if (valueReference.isLoading()) {
              createNewEntry = false;
            } else {
              V value = valueReference.get();
              if (value == null) {
                enqueueNotification(
                    entryKey, hash, value, valueReference.getWeight(), RemovalCause.COLLECTED);
              } else if (map.isExpired(e, now)) {

                }
                if ( altPathOffset > 0 ) {
                    this.altPath = readString(buffer, start + altPathOffset, len);
                }
            }
            else {
                int specialNameOffset = SMBUtil.readInt2(buffer, bufferIndex);
                bufferIndex += 2;
                int numExpanded = SMBUtil.readInt2(buffer, bufferIndex);
                bufferIndex += 2;

		exit 1
	else
		echo "Outputs are inconsistent. Waiting for $wait_interval seconds (attempt $attempt/$max_wait_attempts)."
		sleep $wait_interval
	fi

	((attempt++))
done

status=$(./mc admin group info site1 site-replication-issue-group --json | jq .groupStatus | tr -d '"')

if [[ $status == "enabled" ]]; then
	echo "Success"
else

  "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)'
  "$python" -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
fi
# Import tf nightly wheel built with numpy2 from PyPI in numpy1 env for testing.
# This aims to maintain TF compatibility with NumPy 1.x until 2025 b/361369076.
if [[ "$TFCI_WHL_NUMPY_VERSION" == 1 ]]; then

        ClassMetaData targetClass;
        if (className != null) {
            targetClass = repository.find(className);
            if (targetClass == null) {
                return null;
            }
        } else {
            targetClass = classMetaData;
        }

        String methodSignature = matcher.group(3);
        if (matcher.group(5) != null) {
            StringBuilder signature = new StringBuilder();

    Count frequency = backingMap.get(element);
    int oldCount;
    if (frequency == null) {
      oldCount = 0;
      backingMap.put(element, new Count(occurrences));
    } else {
      oldCount = frequency.get();
      long newCount = (long) oldCount + (long) occurrences;
      checkArgument(newCount <= Integer.MAX_VALUE, "too many occurrences: %s", newCount);
      frequency.add(occurrences);

      double populationCovariance = stats.populationCovariance();
      if (values.hasAnyNonFinite()) {
        assertWithMessage("population covariance of " + values).that(populationCovariance).isNaN();
      } else {
        assertWithMessage("population covariance of " + values)
            .that(populationCovariance)
            .isWithin(ALLOWED_ERROR)
            .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);

                            links.map.put(dr.key, dr);

                        roots.put(root, links);
                    } else if (path == null) {
                        roots.put(root, Dfs.FALSE_ENTRY);
                    }
                } else if (links == Dfs.FALSE_ENTRY) {
                    links = null;
                }

                if (links != null) {

			sourceFailed = true
		} else if srcSize != srcCtnt.Size {
			fmt.Printf("unreadable on source - size differs upon read: %s\n", srcCtnt.Key)
			sourceFailed = true
		}
	}()
	go func() {
		defer wg.Done()
		tgtSize, err := io.Copy(tgtSha256, tobj)
		if err != nil {
			fmt.Printf("unreadable on target: %s (%s)\n", tgtCtnt.Key, err)
			targetFailed = true
		} else if tgtSize != tgtCtnt.Size {

				iamLogIf(ctx, err)
			} else if foundGroupDN == nil || !underBaseDN {
				err = errNoSuchGroup
			}
			entityName = foundGroupDN.NormDN
		} else {
			var foundUserDN *xldap.DNSearchResult
			if foundUserDN, err = globalIAMSys.LDAPConfig.GetValidatedDNForUsername(entityName); err != nil {
				iamLogIf(ctx, err)
			} else if foundUserDN == nil {
				err = errNoSuchUser
			}