code: def read_qqp(dir_path):
      df_dict = dict()
      for fold in ["train", "dev", "test"]:
          csv_file = os.path.join(dir_path, "{}.tsv".format(fold))
          df = pd.read_csv(csv_file, "\t")
          if fold == "test":
              df = df[["question1", "question2"]]
              df.columns = ["sentence1", "sentence2"]
          else:
              df = df[["question1", "question2", "is_duplicate"]]
              df.columns = ["sentence1", "sentence2", "label"]
          df_dict[fold] = df
      return df_dict, None
  
imports: import os
  import shutil
  import argparse
  import zipfile
  import json
  import pandas
  import pyarrow
  import pyarrow.json
  from autogluon_contrib_nlp.utils.misc import download, load_checksum_stats
  from autogluon_contrib_nlp.base import get_data_home_dir
  from autogluon_contrib_nlp.data.tokenizers import WhitespaceTokenizer
label_desc: Use image node_id 6 for calling a global function with example usage: read_qqp(dir_path) and returns: df_dict,  None