condition is reported, including the value of the argument to <code>panic</code>.
This termination sequence is called <i>panicking</i>.
</p>

<pre>
panic(42)
panic("unreachable")
panic(Error("cannot parse"))
</pre>

<p>
The <code>recover</code> function allows a program to manage behavior
of a panicking goroutine.
Suppose a function <code>G</code> defers a function <code>D</code> that calls

- Allowed calling Stop multiple times on RetryWatcher without panicking. ([#126125](https://github.com/kubernetes/kubernetes/pull/126125), [@mprahl](https://github.com/mprahl))

#
#   Important for patching:
#
#   (2) This script targets any POSIX shell, so it avoids extensions provided
#       by Bash, Ksh, etc; in particular arrays are avoided.
#
#       The "traditional" practice of packing multiple parameters into a
#       space-separated string is a well documented source of bugs and security
#       problems, so this is (mostly) avoided, by progressively accumulating

  "durations" : [ {
    "testProject" : "archivePerformanceProject",
    "linux" : 178
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.corefeature.ArchiveTreePerformanceTest.packing tar",
  "durations" : [ {
    "testProject" : "archivePerformanceProject",
    "linux" : 164
  } ]
}, {

      "coverage" : {
        "per_commit" : [ "linux" ]
      }
    } ]
  }, {
    "testId" : "org.gradle.performance.regression.corefeature.ArchiveTreePerformanceTest.packing tar",
    "groups" : [ {
      "testProject" : "archivePerformanceProject",
      "coverage" : {
        "per_commit" : [ "linux" ]
      }
    } ]
  }, {

- DRA: when asking for "All" devices on a node, Kubernetes <= 1.32 proceeded to schedule pods onto nodes with no devices by not allocating any devices for those pods. Kubernetes 1.33 changes that to only picking nodes which have at least one device. Users who want the "proceed with scheduling also without devices" semantic can use the upcoming prioritized list feature with one sub-request for "all" devices and a second alternative with "count: 0". ([#129...

        [example](https://github.com/tensorflow/models/blob/master/official/modeling/grad_utils.py)
        usage.
    *   Experimental support of
        [all reduce gradient packing](https://www.tensorflow.org/api_docs/python/tf/distribute/experimental/CollectiveHints)
        to allow overlapping gradient aggregation with backward path
        computation.