code: def _update_transformation_fn(self):
      text_col = self.getTextCol()
      label_col = self.getLabelCol()
      max_token_len = self.getMaxTokenLen()
      # load it inside to avoid `Already borrowed` error (https://github.com/huggingface/tokenizers/issues/537)
      if self.getTokenizer() is None:
          self.setTokenizer(
              AutoTokenizer.from_pretrained(self.getCheckpoint())
          )
      tokenizer = self.getTokenizer()
  
      def _encoding_text(row):
          text = row[text_col]
          label = row[label_col]
          encoding = tokenizer(
              text,
              max_length=max_token_len,
              padding="max_length",
              truncation=True,
              return_attention_mask=True,
              return_tensors="pt",
          )
          input_ids = encoding["input_ids"].flatten().numpy()
          attention_mask = encoding["attention_mask"].flatten().numpy()
          return {
              "input_ids": input_ids,
              "attention_mask": attention_mask,
              "labels": torch.tensor(label, dtype=int),
          }
  
      transformation_edit_fields = [
          ("input_ids", int, None, True),
          ("attention_mask", int, None, True),
          ("labels", int, None, False),
      ]
      self.setTransformationEditFields(transformation_edit_fields)
      transformation_removed_fields = [
          self.getTextCol(),
          self.getLabelCol(),
      ]
      self.setTransformationRemovedFields(transformation_removed_fields)
      self.setTransformationFn(_encoding_text)
  
imports: from horovod.spark.lightning import TorchEstimator
  import torch
  from pyspark.ml.param.shared import Param, Params
  from pytorch_lightning.utilities import _module_available
  from synapse.ml.dl.DeepTextModel import DeepTextModel
  from synapse.ml.dl.LitDeepTextModel import LitDeepTextModel
  from synapse.ml.dl.utils import keywords_catch, get_or_create_backend
  from synapse.ml.dl.PredictionParams import TextPredictionParams
label_desc: Use image node_id 23 for calling the DeepTextClassifier obj's underlying member method code with example usage: obj._update_transformation_fn() and returns: dict