"-p", iptablesconstants.TCP,
			"-i", "lo",
			"-j", "ACCEPT")
		// CLI: -A ISTIO_PRERT -p tcp -m tcp --dport <INPORT> -m mark ! --mark 0x539/0xfff -j TPROXY --on-port <INPORT> --on-ip 127.0.0.1 --tproxy-mark 0x111/0xfff
		//
		// DESC: Anything heading to <INPORT> that does not have the mark, TPROXY to ztunnel inbound port <INPORT>
		iptablesBuilder.AppendRule(
			iptableslog.UndefinedCommand, ChainInpodPrerouting, iptablesconstants.MANGLE,

  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);

  // Infer shape when everything is known.
  CheckOutputShapes(matmul_op,
                    /*input_shapes*/ {make_shape({3, 2}), make_shape({2, 4})},
                    /*input_tensors*/ {},
                    /*expected_shape*/ make_shape({3, 4}));

  // Infer shape when second operand has unknown shape.
  CheckOutputShapes(matmul_op,

   *       {@link Object#equals(Object)}.
   *   <li>{@code false} in all other situations.
   * </ul>
   *
   * <p>This assumes that any non-null objects passed to this function conform to the {@code
   * equals()} contract.
   *
   * <p><b>Note:</b> this method is now unnecessary and should be treated as deprecated; use {@link
   * java.util.Objects#equals} instead.
   */

				"application/vnd.semf",
				"application/vnd.shana.informed.formdata",
				"application/vnd.shana.informed.formtemplate",
				"application/vnd.shana.informed.interchange",
				"application/vnd.shana.informed.package",
				"application/vnd.simtech-mindmapper",
				"application/vnd.smaf",
				"application/vnd.smart.teacher",
				"application/vnd.software602.filler.form+xml",
				"application/vnd.software602.filler.form-xml-zip",

class CustomDeviceAPI : public tensorflow::CustomDevice {
 public:
  CustomDeviceAPI(TFE_Context* context, TFE_CustomDevice device, void* info,
                  string name)
      : context_(context), device_(device), info_(info), name_(name) {}

  ~CustomDeviceAPI() override { device_.delete_device(info_); }

  const string& name() override { return name_; }

  absl::Status CopyTensorToDevice(

@ElementTypesAreNonnullByDefault
final class SingletonImmutableList<E> extends ForwardingImmutableList<E> {

  final transient List<E> delegate;
  // This reference is used both by the custom field serializer, and by the
  // GWT compiler to infer the elements of the lists that needs to be
  // serialized.
  E element;

  SingletonImmutableList(E element) {
    this.delegate = singletonList(checkNotNull(element));
    this.element = element;
  }

affinity towards odd number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution, one of the nodes would participate more drives. To avoid this the affinity is given towards nodes which leads to next best GCD factor of 12 which provides uniform distribution.

- In this algorithm, we also make...

<a href="info.html">INFO</a>...

                clickLog.setQueryRequestedAt(DfTypeUtil.toLocalDateTime(Long.parseLong(form.rt)));
                clickLog.setUserSessionId(userSessionId);
                clickLog.setDocId(form.docId);
                clickLog.setQueryId(form.queryId);
                if (form.order != null) {
                    clickLog.setOrder(form.order);
                }
                searchLogHelper.addClickLog(clickLog);
            }

  // to the given dividend, so that we don't have half of our divisions being
  // trivial because the divisor is bigger than the dividend.
  // Using remainder here does not give us a uniform distribution but it should
  // not have a big impact on the measurement.
  private static long randomDivisor(long dividend) {
    long r = RANDOM_SOURCE.nextLong();
    if (dividend == -1) {
      return r;