



from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_								=       logging.get_logger(__name__)

a_								=       {
    """studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json""",
    """studio-ousia/luke-large""": """https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json""",
}



class 			__lowerCAmelCase  (						__UpperCAmelCase ):
 lowerCAmelCase__							       =	'''luke'''




 def __init__(    self						,					__UpperCAmelCase=50267						,					__UpperCAmelCase=500000						,					__UpperCAmelCase=768						,					__UpperCAmelCase=256						,					__UpperCAmelCase=12						,					__UpperCAmelCase=12						,					__UpperCAmelCase=3072						,					__UpperCAmelCase="gelu"						,					__UpperCAmelCase=0.1						,					__UpperCAmelCase=0.1						,					__UpperCAmelCase=512						,					__UpperCAmelCase=2						,					__UpperCAmelCase=0.02						,					__UpperCAmelCase=1E-1_2						,					__UpperCAmelCase=True						,					__UpperCAmelCase=None						,					__UpperCAmelCase=1						,					__UpperCAmelCase=0						,					__UpperCAmelCase=2						,					**__UpperCAmelCase						,					):



    '''simple docstring'''
    super().__init__(pad_token_id=lowerCamelCase__						,					bos_token_id=lowerCamelCase__						,					eos_token_id=lowerCamelCase__						,					**lowerCamelCase__					)

    __lowerCamelCase    				=     vocab_size
    __lowerCamelCase    				=     entity_vocab_size
    __lowerCamelCase    				=     hidden_size
    __lowerCamelCase    				=     entity_emb_size
    __lowerCamelCase    				=     num_hidden_layers
    __lowerCamelCase    				=     num_attention_heads
    __lowerCamelCase    				=     hidden_act
    __lowerCamelCase    				=     intermediate_size
    __lowerCamelCase    				=     hidden_dropout_prob
    __lowerCamelCase    				=     attention_probs_dropout_prob
    __lowerCamelCase    				=     max_position_embeddings
    __lowerCamelCase    				=     type_vocab_size
    __lowerCamelCase    				=     initializer_range
    __lowerCamelCase    				=     layer_norm_eps
    __lowerCamelCase    				=     use_entity_aware_attention
    __lowerCamelCase    				=     classifier_dropout










"""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 				_SCREAMING_SNAKE_CASE				(							__UpperCAmelCase     ,   unittest.TestCase  ):
   """simple docstring"""



   _a   :       Optional[int]									=    LayoutLMTokenizer
   _a   :       Dict									=    LayoutLMTokenizerFast
   _a   :       Dict									=    True
   _a   :       Any									=    True


   def 					UpperCAmelCase__(						self						)      ->							List[str]:
    super().setUp()

    lowercase__       :       int				=						[
        """[UNK]""",
        """[CLS]""",
        """[SEP]""",
        """want""",
        """##want""",
        """##ed""",
        """wa""",
        """un""",
        """runn""",
        """##ing""",
        """,""",
        """low""",
        """lowest""",
    ]
    lowercase__       :       Dict				=						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 ,     **lowerCamelCase__						)      ->							Optional[int]:
    return LayoutLMTokenizer.from_pretrained(self.tmpdirname ,     **lowerCamelCase__						)


   def 					UpperCAmelCase__(						self ,     lowerCamelCase__						)      ->							List[Any]:
    lowercase__       :       List[str]				=						"""UNwant\u00E9d,running"""
    lowercase__       :       Optional[int]				=						"""unwanted, running"""
    return input_text, output_text


   def 					UpperCAmelCase__(						self						)      ->							Optional[int]:
    lowercase__       :       str				=						self.tokenizer_class(self.vocab_file						)

    lowercase__       :       Optional[Any]				=						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						)      ->							Any:
    pass