


from pathlib import Path

import fire
from tqdm import tqdm




def    snake_case_     (  snake_case="ro"			,							snake_case="en"			,							snake_case="wmt16"			,							snake_case=None     )  ->				None:
       try:
              import datasets
       except (ModuleNotFoundError, ImportError):
              raise ImportError('run pip install datasets'     )
       lowercase__:   List[str]  			=   f'{src_lang}-{tgt_lang}'
       print(f'Converting {dataset}-{pair}'     )
       lowercase__:   Union[str, Any]  			=   datasets.load_dataset(snake_case			,							snake_case     )
       if save_dir is None:
              lowercase__:   Union[str, Any]  			=   f'{dataset}-{pair}'
       lowercase__:   Optional[Any]  			=   Path(snake_case     )
       save_dir.mkdir(exist_ok=snake_case     )

       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__:   List[Any]  			=   'val' if split == 'validation' else split
              lowercase__:   int  			=   save_dir.joinpath(f'{fn}.source'     )
              lowercase__:   Dict  			=   save_dir.joinpath(f'{fn}.target'     )
              lowercase__:   Optional[int]  			=   src_path.open('w+'     )
              lowercase__:   str  			=   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__:   Optional[Any]  			=   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)






import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin





@require_jieba
class   __a			(    __UpperCamelCase       ,       unittest.TestCase      ):
 __lowercase :							str        = CpmAntTokenizer
 __lowercase :							List[Any]        = False
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				str:




        '''simple docstring'''
        super().setUp()

        lowercase__:   Any  			=   [
            '<d>',
            '</d>',
            '<s>',
            '</s>',
            '</_>',
            '<unk>',
            '<pad>',
            '</n>',
            '我',
            '是',
            'C',
            'P',
            'M',
            'A',
            'n',
            't',
        ]
        lowercase__:   List[Any]  			=   os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES['vocab_file'] )
        with open(self.vocab_file				, 'w'				, encoding='utf-8' ) as vocab_writer:
               vocab_writer.write(''.join([x + '\n' for x in vocab_tokens] ) )
 @tooslow
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Tuple:




        '''simple docstring'''
        lowercase__:   Optional[int]  			=   CpmAntTokenizer.from_pretrained('openbmb/cpm-ant-10b' )
        lowercase__:   Optional[Any]  			=   '今天天气真好！'
        lowercase__:   str  			=   ['今天', '天气', '真', '好', '！']
        lowercase__:   Optional[Any]  			=   tokenizer.tokenize(lowerCAmelCase__ )
        self.assertListEqual(lowerCAmelCase__				, lowerCAmelCase__ )
        lowercase__:   List[str]  			=   '今天天气真好！'
        lowercase__:   List[str]  			=   [tokenizer.bos_token] + tokens

        lowercase__:   Tuple  			=   [6, 9_802, 14_962, 2_082, 831, 244]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase__ )				, lowerCAmelCase__ )

        lowercase__:   Any  			=   tokenizer.decode(lowerCAmelCase__ )
        self.assertEqual(lowerCAmelCase__				, lowerCAmelCase__ )


