code: def convert_to_features(self, example_batch):
      # Either encode single sentence or sentence pairs
      if len(self.text_fields) > 1:
          texts_or_text_pairs = list(
              zip(
                  example_batch[self.text_fields[0]],
                  example_batch[self.text_fields[1]],
              )
          )
      else:
          texts_or_text_pairs = example_batch[self.text_fields[0]]
  
      # Tokenize the text/text pairs
      features = self.tokenizer.batch_encode_plus(
          texts_or_text_pairs,
          max_length=self.max_seq_length,
          padding="max_length",
          truncation=True,
      )
  
      # Rename label to labels to make it easier to pass to model forward
      features["labels"] = example_batch["label"]
  
      return features
  
file_path: colossalai/examples/language/bert/data.py
imports: import datasets
  from transformers import AutoTokenizer, PreTrainedTokenizer
  from colossalai.booster.plugin.dp_plugin_base import DPPluginBase
label_desc: Use image node_id 7 for calling the GLUEDataBuilder obj's underlying member method code with example usage: obj.convert_to_features(example_batch) and returns: features