*            4番目の値
     * @return 4つの値の組
     */
    public static <T1, T2, T3, T4> Tuple4<T1, T2, T3, T4> tuple4(final T1 value1, final T2 value2, final T3 value3, final T4 value4) {
        return new Tuple4<>(value1, value2, value3, value4);
    }

    /**
     * インスタンスを構築します。
     */
    public Tuple4() {
    }

    /**
     * インスタンスを構築します。
     *
     * @param value1
     *            1番目の値

     * @param value3
     *            3番目の値
     * @return 3つの値の組
     */
    public static <T1, T2, T3> Tuple3<T1, T2, T3> tuple3(final T1 value1, final T2 value2, final T3 value3) {
        return new Tuple3<>(value1, value2, value3);
    }

    /**
     * インスタンスを構築します。
     */
    public Tuple3() {
    }

    /**
     * インスタンスを構築します。
     *
     * @param value1
     *            1番目の値

     * @return 5つの値の組
     */
    public static <T1, T2, T3, T4, T5> Tuple5<T1, T2, T3, T4, T5> tuple5(final T1 value1, final T2 value2, final T3 value3, final T4 value4,
            final T5 value5) {
        return new Tuple5<>(value1, value2, value3, value4, value5);
    }

    /**
     * インスタンスを構築します。
     */
    public Tuple5() {
    }

    /**
     * インスタンスを構築します。
     *
     * @param value1

  if proc.wait():
    # Errors from find_cuda_config.py were sent to stderr.
    print('Asking for detailed CUDA configuration...\n')
    return False

  config = dict(
      tuple(line.decode('ascii').rstrip().split(': ')) for line in proc.stdout)

  print('Found CUDA %s in:' % config['cuda_version'])
  print('    %s' % config['cuda_library_dir'])
  print('    %s' % config['cuda_include_dir'])

	}

	return buf[8:], major, minor, nil
}

func isXL2V1Format(buf []byte) bool {
	_, _, _, err := checkXL2V1(buf)
	return err == nil
}

//msgp:tuple xlMetaV2VersionHeader
type xlMetaV2VersionHeader struct {
	VersionID [16]byte
	ModTime   int64
	Signature [4]byte
	Type      VersionType
	Flags     xlFlags

        and `audio_dataset_from_directory`, to be used with the
        `validation_split` argument, for returning both dataset splits at once,
        as a tuple.
    *   Added `tf.keras.utils.split_dataset` utility to split a `Dataset` object
        or a list/tuple of arrays into two `Dataset` objects (e.g. train/test).
    *   Added step granularity to `BackupAndRestore` callback for handling

  // More info: https://kubernetes.io/docs/concepts/storage/volumes#emptydir
  // +optional
  optional k8s.io.apimachinery.pkg.api.resource.Quantity sizeLimit = 2;
}

// EndpointAddress is a tuple that describes single IP address.
// +structType=atomic
message EndpointAddress {
  // The IP of this endpoint.
  // May not be loopback (127.0.0.0/8 or ::1), link-local (169.254.0.0/16 or fe80::/10),

    }

    String getCrawlerMetadataNameMapping();

    default Tuple3<String, String, String> getCrawlerMetadataNameMapping(final String name) {
        @SuppressWarnings("unchecked")
        Map<String, Tuple3<String, String, String>> params =
                (Map<String, Tuple3<String, String, String>>) propMap.get(CRAWLER_METADATA_NAME_MAPPING);
        if (params == null) {

                    List<Tuple3<String, QueryBuilder, ScoreFunctionBuilder<?>>> boostList = queryMap.get(termKey);
                    if (boostList == null) {
                        boostList = new ArrayList<>();
                        queryMap.put(termKey, boostList);
                    }
                    boostList.add(

        });
    }

    protected <T> T processVirtualHost(final Function<String, T> func, final T defaultValue) {
        final Tuple3<String, String, String>[] vHosts = ComponentUtil.getFessConfig().getVirtualHosts();
        return LaRequestUtil.getOptionalRequest().map(req -> {
            for (final Tuple3<String, String, String> host : vHosts) {
                final String headerValue = req.getHeader(host.getValue1());