=($ROCBLAS_ARCH_SPECIFIC_FILES $OTHER_FILES)
+ARCH=$(echo $PYTORCH_ROCM_ARCH | sed 's/;/|/g') # Replace ; seperated arch list to bar for grep
+ARCH_SPECIFIC_FILES=$(ls $ROCBLAS_LIB_SRC | grep -E $ARCH)
+OTHER_FILES=$(ls $ROCBLAS_LIB_SRC | grep -v gfx)
+ROCBLAS_LIB_FILES=($ARCH_SPECIFIC_FILES $OTHER_FILES)
 
 # hipblaslt library files
 HIPBLASLT_LIB_SRC=$ROCM_HOME/lib/hipblaslt/library
 HIPBLASLT_LIB_DST=lib/hipblaslt/library
-HIPBLASLT_ARCH_SPECIFIC_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -E $ARCH)
-HIPBLASLT_OTHER_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -v gfx)
-HIPBLASLT_LIB_FILES=($HIPBLASLT_ARCH_SPECIFIC_FILES $HIPBLASLT_OTHER_FILES)
-
-# hipsparselt library files
-HIPSPARSELT_LIB_SRC=$ROCM_HOME/lib/hipsparselt/library
-HIPSPARSELT_LIB_DST=lib/hipsparselt/library
-HIPSPARSELT_ARCH_SPECIFIC_FILES=$(ls $HIPSPARSELT_LIB_SRC | grep -E $ARCH)
-#HIPSPARSELT_OTHER_FILES=$(ls $HIPSPARSELT_LIB_SRC | grep -v gfx)
-HIPSPARSELT_LIB_FILES=($HIPSPARSELT_ARCH_SPECIFIC_FILES $HIPSPARSELT_OTHER_FILES)
+ARCH_SPECIFIC_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -E $ARCH)
+OTHER_FILES=$(ls $HIPBLASLT_LIB_SRC | grep -v gfx)
+HIPBLASLT_LIB_FILES=($ARCH_SPECIFIC_FILES $OTHER_FILES)
 
 # ROCm library files
 ROCM_SO_PATHS=()
@@ -243,14 +234,12 @@ DEPS_SONAME=(
 DEPS_AUX_SRCLIST=(
     "${ROCBLAS_LIB_FILES[@]/#/$ROCBLAS_LIB_SRC/}"
     "${HIPBLASLT_LIB_FILES[@]/#/$HIPBLASLT_LIB_SRC/}"
-    "${HIPSPARSELT_LIB_FILES[@]/#/$HIPSPARSELT_LIB_SRC/}"
     "/opt/amdgpu/share/libdrm/amdgpu.ids"
 )
 
 DEPS_AUX_DSTLIST=(
     "${ROCBLAS_LIB_FILES[@]/#/$ROCBLAS_LIB_DST/}"
     "${HIPBLASLT_LIB_FILES[@]/#/$HIPBLASLT_LIB_DST/}"
-    "${HIPSPARSELT_LIB_FILES[@]/#/$HIPSPARSELT_LIB_DST/}"
     "share/libdrm/amdgpu.ids"
 )
 

.ci/manywheel/build_xpu.sh

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

.ci/onnx/README.md

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

.ci/onnx/test.sh

@@ -19,7 +19,7 @@ git config --global --add safe.directory /var/lib/jenkins/workspace
 
 if [[ "$BUILD_ENVIRONMENT" == *onnx* ]]; then
   # TODO: This can be removed later once vision is also part of the Docker image
-  pip install -q --no-use-pep517 "git+https://github.com/pytorch/vision.git@$(cat .github/ci_commit_pins/vision.txt)"
+  pip install -q --user --no-use-pep517 "git+https://github.com/pytorch/vision.git@$(cat .github/ci_commit_pins/vision.txt)"
   # JIT C++ extensions require ninja, so put it into PATH.
   export PATH="/var/lib/jenkins/.local/bin:$PATH"
   # NB: ONNX test is fast (~15m) so it's ok to retry it few more times to avoid any flaky issue, we

.ci/pytorch/build.sh

@@ -27,12 +27,6 @@ cmake --version
 echo "Environment variables:"
 env
 
-# The sccache wrapped version of nvcc gets put in /opt/cache/lib in docker since
-# there are some issues if it is always wrapped, so we need to add it to PATH
-# during CI builds.
-# https://github.com/pytorch/pytorch/blob/0b6c0898e6c352c8ea93daec854e704b41485375/.ci/docker/common/install_cache.sh#L97
-export PATH="/opt/cache/lib:$PATH"
-
 if [[ "$BUILD_ENVIRONMENT" == *cuda* ]]; then
   # Use jemalloc during compilation to mitigate https://github.com/pytorch/pytorch/issues/116289
   export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.2
@@ -58,6 +52,12 @@ fi
 export USE_LLVM=/opt/llvm
 export LLVM_DIR=/opt/llvm/lib/cmake/llvm
 
+if [[ "$BUILD_ENVIRONMENT" == *executorch* ]]; then
+  # To build test_edge_op_registration
+  export BUILD_EXECUTORCH=ON
+  export USE_CUDA=0
+fi
+
 if ! which conda; then
   # In ROCm CIs, we are doing cross compilation on build machines with
   # intel cpu and later run tests on machines with amd cpu.
@@ -171,12 +171,6 @@ fi
 if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   # shellcheck disable=SC1091
   source /opt/intel/oneapi/compiler/latest/env/vars.sh
-  # shellcheck disable=SC1091
-  source /opt/intel/oneapi/ccl/latest/env/vars.sh
-  # shellcheck disable=SC1091
-  source /opt/intel/oneapi/mpi/latest/env/vars.sh
-  # Enable XCCL build
-  export USE_XCCL=1
   # XPU kineto feature dependencies are not fully ready, disable kineto build as temp WA
   export USE_KINETO=0
   export TORCH_XPU_ARCH_LIST=pvc
@@ -198,8 +192,10 @@ fi
 
 # We only build FlashAttention files for CUDA 8.0+, and they require large amounts of
 # memory to build and will OOM
-if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ 1 -eq $(echo "${TORCH_CUDA_ARCH_LIST} >= 8.0" | bc) ]]; then
-  export BUILD_CUSTOM_STEP="ninja -C build flash_attention -j 2"
+if [[ "$BUILD_ENVIRONMENT" == *cuda* ]] && [[ 1 -eq $(echo "${TORCH_CUDA_ARCH_LIST} >= 8.0" | bc) ]] && [ -z "$MAX_JOBS_OVERRIDE" ]; then
+  echo "WARNING: FlashAttention files require large amounts of memory to build and will OOM"
+  echo "Setting MAX_JOBS=(nproc-2)/3 to reduce memory usage"
+  export MAX_JOBS="$(( $(nproc --ignore=2) / 3 ))"
 fi
 
 if [[ "${BUILD_ENVIRONMENT}" == *clang* ]]; then
@@ -255,7 +251,6 @@ if [[ "$BUILD_ENVIRONMENT" == *-bazel-* ]]; then
   set -e -o pipefail
 
   get_bazel
-  python3 tools/optional_submodules.py checkout_eigen
 
   # Leave 1 CPU free and use only up to 80% of memory to reduce the change of crashing
   # the runner
@@ -393,8 +388,10 @@ else
     # This is an attempt to mitigate flaky libtorch build OOM error. By default, the build parallelization
     # is set to be the number of CPU minus 2. So, let's try a more conservative value here. A 4xlarge has
     # 16 CPUs
-    MAX_JOBS=$(nproc --ignore=4)
-    export MAX_JOBS
+    if [ -z "$MAX_JOBS_OVERRIDE" ]; then
+      MAX_JOBS=$(nproc --ignore=4)
+      export MAX_JOBS
+    fi
 
     # NB: Install outside of source directory (at the same level as the root
     # pytorch folder) so that it doesn't get cleaned away prior to docker push.

