code: def mod_batch_shape(module: Module, names: List[str], b: int) -> None:
      r"""Recursive helper to modify gpytorch modules' batch shape attribute.
  
      Modifies the module in-place.
  
      Args:
          module: The module to be modified.
          names: The list of names to access the attribute. If the full name of
              the module is `"module.sub_module.leaf_module"`, this will be
              `["sub_module", "leaf_module"]`.
          b: The new size of the last element of the module's `batch_shape`
              attribute.
      """
      if len(names) == 0:
          return
      m = getattr(module, names[0])
      if (
          len(names) == 1
          and hasattr(m, "batch_shape")
          and len(m.batch_shape) > 0
      ):
          m.batch_shape = m.batch_shape[:-1] + torch.Size(
              [b] if b > 0 else []
          )
      else:
          mod_batch_shape(module=m, names=names[1:], b=b)
  
imports: from __future__ import annotations
  import warnings
  from contextlib import contextmanager, ExitStack
  from typing import Iterator, List, Optional, Tuple
  import torch
  from botorch import settings
  from botorch.exceptions import InputDataError, InputDataWarning
  from botorch.settings import _Flag
  from gpytorch import settings
  from gpytorch.module import Module
  from torch import Tensor
label_desc: Use image node_id 8 for calling a global function with example usage: mod_batch_shape(module, names, b) without return types