uses: actions/setup-java@v4
        with:
          distribution: 'zulu'
          java-version: 17

      - name: Enable KVM group perms
        # https://github.blog/changelog/2023-02-23-hardware-accelerated-android-virtualization-on-actions-windows-and-linux-larger-hosted-runners/
        run: |
          echo 'KERNEL=="kvm", GROUP="kvm", MODE="0666", OPTIONS+="static_node=kvm"' | sudo tee /etc/udev/rules.d/99-kvm4all.rules

# is a request for 2 SCSI formatted and mounted SSDs and 1 NVMe block device SSD.
NODE_LOCAL_SSDS_EXT=${NODE_LOCAL_SSDS_EXT:-}
# Accelerators to be attached to each node. Format "type=<accelerator-type>,count=<accelerator-count>"
# More information on available GPUs here - https://cloud.google.com/compute/docs/gpus/
NODE_ACCELERATORS=${NODE_ACCELERATORS:-""}
export REGISTER_MASTER_KUBELET=${REGISTER_MASTER:-true}

- Introduced a new alpha feature gate, `SELinuxMount`, which can now be enabled to accelerate SELinux relabeling. ([#123157](https://github.com/kubernetes/kubernetes/pull/123157), [@jsafrane](https://github.com/jsafrane))

    std::function<bool(Operation*)> is_ignored_op) {
  // Iteratively find clusters of different targets within the `block`.
  // Whenever we see an operation that is assigned to an accelerator target
  // (ie. get_target(op) != ""), we try to merge it into the last cluster
  // of same target. If that is infeasible (say because of violating
  // def-before-use), create a new cluster with that operation and move on.

  let summary = "Lifting resource operations out of device computation";
  let description = [{
    This pass lifts resource variable operations outside of device computation.
    This is useful because a lot of accelerator devices can not interact with
    resource variables directly..

    Here is a simple example in TensorFlow where a device doubles the value of a
    TensorFlow resource variable and returns new value:

    ```mlir

implementation bugs that might allow attackers to leave malicious code running
and leak or tamper with applications from other users. Please report
vulnerabilities to the vendor of the affected hardware accelerator.

## Reporting vulnerabilities

### Vulnerabilities in TensorFlow

This document covers different use cases for TensorFlow together with comments

        "//learning/brain/mlir/...",
        "//third_party/iree/...",
        "//third_party/odml/infra/...",
        "//tensorflow/compiler/mlir/...",
        "//tensorflow/lite/python/...",
        "//waymo/accelerator/alpine/tools/...",
        "//waymo/ml/compiler/mlir/...",
        # Allow visibility from the mlir language server.
        "//learning/brain/mlir/mlir_lsp_server/...",

fi

if [[ -n "${NODE_ACCELERATORS}" ]]; then
    if [[ "${NODE_ACCELERATORS}" =~ .*type=([a-zA-Z0-9-]+).* ]]; then
        NON_MASTER_NODE_LABELS="${NON_MASTER_NODE_LABELS},cloud.google.com/gke-accelerator=${BASH_REMATCH[1]}"
    fi
fi

# List of the set of feature gates recognized by the GCP CCM

        "//third_party/py/guesslang/...",
        "//third_party/py/keras/...",
        "//third_party/py/tf_keras/...",
        "//third_party/yggdrasil_decision_forests/...",
        "//waymo/accelerator/...",
        "//waymo/ml/cn/...",
        "//waymo/ml/models/...",
    ],
)

package_group(
    name = "ndarray_tensor_allow_list",
    packages = [
        "//third_party/py/courier/...",

  - [Known Issues](#known-issues)
    - [Summary API in kubelet doesn't have accelerator metrics](#summary-api-in-kubelet-doesnt-have-accelerator-metrics)
  - [Urgent Upgrade Notes](#urgent-upgrade-notes)
    - [(No, really, you MUST read this before you upgrade)](#no-really-you-must-read-this-before-you-upgrade)