code: def dispatch_lambda_return_str(f: NativeFunction) -> str:
      # [old codegen] Remove type annotation (e.g. 'Tensor' rather than 'Tensor &')
      # because the dispatch lambdas take mutable arguments *by value*, not
      # by reference. If you then return a reference to such an argument, you
      # will now have a pointer to a dangling stack entry. Not good.
      #
      # You want:
      #
      #   auto dispatch_selu_ = [](Tensor self) -> Tensor { ...; return at::selu_(self); };
      #                                            ^^^^^^
      #
      # *not*
      #
      #   auto dispatch_selu_ = [](Tensor self) -> Tensor& { ...; return at::selu_(self); };
      #                                            ^^^^^^^
      #
      # (NB: We can't make dispatch_selu_ take Tensor&, because the enclosing
      # codegen looks like dispatch_selu_(_r.tensor(0)), and you can't take a
      # mutable reference to temporary.  Maybe we could assign it to a
      # variable itself.)
      returns_without_annotation = tuple(
          Return(r.name, r.type, None) for r in f.func.returns
      )
      return_str = cpp.returns_type(
          returns_without_annotation, symint=True
      ).cpp_type()
      if return_str not in SUPPORTED_RETURN_TYPES:
          raise RuntimeError(
              f"{f.func.name} returns unsupported type {return_str}"
          )
      return return_str
  
imports: from dataclasses import dataclass
  from typing import Dict, List, Optional, Sequence, Set, Tuple, Union
  from torchgen.api import cpp
  from torchgen.api.types import Binding, CppSignature, CppSignatureGroup
  from torchgen.gen import pythonify_default
  from torchgen.model import Argument, BaseTy, BaseType, FunctionSchema, ListType, NativeFunction, OptionalType, Return, Type, Variant
label_desc: Use image node_id 14 for calling a global function with example usage: dispatch_lambda_return_str(f) and returns: return_str