code: def _num_outputs(
      batched_outputs: Union[Tensor, Tuple[Tensor, ...]]
  ) -> int:
      if isinstance(batched_outputs, tuple):
          return len(batched_outputs)
      return 1
  
imports: import torch
  import functools
  import threading
  from torch import Tensor
  from typing import Any, Callable, Optional, Tuple, Union, List
  from torch.utils._pytree import tree_flatten, tree_unflatten, tree_map_, _broadcast_to_and_flatten, TreeSpec
  from functools import partial
  import os
  import itertools
  from torch._C._functorch import _add_batch_dim, _remove_batch_dim, _vmap_decrement_nesting, _vmap_increment_nesting, is_batchedtensor
label_desc: Use image node_id 3 for calling a global function with example usage: _num_outputs(batched_outputs) and returns: int, len