.ci/pytorch/check_binary.sh

@@ -302,22 +302,19 @@ except RuntimeError as e:
 fi
 
 ###############################################################################
-# Check for C++ ABI compatibility to GCC-11 - GCC 13
+# Check for C++ ABI compatibility to GCC-11
 ###############################################################################
 if [[ "$(uname)" == 'Linux' &&  "$PACKAGE_TYPE" == 'manywheel' ]]; then
   pushd /tmp
-  # Per https://gcc.gnu.org/onlinedocs/gcc/C_002b_002b-Dialect-Options.html
-  # gcc-11 is ABI16, gcc-13 is ABI18, gcc-14 is ABI19
-  # gcc 11 - CUDA 11.8, xpu, rocm
-  # gcc 13 - CUDA 12.6, 12.8 and cpu
-  # Please see issue for reference: https://github.com/pytorch/pytorch/issues/152426
-  if [[ "$(uname -m)" == "s390x" ]]; then
-    cxx_abi="19"
-  elif [[ "$DESIRED_CUDA" != 'xpu' && "$DESIRED_CUDA" != 'rocm'* ]]; then
-    cxx_abi="18"
-  else
-    cxx_abi="16"
+  # Per https://gcc.gnu.org/onlinedocs/gcc/C_002b_002b-Dialect-Options.html gcc-11 is ABI16
+  # Though manylinux_2.28 should have been build with gcc-14, per
+  # https://github.com/pypa/manylinux?tab=readme-ov-file#manylinux_2_28-almalinux-8-based
+  # On s390x gcc 14 is used because it contains fix for interaction
+  # between precompiled headers and vectorization builtins.
+  # This fix is not available in earlier gcc versions.
+  # gcc-14 uses ABI19.
+  if [[ "$(uname -m)" != "s390x" ]]; then
+    python -c "import torch; exit(0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi1016' else 1)"
   fi
-  python -c "import torch; exit(0 if torch._C._PYBIND11_BUILD_ABI == '_cxxabi10${cxx_abi}' else 1)"
   popd
 fi

.ci/pytorch/common-build.sh

@@ -13,13 +13,6 @@ if [[ "$BUILD_ENVIRONMENT" != *win-* ]]; then
     fi
 
     if which sccache > /dev/null; then
-        # Clear SCCACHE_BUCKET and SCCACHE_REGION if they are empty, otherwise
-        # sccache will complain about invalid bucket configuration
-        if [[ -z "${SCCACHE_BUCKET:-}" ]]; then
-          unset SCCACHE_BUCKET
-          unset SCCACHE_REGION
-        fi
-
         # Save sccache logs to file
         sccache --stop-server > /dev/null  2>&1 || true
         rm -f ~/sccache_error.log || true

.ci/pytorch/common.sh

@@ -13,8 +13,12 @@ if [[ "${BUILD_ENVIRONMENT}" == *rocm* ]]; then
   # HIP_PLATFORM is auto-detected by hipcc; unset to avoid build errors
   unset HIP_PLATFORM
   export PYTORCH_TEST_WITH_ROCM=1
+  # temporary to locate some kernel issues on the CI nodes
+  export HSAKMT_DEBUG_LEVEL=4
+  # improve rccl performance for distributed tests
+  export HSA_FORCE_FINE_GRAIN_PCIE=1
 fi
 
-# TODO: Reenable libtorch testing for MacOS, see https://github.com/pytorch/pytorch/issues/62598
+# TODO: Renable libtorch testing for MacOS, see https://github.com/pytorch/pytorch/issues/62598
 # shellcheck disable=SC2034
 BUILD_TEST_LIBTORCH=0

.ci/pytorch/common_utils.sh

@@ -127,9 +127,9 @@ function install_torchaudio() {
   if [[ "$1" == "cuda" ]]; then
     # TODO: This is better to be passed as a parameter from _linux-test workflow
     # so that it can be consistent with what is set in build
-    TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install --no-use-pep517 "git+https://github.com/pytorch/audio.git@${commit}"
+    TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install --no-use-pep517 --user "git+https://github.com/pytorch/audio.git@${commit}"
   else
-    pip_install --no-use-pep517 "git+https://github.com/pytorch/audio.git@${commit}"
+    pip_install --no-use-pep517 --user "git+https://github.com/pytorch/audio.git@${commit}"
   fi
 
 }
@@ -139,8 +139,8 @@ function install_torchtext() {
   local text_commit
   data_commit=$(get_pinned_commit data)
   text_commit=$(get_pinned_commit text)
-  pip_install --no-use-pep517 "git+https://github.com/pytorch/data.git@${data_commit}"
-  pip_install --no-use-pep517 "git+https://github.com/pytorch/text.git@${text_commit}"
+  pip_install --no-use-pep517 --user "git+https://github.com/pytorch/data.git@${data_commit}"
+  pip_install --no-use-pep517 --user "git+https://github.com/pytorch/text.git@${text_commit}"
 }
 
 function install_torchvision() {
@@ -153,12 +153,17 @@ function install_torchvision() {
     echo 'char* dlerror(void) { return "";}'|gcc -fpic -shared -o "${HOME}/dlerror.so" -x c -
     LD_PRELOAD=${orig_preload}:${HOME}/dlerror.so
   fi
-  pip_install --no-use-pep517 "git+https://github.com/pytorch/vision.git@${commit}"
+  pip_install --no-use-pep517 --user "git+https://github.com/pytorch/vision.git@${commit}"
   if [ -n "${LD_PRELOAD}" ]; then
     LD_PRELOAD=${orig_preload}
   fi
 }
 
+function install_tlparse() {
+  pip_install --user "tlparse==0.3.30"
+  PATH="$(python -m site --user-base)/bin:$PATH"
+}
+
 function install_torchrec_and_fbgemm() {
   local torchrec_commit
   torchrec_commit=$(get_pinned_commit torchrec)
@@ -173,7 +178,7 @@ function install_torchrec_and_fbgemm() {
 
   if [[ "$BUILD_ENVIRONMENT" == *rocm* ]] ; then
     # install torchrec first because it installs fbgemm nightly on top of rocm fbgemm
-    pip_install --no-use-pep517 "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
+    pip_install --no-use-pep517 --user "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
     pip_uninstall fbgemm-gpu-nightly
 
     pip_install tabulate  # needed for newer fbgemm
@@ -190,8 +195,8 @@ function install_torchrec_and_fbgemm() {
     rm -rf fbgemm
   else
     # See https://github.com/pytorch/pytorch/issues/106971
-    CUDA_PATH=/usr/local/cuda-12.1 pip_install --no-use-pep517 "git+https://github.com/pytorch/FBGEMM.git@${fbgemm_commit}#egg=fbgemm-gpu&subdirectory=fbgemm_gpu"
-    pip_install --no-use-pep517 "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
+    CUDA_PATH=/usr/local/cuda-12.1 pip_install --no-use-pep517 --user "git+https://github.com/pytorch/FBGEMM.git@${fbgemm_commit}#egg=fbgemm-gpu&subdirectory=fbgemm_gpu"
+    pip_install --no-use-pep517 --user "git+https://github.com/pytorch/torchrec.git@${torchrec_commit}"
   fi
 }
 
@@ -234,7 +239,7 @@ function checkout_install_torchbench() {
 function install_torchao() {
   local commit
   commit=$(get_pinned_commit torchao)
-  pip_install --no-use-pep517 "git+https://github.com/pytorch/ao.git@${commit}"
+  pip_install --no-use-pep517 --user "git+https://github.com/pytorch/ao.git@${commit}"
 }
 
 function print_sccache_stats() {

.ci/pytorch/cpp_doc_push_script.sh

@@ -58,7 +58,6 @@ time python tools/setup_helpers/generate_code.py \
 
 # Build the docs
 pushd docs/cpp
-pip install -e git+https://github.com/pytorch/pytorch_sphinx_theme.git@pytorch_sphinx_theme2#egg=pytorch_sphinx_theme2
 time make VERBOSE=1 html -j
 
 popd

.ci/pytorch/functorch_doc_push_script.sh

@@ -12,7 +12,6 @@ echo "version: $version"
 
 # Build functorch docs
 pushd $pt_checkout/functorch/docs
-pip install -e git+https://github.com/pytorch/pytorch_sphinx_theme.git@pytorch_sphinx_theme2#egg=pytorch_sphinx_theme2
 make html
 popd
 

.ci/pytorch/install_cache_xla.sh

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

.ci/pytorch/macos-build.sh

@@ -40,7 +40,7 @@ if [[ ${BUILD_ENVIRONMENT} == *"distributed"* ]]; then
 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 setup.py bdist_wheel --plat-name macosx_11_0_arm64
+  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
 fi
 if which sccache > /dev/null; then
   print_sccache_stats

.ci/pytorch/macos-common.sh

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

.ci/pytorch/macos-test.sh

@@ -5,6 +5,11 @@ set -x
 # shellcheck source=./macos-common.sh
 source "$(dirname "${BASH_SOURCE[0]}")/macos-common.sh"
 
+if [[ -n "$CONDA_ENV" ]]; then
+  # Use binaries under conda environment
+  export PATH="$CONDA_ENV/bin":$PATH
+fi
+
 # Test that OpenMP is enabled
 pushd test
 if [[ ! $(python -c "import torch; print(int(torch.backends.openmp.is_available()))") == "1" ]]; then
@@ -37,16 +42,6 @@ test_python_all() {
   assert_git_not_dirty
 }
 
