






'''simple docstring'''



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


SCREAMING_SNAKE_CASE							=						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							=						{
    '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_       (     __A					):




      """simple docstring"""




      UpperCamelCase_             =      '''luke'''






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


       '''simple docstring'''

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

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





"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


UpperCamelCase__          =	{
    'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__          =	[
        'MEGA_PRETRAINED_MODEL_ARCHIVE_LIST',
        'MegaForCausalLM',
        'MegaForMaskedLM',
        'MegaForMultipleChoice',
        'MegaForQuestionAnswering',
        'MegaForSequenceClassification',
        'MegaForTokenClassification',
        'MegaModel',
        'MegaPreTrainedModel',
    ]

if TYPE_CHECKING:
    from .configuration_mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig, MegaOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mega import (
            MEGA_PRETRAINED_MODEL_ARCHIVE_LIST,
            MegaForCausalLM,
            MegaForMaskedLM,
            MegaForMultipleChoice,
            MegaForQuestionAnswering,
            MegaForSequenceClassification,
            MegaForTokenClassification,
            MegaModel,
            MegaPreTrainedModel,
        )

else:
    import sys

    UpperCamelCase__          =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

