type: integer
              nodeSelectors:
                description: NodeSelectors allows to limit the nodes to announce as
                  next hops for the LoadBalancer IP. When empty, all the nodes having  are
                  announced as next hops.
                items:
                  description: A label selector is a label query over a set of resources.

				consistent = false
				continue
			}
			ver := vers[0]
			if len(tops) == 0 {
				consistent = true
				topSig = ver.header
			} else {
				consistent = consistent && ver.header == topSig
			}
			tops = append(tops, vers[0])
		}

		// Check if done...
		if len(tops) < quorum {
			// We couldn't gather enough for quorum
			break
		}

# A shared object which includes registration mechanisms for ops and
# kernels. Does not include the implementations of any ops or kernels. Instead,
# the library which loads libtensorflow_framework.so
# (e.g. _pywrap_tensorflow_internal.so for Python, libtensorflow.so for the C
# API) is responsible for registering ops with libtensorflow_framework.so. In
# addition to this core set of ops, user libraries which are loaded (via

      ASSERT_EQ(expected[i], data[i]) << "Different data at index " << i;
    }
  }

  std::vector<TF_Output> ToOutput(const std::vector<TF_Operation*> ops) {
    std::vector<TF_Output> out;
    for (auto op : ops) {
      out.push_back({op, 0});
    }
    return out;
  }

  void Define(int num_opers, const std::vector<TF_Operation*>& opers,

// --------------------------------------------------------------------------
// Load plugins containing custom ops and kernels

// TF_Library holds information about dynamically loaded TensorFlow plugins.
typedef struct TF_Library TF_Library;

// Load the library specified by library_filename and register the ops and
// kernels present in that library.
//

    typedef tensorflow::protobuf::RepeatedPtrField<tensorflow::OpDef> OpDefs;
    const OpDefs& ops = op_list.op();
    bool found = std::find_if(ops.begin(), ops.end(),
                              [](const tensorflow::OpDef& op_def) {
                                return op_def.name() == "TestCApi";
                              }) != ops.end();
    EXPECT_TRUE(found);
    TF_DeleteBuffer(op_list_buffer);
  }
}

				protocol = fmt.Sprintf("/%s", port.Protocol)
			}
			ports = append(ports, fmt.Sprintf("%d%s (%s)", port.ContainerPort, protocol, container.Name))
		}
		// Ref: https://istio.io/latest/docs/ops/deployment/requirements/#pod-requirements
		if container.Name != "istio-proxy" && container.Name != "istio-operator" {
			if container.SecurityContext != nil && container.SecurityContext.RunAsUser != nil {

dagod.citsalej,s&nd&ps,uolc,?ppatikria,?ysrab,??g!.&bew?gro?m&aug?oc??ofni?ten?ude?vog???h!.&0002?a&citore?idem?kitore??edszot?gro?ilus?letoh?m&alker?lif?t?urof??naltagni?o&c?ediv?fni?levynok?nisac??pohs?rarga?s&a&kal?zatu??emag?wen??t&lob?opsgolb,rops??virp?xe&s?zs??ytic?zsagoj??os?sut??l!.&etisbew321,topsgolb,??m!.&ca?gro?moc?oc?ro?ten?vog???n!.&duolcesirpretne,eni&esrem,m,?tenkcahs,?em!.&enilnoysrab,ysrab,???o&ggnaw?y!c???r!.&3kl,a&i&kymlak,rikhsab,vodrom,?yegyda,?bps,ca,duolcrim,e&niram,rpcm...

dagod.citsalej,s&nd&ps,uolc,?ppatikria,?ysrab,??g!.&bew?gro?m&aug?oc??ofni?ten?ude?vog???h!.&0002?a&citore?idem?kitore??edszot?gro?ilus?letoh?m&alker?lif?t?urof??naltagni?o&c?ediv?fni?levynok?nisac??pohs?rarga?s&a&kal?zatu??emag?wen??t&lob?opsgolb,rops??virp?xe&s?zs??ytic?zsagoj??os?sut??l!.&etisbew321,topsgolb,??m!.&ca?gro?moc?oc?ro?ten?vog???n!.&duolcesirpretne,eni&esrem,m,?tenkcahs,?em!.&enilnoysrab,ysrab,???o&ggnaw?y!c???r!.&3kl,a&i&kymlak,rikhsab,vodrom,?yegyda,?bps,ca,duolcrim,e&niram,rpcm...

	VREV32	V5.B16, V5.B16                  // a508206e
	VREV64	V2.S2, V3.S2                    // 4308a00e
	VREV64	V2.S4, V3.S4                    // 4308a04e

// logical ops
//
// make sure constants get encoded into an instruction when it could
	AND	R1@>33, R2
	AND	$(1<<63), R1                        // AND	$-9223372036854775808, R1       // 21004192