stream(tags).of(stream -> stream.sorted().reduce((l, r) -> l + r).ifPresent(v -> buf.append(v)));
        buf.append(CACHE_KEY_SPLITTER);
        stream(roles).of(stream -> stream.sorted().reduce((l, r) -> l + r).ifPresent(v -> buf.append(v)));
        buf.append(CACHE_KEY_SPLITTER);
        stream(fields).of(stream -> stream.sorted().reduce((l, r) -> l + r).ifPresent(v -> buf.append(v)));

    public static String createMavenVersionString(Properties buildProperties) {
        String timestamp = reduce(buildProperties.getProperty("timestamp"));
        String version = reduce(buildProperties.getProperty(BUILD_VERSION_PROPERTY));
        String rev = reduce(buildProperties.getProperty("buildNumber"));
        String distributionName = reduce(buildProperties.getProperty("distributionName"));

        String msg = distributionName + " ";

- Provide IPv6 support for internal load balancer. ([#103794](https://github.com/kubernetes/kubernetes/pull/103794), [@nilo19](https://github.com/nilo19))
- Reduce the number of calls to docker for stats via dockershim. For Windows this reduces the latency when calling docker, for Linux this saves cpu cycles. ([#104287](https://github.com/kubernetes/kubernetes/pull/104287), [@jsturtevant](https://github.com/jsturtevant)) [SIG Node and Windows]

 *
 * <p><dfn>Dependency collection</dfn> builds a graph of {@link org.apache.maven.api.Node} objects containing
 * all the dependencies.</p>
 *
 * <p>The <dfn>Dependency graph flattening</dfn> process in Maven reduces a complex,
 * multi-level dependency graph to a map of ordered lists that can be turned into classpaths.
 * During this process only the most relevant version of each artifact

     */
    public static String createMavenVersionString(Properties buildProperties) {
        String version = reduce(buildProperties.getProperty(BUILD_VERSION_PROPERTY));
        String rev = reduce(buildProperties.getProperty("buildNumber"));
        String distributionName = reduce(buildProperties.getProperty("distributionName"));

        return distributionName + " "

Doing this provides the following specific benefits:
- **Reduce the API surface** - We no longer need to maintain two methods.
- **Consistency** - All languages have consistent access to the same APIs and ergonomics in the DSL.
- **Reduce the size of the Gradle distribution** - We no longer need to carry multiple standard libraries for different languages.

## Decision

/**
 * A pluggable service for processing model objects during model building.
 *
 * <p>This service allows implementations to:</p>
 * <ul>
 *   <li>Pool identical objects to reduce memory footprint</li>
 *   <li>Intern objects for faster equality comparisons</li>
 *   <li>Apply custom optimization strategies</li>
 *   <li>Transform or modify objects during building</li>
 * </ul>
 *

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

        case LOCK:
            return "Release existing locks or wait for them to be released";
        case BUFFER:
            return "Reduce buffer usage or increase buffer pool size";
        case THREAD_POOL:
            return "Reduce concurrent operations or increase thread pool size";
        default:
            return "Check resource availability and retry";
        }
    }

    /**

				// Number of probes.
				// ~ cat /proc/sys/net/ipv4/tcp_keepalive_probes (defaults to 9, we reduce it to 5)
				_ = syscall.SetsockoptInt(fd, syscall.IPPROTO_TCP, syscall.TCP_KEEPCNT, 5)

				// Wait time after successful probe in seconds.
				// ~ cat /proc/sys/net/ipv4/tcp_keepalive_intvl (defaults to 75 secs, we reduce it to 15 secs)
				_ = syscall.SetsockoptInt(fd, syscall.IPPROTO_TCP, syscall.TCP_KEEPINTVL, 15)
			}