auto tensor_string_type =
      RankedTensorType::get({}, TF::StringType::get(builder.getContext()));
  main_func.getArguments().front().setType(tensor_string_type);
  main_func.setType(
      FunctionType::get(builder.getContext(), {tensor_string_type},
                        main_func.getFunctionType().getResults()));
  // Name of the main function for the eventual executable needs to be set.

        m.print(os);
        return os.str();
      });

  py::class_<mlir::func::FuncOp>(m, "FuncOp")
      .def("create",
           [](mlir::Location location, std::string name,
              mlir::FunctionType type) {
             auto func = mlir::func::FuncOp::create(location, name, type);
             func.addEntryBlock();
             return func;
           })
      .def(
          "getBody",

              module.getContext()));

      arg.setType(new_arg_type);
    }

    // Update the function type.
    func.setType(mlir::FunctionType::get(module.getContext(),
                                         func.getBody().getArgumentTypes(),
                                         func.getFunctionType().getResults()));
  }
  return success();
}

    Note the arguments are ordered by the following rule:
      tfr.tensor > tfr.tensor_list > tfr.attr/i32/...,
    and only one trfr.tensor_list argument is allowed.
  }];

  let arguments = (ins
    TypeAttrOf<FunctionType>:$function_type,
    StrAttr:$sym_name,
    OptionalAttr<DictArrayAttr>:$arg_attrs,
    OptionalAttr<DictArrayAttr>:$res_attrs
  );

  let results = (outs);

    // to contain the ops in the tfg::GraphOp. That means the arguments/results
    // will be the operations inside the function body rather than representing
    // them in the function signature.
    FunctionType func_type = rewriter.getFunctionType({}, {});
    func::FuncOp func = rewriter.create<func::FuncOp>(
        loc, kImportModelDefaultGraphFuncName, func_type);
    rewriter.setInsertionPointToStart(func.addEntryBlock());

    }
  }

  // Patch up function types (with less number of return values and potentially
  // less number of arguments)
  for (func::FuncOp func : cloned_branches) {
    func.setType(
        FunctionType::get(func.getContext(), func.front().getArgumentTypes(),
                          func.front().getTerminator()->getOperandTypes()));
  }

  EliminateUnusedResults(op);
}

      op.erase();
    }
  }
  if (lifted_op_and_arg_idx.empty()) return success();

  // Update the function signature as well as its uses.
  target_func.setType(FunctionType::get(target_func.getContext(),
                                        block.getArgumentTypes(),
                                        func_type.getResults()));

  IRMapping mapping;
  OpBuilder builder(module_op);

    }
    std::vector<Type> return_types;
    for (auto ret_op : ret->getOperands()) {
      return_types.push_back(ret_op.getType());
    }
    auto newType =
        FunctionType::get(rewriter.getContext(), argument_types, return_types);
    if (f.getFunctionType() == newType) {
      return failure();
    }
    rewriter.modifyOpInPlace(f, [&] { f.setType(newType); });

  // Handle the entry functions only.
  if (func.getName() != "main" && (!attrs || attrs.empty())) {
    return;
  }

  OpBuilder builder(func);
  FunctionType func_type = func.getFunctionType();
  llvm::SmallVector<Type, 4> new_input_types(func_type.getInputs().begin(),
                                             func_type.getInputs().end());

}

// FunctionType is a function type.
type FunctionType struct {
	Return AST
	Args   []AST

	// The forLocalName field reports whether this FunctionType
	// was created for a local name. With the default GNU demangling
	// output we don't print the return type in that case.
	ForLocalName bool
}

func (ft *FunctionType) print(ps *printState) {
	retType := ft.Return