





'''simple docstring'''







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


A						    =							logging.get_logger(__name__)

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




class 							__SCREAMING_SNAKE_CASE			(       lowerCAmelCase__      ):
      '''simple docstring'''



      lowerCAmelCase__       :      int 		=		"""videomae"""

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

           _lowercase							:      Optional[int]  						=							image_size
           _lowercase							:      Dict  						=							patch_size
           _lowercase							:      Any  						=							num_channels
           _lowercase							:      Optional[int]  						=							num_frames
           _lowercase							:      List[str]  						=							tubelet_size

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

           _lowercase							:      str  						=							decoder_num_attention_heads
           _lowercase							:      Tuple  						=							decoder_hidden_size
           _lowercase							:      List[str]  						=							decoder_num_hidden_layers
           _lowercase							:      List[str]  						=							decoder_intermediate_size
           _lowercase							:      Dict  						=							norm_pix_loss






'''simple docstring'''







import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


A						    =							logging.get_logger(__name__)



class 							__SCREAMING_SNAKE_CASE			(       lowerCAmelCase__      ):
      '''simple docstring'''



      def __init__(							self    : Tuple   ,*UpperCamelCase    : str   ,**UpperCamelCase    : List[Any]  )		->  None:
           warnings.warn(
               'The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
               ' Please use MobileNetV2ImageProcessor instead.'   ,UpperCamelCase   ,)
           super().__init__(*UpperCamelCase   ,**UpperCamelCase  )