class_docstr: A single set of features of data.
class_docstr_tok: ["A","single","set","of","features","of","data","."]
code: def __init__(self, input_ids, input_mask, segment_ids, label_ids):
      self.input_ids = input_ids
      self.input_mask = input_mask
      self.segment_ids = segment_ids
      self.label_ids = label_ids
  
imports: from __future__ import print_function, unicode_literals
  import random
  from contextlib import closing
  from multiprocessing import Pool
  import numpy
  import pandas
  import torch
  from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset, random_split
  from torchtext.legacy import data
  from tqdm import tqdm
label_desc: Use image node_id 1 to create a new InputFeatures object from inherited base classes: object with example: obj = InputFeatures(input_ids, input_mask, segment_ids, label_ids)