"""simple docstring"""




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


_a      :		Optional[Any]           =   logging.get_logger(__name__)

_a      :		Dict           =   {
    '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 						__A							( __snake_case		):
     _UpperCamelCase							:			Any							=		"luke"






     def __init__(		self				,     a__=50267				,     a__=500000				,     a__=768				,     a__=256				,     a__=12				,     a__=12				,     a__=3072				,     a__="gelu"				,     a__=0.1				,     a__=0.1				,     a__=512				,     a__=2				,     a__=0.0_2				,     a__=1e-12				,     a__=True				,     a__=None				,     a__=1				,     a__=0				,     a__=2				,     **a__				,     ):
       super().__init__(pad_token_id=a__				,     bos_token_id=a__				,     eos_token_id=a__				,     **a__  )

       _lowerCAmelCase						:       Union[str, Any]  			=     vocab_size
       _lowerCAmelCase						:       int  			=     entity_vocab_size
       _lowerCAmelCase						:       Optional[int]  			=     hidden_size
       _lowerCAmelCase						:       Union[str, Any]  			=     entity_emb_size
       _lowerCAmelCase						:       List[str]  			=     num_hidden_layers
       _lowerCAmelCase						:       Optional[Any]  			=     num_attention_heads
       _lowerCAmelCase						:       List[str]  			=     hidden_act
       _lowerCAmelCase						:       Union[str, Any]  			=     intermediate_size
       _lowerCAmelCase						:       Tuple  			=     hidden_dropout_prob
       _lowerCAmelCase						:       Tuple  			=     attention_probs_dropout_prob
       _lowerCAmelCase						:       Tuple  			=     max_position_embeddings
       _lowerCAmelCase						:       List[Any]  			=     type_vocab_size
       _lowerCAmelCase						:       int  			=     initializer_range
       _lowerCAmelCase						:       Optional[Any]  			=     layer_norm_eps
       _lowerCAmelCase						:       List[str]  			=     use_entity_aware_attention
       _lowerCAmelCase						:       List[str]  			=     classifier_dropout






'''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				(							__snake_case						):
     __magic_name__						=		DistilBertTokenizer
     __magic_name__						=		DistilBertTokenizerFast
     __magic_name__						=		True





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Any:






         """simple docstring"""






         A       :   List[Any]					=						DistilBertTokenizer.from_pretrained('''distilbert-base-uncased'''	)

         A       :   Dict					=						tokenizer.encode('''sequence builders'''						,			add_special_tokens=SCREAMING_SNAKE_CASE	)
         A       :   List[str]					=						tokenizer.encode('''multi-sequence build'''						,			add_special_tokens=SCREAMING_SNAKE_CASE	)

         A       :   Optional[Any]					=						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE	)
         A       :   Tuple					=						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

         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
         ]




