You can now bind tokens to service requests. ([ref](https://github.com/kubernetes/enhancements/issues/542))

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  for (int i = 0; i < inputs.size(); i++) {
    input_ids[i] = ToId(inputs[i]);
    input_dtypes[i] = inputs[i]->DataType();
  }
  std::vector<TapeTensor> tape_tensors;
  tape_tensors.reserve(outputs.size());
  for (auto t : outputs) {
    tape_tensors.push_back(TapeTensor(t));
  }
  GradientTape::RecordOperation(
      op_name, tape_tensors, input_ids, input_dtypes,

    * Bump ip-masq-agent version to v2.3.0 with flag `nomasq-all-reserved-ranges` turned on.
* Implement un-reserve extension point for the scheduling framework. ([#77457](https://github.com/kubernetes/kubernetes/pull/77457), [@danielqsj](https://github.com/danielqsj))

  return grads;
}

std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def) {
  std::vector<string> names;
  auto functions = graph_def.library().function();
  names.reserve(functions.size());
  for (const tensorflow::FunctionDef& func : functions) {
    names.push_back(func.signature().name());
  }
  std::sort(names.begin(), names.end());
  return names;
}

- Remove kubescheduler.config.k8s.io/v1alpha1 ([#89298](https://github.com/kubernetes/kubernetes/pull/89298), [@gavinfish](https://github.com/gavinfish)) [SIG Scheduling]
- Reserve plugins that fail to reserve will trigger the unreserve extension point ([#92391](https://github.com/kubernetes/kubernetes/pull/92391), [@adtac](https://github.com/adtac)) [SIG Scheduling and Testing]

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`--enforce-node-allocatable` with a default value of `pods` is added which will make kubelet create a top level cgroup for all pods to enforce Node Allocatable. Optionally, `system-reserved` & `kube-reserved` values can also be specified separated by comma to enforce node allocatable on cgroups specified via `--system-reserved-cgroup` & `--kube-reserved-cgroup` respectively. Note the default value of the latter flags are "". ([#41234](https://github.com/kubernetes/kubernetes/pull/41234), [@vishh](https://github.com/vishh))...

                                               int* num_handles,
                                               TF_Status* status) {
  std::vector<tensorflow::TensorHandle*> tensor_handles;
  tensor_handles.reserve(*num_handles);
  for (int i = 0; i < *num_handles; ++i) {
    tensorflow::ImmediateExecutionTensorHandle* unwrapped_handle =
        tensorflow::unwrap(handles[i]);

  - [Changelog since v1.18.17](#changelog-since-v11817)
  - [Important Security Information](#important-security-information)
    - [CVE-2021-25735: Validating Admission Webhook does not observe some previous fields](#cve-2021-25735-validating-admission-webhook-does-not-observe-some-previous-fields)
  - [Changes by Kind](#changes-by-kind-2)
    - [API Change](#api-change-1)
    - [Feature](#feature)
    - [Bug or Regression](#bug-or-regression-2)