code: def read_snli(dir_path):
      df_dict = dict()
      for fold in ["train", "dev", "test"]:
          csv_file = os.path.join(dir_path, "{}.tsv".format(fold))
          column_names = None
          out = []
          with open(csv_file) as f:
              for i, line in enumerate(f):
                  line = line.strip()
                  if i == 0:
                      column_names = line.split()
                      column_names = column_names[:10] + [
                          column_names[-1]
                      ]
                      continue
                  elements = line.split("\t")
                  first_few_elements = elements[:10]
                  gold_label = elements[-1]
                  out.append(first_few_elements + [gold_label])
          df = pd.DataFrame(out, columns=column_names)
          df = df[["sentence1", "sentence2", "gold_label"]]
          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 9 for calling a global function with example usage: read_snli(dir_path) and returns: df_dict,  None