-test_python_mps() {
-  setup_test_python
-
-  time python test/run_test.py --verbose --mps
-  MTL_CAPTURE_ENABLED=1 ${CONDA_RUN} python3 test/test_mps.py --verbose -k test_metal_capture
-
-  assert_git_not_dirty
-}
-
-
 test_python_shard() {
   if [[ -z "$NUM_TEST_SHARDS" ]]; then
     echo "NUM_TEST_SHARDS must be defined to run a Python test shard"
@@ -160,7 +155,6 @@ test_jit_hooks() {
 torchbench_setup_macos() {
   git clone --recursive https://github.com/pytorch/vision torchvision
   git clone --recursive https://github.com/pytorch/audio torchaudio
-  brew install jpeg-turbo libpng
 
   pushd torchvision
   git fetch
@@ -175,8 +169,7 @@ torchbench_setup_macos() {
   git checkout "$(cat ../.github/ci_commit_pins/audio.txt)"
   git submodule update --init --recursive
   python setup.py clean
-  #TODO: Remove me, when figure out how to make TorchAudio find brew installed openmp
-  USE_OPENMP=0 python setup.py develop
+  python setup.py develop
   popd
 
   # Shellcheck doesn't like it when you pass no arguments to a function that can take args. See https://www.shellcheck.net/wiki/SC2120
@@ -184,8 +177,9 @@ torchbench_setup_macos() {
   checkout_install_torchbench
 }
 
-pip_benchmark_deps() {
-  python -mpip install --no-input requests cython scikit-learn six
+conda_benchmark_deps() {
+  conda install -y astunparse numpy scipy ninja pyyaml setuptools cmake typing-extensions requests protobuf numba cython scikit-learn
+  conda install -y -c conda-forge librosa
 }
 
 
@@ -193,7 +187,7 @@ test_torchbench_perf() {
   print_cmake_info
 
   echo "Launching torchbench setup"
-  pip_benchmark_deps
+  conda_benchmark_deps
   torchbench_setup_macos
 
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
@@ -220,7 +214,7 @@ test_torchbench_smoketest() {
   print_cmake_info
 
   echo "Launching torchbench setup"
-  pip_benchmark_deps
+  conda_benchmark_deps
   # shellcheck disable=SC2119,SC2120
   torchbench_setup_macos
 
@@ -228,52 +222,37 @@ test_torchbench_smoketest() {
   mkdir -p "$TEST_REPORTS_DIR"
 
   local device=mps
-  local dtypes=(undefined float16 bfloat16 notset)
-  local dtype=${dtypes[$1]}
-  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)
+  local models=(hf_T5 llama BERT_pytorch dcgan hf_GPT2 yolov3 resnet152 sam pytorch_unet stable_diffusion_text_encoder moco speech_transformer)
 
   for backend in eager inductor; do
 
-    echo "Launching torchbench inference performance run for backend ${backend} and dtype ${dtype}"
-    local dtype_arg="--${dtype}"
-    if [ "$dtype" == notset ]; then
-        dtype_arg="--float32"
-    fi
-    touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
-    for model in "${models[@]}"; do
-      PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-        --performance --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
-        --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv" || true
-      if [ "$backend" == "inductor" ]; then
-        PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-          --accuracy --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
-          --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_accuracy.csv" || true
-      fi
-    done
-    if [ "$backend" == "inductor" ]; then
-      PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/huggingface.py \
-        --performance --backend "$backend" --inference --devices "$device" "$dtype_arg" \
-        --output "$TEST_REPORTS_DIR/inductor_${backend}_huggingface_${dtype}_inference_${device}_performance.csv" || true
-      PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/huggingface.py \
-        --accuracy --backend "$backend" --inference --devices "$device" "$dtype_arg" \
-        --output "$TEST_REPORTS_DIR/inductor_${backend}_huggingface_${dtype}_inference_${device}_accuracy.csv" || true
-    fi
-
-    if [ "$dtype" == notset ]; then
-      for dtype_ in notset amp; do
-        echo "Launching torchbench training performance run for backend ${backend} and dtype ${dtype_}"
-        touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype_}_training_${device}_performance.csv"
-        local dtype_arg="--${dtype_}"
-        if [ "$dtype_" == notset ]; then
+    for dtype in notset float16 bfloat16; do
+      echo "Launching torchbench inference performance run for backend ${backend} and dtype ${dtype}"
+      local dtype_arg="--${dtype}"
+      if [ "$dtype" == notset ]; then
           dtype_arg="--float32"
-        fi
-        for model in "${models[@]}"; do
-          PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
-            --performance --only "$model" --backend "$backend" --training --devices "$device" "$dtype_arg" \
-            --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype_}_training_${device}_performance.csv" || true
-        done
+      fi
+      touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv"
+      for model in "${models[@]}"; do
+        PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
+          --performance --only "$model" --backend "$backend" --inference --devices "$device" "$dtype_arg" \
+          --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_inference_${device}_performance.csv" || true
       done
-    fi
+    done
+
+    for dtype in notset amp; do
+      echo "Launching torchbench training performance run for backend ${backend} and dtype ${dtype}"
+      touch "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv"
+      local dtype_arg="--${dtype}"
+      if [ "$dtype" == notset ]; then
+          dtype_arg="--float32"
+      fi
+      for model in "${models[@]}"; do
+        PYTHONPATH="$(pwd)"/torchbench python benchmarks/dynamo/torchbench.py \
+          --performance --only "$model" --backend "$backend" --training --devices "$device" "$dtype_arg" \
+          --output "$TEST_REPORTS_DIR/inductor_${backend}_torchbench_${dtype}_training_${device}_performance.csv" || true
+      done
+    done
 
   done
 
@@ -284,7 +263,7 @@ test_hf_perf() {
   print_cmake_info
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
-  pip_benchmark_deps
+  conda_benchmark_deps
   torchbench_setup_macos
 
   echo "Launching HuggingFace training perf run"
@@ -300,7 +279,7 @@ test_timm_perf() {
   print_cmake_info
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
-  pip_benchmark_deps
+  conda_benchmark_deps
   torchbench_setup_macos
 
   echo "Launching timm training perf run"
@@ -312,6 +291,8 @@ test_timm_perf() {
   echo "timm benchmark on mps device completed"
 }
 
+install_tlparse
+
 if [[ $TEST_CONFIG == *"perf_all"* ]]; then
   test_torchbench_perf
   test_hf_perf
@@ -323,9 +304,7 @@ elif [[ $TEST_CONFIG == *"perf_hf"* ]]; then
 elif [[ $TEST_CONFIG == *"perf_timm"* ]]; then
   test_timm_perf
 elif [[ $TEST_CONFIG == *"perf_smoketest"* ]]; then
-  test_torchbench_smoketest "${SHARD_NUMBER}"
-elif [[ $TEST_CONFIG == *"mps"* ]]; then
-  test_python_mps
+  test_torchbench_smoketest
 elif [[ $NUM_TEST_SHARDS -gt 1 ]]; then
   test_python_shard "${SHARD_NUMBER}"
   if [[ "${SHARD_NUMBER}" == 1 ]]; then

.ci/pytorch/perf_test/common.sh

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

.ci/pytorch/perf_test/compare_with_baseline.py

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

.ci/pytorch/perf_test/get_stats.py

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

.ci/pytorch/perf_test/test_cpu_speed_mini_sequence_labeler.sh

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

.ci/pytorch/perf_test/test_cpu_speed_mnist.sh

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

.ci/pytorch/perf_test/test_cpu_speed_torch.sh

@@ -0,0 +1,29 @@
+#!/bin/bash
+
+. ./common.sh
+
+test_cpu_speed_torch () {
+  echo "Testing: torch.*, CPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/yf225/perf-tests.git
+
+  if [ "$1" == "compare_with_baseline" ]; then
+    export ARGS=(--compare ../cpu_runtime.json)
+  elif [ "$1" == "compare_and_update" ]; then
+    export ARGS=(--compare ../cpu_runtime.json --update ../new_cpu_runtime.json)
+  elif [ "$1" == "update_only" ]; then
+    export ARGS=(--update ../new_cpu_runtime.json)
+  fi
+
+  if ! python perf-tests/modules/test_cpu_torch.py "${ARGS[@]}"; then
+    echo "To reproduce this regression, run \`cd .ci/pytorch/perf_test/ && bash ${FUNCNAME[0]}.sh\` on your local machine and compare the runtime before/after your code change."
+    exit 1
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_cpu_speed_torch "$@"
+fi

