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_id):
      self.input_ids = input_ids
      self.input_mask = input_mask
      self.segment_ids = segment_ids
      self.label_id = label_id
  
imports: import pandas
  import os
  import torch
  from pathlib import Path
  import pickle
  from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
  from torch.utils.data.distributed import DistributedSampler
  from transformers import WEIGHTS_NAME, BertConfig, BertForSequenceClassification, BertTokenizer, XLMConfig, XLMForSequenceClassification, XLMTokenizer, XLNetConfig, XLNetForSequenceClassification, XLNetTokenizer
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_id)