





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


_lowerCamelCase :    List[Any]  							= logging.get_logger(__name__)

_lowerCamelCase :    Optional[Any]  							= {
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}


class 						lowerCamelCase       (UpperCamelCase__      ):
							UpperCAmelCase_      						=   "lilt"






							def __init__( self     :					List[str],			_UpperCAmelCase     :					Tuple=3_0_5_2_2,			_UpperCAmelCase     :					List[Any]=7_6_8,			_UpperCAmelCase     :					List[Any]=1_2,			_UpperCAmelCase     :					List[str]=1_2,			_UpperCAmelCase     :					Any=3_0_7_2,			_UpperCAmelCase     :					Union[str, Any]="gelu",			_UpperCAmelCase     :					Any=0.1,			_UpperCAmelCase     :					int=0.1,			_UpperCAmelCase     :					Union[str, Any]=5_1_2,			_UpperCAmelCase     :					str=2,			_UpperCAmelCase     :					Optional[Any]=0.02,			_UpperCAmelCase     :					List[str]=1E-12,			_UpperCAmelCase     :					Optional[Any]=0,			_UpperCAmelCase     :					Any="absolute",			_UpperCAmelCase     :					int=None,			_UpperCAmelCase     :					str=4,			_UpperCAmelCase     :					List[str]=1_0_2_4,			**_UpperCAmelCase     :					str,			)				->			Union[str, Any]:





														"""simple docstring"""
														super().__init__(pad_token_id=__lowerCamelCase,			**__lowerCamelCase						)

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













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase :    Union[str, Any]  							= {
    '''configuration_bigbird_pegasus''': [
        '''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''BigBirdPegasusConfig''',
        '''BigBirdPegasusOnnxConfig''',
    ],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowerCamelCase :    int  							= [
		    '''BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BigBirdPegasusForCausalLM''',
		    '''BigBirdPegasusForConditionalGeneration''',
		    '''BigBirdPegasusForQuestionAnswering''',
		    '''BigBirdPegasusForSequenceClassification''',
		    '''BigBirdPegasusModel''',
		    '''BigBirdPegasusPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_bigbird_pegasus import (
		    BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    BigBirdPegasusConfig,
		    BigBirdPegasusOnnxConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_bigbird_pegasus import (
				    BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BigBirdPegasusForCausalLM,
				    BigBirdPegasusForConditionalGeneration,
				    BigBirdPegasusForQuestionAnswering,
				    BigBirdPegasusForSequenceClassification,
				    BigBirdPegasusModel,
				    BigBirdPegasusPreTrainedModel,
				)


else:
		import sys

		_lowerCamelCase :    Optional[Any]  							= _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






