





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


lowerCamelCase__				  =   logging.get_logger(__name__)

lowerCamelCase__				  =   {
    "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      __SCREAMING_SNAKE_CASE    (						a__   ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:int	     =					"vit_mae"

  def __init__(		self   :       Any					,   __a   :       List[str]=768					,   __a   :       Tuple=12					,   __a   :       List[str]=12					,   __a   :       Tuple=3072					,   __a   :       int="gelu"					,   __a   :       Any=0.0					,   __a   :       List[Any]=0.0					,   __a   :       List[Any]=0.02					,   __a   :       Tuple=1e-1_2					,   __a   :       Union[str, Any]=224					,   __a   :       List[Any]=16					,   __a   :       Any=3					,   __a   :       Union[str, Any]=True					,   __a   :       Tuple=16					,   __a   :       Optional[int]=512					,   __a   :       Optional[Any]=8					,   __a   :       Any=2048					,   __a   :       Dict=0.75					,   __a   :       str=False					,   **__a   :       Optional[Any]					,   )		->				List[str]:
        super().__init__(**lowerCamelCase_	)

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







"""simple docstring"""


def 					lowercase__    (					lowercase_		,lowercase_			)					->		None:




      """simple docstring"""

      _UpperCamelCase      :	List[Any]						=       len(lowercase_			)
      print("The following activities are selected:"			)

      # The first activity is always selected
      _UpperCamelCase      :	List[Any]						=       0
      print(lowercase_		,end=","			)

      # Consider rest of the activities
      for j in range(lowercase_			):
            # If this activity has start time greater than
            # or equal to the finish time of previously
            # selected activity, then select it
            if start[j] >= finish[i]:
                  print(lowercase_		,end=","			)
                  _UpperCamelCase      :	Optional[Any]						=       j


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  lowerCamelCase__				  =   [1, 3, 0, 5, 8, 5]
  lowerCamelCase__				  =   [2, 4, 6, 7, 9, 9]
  print_max_activities(start, finish)
