



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


lowerCamelCase		       =      logging.get_logger(__name__)

lowerCamelCase		       =      {
    """SCUT-DLVCLab/lilt-roberta-en-base""": (
        """https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"""
    ),
}


class 				_a						(       SCREAMING_SNAKE_CASE			):





							'''simple docstring'''

							A				:Optional[int] =       "lilt"



							def __init__(							self ,					__UpperCAmelCase=3_0522 ,					__UpperCAmelCase=768 ,					__UpperCAmelCase=12 ,					__UpperCAmelCase=12 ,					__UpperCAmelCase=3072 ,					__UpperCAmelCase="gelu" ,					__UpperCAmelCase=0.1 ,					__UpperCAmelCase=0.1 ,					__UpperCAmelCase=512 ,					__UpperCAmelCase=2 ,					__UpperCAmelCase=0.0_2 ,					__UpperCAmelCase=1E-12 ,					__UpperCAmelCase=0 ,					__UpperCAmelCase="absolute" ,					__UpperCAmelCase=None ,					__UpperCAmelCase=4 ,					__UpperCAmelCase=1024 ,					**__UpperCAmelCase ,					):







											"""simple docstring"""



											super().__init__(pad_token_id=__UpperCAmelCase ,					**__UpperCAmelCase				)

											a__	:							List[Any]      						= vocab_size
											a__	:							Any      						= hidden_size
											a__	:							List[str]      						= num_hidden_layers
											a__	:							int      						= num_attention_heads
											a__	:							Any      						= hidden_act
											a__	:							List[Any]      						= intermediate_size
											a__	:							List[str]      						= hidden_dropout_prob
											a__	:							List[str]      						= attention_probs_dropout_prob
											a__	:							List[str]      						= max_position_embeddings
											a__	:							int      						= type_vocab_size
											a__	:							Optional[int]      						= initializer_range
											a__	:							Any      						= layer_norm_eps
											a__	:							Tuple      						= position_embedding_type
											a__	:							Optional[int]      						= classifier_dropout
											a__	:							Tuple      						= channel_shrink_ratio
											a__	:							Dict      						= max_ad_position_embeddings







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


lowerCamelCase		       =      {}


try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase		       =      ["""MLukeTokenizer"""]

if TYPE_CHECKING:
						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_mluke import MLukeTokenizer


else:
						import sys

						lowerCamelCase		       =      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


