



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


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

A_		:  List[Any]										=  {
    'MCG-NJU/videomae-base': 'https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json',
}



class 		_lowercase		(							UpperCAmelCase__						):
   _UpperCAmelCase  						=      """videomae"""

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


    """simple docstring"""






    super().__init__(**snake_case_				)

    a							=		image_size
    a							=		patch_size
    a							=		num_channels
    a							=		num_frames
    a							=		tubelet_size

    a							=		hidden_size
    a							=		num_hidden_layers
    a							=		num_attention_heads
    a							=		intermediate_size
    a							=		hidden_act
    a							=		hidden_dropout_prob
    a							=		attention_probs_dropout_prob
    a							=		initializer_range
    a							=		layer_norm_eps
    a							=		qkv_bias
    a							=		use_mean_pooling

    a							=		decoder_num_attention_heads
    a							=		decoder_hidden_size
    a							=		decoder_num_hidden_layers
    a							=		decoder_intermediate_size
    a							=		norm_pix_loss








"""simple docstring"""




import warnings

from ...utils import logging
from .image_processing_detr import DetrImageProcessor


lowerCamelCase_	:		List[str]         =   logging.get_logger(__name__)

class 					_UpperCAmelCase    (  UpperCAmelCase__						):



      '''simple docstring'''

      def __init__(	self   , *snake_case_   , **snake_case_    ):

        """simple docstring"""

        warnings.warn(
            'The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
            ' Please use DetrImageProcessor instead.'   , snake_case_   , )
        super().__init__(*snake_case_   , **snake_case_    )