return;
  } else if (context->GetContextId() ==
             tensorflow::EagerContext::kInvalidContextId) {
    status->status = tensorflow::errors::InvalidArgument(
        "Trying to update a context with invalid context id.");
  }
  status->status =
      tensorflow::unwrap(ctx)->GetDistributedManager()->SetOrUpdateServerDef(
          server_def, /*reset_context=*/false, keep_alive_secs,

            context = SingletonContext.getInstance().withCredentials(auth);
        } catch (Exception e) {
            log.warn("Failed to create authenticated context, trying guest access", e);
            context = SingletonContext.getInstance();
        }

        // Wait for server to be ready - with proper error handling for CI environments
        try {

			attempts := 1
			for attempts <= 3 {
				aerr := api.AbortMultipartUpload(ctx, tgtBucket, tgtObject, res.UploadID, ObjectOptions{})
				if aerr == nil {
					return
				}
				batchLogIf(ctx,
					fmt.Errorf("trying %s: Unable to cleanup failed multipart replication %s on remote %s/%s: %w - this may consume space on remote cluster",
						humanize.Ordinal(attempts), res.UploadID, tgtBucket, tgtObject, aerr))
				attempts++

  //      since, after all, this class is also a reentrant mutual exclusion lock!?

  /*
   * One of the key challenges of this class is to prevent lost signals, while trying hard to
   * minimize unnecessary signals. One simple and correct algorithm is to signal some other waiter
   * with a satisfied guard (if one exists) whenever any thread occupying the monitor exits the

enough",badNumberOfSelectedOptionsStart:"You have to choose at least ",badNumberOfSelectedOptionsEnd:" answers",badAlphaNumeric:"The input value can only contain alphanumeric characters ",badAlphaNumericExtra:" and ",wrongFileSize:"The file you are trying to upload is too large (max %s)",wrongFileType:"Only files of type %s is allowed",groupCheckedRangeStart:"Please choose between ",groupCheckedTooFewStart:"Please choose at least ",groupCheckedTooManyStart:"Please choose a maximum of ",groupCheckedEnd:"...

- Fixed kubelet startup getting stuck with `NewVolumeManagerReconstruction`...

            }

            /* out of phase maybe? */
            /* inch forward 1 byte and try again */
            for (int i = 0; i < 35; i++) {
                log.warn("Possibly out of phase, trying to resync " + Hexdump.toHexString(this.sbuf, 0, 16));
                this.sbuf[i] = this.sbuf[i + 1];
            }
            int b = this.in.read();
            if (b == -1) {
                return null;

* Fixes a bug where kubelet crashes trying to free memory under memory pressure. ([#58574](https://github.com/kubernetes/kubernetes/pull/58574), [@yastij](https://github.com/yastij))

### Other notable changes

* Removing images with multiple tags ([#29316](https://github.com/kubernetes/kubernetes/pull/29316), [@ronnielai](https://github.com/ronnielai))
* kubectl: don't display an empty list when trying to get a single resource that isn't found ([#28294](https://github.com/kubernetes/kubernetes/pull/28294), [@ncdc](https://github.com/ncdc))

  // TF_FinishOperation should fail if the shape of the added operation cannot
  // be inferred.
  TF_Status* status = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Create this failure by trying to add two nodes with incompatible shapes
  // (A tensor with shape [2] and a tensor with shape [3] cannot be added).
  const char data[] = {1, 2, 3};
  const int64_t vec2_dims[] = {2};
  unique_tensor_ptr vec2_tensor(