class_docstr: A single set of features of data.
class_docstr_tok: ["A","single","set","of","features","of","data","."]
code: def __init__(
      self,
      unique_id: int,
      input_ids: List[int],
      input_mask: List[int],
      segment_ids: List[int],
      example_index: int = None,
      doc_span_index: int = None,
      tokens: List[str] = None,
      token_to_orig_map: Dict[int, int] = None,
      token_is_max_context: Dict[int, bool] = None,
      start_position: Optional[int] = None,
      end_position: Optional[int] = None,
      is_impossible: Optional[int] = None,
  ):
      self.unique_id = unique_id
      self.example_index = example_index
      self.doc_span_index = doc_span_index
      self.tokens = tokens
      self.token_to_orig_map = token_to_orig_map
      self.token_is_max_context = token_is_max_context
      self.input_ids = input_ids
      self.input_mask = input_mask
      self.segment_ids = segment_ids
      self.start_position = start_position
      self.end_position = end_position
      self.is_impossible = is_impossible
  
imports: import collections
  import os
  import pickle
  from functools import lru_cache
  from typing import Dict, List, Optional
  import numpy
  import psutil
  import torch
  from tqdm import trange
  from nemo.collections.common.parts.utils import _compute_softmax
  from nemo.collections.nlp.data.data_utils import is_whitespace
  from nemo.collections.nlp.data.question_answering_squad.qa_squad_processing import EVALUATION_MODE, INFERENCE_MODE, TRAINING_MODE, SquadProcessor, _improve_answer_span, apply_no_ans_threshold, exact_match_score, f1_score, find_all_best_thresh, get_best_indexes, get_final_text, make_eval_dict, merge_eval, normalize_answer
  from nemo.core.classes import Dataset
  from nemo.utils import logging
label_desc: Use image node_id 1 to create a new InputFeatures object from inherited base classes: object with example: obj = InputFeatures(unique_id, input_ids, input_mask, segment_ids, example_index, doc_span_index, tokens, token_to_orig_map, token_is_max_context, start_position, end_position, is_impossible)