"//tensorflow/core/distributed_runtime/rpc:rpc_rendezvous_mgr",
        "//tensorflow/core/distributed_runtime/rpc/eager:grpc_eager_client",
        "@com_google_absl//absl/memory",
        "@com_google_absl//absl/strings:str_format",
        "@local_xla//xla/tsl/c:tsl_status_internal",
    ],
    alwayslink = 1,
)

filegroup(
    name = "pywrap_required_hdrs",
    srcs = [

 * This class provides methods for managing a queue of URLs to be crawled,
 * including adding, deleting, and retrieving URLs from the queue.
 * It uses a {@link MemoryDataHelper} to store the URL queue data in memory.
 *
 * <p>
 * The class is responsible for:
 * </p>
 * <ul>
 *   <li>Updating session IDs for URL queues.</li>
 *   <li>Adding new URLs to the queue.</li>

 */
package okhttp3.internal.tls

import java.security.cert.X509Certificate
import javax.security.auth.x500.X500Principal

/** A simple index that of trusted root certificates that have been loaded into memory. */
class BasicTrustRootIndex(
  vararg caCerts: X509Certificate,
) : TrustRootIndex {
  private val subjectToCaCerts: Map<X500Principal, Set<X509Certificate>>

  init {

/**
 * {@linkplain CacheBuilder Discouraged} (in favor of <a
 * href="https://github.com/ben-manes/caffeine/wiki">Caffeine</a>) caching utilities.
 *
 * <p>The core interface used to represent caches is {@link Cache}. In-memory caches can be
 * configured and created using {@link CacheBuilder}, with cache entries being loaded by {@link
 * CacheLoader}. Statistics about cache performance are exposed using {@link CacheStats}.
 *

        }
    }

    /**
     * Reads the contents of a file into a byte array and returns it.
     * <p>
     * <strong>Note:</strong> This method loads the entire file into memory.
     * For files larger than {@value #MAX_BUF_SIZE} bytes (10MB), an
     * {@link IORuntimeException} will be thrown to prevent OutOfMemoryError.
     * For large files, use streaming APIs instead.
     * </p>
     *

```
./bin/spark-submit --class org.apache.spark.examples.SparkPi \
    --master yarn-client \
    --num-executors 1 \
    --driver-memory 512m \
    --executor-memory 512m \
    --executor-cores 1 \
    examples/jars/spark-examples*.jar 10
```

The job should produce an output as shown below. Note the value of pi in the output.

```

            assertEquals("Hello World!", scanner.nextLine());
        }
    }

    @Test
    void testGetLocation() {
        StringSource source = new StringSource("Hello World!");
        assertEquals("(memory)", source.getLocation());

        source = new StringSource("Hello World!", "LOCATION");
        assertEquals("LOCATION", source.getLocation());
    }

    @Test
    void testGetContent() {

  // ExtendSessionGraphHelper manually.
  std::atomic<bool> extend_before_run;
};

struct TF_ImportGraphDefOptions {
  tensorflow::ImportGraphDefOptions opts;

  // Backing memory for TensorId fields in opts.
  // TODO(skyewm): it'd be better if ImportGraphDefOptions owned this.
  std::vector<tensorflow::string> tensor_id_data;
};

struct TF_ImportGraphDefResults {

      disable: true # optionally turn-off snowball archive transfer
#      batch: 100 # upto this many objects per archive
#      inmemory: true # indicates if the archive must be staged locally or in-memory
#      compress: false # S2/Snappy compressed archive
#      smallerThan: 5MiB # create archive for all objects smaller than 5MiB
#      skipErrs: false # skips any source side read() errors

 */
final class Platform {
  static CharMatcher precomputeCharMatcher(CharMatcher matcher) {
    // CharMatcher.precomputed() produces CharMatchers that are maybe a little
    // faster (and that's debatable), but definitely more memory-hungry. We're
    // choosing to turn .precomputed() into a no-op in GWT, because it doesn't
    // seem to be a worthwhile tradeoff in a browser.
    return matcher;
  }