class_docstr: Arguments pertaining to what data we are going to input our model for training and eval.
class_docstr_tok: ["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."
          )
      elif self.source_lang is None or self.target_lang is None:
          raise ValueError(
              "Need to specify the source language and the target language."
          )
  
      # accepting both json and jsonl file extensions, as
      # many jsonlines files actually have a .json extension
      valid_extensions = ["json", "jsonl"]
  
      if self.train_file is not None:
          extension = self.train_file.split(".")[-1]
          assert (
              extension in valid_extensions
          ), "`train_file` should be a jsonlines file."
      if self.validation_file is not None:
          extension = self.validation_file.split(".")[-1]
          assert (
              extension in valid_extensions
          ), "`validation_file` should be a jsonlines file."
      if self.val_max_target_length is None:
          self.val_max_target_length = self.max_target_length
  
file_path: transformers/examples/pytorch/translation/run_translation.py
imports: import logging
  import os
  import sys
  import warnings
  from dataclasses import dataclass, field
  from typing import Optional
  import datasets
  import evaluate
  import numpy
  from datasets import load_dataset
  import transformers
  from transformers import AutoConfig, AutoModelForSeq2SeqLM, AutoTokenizer, DataCollatorForSeq2Seq, HfArgumentParser, M2M100Tokenizer, MBart50Tokenizer, MBart50TokenizerFast, MBartTokenizer, MBartTokenizerFast, Seq2SeqTrainer, Seq2SeqTrainingArguments, default_data_collator, 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