# instead depend on the dummy plugins in //tensorflow/compiler/xla/tsl/platform/default/build_config
# and use header only targets.
# TODO(ddunleavy): This seems completely broken. :tensorflow_cc depends on
# cuda_platform from tf_additional_binary_deps and this doesn't break.
check_deps(
    name = "cuda_plugins_check_deps",
    disallowed_deps = if_static(
        [],

   * values.length) are all {@code null}.
   */
  @VisibleForTesting transient @Nullable Object @Nullable [] values;

  /**
   * Keeps track of metadata like the number of hash table bits and modifications of this data
   * structure (to make it possible to throw ConcurrentModificationException in the iterator). Note

      File file, Charset charset, LineProcessor<T> callback) throws IOException {
    return asCharSource(file, charset).readLines(callback);
  }

  /**
   * Process the bytes of a file.
   *
   * <p>(If this seems too complicated, maybe you're looking for {@link #toByteArray}.)
   *
   * @param file the file to read
   * @param processor the object to which the bytes of the file are passed.
   * @return the result of the byte processor

Si ejecutas **múltiples procesos por contenedor**, tendrás que asegurarte de que el número de procesos iniciados no **consuma más memoria** de la que está disponible.

## Pasos Previos Antes de Comenzar y Contenedores { #previous-steps-before-starting-and-containers }

Si estás usando contenedores (por ejemplo, Docker, Kubernetes), entonces hay dos enfoques principales que puedes usar.

### Múltiples Contenedores { #multiple-containers }

      File file, Charset charset, LineProcessor<T> callback) throws IOException {
    return asCharSource(file, charset).readLines(callback);
  }

  /**
   * Process the bytes of a file.
   *
   * <p>(If this seems too complicated, maybe you're looking for {@link #toByteArray}.)
   *
   * @param file the file to read
   * @param processor the object to which the bytes of the file are passed.
   * @return the result of the byte processor

    /**
     * @return {@code true} if the current thread has acquired this lock.
     */
    boolean isAcquiredByCurrentThread();
  }

  /**
   * A {@code LockGraphNode} associated with each lock instance keeps track of the directed edges in
   * the lock acquisition graph.
   */
  private static final class LockGraphNode {

    /**

Se você executar **múltiplos processos por contêiner**, deve garantir que o número de processos iniciados não **consuma mais memória** do que o disponível.

## Passos anteriores antes de iniciar e contêineres { #previous-steps-before-starting-and-containers }

Se você estiver usando contêineres (por exemplo, Docker, Kubernetes), existem duas abordagens principais que você pode usar.

### Contêineres Múltiplos { #multiple-containers }

		duration := max(time.Duration(r.Float64()*float64(time.Minute)),
			// Make sure to sleep at least a second to avoid high CPU ticks.
			time.Second)
		time.Sleep(duration)
	}
	c.RLock()
	defer c.RUnlock()
	if c.enabled {
		logger.Info("Cluster replication initialized")
	}
	return nil
}

* PetSet has been renamed to StatefulSet.
  If you have existing PetSets, **you must perform extra migration steps** both

	echo
	echo "Starting MinIO instance: ${START_CMD}"
	echo
	eval "$START_CMD"
	MINIO_SRVR_PID="$!"
	echo "MinIO Server PID: ${MINIO_SRVR_PID}"
	echo
	echo "Waiting for MinIO instance to get ready!"
	sleep 10
}

main "$@"`, scheme)
	adminLogIf(ctx, embedFileInZip(inspectZipW, "start-minio.sh", scrb.Bytes(), 0o755))
}

func getSubnetAdminPublicKey() []byte {
	if globalIsCICD {