.ci/pytorch/perf_test/test_cpu_speed_torch_tensor.sh

@@ -0,0 +1,29 @@
+#!/bin/bash
+
+. ./common.sh
+
+test_cpu_speed_torch_tensor () {
+  echo "Testing: torch.Tensor.*, CPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/yf225/perf-tests.git
+
+  if [ "$1" == "compare_with_baseline" ]; then
+    export ARGS=(--compare ../cpu_runtime.json)
+  elif [ "$1" == "compare_and_update" ]; then
+    export ARGS=(--compare ../cpu_runtime.json --update ../new_cpu_runtime.json)
+  elif [ "$1" == "update_only" ]; then
+    export ARGS=(--update ../new_cpu_runtime.json)
+  fi
+
+  if ! python perf-tests/modules/test_cpu_torch_tensor.py "${ARGS[@]}"; then
+    echo "To reproduce this regression, run \`cd .ci/pytorch/perf_test/ && bash ${FUNCNAME[0]}.sh\` on your local machine and compare the runtime before/after your code change."
+    exit 1
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_cpu_speed_torch_tensor "$@"
+fi

.ci/pytorch/perf_test/test_gpu_speed_cudnn_lstm.sh

@@ -0,0 +1,44 @@
+#!/bin/bash
+set -e
+
+. ./common.sh
+
+test_gpu_speed_cudnn_lstm () {
+  echo "Testing: CuDNN LSTM, GPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/pytorch/benchmark.git
+
+  cd benchmark/
+
+  git checkout 43dfb2c0370e70ef37f249dc09aff9f0ccd2ddb0
+
+  cd scripts/
+
+  SAMPLE_ARRAY=()
+  NUM_RUNS=$1
+
+  for (( i=1; i<=NUM_RUNS; i++ )) do
+    runtime=$(get_runtime_of_command python cudnn_lstm.py --skip-cpu-governor-check)
+    echo "$runtime"
+    SAMPLE_ARRAY+=("${runtime}")
+  done
+
+  cd ../..
+
+  stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
+  echo "Runtime stats in seconds:"
+  echo "$stats"
+
+  if [ "$2" == "compare_with_baseline" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
+  elif [ "$2" == "compare_and_update" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_gpu_speed_cudnn_lstm "$@"
+fi

.ci/pytorch/perf_test/test_gpu_speed_lstm.sh

@@ -0,0 +1,44 @@
+#!/bin/bash
+set -e
+
+. ./common.sh
+
+test_gpu_speed_lstm () {
+  echo "Testing: LSTM, GPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/pytorch/benchmark.git
+
+  cd benchmark/
+
+  git checkout 43dfb2c0370e70ef37f249dc09aff9f0ccd2ddb0
+
+  cd scripts/
+
+  SAMPLE_ARRAY=()
+  NUM_RUNS=$1
+
+  for (( i=1; i<=NUM_RUNS; i++ )) do
+    runtime=$(get_runtime_of_command python lstm.py --skip-cpu-governor-check)
+    echo "$runtime"
+    SAMPLE_ARRAY+=("${runtime}")
+  done
+
+  cd ../..
+
+  stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
+  echo "Runtime stats in seconds:"
+  echo "$stats"
+
+  if [ "$2" == "compare_with_baseline" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
+  elif [ "$2" == "compare_and_update" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_gpu_speed_lstm "$@"
+fi

.ci/pytorch/perf_test/test_gpu_speed_mlstm.sh

@@ -0,0 +1,44 @@
+#!/bin/bash
+set -e
+
+. ./common.sh
+
+test_gpu_speed_mlstm () {
+  echo "Testing: MLSTM, GPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/pytorch/benchmark.git
+
+  cd benchmark/
+
+  git checkout 43dfb2c0370e70ef37f249dc09aff9f0ccd2ddb0
+
+  cd scripts/
+
+  SAMPLE_ARRAY=()
+  NUM_RUNS=$1
+
+  for (( i=1; i<=NUM_RUNS; i++ )) do
+    runtime=$(get_runtime_of_command python mlstm.py --skip-cpu-governor-check)
+    echo "$runtime"
+    SAMPLE_ARRAY+=("${runtime}")
+  done
+
+  cd ../..
+
+  stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
+  echo "Runtime stats in seconds:"
+  echo "$stats"
+
+  if [ "$2" == "compare_with_baseline" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
+  elif [ "$2" == "compare_and_update" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_gpu_speed_mlstm "$@"
+fi

.ci/pytorch/perf_test/test_gpu_speed_mnist.sh

@@ -0,0 +1,48 @@
+#!/bin/bash
+set -e
+
+. ./common.sh
+
+test_gpu_speed_mnist () {
+  echo "Testing: MNIST, GPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/pytorch/examples.git -b perftests
+
+  cd examples/mnist
+
+  conda install -c pytorch torchvision
+
+  # Download data
+  python main.py --epochs 0
+
+  SAMPLE_ARRAY=()
+  NUM_RUNS=$1
+
+  # Needs warm up to get accurate number
+  python main.py --epochs 1 --no-log
+
+  for (( i=1; i<=NUM_RUNS; i++ )) do
+    runtime=$(get_runtime_of_command python main.py --epochs 1 --no-log)
+    echo "$runtime"
+    SAMPLE_ARRAY+=("${runtime}")
+  done
+
+  cd ../..
+
+  stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
+  echo "Runtime stats in seconds:"
+  echo "$stats"
+
+  if [ "$2" == "compare_with_baseline" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
+  elif [ "$2" == "compare_and_update" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_gpu_speed_mnist "$@"
+fi

.ci/pytorch/perf_test/test_gpu_speed_word_language_model.sh

@@ -0,0 +1,53 @@
+#!/bin/bash
+set -e
+
+. ./common.sh
+
+test_gpu_speed_word_language_model () {
+  echo "Testing: word language model on Wikitext-2, GPU"
+
+  export OMP_NUM_THREADS=4
+  export MKL_NUM_THREADS=4
+
+  git clone https://github.com/pytorch/examples.git -b perftests
+
+  cd examples/word_language_model
+
+  cd data/wikitext-2
+
+  # Reduce dataset size, so that we can have more runs per test
+  sed -n '1,200p' test.txt > test_tmp.txt
+  sed -n '1,1000p' train.txt > train_tmp.txt
+  sed -n '1,200p' valid.txt > valid_tmp.txt
+
+  mv test_tmp.txt test.txt
+  mv train_tmp.txt train.txt
+  mv valid_tmp.txt valid.txt
+
+  cd ../..
+
+  SAMPLE_ARRAY=()
+  NUM_RUNS=$1
+
+  for (( i=1; i<=NUM_RUNS; i++ )) do
+    runtime=$(get_runtime_of_command python main.py --cuda --epochs 1)
+    echo "$runtime"
+    SAMPLE_ARRAY+=("${runtime}")
+  done
+
+  cd ../..
+
+  stats=$(python ../get_stats.py "${SAMPLE_ARRAY[@]}")
+  echo "Runtime stats in seconds:"
+  echo "$stats"
+
+  if [ "$2" == "compare_with_baseline" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}"
+  elif [ "$2" == "compare_and_update" ]; then
+    python ../compare_with_baseline.py --test-name "${FUNCNAME[0]}" --sample-stats "${stats}" --update
+  fi
+}
+
+if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
+  run_test test_gpu_speed_word_language_model "$@"
+fi

.ci/pytorch/perf_test/update_commit_hash.py

@@ -0,0 +1,14 @@
+import json
+import sys
+
+
+data_file_path = sys.argv[1]
+commit_hash = sys.argv[2]
+
+with open(data_file_path) as data_file:
+    data = json.load(data_file)
+
+data["commit"] = commit_hash
+
+with open(data_file_path, "w") as data_file:
+    json.dump(data, data_file)

.ci/pytorch/python_doc_push_script.sh

@@ -46,7 +46,7 @@ echo "error: python_doc_push_script.sh: branch (arg3) not specified"
 fi
 
 echo "install_path: $install_path  version: $version"
-pip install -e git+https://github.com/pytorch/pytorch_sphinx_theme.git@pytorch_sphinx_theme2#egg=pytorch_sphinx_theme2
+
 
 build_docs () {
   set +e

.ci/pytorch/run_tests.sh

@@ -76,7 +76,7 @@ fi
 # Environment initialization
 if [[ "$(uname)" == Darwin ]]; then
     # Install the testing dependencies
-    retry pip install -q future hypothesis ${NUMPY_PACKAGE} ${PROTOBUF_PACKAGE} pytest setuptools six typing_extensions pyyaml
+    retry conda install -yq future hypothesis ${NUMPY_PACKAGE} ${PROTOBUF_PACKAGE} pytest setuptools six typing_extensions pyyaml
 else
     retry pip install -qr requirements.txt || true
     retry pip install -q hypothesis protobuf pytest setuptools || true
@@ -91,6 +91,7 @@ fi
 
 echo "Testing with:"
 pip freeze
+conda list || true
 
 ##############################################################################
 # Smoke tests

