*/
    private void setConfigFailurePolicy(TestNG testNg, String value) {
        Class<?> argType;
        Object argValue;
        try {
            argType = Class.forName("org.testng.xml.XmlSuite$FailurePolicy", false, testNg.getClass().getClassLoader());
            argValue = argType.getMethod("getValidPolicy", String.class).invoke(null, value);
        } catch (Exception e) {

		switch {
		case fromType == argType:
			// already in the right type, nothing to do
			arg = n
		case fromType.Kind() == argType.Kind(),
			fromType.IsPtrShaped() && argType.IsPtrShaped():
			// can directly convert (e.g. named type to underlying type, or one pointer to another)
			// TODO: never happens because pointers are directIface?
			arg = ir.NewConvExpr(pos, ir.OCONVNOP, argType, n)

			}
			continue
		}
		// First arg need not be a pointer.
		argType := mtype.In(1)
		if !isExportedOrBuiltinType(argType) {
			if logErr {
				log.Printf("rpc.Register: argument type of method %q is not exported: %q\n", mname, argType)
			}
			continue
		}
		// Second arg must be a pointer.
		replyType := mtype.In(2)

  // Collects argument and result types.
  llvm::SmallVector<Location> arg_locs;
  llvm::SmallVector<Type> arg_types, result_types;

  for (auto func_op : module_op.getOps<func::FuncOp>()) {
    if (!ShouldIncludeInMainFunction(func_op)) continue;

    arg_types.append(func_op.getArgumentTypes().begin(),
                     func_op.getArgumentTypes().end());

#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace generator {
namespace cpp {

ArgTypeView::ArgTypeView(ArgType arg_type) : arg_type_(arg_type) {}

string ArgTypeView::TypeName() const {
  if (arg_type_.is_read_only()) {
    if (arg_type_.is_list()) {
      return "absl::Span<AbstractTensorHandle* const>";
    } else {

  SmallVector<Type> arg_types;
  SmallVector<Location> arg_locs;

  // Add an argument for platform_index. This allows for multiple platforms.
  // TODO: b/310291615 - find a better way for platform support.
  arg_types.push_back(RankedTensorType::get({}, builder.getI32Type()));
  arg_locs.push_back(module_op.getLoc());
  for (const Value input_value : inputs) {
    arg_types.push_back(input_value.getType());

		fnname = "makeslice"
		argtype = types.Types[types.TINT]
	}
	fn := typecheck.LookupRuntime(fnname)
	ptr := mkcall1(fn, types.Types[types.TUNSAFEPTR], init, reflectdata.MakeSliceElemRType(base.Pos, n), typecheck.Conv(len, argtype), typecheck.Conv(cap, argtype))
	ptr.MarkNonNil()
	len = typecheck.Conv(len, types.Types[types.TINT])

    absl::flat_hash_set<Node*> control_inputs;
    DataTypeVector arg_types(num_args);

    AddControlInputs(*launch, &control_inputs);

    for (int i = 0; i < num_args; ++i) {
      const Edge* edge = in_edges[i];
      data_inputs[i] = {edge->src(), edge->src_output()};
      arg_types[i] = EdgeType(edge);
    }

    // Appends the variable inputs.

	{{range .}}
	<hr>
	Service {{.Name}}
	<hr>
		<table>
		<th align=center>Method</th><th align=center>Calls</th>
		{{range .Method}}
			<tr>
			<td align=left font=fixed>{{.Name}}({{.Type.ArgType}}, {{.Type.ReplyType}}) error</td>
			<td align=center>{{.Type.NumCalls}}</td>
			</tr>
		{{end}}
		</table>
	{{end}}
	</body>
	</html>`

var debug = template.Must(template.New("RPC debug").Parse(debugText))

  // Create the kernel.
  Device* dev = flr->device();
  Status s;
  auto props = std::make_shared<NodeProperties>(
      &fbody->record->fdef().signature(), node_def, fbody->arg_types,
      fbody->ret_types);
  OpKernelConstruction construction(DeviceType(dev->device_type()), dev,
                                    dev->GetAllocator(AllocatorAttributes()),