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


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

lowerCAmelCase      :				Tuple     			={
    'MCG-NJU/videomae-base': 'https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json',
}




class 						__snake_case						(			SCREAMING_SNAKE_CASE__		):





      '''simple docstring'''






      _snake_case     		=							'videomae'



      def __init__(       self  :					Union[str, Any]     ,	_UpperCamelCase  :					Tuple=224     ,	_UpperCamelCase  :					str=16     ,	_UpperCamelCase  :					Union[str, Any]=3     ,	_UpperCamelCase  :					Optional[int]=16     ,	_UpperCamelCase  :					List[Any]=2     ,	_UpperCamelCase  :					int=768     ,	_UpperCamelCase  :					int=12     ,	_UpperCamelCase  :					str=12     ,	_UpperCamelCase  :					Union[str, Any]=3072     ,	_UpperCamelCase  :					Tuple="gelu"     ,	_UpperCamelCase  :					Optional[int]=0.0     ,	_UpperCamelCase  :					Optional[Any]=0.0     ,	_UpperCamelCase  :					Optional[int]=0.0_2     ,	_UpperCamelCase  :					Union[str, Any]=1E-1_2     ,	_UpperCamelCase  :					Optional[Any]=True     ,	_UpperCamelCase  :					Optional[Any]=True     ,	_UpperCamelCase  :					int=6     ,	_UpperCamelCase  :					List[str]=384     ,	_UpperCamelCase  :					List[str]=4     ,	_UpperCamelCase  :					Any=1536     ,	_UpperCamelCase  :					Any=True     ,	**_UpperCamelCase  :					List[str]     ,	)					->List[str]:


          """simple docstring"""


          super().__init__(**_UpperCamelCase)

          _lowerCamelCase  :		Union[str, Any]			    =    image_size
          _lowerCamelCase  :		Union[str, Any]			    =    patch_size
          _lowerCamelCase  :		Union[str, Any]			    =    num_channels
          _lowerCamelCase  :		Union[str, Any]			    =    num_frames
          _lowerCamelCase  :		str			    =    tubelet_size

          _lowerCamelCase  :		Optional[Any]			    =    hidden_size
          _lowerCamelCase  :		Dict			    =    num_hidden_layers
          _lowerCamelCase  :		Tuple			    =    num_attention_heads
          _lowerCamelCase  :		Tuple			    =    intermediate_size
          _lowerCamelCase  :		Union[str, Any]			    =    hidden_act
          _lowerCamelCase  :		Union[str, Any]			    =    hidden_dropout_prob
          _lowerCamelCase  :		Union[str, Any]			    =    attention_probs_dropout_prob
          _lowerCamelCase  :		Optional[Any]			    =    initializer_range
          _lowerCamelCase  :		int			    =    layer_norm_eps
          _lowerCamelCase  :		List[Any]			    =    qkv_bias
          _lowerCamelCase  :		List[str]			    =    use_mean_pooling

          _lowerCamelCase  :		Any			    =    decoder_num_attention_heads
          _lowerCamelCase  :		Any			    =    decoder_hidden_size
          _lowerCamelCase  :		int			    =    decoder_num_hidden_layers
          _lowerCamelCase  :		Tuple			    =    decoder_intermediate_size
          _lowerCamelCase  :		str			    =    norm_pix_loss











from ..utils import DummyObject, requires_backends



class  SCREAMING_SNAKE_CASE_  ( metaclass=SCREAMING_SNAKE_CASE__			):


  """simple docstring"""





  _a								=							["""torch""", """transformers""", """k_diffusion"""]





  def __init__(  self	,  *A	,  **A						)		->   Optional[Any]:





       '''simple docstring'''







       requires_backends(self	,  ['''torch''', '''transformers''', '''k_diffusion''']						)





  @classmethod
  def 			__A      (  cls	,  *A	,  **A						)		->   Dict:





       '''simple docstring'''







       requires_backends(cls	,  ['''torch''', '''transformers''', '''k_diffusion''']						)







  @classmethod
  def 			__A      (  cls	,  *A	,  **A						)		->   Optional[Any]:





       '''simple docstring'''







       requires_backends(cls	,  ['''torch''', '''transformers''', '''k_diffusion''']						)