

"""simple docstring"""
import json
import os
import unittest

from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES, FSMTTokenizer
from transformers.testing_utils import slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


# using a different tiny model than the one used for default params defined in init to ensure proper testing
A									=						"""stas/tiny-wmt19-en-ru"""

class        _UpperCamelCase	(						lowerCamelCase__   ,				unittest.TestCase	):


  """simple docstring"""





  snake_case_        =    FSMTTokenizer
  snake_case_        =    False



  def 							_UpperCAmelCase      ( self					: Optional[int]      )	->			int:


         '''simple docstring'''





         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         __magic_name__			:		Union[str, Any]        =     [
             '''l''',
             '''o''',
             '''w''',
             '''e''',
             '''r''',
             '''s''',
             '''t''',
             '''i''',
             '''d''',
             '''n''',
             '''w</w>''',
             '''r</w>''',
             '''t</w>''',
             '''lo''',
             '''low''',
             '''er</w>''',
             '''low</w>''',
             '''lowest</w>''',
             '''newer</w>''',
             '''wider</w>''',
             '''<unk>''',
         ]
         __magic_name__			:		List[str]        =     dict(zip(snake_case       ,       range(len(snake_case      )      )      )      )
         __magic_name__			:		Optional[int]        =     ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

         __magic_name__			:		List[Any]        =     ['''en''', '''ru''']
         __magic_name__			:		Optional[int]        =     {
             '''langs''': self.langs,
             '''src_vocab_size''': 10,
             '''tgt_vocab_size''': 20,
         }

         __magic_name__			:		str        =     os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['''src_vocab_file''']      )
         __magic_name__			:		Optional[Any]        =     os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['''tgt_vocab_file''']      )
         __magic_name__			:		int        =     os.path.join(self.tmpdirname       ,       '''tokenizer_config.json'''      )
         __magic_name__			:		int        =     os.path.join(self.tmpdirname       ,       VOCAB_FILES_NAMES['''merges_file''']      )
         with open(self.src_vocab_file       ,       '''w'''      ) as fp:
                fp.write(json.dumps(snake_case      )      )
         with open(self.tgt_vocab_file       ,       '''w'''      ) as fp:
                fp.write(json.dumps(snake_case      )      )
         with open(self.merges_file       ,       '''w'''      ) as fp:
                fp.write('''\n'''.join(snake_case      )      )
         with open(snake_case       ,       '''w'''      ) as fp:
                fp.write(json.dumps(snake_case      )      )



  @cached_property
  def 							_UpperCAmelCase      ( self					: List[str]      )	->			List[str]:


         '''simple docstring'''





         return FSMTTokenizer.from_pretrained('''facebook/wmt19-ru-en'''      )



  @cached_property
  def 							_UpperCAmelCase      ( self					: Dict      )	->			int:


         '''simple docstring'''





         return FSMTTokenizer.from_pretrained('''facebook/wmt19-en-ru'''      )



  def 							_UpperCAmelCase      ( self					: Dict      )	->			Union[str, Any]:


         '''simple docstring'''





         __magic_name__			:		List[str]        =     FSMTTokenizer.from_pretrained(snake_case      )
         self.assertListEqual([tokenizer.src_lang, tokenizer.tgt_lang]       ,       ['''en''', '''ru''']      )
         self.assertEqual(tokenizer.src_vocab_size       ,       21      )
         self.assertEqual(tokenizer.tgt_vocab_size       ,       21      )



  def 							_UpperCAmelCase      ( self					: List[Any]      )	->			Dict:


         '''simple docstring'''





         __magic_name__			:		Optional[int]        =     FSMTTokenizer(self.langs       ,       self.src_vocab_file       ,       self.tgt_vocab_file       ,       self.merges_file      )

         __magic_name__			:		Optional[int]        =     '''lower'''
         __magic_name__			:		int        =     ['''low''', '''er</w>''']
         __magic_name__			:		str        =     tokenizer.tokenize(snake_case      )
         self.assertListEqual(snake_case       ,       snake_case      )

