val response3 = client.newCall(request).execute()
    assertThat(response3.body.string()).isEqualTo("def")
    assertThat(server.takeRequest().exchangeIndex).isEqualTo(1) // New connection.
  }

  /**
   * We had a bug where we'd perform infinite retries of route that fail with connection shutdown
   * errors. The problem was that the logic that decided whether to reuse a route didn't track

- The following roles have had `Watch` added to them (prefixed with `system:controller:`):
  
  - `cronjob-controller`
  - `endpoint-controller`
  - `endpointslice-controller`
  - `endpointslicemirroring-controller`

reclaim policy has been deprecated. Users should use dynamic provisioning instead. ([#59063](https://github.com/kubernetes/kubernetes/pull/59063), [@ayushpateria](https://github.com/ayushpateria))

* kube-apiserver flag --tls-ca-file has had no effect for some time.  It is now deprecated and slated for removal in 1.11.  If you are specifying this flag, you must remove it from your launch config before upgrading to 1.11. ([#58968](https://github.com/kubernetes/kubernetes/pull/58968), [@...

- kube-scheduler implemented scheduling hints for the `NodeUnschedulable` plugin. The scheduling hints allowed the scheduler to only retry scheduling a Pod that had been previously rejected by the `NodeSchedulable` plugin if a new Node or a Node update had set `.spec.unschedulable` to false.
   ([#122334](https://github.com/kubernetes/kubernetes/pull/122334), [@carlory](https://github.com/carlory))

		}

		// Check if done...
		if len(tops) < quorum {
			// We couldn't gather enough for quorum
			break
		}

		var latest xlMetaV2ShallowVersion
		if consistent {
			// All had the same signature, easy.
			latest = tops[0]
			merged = append(merged, latest)

			// Calculate latest 'n' non-free versions.
			if !latest.header.FreeVersion() {
				nVersions++
			}
		} else {

  static <E> Queue<E> discardingQueue() {
    return (Queue) DISCARDING_QUEUE;
  }

  /*
   * Note: All of this duplicate code sucks, but it saves a lot of memory. If only Java had mixins!
   * To maintain this code, make a change for the strong reference type. Then, cut and paste, and
   * replace "Strong" with "Soft" or "Weak" within the pasted text. The primary difference is that

        return whenClosed = new CountDownLatch(1);
      }
    }
  }

  /**
   * Returns an object that can be used to wait until this objects' deferred closeables have all had
   * {@link Runnable}s that close them submitted to each one's closing {@link Executor}.
   */
  @VisibleForTesting
  CountDownLatch whenClosedCountDown() {
    return closeables.whenClosedCountDown();
  }

### Bug or Regression

- Fix a scheduler preemption issue where the victim pod was not deleted due to incorrect status patching. This issue occurred when the preemptor and victim pods had different QoS classes in their status, causing the preemption to fail entirely. ([#126695](https://github.com/kubernetes/kubernetes/pull/126695), [@Huang-Wei](https://github.com/Huang-Wei)) [SIG Scheduling]

		// coming from a policy claim based openid provider.
		roleArns := puInfo.roleArns.ToSlice()
		var roleArn string
		if len(roleArns) == 0 {
			iamLogIf(GlobalContext,
				fmt.Errorf("parentUser: %s had no roleArns mapped!", parentUser))
			continue
		}
		roleArn = roleArns[0]
		u, err := sys.OpenIDConfig.LookupUser(roleArn, puInfo.subClaimValue)
		if err != nil {
			iamLogIf(GlobalContext, err)

    * Disabling TensorFloat-32 execution now causes TPUs to use float32 precision for float32 matmuls and other ops. TPUs have always used bfloat16 precision for certain ops, like matmul, when such ops had float32 inputs. Now, disabling TensorFloat-32 by calling `tf.config.experimental.enable_tensor_float_32_execution(False)` will cause TPUs to use float32 precision for such ops instead of bfloat16.

*  `tf.experimental.dtensor`