code: def deserialize_transformer_data(obj, chain=None):
      if "__transformerdata__" in obj:
          return TransformerData.empty().from_dict(
              obj["__transformerdata__"]
          )
      return obj if chain is None else chain(obj)
  
imports: from typing import Optional, List, Dict, Any, Union, Tuple, cast
  from dataclasses import dataclass, field
  import torch
  import numpy
  from transformers.tokenization_utils import BatchEncoding
  from transformers.file_utils import ModelOutput
  from transformers.modeling_outputs import BaseModelOutput
  from thinc.types import Ragged, Floats2d, Floats3d, FloatsXd, Ints1d, Ints2d
  from thinc.api import NumpyOps, get_array_module, xp2torch, torch2xp
  from spacy.tokens import Span
  import srsly
  from .util import transpose_list
  from .align import get_token_positions
label_desc: Use image node_id 2 for calling a global function with example usage: deserialize_transformer_data(obj, chain) and returns: unknown, TransformerData