





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


_lowerCamelCase 					=      logging.get_logger(__name__)

_lowerCamelCase 					=      {
    '''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 	UpperCamelCase_							(  SCREAMING_SNAKE_CASE_     ):
							lowerCamelCase_							     =       "luke"


							def __init__(				self     :Optional[Any]				,					__A     :int=5_0267				,					__A     :Dict=50_0000				,					__A     :List[str]=768				,					__A     :Any=256				,					__A     :Dict=12				,					__A     :List[Any]=12				,					__A     :Optional[Any]=3072				,					__A     :List[str]="gelu"				,					__A     :Any=0.1				,					__A     :Any=0.1				,					__A     :Optional[Any]=512				,					__A     :Tuple=2				,					__A     :Tuple=0.0_2				,					__A     :Tuple=1E-12				,					__A     :Dict=True				,					__A     :Dict=None				,					__A     :Union[str, Any]=1				,					__A     :Optional[int]=0				,					__A     :Tuple=2				,					**__A     :Union[str, Any]				,					) -> Any:



									"""simple docstring"""



									super().__init__(pad_token_id=__a				,					bos_token_id=__a				,					eos_token_id=__a				,					**__a		)

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




'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__    :   List[Any]           =					{
    '''configuration_luke''': ['''LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LukeConfig'''],
    '''tokenization_luke''': ['''LukeTokenizer'''],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A__    :   Union[str, Any]           =					[
        '''LUKE_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''LukeForEntityClassification''',
        '''LukeForEntityPairClassification''',
        '''LukeForEntitySpanClassification''',
        '''LukeForMultipleChoice''',
        '''LukeForQuestionAnswering''',
        '''LukeForSequenceClassification''',
        '''LukeForTokenClassification''',
        '''LukeForMaskedLM''',
        '''LukeModel''',
        '''LukePreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
    from .tokenization_luke import LukeTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_luke import (
            LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
            LukeForEntityClassification,
            LukeForEntityPairClassification,
            LukeForEntitySpanClassification,
            LukeForMaskedLM,
            LukeForMultipleChoice,
            LukeForQuestionAnswering,
            LukeForSequenceClassification,
            LukeForTokenClassification,
            LukeModel,
            LukePreTrainedModel,
        )

else:
    import sys

    A__    :   List[str]           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



