

"""simple docstring"""





from pathlib import Path

import fire
from tqdm import tqdm




def   _A  (  UpperCamelCase_					:	str="ro",      UpperCamelCase_					:	List[Any]="en",      UpperCamelCase_					:	Tuple="wmt16",      UpperCamelCase_					:	str=None)     ->						int:
   '''simple docstring'''


   try:
      import datasets
   except (ModuleNotFoundError, ImportError):
      raise ImportError("run pip install datasets")
   __lowercase								=						F"""{src_lang}-{tgt_lang}"""
   print(F"""Converting {dataset}-{pair}""")
   __lowercase								=						datasets.load_dataset(_a,      _a)
   if save_dir is None:
      __lowercase								=						F"""{dataset}-{pair}"""
   __lowercase								=						Path(_a)
   save_dir.mkdir(exist_ok=_a)

   for split in ds.keys():
      print(F"""Splitting {split} with {ds[split].num_rows} records""")

      # to save to val.source, val.target like summary datasets
      __lowercase								=						"""val""" if split == """validation""" else split
      __lowercase								=						save_dir.joinpath(F"""{fn}.source""")
      __lowercase								=						save_dir.joinpath(F"""{fn}.target""")
      __lowercase								=						src_path.open("w+")
      __lowercase								=						tgt_path.open("w+")

      # reader is the bottleneck so writing one record at a time doesn't slow things down
      for x in tqdm(ds[split]):
         __lowercase								=						x["""translation"""]
         src_fp.write(ex[src_lang] + "\n")
         tgt_fp.write(ex[tgt_lang] + "\n")

   print(F"""Saved {dataset} dataset to {save_dir}""")


if __name__ == "__main__":
   fire.Fire(download_wmt_dataset)







"""simple docstring"""





from unittest import TestCase

from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters




def   _A  (  )     ->						Dict:
   '''simple docstring'''


   __lowercase								=						{
       "repo_name": ["test_repo1", "test_repo2", "test_repo3"],
       "path": ["test_1.py", "test_2.py", "unit_test.py"],
       "content": ["a " * 20, "a " * 30, "b " * 7],
   }
   __lowercase								=						Dataset.from_dict(UpperCamelCase_)
   return dataset




class  _lowerCAmelCase  (     lowercase       ):







 """simple docstring"""







 def  _lowercase			(      self							:      int     ):
    __lowercase								=						get_dataset()
    __lowercase								=						make_duplicate_clusters(UpperCAmelCase__, 0.85     )
    self.assertEqual(len(duplicate_clusters[0]     ), 2     )



 def  _lowercase			(      self							:      Any     ):
    __lowercase								=						get_dataset()
    __lowercase		,__lowercase								=						deduplicate_dataset(UpperCAmelCase__     )
    self.assertEqual(len(UpperCAmelCase__     ), 2     )
    print(UpperCAmelCase__     )
    self.assertEqual(duplicate_clusters[0][0]["copies"], 2     )
    self.assertEqual(duplicate_clusters[0][0]["is_extreme"], UpperCAmelCase__     )




