docstr: Creates examples for the training and dev sets.
docstr_tok: ["Creates","examples","for","the","training","and","dev","sets","."]
code: def _create_examples(self, df, set_type, text_col, label_col):
      """Creates examples for the training and dev sets."""
      if label_col == None:
          return list(
              df.apply(
                  lambda row: InputExample(
                      guid=row.index, text_a=row[text_col], label=None
                  ),
                  axis=1,
              )
          )
      else:
          return list(
              df.apply(
                  lambda row: InputExample(
                      guid=row.index,
                      text_a=row[text_col],
                      label=str(row[label_col]),
                  ),
                  axis=1,
              )
          )
  
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 6 for calling the TextProcessor obj's underlying member method code with example usage: obj._create_examples(df, set_type, text_col, label_col) and returns: list, list