



'''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
_UpperCamelCase							       =		"""stas/tiny-wmt19-en-ru"""






class       lowerCamelCase_					(       snake_case__     ,     unittest.TestCase  ):
  """simple docstring"""




  a_							      =FSMTTokenizer
  a_							      =False




  def 		_lowercase  (				self   :			Optional[Any]     )      ->      Optional[Any]:
    super().setUp()

    # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
    __lowerCamelCase : List[str]					 =				[
        '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>',
    ]
    __lowerCamelCase : Optional[int]					 =				dict(zip(_a    ,			range(len(_a     )     )     )     )
    __lowerCamelCase : List[str]					 =				['l o 123', 'lo w 1456', 'e r</w> 1789', '']

    __lowerCamelCase : Tuple					 =				['en', 'ru']
    __lowerCamelCase : str					 =				{
        'langs': self.langs,
        'src_vocab_size': 10,
        'tgt_vocab_size': 20,
    }

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




  @cached_property
  def 		_lowercase  (				self   :			Tuple     )      ->      Tuple:
    return FSMTTokenizer.from_pretrained('facebook/wmt19-ru-en'     )




  @cached_property
  def 		_lowercase  (				self   :			List[Any]     )      ->      Tuple:
    return FSMTTokenizer.from_pretrained('facebook/wmt19-en-ru'     )




  def 		_lowercase  (				self   :			Tuple     )      ->      List[Any]:
    __lowerCamelCase : List[str]					 =				FSMTTokenizer.from_pretrained(_a     )
    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 		_lowercase  (				self   :			List[str]     )      ->      Any:
    __lowerCamelCase : Optional[Any]					 =				FSMTTokenizer(self.langs    ,			self.src_vocab_file    ,			self.tgt_vocab_file    ,			self.merges_file     )

    __lowerCamelCase : Tuple					 =				'lower'
    __lowerCamelCase : List[str]					 =				['low', 'er</w>']
    __lowerCamelCase : Any					 =				tokenizer.tokenize(_a     )
    self.assertListEqual(_a    ,			_a     )

    __lowerCamelCase : List[str]					 =				tokens + ['<unk>']
    __lowerCamelCase : List[Any]					 =				[14, 15, 20]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(_a     )    ,			_a     )




  @slow
  def 		_lowercase  (				self   :			Optional[Any]     )      ->      Optional[int]:
    __lowerCamelCase : Optional[Any]					 =				self.tokenizer_ru_en

    __lowerCamelCase : List[str]					 =				tokenizer.encode('sequence builders'    ,			add_special_tokens=_a     )
    __lowerCamelCase : Optional[int]					 =				tokenizer.encode('multi-sequence build'    ,			add_special_tokens=_a     )

    __lowerCamelCase : Optional[Any]					 =				tokenizer.build_inputs_with_special_tokens(_a     )
    __lowerCamelCase : List[str]					 =				tokenizer.build_inputs_with_special_tokens(_a    ,			_a     )

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




  @slow
  def 		_lowercase  (				self   :			List[str]     )      ->      List[Any]:
    __lowerCamelCase : List[Any]					 =				self.tokenizer_en_ru
    __lowerCamelCase : int					 =				self.tokenizer_ru_en

    __lowerCamelCase : List[Any]					 =				[
        [
            '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:
      __lowerCamelCase : Any					 =				tokenizer_enc.encode(_a    ,			return_tensors=_a     )
      self.assertListEqual(_a    ,			_a     )

      # and decode backward, using the reversed languages model
      __lowerCamelCase : Optional[Any]					 =				tokenizer_dec.decode(_a    ,			skip_special_tokens=_a     )
      self.assertEqual(_a    ,			_a     )




  @slow
  def 		_lowercase  (				self   :			Optional[Any]     )      ->      Optional[int]:
    __lowerCamelCase : Any					 =				FSMTTokenizer.from_pretrained('facebook/wmt19-ru-en'    ,			do_lower_case=_a     )
    __lowerCamelCase : Dict					 =				tokenizer.tokenize('USA is United States of America'     )
    __lowerCamelCase : Optional[int]					 =				['us', 'a</w>', 'is</w>', 'un', 'i', 'ted</w>', 'st', 'ates</w>', 'of</w>', 'am', 'er', 'ica</w>']
    self.assertListEqual(_a    ,			_a     )




  @unittest.skip('FSMTConfig.__init__  requires non-optional args'     )
  def 		_lowercase  (				self   :			str     )      ->      List[str]:
    pass






  @unittest.skip('FSMTConfig.__init__  requires non-optional args'     )
  def 		_lowercase  (				self   :			List[Any]     )      ->      Dict:
    pass











'''simple docstring'''





def  a_  (							_lowerCAmelCase = 1000 )   ->   int:
  return sum(i for i in range(_lowerCAmelCase ) if i % 3 == 0 or i % 5 == 0 )


if __name__ == "__main__":
   print(f'''{solution() = }''')






