code: def convert_batch_to_sample_list(
      batch: Union[SampleList, Dict[str, Any]]
  ) -> SampleList:
      # Create and return sample list with proper name
      # and type set if it is already not a sample list
      # (case of batched iterators)
      sample_list = batch
      if (
          # Check if batch is a list before checking batch[0]
          # or len as sometimes batch is already SampleList
          isinstance(batch, list)
          and len(batch) == 1
          and isinstance(batch[0], SampleList)
      ):
          sample_list = batch[0]
      elif not isinstance(batch, SampleList):
          sample_list = SampleList(batch)
  
      if sample_list._get_tensor_field() is None:
          sample_list = SampleList(sample_list.to_dict())
  
      return sample_list
  
imports: import collections
  import collections.abc
  import warnings
  from collections import OrderedDict
  from typing import Any, Dict, Union
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: convert_batch_to_sample_list(batch) and returns: sample_list