.ci/pytorch/short-perf-test-cpu.sh

@@ -0,0 +1,71 @@
+#!/bin/bash
+
+SCRIPT_PARENT_DIR=$(dirname "${BASH_SOURCE[0]}")
+
+# shellcheck source=.ci/pytorch/common.sh
+source "$SCRIPT_PARENT_DIR/common.sh"
+
+cd .ci/pytorch/perf_test
+
+echo "Running CPU perf test for PyTorch..."
+
+pip install -q awscli
+
+# Set multipart_threshold to be sufficiently high, so that `aws s3 cp` is not a multipart read
+# More info at https://github.com/aws/aws-cli/issues/2321
+aws configure set default.s3.multipart_threshold 5GB
+UPSTREAM_DEFAULT_BRANCH="$(git remote show https://github.com/pytorch/pytorch.git | awk '/HEAD branch/ {print $NF}')"
+
+if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
+    # Get current default branch commit hash
+    DEFAULT_BRANCH_COMMIT_ID=$(git log --format="%H" -n 1)
+    export DEFAULT_BRANCH_COMMIT_ID
+fi
+
+# Find the default branch commit to test against
+git remote add upstream https://github.com/pytorch/pytorch.git
+git fetch upstream
+IFS=$'\n'
+while IFS='' read -r commit_id; do
+    if aws s3 ls s3://ossci-perf-test/pytorch/cpu_runtime/"${commit_id}".json; then
+        LATEST_TESTED_COMMIT=${commit_id}
+        break
+    fi
+done < <(git rev-list upstream/"$UPSTREAM_DEFAULT_BRANCH")
+aws s3 cp s3://ossci-perf-test/pytorch/cpu_runtime/"${LATEST_TESTED_COMMIT}".json cpu_runtime.json
+
+if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
+    # Prepare new baseline file
+    cp cpu_runtime.json new_cpu_runtime.json
+    python update_commit_hash.py new_cpu_runtime.json "${DEFAULT_BRANCH_COMMIT_ID}"
+fi
+
+# Include tests
+# shellcheck source=./perf_test/test_cpu_speed_mini_sequence_labeler.sh
+. ./test_cpu_speed_mini_sequence_labeler.sh
+# shellcheck source=./perf_test/test_cpu_speed_mnist.sh
+. ./test_cpu_speed_mnist.sh
+# shellcheck source=./perf_test/test_cpu_speed_torch.sh
+. ./test_cpu_speed_torch.sh
+# shellcheck source=./perf_test/test_cpu_speed_torch_tensor.sh
+. ./test_cpu_speed_torch_tensor.sh
+
+# Run tests
+export TEST_MODE="compare_with_baseline"
+if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
+    export TEST_MODE="compare_and_update"
+fi
+
+# Operator tests
+run_test test_cpu_speed_torch ${TEST_MODE}
+run_test test_cpu_speed_torch_tensor ${TEST_MODE}
+
+# Sample model tests
+run_test test_cpu_speed_mini_sequence_labeler 20 ${TEST_MODE}
+run_test test_cpu_speed_mnist 20 ${TEST_MODE}
+
+if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
+    # This could cause race condition if we are testing the same default branch commit twice,
+    # but the chance of them executing this line at the same time is low.
+    aws s3 cp new_cpu_runtime.json s3://ossci-perf-test/pytorch/cpu_runtime/"${DEFAULT_BRANCH_COMMIT_ID}".json --acl public-read
+fi

.ci/pytorch/short-perf-test-gpu.sh

@@ -0,0 +1,76 @@
+#!/bin/bash
+
+# shellcheck source=./common.sh
+source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
+
+pushd .ci/pytorch/perf_test
+
+echo "Running GPU perf test for PyTorch..."
+
+# Trying to uninstall PyYAML can cause problem. Workaround according to:
+# https://github.com/pypa/pip/issues/5247#issuecomment-415571153
+pip install -q awscli --ignore-installed PyYAML
+
+# Set multipart_threshold to be sufficiently high, so that `aws s3 cp` is not a multipart read
+# More info at https://github.com/aws/aws-cli/issues/2321
+aws configure set default.s3.multipart_threshold 5GB
+UPSTREAM_DEFAULT_BRANCH="$(git remote show https://github.com/pytorch/pytorch.git | awk '/HEAD branch/ {print $NF}')"
+
+if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
+    # Get current default branch commit hash
+    DEFAULT_BRANCH_COMMIT_ID=$(git log --format="%H" -n 1)
+    export DEFAULT_BRANCH_COMMIT_ID
+fi
+
+# Find the default branch commit to test against
+git remote add upstream https://github.com/pytorch/pytorch.git
+git fetch upstream
+IFS=$'\n'
+while IFS='' read -r commit_id; do
+    if aws s3 ls s3://ossci-perf-test/pytorch/gpu_runtime/"${commit_id}".json; then
+        LATEST_TESTED_COMMIT=${commit_id}
+        break
+    fi
+done < <(git rev-list upstream/"$UPSTREAM_DEFAULT_BRANCH")
+aws s3 cp s3://ossci-perf-test/pytorch/gpu_runtime/"${LATEST_TESTED_COMMIT}".json gpu_runtime.json
+
+if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
+    # Prepare new baseline file
+    cp gpu_runtime.json new_gpu_runtime.json
+    python update_commit_hash.py new_gpu_runtime.json "${DEFAULT_BRANCH_COMMIT_ID}"
+fi
+
+# Include tests
+# shellcheck source=./perf_test/test_gpu_speed_mnist.sh
+. ./test_gpu_speed_mnist.sh
+# shellcheck source=./perf_test/test_gpu_speed_word_language_model.sh
+. ./test_gpu_speed_word_language_model.sh
+# shellcheck source=./perf_test/test_gpu_speed_cudnn_lstm.sh
+. ./test_gpu_speed_cudnn_lstm.sh
+# shellcheck source=./perf_test/test_gpu_speed_lstm.sh
+. ./test_gpu_speed_lstm.sh
+# shellcheck source=./perf_test/test_gpu_speed_mlstm.sh
+. ./test_gpu_speed_mlstm.sh
+
+# Run tests
+if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
+    run_test test_gpu_speed_mnist 20 compare_and_update
+    run_test test_gpu_speed_word_language_model 20 compare_and_update
+    run_test test_gpu_speed_cudnn_lstm 20 compare_and_update
+    run_test test_gpu_speed_lstm 20 compare_and_update
+    run_test test_gpu_speed_mlstm 20 compare_and_update
+else
+    run_test test_gpu_speed_mnist 20 compare_with_baseline
+    run_test test_gpu_speed_word_language_model 20 compare_with_baseline
+    run_test test_gpu_speed_cudnn_lstm 20 compare_with_baseline
+    run_test test_gpu_speed_lstm 20 compare_with_baseline
+    run_test test_gpu_speed_mlstm 20 compare_with_baseline
+fi
+
+if [[ "$COMMIT_SOURCE" == "$UPSTREAM_DEFAULT_BRANCH" ]]; then
+    # This could cause race condition if we are testing the same default branch commit twice,
+    # but the chance of them executing this line at the same time is low.
+    aws s3 cp new_gpu_runtime.json s3://ossci-perf-test/pytorch/gpu_runtime/"${DEFAULT_BRANCH_COMMIT_ID}".json --acl public-read
+fi
+
+popd

.ci/pytorch/smoke_test/check_binary_symbols.py

@@ -93,7 +93,7 @@ def check_lib_symbols_for_abi_correctness(lib: str) -> None:
             f"Found pre-cxx11 symbols, but there shouldn't be any, see: {pre_cxx11_symbols[:100]}"
         )
     if num_cxx11_symbols < 100:
-        raise RuntimeError("Didn't find enough cxx11 symbols")
+        raise RuntimeError("Didn't find enought cxx11 symbols")
 
 
 def main() -> None:

