


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case    :   int	    =					{'''configuration_ibert''': ['''IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''IBertConfig''', '''IBertOnnxConfig''']}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     snake_case    :   str	    =					[
         '''IBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''IBertForMaskedLM''',
         '''IBertForMultipleChoice''',
         '''IBertForQuestionAnswering''',
         '''IBertForSequenceClassification''',
         '''IBertForTokenClassification''',
         '''IBertModel''',
         '''IBertPreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_ibert import (
              IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
              IBertForMaskedLM,
              IBertForMultipleChoice,
              IBertForQuestionAnswering,
              IBertForSequenceClassification,
              IBertForTokenClassification,
              IBertModel,
              IBertPreTrainedModel,
          )

else:
     import sys

     snake_case    :   Dict	    =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)









import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


snake_case    :   List[Any]	    =					get_tests_dir('''fixtures/test_sentencepiece_bpe.model''')







class 		_snake_case  (				_snake_case						,   unittest.TestCase							):
 SCREAMING_SNAKE_CASE__				=	BartphoTokenizer
 SCREAMING_SNAKE_CASE__				=	False
 SCREAMING_SNAKE_CASE__				=	True




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       super().setUp()

       a						:Dict										=	['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']
       a						:Optional[Any]										=	dict(zip(_lowerCamelCase ,  range(len(_lowerCamelCase   )   )   )   )
       a						:Tuple										=	{'''unk_token''': '''<unk>'''}

       a						:Union[str, Any]										=	os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES['''monolingual_vocab_file''']   )
       with open(self.monolingual_vocab_file ,  '''w''' ,  encoding='''utf-8'''   ) as fp:
             for token in vocab_tokens:
                   fp.write(F'''{token} {vocab_tokens[token]}\n'''   )

       a						:Any										=	BartphoTokenizer(_lowerCamelCase ,  self.monolingual_vocab_file ,  **self.special_tokens_map   )
       tokenizer.save_pretrained(self.tmpdirname   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  **_lowerCamelCase   ):
       kwargs.update(self.special_tokens_map   )
       return BartphoTokenizer.from_pretrained(self.tmpdirname ,  **_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       a						:int										=	'''This is a là test'''
       a						:str										=	'''This is a<unk><unk> test'''
       return input_text, output_text




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       a						:List[str]										=	BartphoTokenizer(_lowerCamelCase ,  self.monolingual_vocab_file ,  **self.special_tokens_map   )
       a						:Optional[Any]										=	'''This is a là test'''
       a						:Tuple										=	'''▁This ▁is ▁a ▁l à ▁t est'''.split()
       a						:int										=	tokenizer.tokenize(_lowerCamelCase   )
       self.assertListEqual(_lowerCamelCase ,  _lowerCamelCase   )

       a						:Union[str, Any]										=	tokens + [tokenizer.unk_token]
       a						:str										=	[4, 5, 6, 3, 3, 7, 8, 3]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase   ) ,  _lowerCamelCase   )





