code: def from_outputs(
      outputs: Tuple[PythonArgument, ...]
  ) -> Optional["PythonOutArgument"]:
      if not outputs:
          return None
  
      size = len(outputs)
      if size == 1:
          return PythonOutArgument(
              name=outputs[0].name,
              type=outputs[0].type,
              default="None",
              default_init=None,
              outputs=outputs,
          )
      elif size > 1:
          if any(not a.type.is_tensor_like() for a in outputs):
              raise RuntimeError(f"Unsupported output type: {outputs}")
          return PythonOutArgument(
              name="out",
              # TODO: shouldn't this be OptionalType[ListType[...]], since it defaults to None?
              type=ListType(BaseType(BaseTy.Tensor), size),
              default="None",
              default_init=None,
              outputs=outputs,
          )
      raise AssertionError(r"Unexpected PythonOutArgument size")
  
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 1 for calling the PythonOutArgument obj's underlying member method code with example usage: obj.from_outputs(outputs) and returns: None, PythonOutArgument, PythonOutArgument