         __magic_name__			:		List[Any]        =     tokens + ['''<unk>''']
         __magic_name__			:		Tuple        =     [14, 15, 20]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case      )       ,       snake_case      )



  @slow
  def 							_UpperCAmelCase      ( self					: str      )	->			Optional[Any]:


         '''simple docstring'''





         __magic_name__			:		Dict        =     self.tokenizer_ru_en

         __magic_name__			:		Dict        =     tokenizer.encode('''sequence builders'''       ,       add_special_tokens=snake_case      )
         __magic_name__			:		Union[str, Any]        =     tokenizer.encode('''multi-sequence build'''       ,       add_special_tokens=snake_case      )

         __magic_name__			:		Optional[Any]        =     tokenizer.build_inputs_with_special_tokens(snake_case      )
         __magic_name__			:		str        =     tokenizer.build_inputs_with_special_tokens(snake_case       ,       snake_case      )

         assert encoded_sentence == text + [2]
         assert encoded_pair == text + [2] + text_a + [2]



  @slow
  def 							_UpperCAmelCase      ( self					: Union[str, Any]      )	->			List[str]:


         '''simple docstring'''





         __magic_name__			:		List[Any]        =     self.tokenizer_en_ru
         __magic_name__			:		List[str]        =     self.tokenizer_ru_en

         __magic_name__			:		List[str]        =     [
             [
                 '''Here\'s a little song I wrote. Don\'t worry, be happy.''',
                 [2470, 39, 11, 2349, 7222, 70, 5979, 7, 8450, 1050, 1_3160, 5, 26, 6445, 7, 2],
             ],
             ['''This is it. No more. I\'m done!''', [132, 21, 37, 7, 1434, 86, 7, 70, 6476, 1305, 427, 2]],
         ]

         # if data needs to be recreated or added, run:
         # import torch
         # model = torch.hub.load("pytorch/fairseq", "transformer.wmt19.en-ru", checkpoint_file="model4.pt", tokenizer="moses", bpe="fastbpe")
         # for src_text, _ in targets: print(f"""[\n"{src_text}",\n {model.encode(src_text).tolist()}\n],""")

         for src_text, tgt_input_ids in targets:
                __magic_name__			:		Dict        =     tokenizer_enc.encode(snake_case       ,       return_tensors=snake_case      )
                self.assertListEqual(snake_case       ,       snake_case      )

                # and decode backward, using the reversed languages model
                __magic_name__			:		Union[str, Any]        =     tokenizer_dec.decode(snake_case       ,       skip_special_tokens=snake_case      )
                self.assertEqual(snake_case       ,       snake_case      )



  @slow
  def 							_UpperCAmelCase      ( self					: Union[str, Any]      )	->			Tuple:


         '''simple docstring'''





         __magic_name__			:		int        =     FSMTTokenizer.from_pretrained('''facebook/wmt19-ru-en'''       ,       do_lower_case=snake_case      )
         __magic_name__			:		Tuple        =     tokenizer.tokenize('''USA is United States of America'''      )
         __magic_name__			:		str        =     ['''us''', '''a</w>''', '''is</w>''', '''un''', '''i''', '''ted</w>''', '''st''', '''ates</w>''', '''of</w>''', '''am''', '''er''', '''ica</w>''']
         self.assertListEqual(snake_case       ,       snake_case      )



  @unittest.skip('''FSMTConfig.__init__  requires non-optional args'''      )
  def 							_UpperCAmelCase      ( self					: Optional[int]      )	->			str:


         '''simple docstring'''





         pass




  @unittest.skip('''FSMTConfig.__init__  requires non-optional args'''      )
  def 							_UpperCAmelCase      ( self					: int      )	->			Dict:


         '''simple docstring'''





         pass



"""simple docstring"""
def       UpperCamelCase_					(     lowerCamelCase							:					str   )						->     str:



       """simple docstring"""







       return " ".join([word[::-1] for word in input_str.split()]   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
