code: def single_sentence_featurize(
      guid: str,
      input_tokens: List[str],
      label_id: int,
      tokenizer,
      feat_spec: FeaturizationSpec,
      data_row_class,
  ):
      unpadded_inputs = construct_single_input_tokens_and_segment_ids(
          input_tokens=input_tokens,
          tokenizer=tokenizer,
          feat_spec=feat_spec,
      )
      return create_generic_data_row_from_tokens_and_segments(
          guid=guid,
          unpadded_tokens=unpadded_inputs.unpadded_tokens,
          unpadded_segment_ids=unpadded_inputs.unpadded_segment_ids,
          label_id=label_id,
          tokenizer=tokenizer,
          feat_spec=feat_spec,
          data_row_class=data_row_class,
      )
  
imports: import numpy
  from dataclasses import dataclass
  from typing import List, NamedTuple
  from jiant.tasks.core import FeaturizationSpec
  from jiant.tasks.utils import truncate_sequences, pad_to_max_seq_length
  from jiant.utils.python.datastructures import BiMap
label_desc: Use image node_id 1 for calling a global function with example usage: single_sentence_featurize(guid, input_tokens, label_id, tokenizer, feat_spec, data_row_class) and returns: create_generic_data_row_from_tokens_and_segments