



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


__SCREAMING_SNAKE_CASE     =	logging.get_logger(__name__)

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

class 						lowerCamelCase_     (			a_    ):






						'''simple docstring'''
						a__ =	"videomae"







						def __init__(						self   :      List[Any]						,						__lowerCamelCase   :      int=2_24						,						__lowerCamelCase   :      Union[str, Any]=16						,						__lowerCamelCase   :      Union[str, Any]=3						,						__lowerCamelCase   :      str=16						,						__lowerCamelCase   :      Optional[Any]=2						,						__lowerCamelCase   :      Optional[int]=7_68						,						__lowerCamelCase   :      List[Any]=12						,						__lowerCamelCase   :      Tuple=12						,						__lowerCamelCase   :      Optional[int]=30_72						,						__lowerCamelCase   :      str="gelu"						,						__lowerCamelCase   :      Any=0.0						,						__lowerCamelCase   :      Tuple=0.0						,						__lowerCamelCase   :      Optional[Any]=0.02						,						__lowerCamelCase   :      int=1e-12						,						__lowerCamelCase   :      Optional[int]=True						,						__lowerCamelCase   :      int=True						,						__lowerCamelCase   :      List[Any]=6						,						__lowerCamelCase   :      Optional[int]=3_84						,						__lowerCamelCase   :      List[str]=4						,						__lowerCamelCase   :      Union[str, Any]=15_36						,						__lowerCamelCase   :      Optional[Any]=True						,						**__lowerCamelCase   :      Union[str, Any]						,						)   ->					Optional[int]:
									super().__init__(**UpperCAmelCase_			)

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

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

									A				:       str														=    decoder_num_attention_heads
									A				:       Tuple														=    decoder_hidden_size
									A				:       List[Any]														=    decoder_num_hidden_layers
									A				:       int														=    decoder_intermediate_size
									A				:       List[str]														=    norm_pix_loss
'''simple docstring'''





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


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

UpperCamelCase       :     Union[str, Any]			=    {
    """ZinengTang/tvlt-base""": """https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json""",
}



class   UpperCamelCase					(       a_       ):







    """simple docstring"""





    A     :    int				=			"tvlt"





    def __init__(					self     :						List[str]							,							UpperCAmelCase_     :						Any=2_2_4							,							UpperCAmelCase_     :						Optional[Any]=2_0_4_8							,							UpperCAmelCase_     :						Dict=1_2_8							,							UpperCAmelCase_     :						str=[1_6, 1_6]							,							UpperCAmelCase_     :						int=[1_6, 1_6]							,							UpperCAmelCase_     :						int=3							,							UpperCAmelCase_     :						Optional[int]=1							,							UpperCAmelCase_     :						List[str]=8							,							UpperCAmelCase_     :						List[Any]=7_6_8							,							UpperCAmelCase_     :						int=1_2							,							UpperCAmelCase_     :						List[Any]=1_2							,							UpperCAmelCase_     :						Optional[Any]=3_0_7_2							,							UpperCAmelCase_     :						List[str]="gelu"							,							UpperCAmelCase_     :						Tuple=0.0							,							UpperCAmelCase_     :						Optional[Any]=0.0							,							UpperCAmelCase_     :						Tuple=0.02							,							UpperCAmelCase_     :						Any=1e-6							,							UpperCAmelCase_     :						Dict=True							,							UpperCAmelCase_     :						Union[str, Any]=False							,							UpperCAmelCase_     :						Tuple=1_6							,							UpperCAmelCase_     :						str=5_1_2							,							UpperCAmelCase_     :						List[str]=8							,							UpperCAmelCase_     :						Union[str, Any]=2_0_4_8							,							UpperCAmelCase_     :						Tuple=0.75							,							UpperCAmelCase_     :						Optional[Any]=0.15							,							UpperCAmelCase_     :						Union[str, Any]="frame-level"							,							UpperCAmelCase_     :						List[str]=True							,							UpperCAmelCase_     :						Any=True							,							UpperCAmelCase_     :						Optional[int]="classification"							,							**UpperCAmelCase_     :						Any							,							):


         """simple docstring"""







         super().__init__(**UpperCAmelCase_)

         if audio_mask_type not in ("frame-level", "patch_level"):
              raise ValueError(
                  'audio_mask_type must be one of two acceptable strategies - {\'frame_level\', \'patch-level\') '
                  f"""got {audio_mask_type}""")

         a					:							str							= image_size
         a					:							List[Any]							= spectrogram_length
         a					:							Union[str, Any]							= frequency_length
         a					:							str							= image_patch_size
         a					:							Dict							= audio_patch_size
         a					:							Dict							= num_image_channels
         a					:							Tuple							= num_audio_channels
         a					:							Optional[int]							= num_frames

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

         a					:							List[Any]							= decoder_num_attention_heads
         a					:							Any							= decoder_hidden_size
         a					:							int							= decoder_num_hidden_layers
         a					:							Tuple							= decoder_intermediate_size
         a					:							Tuple							= pixel_mask_ratio
         a					:							List[Any]							= audio_mask_ratio
         a					:							Optional[Any]							= audio_mask_type

         a					:							Any							= task_matching
         a					:							Optional[Any]							= task_mae
         a					:							List[str]							= loss_type

