

'''simple docstring'''




from __future__ import annotations




def 						UpperCamelCase	(			a		,						a			)				->     list[str]:






     '''simple docstring'''
     if nth_term == "":
          return [""]
     __magic_name__						       =    int(a			)
     __magic_name__						       =    int(a			)
     __magic_name__						       =    []
     for temp in range(int(a			)			):
          series.append(F'''1 / {pow(temp + 1		,						int(a			)			)}''' if series else '''1'''			)
     return series


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      _lowerCAmelCase         =						int(input("Enter the last number (nth term) of the P-Series"))
      _lowerCAmelCase         =						int(input("Enter the power for  P-Series"))
      print("Formula of P-Series => 1+1/2^p+1/3^p ..... 1/n^p")
      print(p_series(nth_term, power))









'''simple docstring'''




from pathlib import Path

import fire
from tqdm import tqdm




def 						UpperCamelCase	(			a="ro"		,						a="en"		,						a="wmt16"		,						a=None			)				->     None:






     '''simple docstring'''
     try:
          import datasets
     except (ModuleNotFoundError, ImportError):
          raise ImportError('''run pip install datasets'''			)
     __magic_name__						       =    F'''{src_lang}-{tgt_lang}'''
     print(F'''Converting {dataset}-{pair}'''			)
     __magic_name__						       =    datasets.load_dataset(a		,						a			)
     if save_dir is None:
          __magic_name__						       =    F'''{dataset}-{pair}'''
     __magic_name__						       =    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
          __magic_name__						       =    '''val''' if split == '''validation''' else split
          __magic_name__						       =    save_dir.joinpath(F'''{fn}.source'''			)
          __magic_name__						       =    save_dir.joinpath(F'''{fn}.target'''			)
          __magic_name__						       =    src_path.open('''w+'''			)
          __magic_name__						       =    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]			):
               __magic_name__						       =    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)






