code: def get_micro_batch(
      batch: Any, start: int, micro_batch_size: int
  ) -> Any:
      """Get a micro batch of the original batch.
  
      Args:
          batch (Any): Batch to be sliced.
          start (int): Start index of the micro batch.
          micro_batch_size (int): Size of the micro batch.
  
      Returns:
          Any: Target micro batch.
      """
  
      def _get_tensor_slice(x: Any):
          if isinstance(x, torch.Tensor):
              return x[start : start + micro_batch_size]
          return x
  
      return tree_map(_get_tensor_slice, batch)
  
file_path: colossalai/colossalai/pipeline/schedule/_utils.py
imports: from collections import OrderedDict
  from typing import Any, List, Optional, Tuple
  import torch
  import torch.cuda
  from torch.nn import Module
  from torch.utils._pytree import SUPPORTED_NODES, TreeSpec, _register_pytree_node, tree_flatten, tree_map, tree_unflatten
label_desc: Use image node_id 7 for calling a global function with example usage: get_micro_batch(batch, start, micro_batch_size) and returns: tree_map, x, x