.ci/pytorch/smoke_test/check_gomp.py

@@ -1,77 +0,0 @@
-import ctypes
-import os
-import sys
-from pathlib import Path
-
-
-def get_gomp_thread():
-    """
-    Retrieves the maximum number of OpenMP threads after loading the `libgomp.so.1` library
-    and the `libtorch_cpu.so` library. It then queries the
-    maximum number of threads available for OpenMP parallel regions using the
-    `omp_get_max_threads` function.
-
-    Returns:
-        int: The maximum number of OpenMP threads available.
-
-    Notes:
-        - The function assumes the default path for `libgomp.so.1` on AlmaLinux OS.
-        - The path to `libtorch_cpu.so` is constructed based on the Python executable's
-          installation directory.
-        - This function is specific to environments where PyTorch and OpenMP are used
-          together and may require adjustments for other setups.
-    """
-    python_path = Path(sys.executable).resolve()
-    python_prefix = (
-        python_path.parent.parent
-    )  # Typically goes to the Python installation root
-
-    # Get the additional ABI flags (if any); it may be an empty string.
-    abiflags = getattr(sys, "abiflags", "")
-
-    # Construct the Python directory name correctly (e.g., "python3.13t").
-    python_version = (
-        f"python{sys.version_info.major}.{sys.version_info.minor}{abiflags}"
-    )
-
-    libtorch_cpu_path = (
-        python_prefix
-        / "lib"
-        / python_version
-        / "site-packages"
-        / "torch"
-        / "lib"
-        / "libtorch_cpu.so"
-    )
-
-    # use the default gomp path of AlmaLinux OS
-    libgomp_path = "/usr/lib64/libgomp.so.1"
-    # if it does not exist, try Ubuntu path
-    if not os.path.exists(libgomp_path):
-        libgomp_path = f"/usr/lib/{os.uname().machine}-linux-gnu/libgomp.so.1"
-
-    os.environ["GOMP_CPU_AFFINITY"] = "0-3"
-
-    libgomp = ctypes.CDLL(libgomp_path)
-    libgomp = ctypes.CDLL(libtorch_cpu_path)
-
-    libgomp.omp_get_max_threads.restype = ctypes.c_int
-    libgomp.omp_get_max_threads.argtypes = []
-
-    omp_max_threads = libgomp.omp_get_max_threads()
-    return omp_max_threads
-
-
-def main():
-    omp_max_threads = get_gomp_thread()
-    print(
-        f"omp_max_threads after loading libgomp.so and libtorch_cpu.so: {omp_max_threads}"
-    )
-    if omp_max_threads == 1:
-        raise RuntimeError(
-            "omp_max_threads is 1. Check whether libgomp.so is loaded twice."
-        )
-
-
-if __name__ == "__main__":
-    main()

.ci/pytorch/smoke_test/smoke_test.py

@@ -276,7 +276,7 @@ def smoke_test_cuda(
             torch_nccl_version = ".".join(str(v) for v in torch.cuda.nccl.version())
             print(f"Torch nccl; version: {torch_nccl_version}")
 
-        # Pypi dependencies are installed on linux only and nccl is available only on Linux.
+        # Pypi dependencies are installed on linux ony and nccl is availbale only on Linux.
         if pypi_pkg_check == "enabled" and sys.platform in ["linux", "linux2"]:
             compare_pypi_to_torch_versions(
                 "cudnn", find_pypi_package_version("nvidia-cudnn"), torch_cudnn_version

.ci/pytorch/test.sh

@@ -11,8 +11,6 @@ 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"
 
 # Do not change workspace permissions for ROCm and s390x CI jobs
 # as it can leave workspace with bad permissions for cancelled jobs
@@ -165,6 +163,8 @@ elif [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
   export PYTORCH_TESTING_DEVICE_ONLY_FOR="xpu"
   # setting PYTHON_TEST_EXTRA_OPTION
   export PYTHON_TEST_EXTRA_OPTION="--xpu"
+  # Disable sccache for xpu test due to flaky issue https://github.com/pytorch/pytorch/issues/143585
+  sudo rm -rf /opt/cache
 fi
 
 if [[ "$TEST_CONFIG" == *crossref* ]]; then
@@ -191,17 +191,13 @@ if [[ "$BUILD_ENVIRONMENT" == *xpu* ]]; then
     # shellcheck disable=SC1091
     source /opt/intel/oneapi/umf/latest/env/vars.sh
   fi
-  # shellcheck disable=SC1091
-  source /opt/intel/oneapi/ccl/latest/env/vars.sh
-  # shellcheck disable=SC1091
-  source /opt/intel/oneapi/mpi/latest/env/vars.sh
   # Check XPU status before testing
-  timeout 30 xpu-smi discovery || true
+  xpu-smi discovery
 fi
 
 if [[ "$BUILD_ENVIRONMENT" != *-bazel-* ]] ; then
   # JIT C++ extensions require ninja.
-  pip_install "ninja==1.10.2"
+  pip_install --user "ninja==1.10.2"
   # ninja is installed in $HOME/.local/bin, e.g., /var/lib/jenkins/.local/bin for CI user jenkins
   # but this script should be runnable by any user, including root
   export PATH="$HOME/.local/bin:$PATH"
@@ -212,6 +208,8 @@ if [[ "$BUILD_ENVIRONMENT" == *aarch64* ]]; then
   export VALGRIND=OFF
 fi
 
+install_tlparse
+
 # DANGER WILL ROBINSON.  The LD_PRELOAD here could cause you problems
 # if you're not careful.  Check this if you made some changes and the
 # ASAN test is not working
@@ -224,7 +222,7 @@ if [[ "$BUILD_ENVIRONMENT" == *asan* ]]; then
     export PYTORCH_TEST_WITH_ASAN=1
     export PYTORCH_TEST_WITH_UBSAN=1
     # TODO: Figure out how to avoid hard-coding these paths
-    export ASAN_SYMBOLIZER_PATH=/usr/lib/llvm-18/bin/llvm-symbolizer
+    export ASAN_SYMBOLIZER_PATH=/usr/lib/llvm-15/bin/llvm-symbolizer
     export TORCH_USE_RTLD_GLOBAL=1
     # NB: We load libtorch.so with RTLD_GLOBAL for UBSAN, unlike our
     # default behavior.
@@ -316,29 +314,6 @@ test_python() {
   assert_git_not_dirty
 }
 
-test_python_smoke() {
-  # 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
-}
-
-test_h100_distributed() {
-  # Distributed tests at H100
-  time python test/run_test.py --include distributed/_composable/test_composability/test_pp_composability.py  $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
-  # This test requires multicast support
-  time python test/run_test.py --include distributed/_composable/fsdp/test_fully_shard_comm.py -k TestFullyShardAllocFromPG $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
-  assert_git_not_dirty
-}
-
-test_h100_symm_mem() {
-  # symmetric memory test
-  time python test/run_test.py --include distributed/test_symmetric_memory.py  $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
-  time python test/run_test.py --include distributed/test_nvshmem.py $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
-  time python test/run_test.py --include distributed/test_nvshmem_triton.py $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
-  time python test/run_test.py --include distributed/test_nccl.py $PYTHON_TEST_EXTRA_OPTION --upload-artifacts-while-running
-  assert_git_not_dirty
-}
-
 test_lazy_tensor_meta_reference_disabled() {
   export TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1
   echo "Testing lazy tensor operations without meta reference"
@@ -353,7 +328,6 @@ test_dynamo_wrapped_shard() {
     exit 1
   fi
   python tools/dynamo/verify_dynamo.py
-  python tools/dynamo/gb_id_mapping.py verify
   # PLEASE DO NOT ADD ADDITIONAL EXCLUDES HERE.
   # Instead, use @skipIfTorchDynamo on your tests.
   time python test/run_test.py --dynamo \
@@ -368,24 +342,12 @@ test_dynamo_wrapped_shard() {
   assert_git_not_dirty
 }
 
-test_einops() {
-  pip install einops==0.6.1
-  time python test/run_test.py --einops --verbose --upload-artifacts-while-running
-  pip install einops==0.7.0
-  time python test/run_test.py --einops --verbose --upload-artifacts-while-running
-  pip install einops==0.8.1
-  time python test/run_test.py --einops --verbose --upload-artifacts-while-running
-  assert_git_not_dirty
-}
-
-
 test_inductor_distributed() {
   # Smuggle a few multi-gpu tests here so that we don't have to request another large node
   echo "Testing multi_gpu tests in test_torchinductor"
+  python test/run_test.py -i inductor/test_torchinductor.py -k test_multi_gpu --verbose
+  python test/run_test.py -i inductor/test_aot_inductor.py -k test_non_default_cuda_device --verbose
   python test/run_test.py -i inductor/test_aot_inductor.py -k test_replicate_on_devices --verbose
-  python test/run_test.py -i inductor/test_aot_inductor.py -k test_on_gpu_device1 --verbose
-  python test/run_test.py -i inductor/test_aot_inductor.py -k test_non_default_gpu_device --verbose
-  python test/run_test.py -i inductor/test_aot_inductor.py -k test_load_package_multiple_gpus --verbose
   python test/run_test.py -i distributed/test_c10d_functional_native.py --verbose
   python test/run_test.py -i distributed/tensor/test_dtensor_compile.py --verbose
   python test/run_test.py -i distributed/tensor/parallel/test_micro_pipeline_tp.py --verbose
@@ -436,22 +398,8 @@ test_inductor_aoti() {
     # 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 "${TEST_ENVS[@]}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference -dist=loadfile
+  BUILD_AOT_INDUCTOR_TEST=1 python setup.py develop
+  CPP_TESTS_DIR="${BUILD_BIN_DIR}" LD_LIBRARY_PATH="${TORCH_LIB_DIR}" python test/run_test.py --cpp --verbose -i cpp/test_aoti_abi_check cpp/test_aoti_inference
 }
 
 test_inductor_cpp_wrapper_shard() {
@@ -464,26 +412,46 @@ test_inductor_cpp_wrapper_shard() {
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
 
