






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase_ :						str      =      logging.get_logger(__name__)

UpperCAmelCase_ :						Optional[Any]      =      {
    '''andreasmadsen/efficient_mlm_m0.40''': (
        '''https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'''
    ),
}

class     _SCREAMING_SNAKE_CASE       (			_a      ):
	snake_case__							:     Any     	=  """roberta-prelayernorm"""





	def __init__(		self				:					Optional[int] ,  __lowerCamelCase				:					List[Any]=50_265 ,  __lowerCamelCase				:					Union[str, Any]=768 ,  __lowerCamelCase				:					List[str]=12 ,  __lowerCamelCase				:					List[str]=12 ,  __lowerCamelCase				:					int=3_072 ,  __lowerCamelCase				:					int="gelu" ,  __lowerCamelCase				:					Optional[int]=0.1 ,  __lowerCamelCase				:					str=0.1 ,  __lowerCamelCase				:					str=512 ,  __lowerCamelCase				:					str=2 ,  __lowerCamelCase				:					str=0.02 ,  __lowerCamelCase				:					str=1E-12 ,  __lowerCamelCase				:					Optional[Any]=1 ,  __lowerCamelCase				:					Union[str, Any]=0 ,  __lowerCamelCase				:					Optional[int]=2 ,  __lowerCamelCase				:					List[Any]="absolute" ,  __lowerCamelCase				:					Optional[Any]=True ,  __lowerCamelCase				:					Union[str, Any]=None ,  **__lowerCamelCase				:					List[str] ,  ):
		super().__init__(pad_token_id=snake_case_ ,  bos_token_id=snake_case_ ,  eos_token_id=snake_case_ ,  **snake_case_	)

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

class     _SCREAMING_SNAKE_CASE       (			_a      ):





	@property
	def 						_A (		self				:					List[Any]	):
		if self.task == "multiple-choice":
			UpperCamelCase     :Optional[Any]          =	{0: """batch""", 1: """choice""", 2: """sequence"""}
		else:
			UpperCamelCase     :Optional[Any]          =	{0: """batch""", 1: """sequence"""}
		return OrderedDict(
		    [
		        ("""input_ids""", dynamic_axis),
		        ("""attention_mask""", dynamic_axis),
		    ]	)





'''simple docstring'''





import warnings

from ...utils import logging
from .image_processing_beit import BeitImageProcessor


__a          =		logging.get_logger(__name__)







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    def __init__(    self					:     List[str] ,     *snake_case_					:     str ,     **snake_case_					:     List[str]						):
          warnings.warn(
              """The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
              """ use BeitImageProcessor instead.""" ,     snake_case_ ,     )
          super().__init__(*snake_case_ ,     **snake_case_						)
