while (merged.hasNext()) {
          C next = merged.next();
          boolean duplicate = lastValue != null && comparator.compare(next, lastValue) == 0;

          // Keep looping till we find a non-duplicate value.
          if (!duplicate) {
            lastValue = next;
            return lastValue;
          }
        }

        lastValue = null; // clear reference to unused data

        while (merged.hasNext()) {
          C next = merged.next();
          boolean duplicate = lastValue != null && comparator.compare(next, lastValue) == 0;

          // Keep looping till we find a non-duplicate value.
          if (!duplicate) {
            lastValue = next;
            return lastValue;
          }
        }

        lastValue = null; // clear reference to unused data

      interpreted as a boolean indicator, assume that the user has made a
      scripting error, and will continue to provide invalid input.
      Raise the error to avoid infinitely looping.
  """
  if not question:
    question = 'Do you wish to build TensorFlow with {} support?'.format(
        query_item)
  if not yes_reply:

    *   Added APIs for switching between interactive logging and absl logging.
        By default, Keras always writes the logs to stdout. However, this is not
        optimal in a non-interactive environment, where you don't have access to
        stdout, but can only view the logs. You can use
        `tf.keras.utils.disable_interactive_logging()` to write the logs to ABSL
        logging. You can also use `tf.keras.utils.enable_interactive_logging()`

handlers = java.util.logging.ConsoleHandler

	logger.LogIf(ctx, "tier", err, errKind...)
}

func kmsLogIf(ctx context.Context, err error, errKind ...any) {
	logger.LogIf(ctx, "kms", err, errKind...)
}

// KMSLogger permits access to kms module specific logging
type KMSLogger struct{}

// LogOnceIf is the implementation of LogOnceIf, accessible using the Logger interface
func (l KMSLogger) LogOnceIf(ctx context.Context, err error, id string, errKind ...any) {

  "durations" : [ {
    "testProject" : "excludeRuleMergingBuild",
    "linux" : 232
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.corefeature.LargeDependencyGraphPerformanceTest.resolve large dependency graph (parallel = false, locking = true)",
  "durations" : [ {
    "testProject" : "excludeRuleMergingBuild",

## 🔧 Configuration

### Logging Configuration
CoreLib supports multiple logging frameworks. Configure your preferred logger:

```java
// Use with SLF4J (add slf4j-api dependency)
Logger logger = Logger.getLogger(MyClass.class);

// Use with Commons Logging (add commons-logging dependency)  
Logger logger = Logger.getLogger(MyClass.class);

// Use with Java Util Logging (built-in)

import java.util.List;
import java.util.Map;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.fess.crawler.container.CrawlerContainer;

import jakarta.annotation.Resource;

/**
 * Creates and manages crawler clients for web crawling operations.
 * This class handles the registration and loading of crawler client factories and their associated clients.
 * <p>

        }
    }

    static void checkCommit(String commit) {
        List<String> parentCommits = parentCommitsOf(commit)
        if (parentCommits.size() != 2) {
            println("$commit is not a merge commit we're looking for. Parents: $parentCommits")
            return
        }

        List<String> commitBranches = branchesOf(commit)
        if (commitBranches.contains("origin/release")) {