+  if [[ "$1" -eq "2" ]]; then
+    # For now, manually put the opinfo tests in shard 2, and all other tests in
+    # shard 1.  Test specific things triggering past bugs, for now.
+    python test/run_test.py \
+      --include inductor/test_torchinductor_opinfo \
+      -k 'linalg or to_sparse' \
+      --verbose
+    exit
+  fi
+
   # Run certain inductor unit tests with cpp wrapper. In the end state, we
   # should be able to run all the inductor unit tests with cpp_wrapper.
-  #
-  # TODO: I'm pretty sure that "TestInductorOpInfoCPU" is not a valid filter,
-  # but change that in another PR to more accurately monitor the increased CI
-  # usage.
-  python test/run_test.py \
-    --include inductor/test_torchinductor_opinfo \
-    -k 'linalg or to_sparse or TestInductorOpInfoCPU' \
-    --shard "$1" "$NUM_TEST_SHARDS" \
-    --verbose
   python test/run_test.py \
     --include inductor/test_torchinductor inductor/test_max_autotune inductor/test_cpu_repro \
-    --shard "$1" "$NUM_TEST_SHARDS" \
-    --verbose
-  python test/run_test.py --inductor \
-    --include test_torch \
-    -k 'take' \
-    --shard "$1" "$NUM_TEST_SHARDS" \
     --verbose
+  python test/run_test.py --inductor --include test_torch -k 'take' --verbose
+
+  # Run inductor benchmark tests with cpp wrapper.
+  # Skip benchmark tests if it's in rerun-disabled-mode.
+  if [[ "${PYTORCH_TEST_RERUN_DISABLED_TESTS}" == "1" ]]; then
+    echo "skip dynamo benchmark tests for rerun-disabled-test"
+  else
+    echo "run dynamo benchmark tests with cpp wrapper"
+    python benchmarks/dynamo/timm_models.py --device cuda --accuracy --amp \
+    --training --inductor --disable-cudagraphs --only vit_base_patch16_224 \
+    --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv"
+    python benchmarks/dynamo/check_accuracy.py \
+      --actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_training.csv" \
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}inductor_timm_training.csv"
+
+    python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
+      --bfloat16 --inference --inductor --only hf_T5 --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
+    python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
+      --bfloat16 --inference --inductor --only llama --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
+    python benchmarks/dynamo/torchbench.py --device cuda --accuracy \
+      --bfloat16 --inference --inductor --only moco --output "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv"
+    python benchmarks/dynamo/check_accuracy.py \
+      --actual "$TEST_REPORTS_DIR/inductor_cpp_wrapper_inference.csv" \
+      --expected "benchmarks/dynamo/ci_expected_accuracy/${MAYBE_ROCM}inductor_torchbench_inference.csv"
+  fi
 }
 
 # "Global" flags for inductor benchmarking controlled by TEST_CONFIG
@@ -496,7 +464,7 @@ DYNAMO_BENCHMARK_FLAGS=()
 
 pr_time_benchmarks() {
 
-  pip_install "fbscribelogger"
+  pip_install --user "fbscribelogger"
 
   TEST_REPORTS_DIR=$(pwd)/test/test-reports
   mkdir -p "$TEST_REPORTS_DIR"
@@ -604,9 +572,7 @@ test_perf_for_dashboard() {
 
   local device=cuda
   if [[ "${TEST_CONFIG}" == *cpu* ]]; then
-    if [[ "${TEST_CONFIG}" == *cpu_x86_zen* ]]; then
-      device=cpu_x86_zen
-    elif [[ "${TEST_CONFIG}" == *cpu_x86* ]]; then
+    if [[ "${TEST_CONFIG}" == *cpu_x86* ]]; then
       device=cpu_x86
     elif [[ "${TEST_CONFIG}" == *cpu_aarch64* ]]; then
       device=cpu_aarch64
@@ -622,11 +588,7 @@ test_perf_for_dashboard() {
 
   for mode in "${modes[@]}"; do
     if [[ "$mode" == "inference" ]]; then
-      if [[ "$device" == "cpu_x86" ]]; then
-        dtype=amp
-      else
-        dtype=bfloat16
-      fi
+      dtype=bfloat16
     elif [[ "$mode" == "training" ]]; then
       dtype=amp
     fi
@@ -638,10 +600,6 @@ test_perf_for_dashboard() {
         target_flag+=( --no-translation-validation)
       fi
 
-      if [[ "$DASHBOARD_TAG" == *freezing-true* ]]; then
-        target_flag+=( --freezing)
-      fi
-
       if [[ "$DASHBOARD_TAG" == *default-true* ]]; then
         $TASKSET python "benchmarks/dynamo/$suite.py" \
             "${target_flag[@]}" --"$mode" --"$dtype" --backend "$backend" --disable-cudagraphs "$@" \
@@ -844,7 +802,16 @@ test_inductor_torchbench_smoketest_perf() {
   done
 }
 
+test_inductor_get_core_number() {
+  if [[ "${TEST_CONFIG}" == *aarch64* ]]; then
+    echo "$(($(lscpu | grep 'Cluster(s):' | awk '{print $2}') * $(lscpu | grep 'Core(s) per cluster:' | awk '{print $4}')))"
+  else
+    echo "$(($(lscpu | grep 'Socket(s):' | awk '{print $2}') * $(lscpu | grep 'Core(s) per socket:' | awk '{print $4}')))"
+  fi
+}
+
 test_inductor_set_cpu_affinity(){
+  #set jemalloc
   JEMALLOC_LIB="$(find /usr/lib -name libjemalloc.so.2)"
   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"
@@ -856,23 +823,14 @@ test_inductor_set_cpu_affinity(){
     export KMP_AFFINITY=granularity=fine,compact,1,0
     export KMP_BLOCKTIME=1
   fi
-
-  # Use nproc here instead of lscpu because it takes into account cgroups slice
-  cpus=$(nproc)
-  thread_per_core=$(lscpu | grep 'Thread(s) per core:' | awk '{print $4}')
-  cores=$((cpus / thread_per_core))
-
-  # Set number of cores to 16 on aarch64 for performance runs
+  cores=$(test_inductor_get_core_number)
+  # Set number of cores to 16 on Aarch64 for performance runs.
   if [[ "${TEST_CONFIG}" == *aarch64* && $cores -gt 16 ]]; then
     cores=16
   fi
   export OMP_NUM_THREADS=$cores
-
-  # Handle cgroups slice start and end CPU
-  start_cpu=$(python -c 'import os; print(min(os.sched_getaffinity(0)))')
-  # Leaving one physical CPU for other tasks
-  end_cpu=$(($(python -c 'import os; print(max(os.sched_getaffinity(0)))') - thread_per_core))
-  export TASKSET="taskset -c $start_cpu-$end_cpu"
+  end_core=$((cores-1))
+  export TASKSET="taskset -c 0-$end_core"
 }
 
 test_inductor_torchbench_cpu_smoketest_perf(){
@@ -1155,12 +1113,6 @@ test_custom_backend() {
 
 test_custom_script_ops() {
   echo "Testing custom script operators"
-
-  if [[ "$BUILD_ENVIRONMENT" == *s390x* ]]; then
-    echo "Skipping custom script operators until it's fixed"
-    return 0
-  fi
-
   CUSTOM_OP_BUILD="${CUSTOM_TEST_ARTIFACT_BUILD_DIR}/custom-op-build"
   pushd test/custom_operator
   cp -a "$CUSTOM_OP_BUILD" build
@@ -1471,8 +1423,8 @@ test_bazel() {
 
 test_benchmarks() {
   if [[ "$BUILD_ENVIRONMENT" == *cuda* && $TEST_CONFIG != *nogpu* ]]; then
-    pip_install "pytest-benchmark==3.2.3"
-    pip_install "requests"
+    pip_install --user "pytest-benchmark==3.2.3"
+    pip_install --user "requests"
     BENCHMARK_DATA="benchmarks/.data"
     mkdir -p ${BENCHMARK_DATA}
     pytest benchmarks/fastrnns/test_bench.py --benchmark-sort=Name --benchmark-json=${BENCHMARK_DATA}/fastrnns_default.json --fuser=default --executor=default
@@ -1524,6 +1476,8 @@ test_executorch() {
   export PYTHON_EXECUTABLE=python
   export CMAKE_ARGS="-DEXECUTORCH_BUILD_PYBIND=ON -DEXECUTORCH_BUILD_XNNPACK=ON -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON"
 
