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


lowercase						:      Union[str, Any]									= logging.get_logger(__name__)

lowercase						:      Any									= {
    '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 				lowerCamelCase__							(       __lowercase):




	'''simple docstring'''




	_A			=  'luke'







	def __init__(      self	:List[Any]  ,     a	:Union[str, Any]=5_0_2_6_7  ,     a	:Union[str, Any]=5_0_0_0_0_0  ,     a	:List[Any]=7_6_8  ,     a	:Union[str, Any]=2_5_6  ,     a	:Union[str, Any]=1_2  ,     a	:Union[str, Any]=1_2  ,     a	:List[Any]=3_0_7_2  ,     a	:Dict="gelu"  ,     a	:List[str]=0.1  ,     a	:str=0.1  ,     a	:List[Any]=5_1_2  ,     a	:int=2  ,     a	:str=0.02  ,     a	:Optional[int]=1E-1_2  ,     a	:List[str]=True  ,     a	:Union[str, Any]=None  ,     a	:Union[str, Any]=1  ,     a	:List[Any]=0  ,     a	:Tuple=2  ,     **a	:Optional[int]  ,     )	->				Optional[int]:
								super().__init__(pad_token_id=a  ,     bos_token_id=a  ,     eos_token_id=a  ,     **a		)

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

from typing import TYPE_CHECKING

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


lowercase						:      str									= {
    'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'VisionEncoderDecoderOnnxConfig']
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase						:      str									= ['VisionEncoderDecoderModel']

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase						:      List[Any]									= ['TFVisionEncoderDecoderModel']

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase						:      int									= ['FlaxVisionEncoderDecoderModel']

if TYPE_CHECKING:
		from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig, VisionEncoderDecoderOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel

else:
		import sys

		lowercase						:      Dict									= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)