from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCAmelCase	:       str						       =	{
    "configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__lowerCAmelCase	:       str						       =	[
					    "LILT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "LiltForQuestionAnswering",
					    "LiltForSequenceClassification",
					    "LiltForTokenClassification",
					    "LiltModel",
					    "LiltPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_lilt import (
										    LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    LiltForQuestionAnswering,
										    LiltForSequenceClassification,
										    LiltForTokenClassification,
										    LiltModel,
										    LiltPreTrainedModel,
										)

else:
					import sys

					__lowerCAmelCase	:       Union[str, Any]						       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

'''simple docstring'''


from ...configuration_utils import PretrainedConfig






class 						A   (   UpperCAmelCase   ):
							a_        =      '''bert-generation'''





							def __init__(      self				:							str     ,		__a				:							str=5_0_3_5_8     ,		__a				:							int=1_0_2_4     ,		__a				:							Optional[Any]=2_4     ,		__a				:							Any=1_6     ,		__a				:							int=4_0_9_6     ,		__a				:							Any="gelu"     ,		__a				:							Union[str, Any]=0.1     ,		__a				:							Any=0.1     ,		__a				:							Union[str, Any]=5_1_2     ,		__a				:							int=0.0_2     ,		__a				:							str=1e-12     ,		__a				:							List[str]=0     ,		__a				:							Optional[int]=2     ,		__a				:							Tuple=1     ,		__a				:							str="absolute"     ,		__a				:							Optional[Any]=True     ,		**__a				:							Tuple     ,		)							->	Any:
								super().__init__(pad_token_id=__a     ,		bos_token_id=__a     ,		eos_token_id=__a     ,		**__a	)

								__UpperCAmelCase							=			vocab_size
								__UpperCAmelCase							=			hidden_size
								__UpperCAmelCase							=			num_hidden_layers
								__UpperCAmelCase							=			num_attention_heads
								__UpperCAmelCase							=			hidden_act
								__UpperCAmelCase							=			intermediate_size
								__UpperCAmelCase							=			hidden_dropout_prob
								__UpperCAmelCase							=			attention_probs_dropout_prob
								__UpperCAmelCase							=			max_position_embeddings
								__UpperCAmelCase							=			initializer_range
								__UpperCAmelCase							=			layer_norm_eps
								__UpperCAmelCase							=			position_embedding_type
								__UpperCAmelCase							=			use_cache