+  # For llama3
+  bash examples/models/llama3_2_vision/install_requirements.sh
   # NB: We need to rebuild ExecuTorch runner here because it depends on PyTorch
   # from the PR
   bash .ci/scripts/setup-linux.sh --build-tool cmake
@@ -1550,7 +1504,7 @@ test_executorch() {
 test_linux_aarch64() {
   python test/run_test.py --include test_modules test_mkldnn test_mkldnn_fusion test_openmp test_torch test_dynamic_shapes \
         test_transformers test_multiprocessing test_numpy_interop test_autograd test_binary_ufuncs test_complex test_spectral_ops \
-        test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops test_cpp_extensions_open_device_registration \
+        test_foreach test_reductions test_unary_ufuncs test_tensor_creation_ops test_ops \
         --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
 
   # Dynamo tests
@@ -1566,7 +1520,7 @@ test_linux_aarch64() {
        inductor/test_inplacing_pass inductor/test_kernel_benchmark inductor/test_layout_optim \
        inductor/test_max_autotune inductor/test_memory_planning inductor/test_metrics inductor/test_multi_kernel inductor/test_pad_mm \
        inductor/test_pattern_matcher inductor/test_perf inductor/test_profiler inductor/test_select_algorithm inductor/test_smoke \
-       inductor/test_split_cat_fx_passes inductor/test_compile inductor/test_torchinductor \
+       inductor/test_split_cat_fx_passes inductor/test_standalone_compile inductor/test_torchinductor \
        inductor/test_torchinductor_codegen_dynamic_shapes inductor/test_torchinductor_dynamic_shapes inductor/test_memory \
        inductor/test_triton_cpu_backend inductor/test_triton_extension_backend inductor/test_mkldnn_pattern_matcher inductor/test_cpu_cpp_wrapper \
        --shard "$SHARD_NUMBER" "$NUM_TEST_SHARDS" --verbose
@@ -1580,12 +1534,11 @@ test_operator_benchmark() {
   test_inductor_set_cpu_affinity
 
   cd benchmarks/operator_benchmark/pt_extension
-  python -m pip install .
+  python setup.py install
 
   cd "${TEST_DIR}"/benchmarks/operator_benchmark
   $TASKSET python -m benchmark_all_test --device "$1" --tag-filter "$2" \
-      --output-csv "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.csv" \
-      --output-json-for-dashboard "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.json" \
+      --output-dir "${TEST_REPORTS_DIR}/operator_benchmark_eager_float32_cpu.csv"
 
   pip_install pandas
   python check_perf_csv.py \
@@ -1670,7 +1623,7 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
     install_torchaudio cuda
   fi
   install_torchvision
-  TORCH_CUDA_ARCH_LIST="8.0;8.6" install_torchao
+  TORCH_CUDA_ARCH_LIST="8.0;8.6" pip_install git+https://github.com/pytorch/ao.git
   id=$((SHARD_NUMBER-1))
   # https://github.com/opencv/opencv-python/issues/885
   pip_install opencv-python==4.8.0.74
@@ -1695,11 +1648,11 @@ elif [[ "${TEST_CONFIG}" == *torchbench* ]]; then
     PYTHONPATH=$(pwd)/torchbench test_dynamo_benchmark torchbench "$id"
   fi
 elif [[ "${TEST_CONFIG}" == *inductor_cpp_wrapper* ]]; then
+  install_torchaudio cuda
   install_torchvision
+  checkout_install_torchbench hf_T5 llama moco
   PYTHONPATH=$(pwd)/torchbench test_inductor_cpp_wrapper_shard "$SHARD_NUMBER"
-  if [[ "$SHARD_NUMBER" -eq "1" ]]; then
-    test_inductor_aoti
-  fi
+  test_inductor_aoti
 elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
   install_torchvision
   test_inductor_shard "${SHARD_NUMBER}"
@@ -1708,8 +1661,6 @@ elif [[ "${TEST_CONFIG}" == *inductor* ]]; then
       test_inductor_distributed
     fi
   fi
-elif [[ "${TEST_CONFIG}" == *einops* ]]; then
-  test_einops
 elif [[ "${TEST_CONFIG}" == *dynamo_wrapped* ]]; then
   install_torchvision
   test_dynamo_wrapped_shard "${SHARD_NUMBER}"
@@ -1755,12 +1706,6 @@ elif [[ "${BUILD_ENVIRONMENT}" == *xpu* ]]; then
   test_python
   test_aten
   test_xpu_bin
-elif [[ "${TEST_CONFIG}" == smoke ]]; then
-  test_python_smoke
-elif [[ "${TEST_CONFIG}" == h100_distributed ]]; then
-  test_h100_distributed
-elif [[ "${TEST_CONFIG}" == "h100-symm-mem" ]]; then
-  test_h100_symm_mem
 else
   install_torchvision
   install_monkeytype

.ci/pytorch/win-build.sh

@@ -31,7 +31,7 @@ PYLONG_API_CHECK=$?
 if [[ $PYLONG_API_CHECK == 0 ]]; then
   echo "Usage of PyLong_{From,As}{Unsigned}Long API may lead to overflow errors on Windows"
   echo "because \`sizeof(long) == 4\` and \`sizeof(unsigned long) == 4\`."
-  echo "Please include \"torch/csrc/utils/python_numbers.h\" and use the corresponding APIs instead."
+  echo "Please include \"torch/csrc/utils/python_numbers.h\" and use the correspoding APIs instead."
   echo "PyLong_FromLong -> THPUtils_packInt32 / THPUtils_packInt64"
   echo "PyLong_AsLong -> THPUtils_unpackInt (32-bit) / THPUtils_unpackLong (64-bit)"
   echo "PyLong_FromUnsignedLong -> THPUtils_packUInt32 / THPUtils_packUInt64"

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

@@ -10,7 +10,7 @@ set PATH=C:\Program Files\CMake\bin;C:\Program Files\7-Zip;C:\ProgramData\chocol
 :: able to see what our cl.exe commands are (since you can actually
 :: just copy-paste them into a local Windows setup to just rebuild a
 :: single file.)
-:: log sizes are too long, but leaving this here in case someone wants to use it locally
+:: log sizes are too long, but leaving this here incase someone wants to use it locally
 :: set CMAKE_VERBOSE_MAKEFILE=1
 
 
@@ -37,12 +37,7 @@ call %INSTALLER_DIR%\activate_miniconda3.bat
 if errorlevel 1 goto fail
 if not errorlevel 0 goto fail
 
-:: Update CMake
-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
-
-call pip install mkl==2024.2.0 mkl-static==2024.2.0 mkl-include==2024.2.0
+call pip install mkl-include==2021.4.0 mkl-devel==2021.4.0
 if errorlevel 1 goto fail
 if not errorlevel 0 goto fail
 
@@ -93,7 +88,7 @@ set PATH=%CUDA_PATH%\bin;%CUDA_PATH%\libnvvp;%PATH%
 :cuda_build_end
 
 set DISTUTILS_USE_SDK=1
-set PATH=%TMP_DIR_WIN%\bin;C:\Program Files\CMake\bin;%PATH%
+set PATH=%TMP_DIR_WIN%\bin;%PATH%
 
 :: The latest Windows CUDA test is running on AWS G5 runner with A10G GPU
 if "%TORCH_CUDA_ARCH_LIST%" == "" set TORCH_CUDA_ARCH_LIST=8.6

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

@@ -24,7 +24,7 @@ if "%CUDA_SUFFIX%" == "" (
 
 if "%REBUILD%"=="" (
   if "%BUILD_ENVIRONMENT%"=="" (
-    curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --output %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z & REM @lint-ignore
+    curl --retry 3 --retry-all-errors -k https://s3.amazonaws.com/ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --output %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z
   ) else (
     aws s3 cp s3://ossci-windows/magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z %TMP_DIR_WIN%\magma_2.5.4_%CUDA_SUFFIX%_%BUILD_TYPE%.7z --quiet
   )