code: def get_bdim_choices(num_tensors):
      choices = []
  
      # full of zeros
      choices.append((0,) * num_tensors)
  
      # All permutations of (-1, None)
      options = (-1, None)
      choices.extend(itertools.product(options, repeat=num_tensors))
  
      assert choices[-1] == (None,) * num_tensors
      return tuple(choices[:-1])
  
imports: import itertools
  import torch
  from functorch import vmap
  import torch.utils._pytree
  from functorch_additional_op_db import additional_op_db
  from torch.testing._internal.common_methods_invocations import DecorateInfo
  from torch.testing._internal.common_methods_invocations import op_db
  from torch.testing._internal.common_modules import module_db
  import os
  import unittest
  from torch.testing._internal.common_device_type import toleranceOverride
  from torch.testing._internal.autograd_function_db import autograd_function_db
  from collections import namedtuple
label_desc: Use image node_id 5 for calling a global function with example usage: get_bdim_choices(num_tensors) and returns: tuple