





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


__lowerCamelCase			:	Optional[int]					    =	logging.get_logger(__name__)

__lowerCamelCase			:	List[Any]					    =	{
    """facebook/vit-mae-base""": """https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json""",
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}



class    A__  (			__snake_case     ):
      _UpperCAmelCase      :int		       =  'vit_mae'





      def __init__(					self			,				A_=768			,				A_=12			,				A_=12			,				A_=3072			,				A_="gelu"			,				A_=0.0			,				A_=0.0			,				A_=0.02			,				A_=1e-12			,				A_=224			,				A_=16			,				A_=3			,				A_=True			,				A_=16			,				A_=512			,				A_=8			,				A_=2048			,				A_=0.75			,				A_=False			,				**A_			,				):
       '''simple docstring'''




       super().__init__(**A_  )

       UpperCamelCase      :   List[str]			      =  hidden_size
       UpperCamelCase      :   Dict			      =  num_hidden_layers
       UpperCamelCase      :   str			      =  num_attention_heads
       UpperCamelCase      :   Optional[int]			      =  intermediate_size
       UpperCamelCase      :   Any			      =  hidden_act
       UpperCamelCase      :   List[str]			      =  hidden_dropout_prob
       UpperCamelCase      :   int			      =  attention_probs_dropout_prob
       UpperCamelCase      :   int			      =  initializer_range
       UpperCamelCase      :   List[str]			      =  layer_norm_eps
       UpperCamelCase      :   int			      =  image_size
       UpperCamelCase      :   int			      =  patch_size
       UpperCamelCase      :   Union[str, Any]			      =  num_channels
       UpperCamelCase      :   Union[str, Any]			      =  qkv_bias
       UpperCamelCase      :   List[Any]			      =  decoder_num_attention_heads
       UpperCamelCase      :   str			      =  decoder_hidden_size
       UpperCamelCase      :   List[str]			      =  decoder_num_hidden_layers
       UpperCamelCase      :   int			      =  decoder_intermediate_size
       UpperCamelCase      :   Tuple			      =  mask_ratio
       UpperCamelCase      :   Any			      =  norm_pix_loss







import warnings

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


__lowerCamelCase			:	Optional[Any]					    =	logging.get_logger(__name__)



class    A__  (			__snake_case     ):





      def __init__(					self			,				*A_			,				**A_  ):
       '''simple docstring'''




       warnings.warn(
           "The class BeitFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
           " use BeitImageProcessor instead."			,				A_			,				)
       super().__init__(*A_			,				**A_  )
