'''simple docstring'''






import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class lowercase_       (		SCREAMING_SNAKE_CASE__    ,    unittest.TestCase			):







   """simple docstring"""

   __lowerCAmelCase         =   LayoutLMTokenizer
   __lowerCAmelCase         =   LayoutLMTokenizerFast
   __lowerCAmelCase         =   True
   __lowerCAmelCase         =   True
   def 	__UpperCAmelCase   (      self      :			Optional[Any]     )  ->			int:
        super().setUp()

        _A    		=  [
            """[UNK]""",
            """[CLS]""",
            """[SEP]""",
            """want""",
            """##want""",
            """##ed""",
            """wa""",
            """un""",
            """runn""",
            """##ing""",
            """,""",
            """low""",
            """lowest""",
        ]
        _A    		=  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]     )     )
   def 	__UpperCAmelCase   (      self      :			str, **UpperCamelCase__      :			List[Any]     )  ->			int:
        return LayoutLMTokenizer.from_pretrained(self.tmpdirname, **__lowerCAmelCase     )
   def 	__UpperCAmelCase   (      self      :			Tuple, UpperCamelCase__      :			Dict     )  ->			str:
        _A    		=  """UNwant\u00E9d,running"""
        _A    		=  """unwanted, running"""
        return input_text, output_text
   def 	__UpperCAmelCase   (      self      :			Any     )  ->			Dict:
        _A    		=  self.tokenizer_class(self.vocab_file     )

        _A    		=  tokenizer.tokenize('UNwant\u00E9d,running'     )
        self.assertListEqual(__lowerCAmelCase, ['un', '##want', '##ed', ',', 'runn', '##ing']     )
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase     ), [7, 4, 5, 10, 8, 9]     )

   def 	__UpperCAmelCase   (      self      :			Optional[int]     )  ->			str:
        pass











'''simple docstring'''

from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest




@require_tokenizers
class      A     (   SCREAMING_SNAKE_CASE__    ):






 """simple docstring"""





 __a      :    Optional[int]			  =    DistilBertTokenizer
 __a      :    Union[str, Any]			  =    DistilBertTokenizerFast
 __a      :    Any			  =    True
 @slow
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: List[Any]            =				DistilBertTokenizer.from_pretrained("""distilbert-base-uncased"""			)

       UpperCamelCase_					: Dict            =				tokenizer.encode("""sequence builders"""      ,  add_special_tokens=__lowerCAmelCase			)
       UpperCamelCase_					: int            =				tokenizer.encode("""multi-sequence build"""      ,  add_special_tokens=__lowerCAmelCase			)

       UpperCamelCase_					: Union[str, Any]            =				tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase			)
       UpperCamelCase_					: Dict            =				tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase      ,  __lowerCAmelCase			)

       assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
       assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
           tokenizer.sep_token_id
       ]






