num_cores_per_replica);
  for (mlir::Region& region : old_parallel_execute.getRegions()) {
    if (!llvm::isa<tf_device::ClusterFuncOp>(region.front().front())) {
      for (Type t : region.front().front().getResultTypes())
        concatenated_output_types.emplace_back(t);
    }
  }

  for (int core = 0; core < num_cores_per_replica; ++core) {

  if (auto control_node = dyn_cast<mlir::TFL::ControlNodeOp>(*op)) {
    return IsFlexDelegate(&control_node.getBody().front().front());
  }
  if (auto custom_tf_op = dyn_cast<mlir::TFL::CustomTfOp>(*op)) {
    return IsFlexDelegate(&custom_tf_op.getBody().front().front());
  }

  // Our MLIR might be the result of a conversion from a previously generated
  // flatbuffer file.

bool IsSupportedGraph(func::FuncOp func) {
  if (!llvm::hasSingleElement(func)) return false;

  Block& block = func.front();
  if (!llvm::hasSingleElement(block.without_terminator())) return false;

  auto graph = llvm::dyn_cast<tf_executor::GraphOp>(block.front());
  if (!graph) return false;

  Operation* terminator = block.getTerminator();

			valid:    true,
		},
		{
			selector: "color=green,env=test,service=front",
			labels:   map[string]string{"color": "green", "env": "test", "service": "front"},
			valid:    true,
		},
		{
			selector: "color=green, env=test, service=front",
			labels:   map[string]string{"color": "green", "env": "test", "service": "front"},
			valid:    true,
		},
		{
			selector: ",",

                               ta_accumulate_on_write, &cond_stats);
  if (failed(DecomposeTensorArrayOps(&body.front(), module, &body_stats,
                                     decomposed_partitioned_call_callees)) ||
      failed(DecomposeTensorArrayOps(&cond.front(), module, &cond_stats,
                                     decomposed_partitioned_call_callees))) {
    return failure();
  }

    if (call.getOperation()->getNumOperands() !=
        f.getBody().front().getNumArguments()) {
      return failure();  // RemoteCall et al
    }

    rewriter.startOpModification(f);
    bool changed = false;
    for (auto [call_arg, body_arg] :
         llvm::zip(call.getOperation()->getOperands(),
                   f.getBody().front().getArguments())) {
      if (call_arg.getType() != body_arg.getType()) {

// KubeadmCertFrontProxyCA is the definition of the CA used for the front end proxy.
func KubeadmCertFrontProxyCA() *KubeadmCert {
	return &KubeadmCert{
		Name:     "front-proxy-ca",
		LongName: "self-signed CA to provision identities for front proxy",
		BaseName: kubeadmconstants.FrontProxyCACertAndKeyBaseName,
		config: pkiutil.CertConfig{
			Config: certutil.Config{
				CommonName: "front-proxy-ca",
			},
		},
	}
}

}

// UsingExternalFrontProxyCA determines whether the user is relying on an external front-proxy CA.  We currently implicitly determine this is the case
// when the front proxy CA Cert is present but the front proxy CA Key is not.
// In case we are using an external front-proxy CA, the function validates the certificates signed by front-proxy CA that should be provided by the user.

  added_call_op->setAttr(kInterfaceNameAttr, interface_name);

  StringAttr device = mlir::cast<StringAttr>(
      added_func_op->getRegion(0).getBlocks().front().front().getAttr(kDevice));
  StringAttr inference_type = mlir::cast<StringAttr>(
      added_func_op->getRegion(0).getBlocks().front().front().getAttr(
          kInferenceType));
  added_call_op->setAttr(kDevice, device);
  added_call_op->setAttr(kInferenceType, inference_type);

  while (!op_worklist.empty()) {
    IslandOp current_op = op_worklist.front();
    op_worklist.pop();
    ops.clear();
    if (incoming) {
      collect_input_defining_islands(current_op, ops);
    } else {
      collect_output_users_islands(current_op, ops);
    }
    for (IslandOp wrapper : ops) {
      Operation* wrapped_op = &wrapper.GetBody().front();
      std::vector<IslandOp> child_ops;
      if (incoming) {