





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


UpperCAmelCase_      							=     logging.get_logger(__name__)

UpperCAmelCase_      							=     {
    "SCUT-DLVCLab/lilt-roberta-en-base": (
        "https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"
    ),
}
class 			UpperCamelCase_		(  _UpperCAmelCase					):
     lowerCAmelCase_							=	'''lilt'''




     def __init__(		self				,						lowerCAmelCase_=3_0522				,						lowerCAmelCase_=768				,						lowerCAmelCase_=12				,						lowerCAmelCase_=12				,						lowerCAmelCase_=3072				,						lowerCAmelCase_="gelu"				,						lowerCAmelCase_=0.1				,						lowerCAmelCase_=0.1				,						lowerCAmelCase_=512				,						lowerCAmelCase_=2				,						lowerCAmelCase_=0.02				,						lowerCAmelCase_=1E-12				,						lowerCAmelCase_=0				,						lowerCAmelCase_="absolute"				,						lowerCAmelCase_=None				,						lowerCAmelCase_=4				,						lowerCAmelCase_=1024				,						**lowerCAmelCase_				,						)		->							Optional[int]:
          super().__init__(pad_token_id=lowerCamelCase_				,						**lowerCamelCase_  )

          _snake_case									=				vocab_size
          _snake_case									=				hidden_size
          _snake_case									=				num_hidden_layers
          _snake_case									=				num_attention_heads
          _snake_case									=				hidden_act
          _snake_case									=				intermediate_size
          _snake_case									=				hidden_dropout_prob
          _snake_case									=				attention_probs_dropout_prob
          _snake_case									=				max_position_embeddings
          _snake_case									=				type_vocab_size
          _snake_case									=				initializer_range
          _snake_case									=				layer_norm_eps
          _snake_case									=				position_embedding_type
          _snake_case									=				classifier_dropout
          _snake_case									=				channel_shrink_ratio
          _snake_case									=				max_ad_position_embeddings










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_      							=     {
    """configuration_bigbird_pegasus""": [
        """BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BigBirdPegasusConfig""",
        """BigBirdPegasusOnnxConfig""",
    ],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase_      							=     [
					    """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

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



