class_docstr: Arguments pertaining to what data we are going to input our model for training and eval.
  
  Using `HfArgumentParser` we can turn this class
  into argparse arguments to be able to specify them on
  the command line.
class_docstr_tok: ["Arguments","pertaining","to","what","data","we","are","going","to","input","our","model","for","training","and","eval",".","Using","`","HfArgumentParser","`","we","can","turn","this","class","into","argparse","arguments","to","be","able","to","specify","them","on","the","command","line","."]
code: def __post_init__(self):
      if self.dataset_name is not None:
          pass
      elif self.train_file is None or self.validation_file is None:
          raise ValueError(
              "Need either a GLUE task, a training/validation file or a dataset name."
          )
      else:
          train_extension = self.train_file.split(".")[-1]
          assert train_extension in [
              "csv",
              "json",
          ], "`train_file` should be a csv or a json file."
          validation_extension = self.validation_file.split(".")[-1]
          assert (
              validation_extension == train_extension
          ), "`validation_file` should have the same extension (csv or json) as `train_file`."
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/examples/research_projects/tapex/run_tabfact_with_tapex.py
imports: import logging
  import os
  import random
  import sys
  from dataclasses import dataclass, field
  from typing import Optional
  import datasets
  import numpy
  import pandas
  from datasets import load_dataset
  import transformers
  from transformers import AutoConfig, BartForSequenceClassification, DataCollatorWithPadding, EvalPrediction, HfArgumentParser, TapexTokenizer, Trainer, TrainingArguments, default_data_collator, set_seed
  from transformers.trainer_utils import get_last_checkpoint
  from transformers.utils import check_min_version
  from transformers.utils.versions import require_version
label_desc: Use image node_id 1 for calling the DataTrainingArguments obj's underlying member method code with example usage: obj.__post_init__() without return types