class_docstr: Arguments pertaining to what data we are going to input our model for training and eval.
code: def __post_init__(self):
      if (
          self.dataset_name is None
          and self.train_file is None
          and self.validation_file is None
      ):
          raise ValueError(
              "Need either a dataset name or a training/validation file."
          )
      else:
          if self.train_file is not None:
              extension = self.train_file.split(".")[-1]
              assert extension in [
                  "csv",
                  "json",
              ], "`train_file` should be a csv or a json file."
          if self.validation_file is not None:
              extension = self.validation_file.split(".")[-1]
              assert extension in [
                  "csv",
                  "json",
              ], "`validation_file` should be a csv or a json file."
          if self.validation_file is not None:
              extension = self.validation_file.split(".")[-1]
              assert (
                  extension == "json"
              ), "`validation_file` should be a json file."
  
imports: import logging
  import os
  import sys
  from dataclasses import dataclass, field
  from typing import Optional
  import torch
  from datasets import load_dataset
  from PIL import Image
  from torchvision.io import ImageReadMode, read_image
  from torchvision.transforms import CenterCrop, ConvertImageDtype, Normalize, Resize
  from torchvision.transforms.functional import InterpolationMode
  import transformers
  from transformers import AutoFeatureExtractor, AutoModel, AutoTokenizer, HfArgumentParser, Trainer, TrainingArguments, set_seed
  from transformers.trainer_utils import get_last_checkpoint
  from transformers.utils import check_min_version, send_example_telemetry
  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