

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


lowerCamelCase_					  =   logging.get_logger(__name__)

lowerCamelCase_					  =   {
    '''ZinengTang/tvlt-base''': '''https://huggingface.co/ZinengTang/tvlt-base/blob/main/config.json''',
}







class 					__lowerCamelCase							(      __snake_case      ):
      lowerCamelCase_      : List[Any]  			=   'tvlt'







      def __init__(	self				,    lowerCamelCase=224				,    lowerCamelCase=2048				,    lowerCamelCase=128				,    lowerCamelCase=[16, 16]				,    lowerCamelCase=[16, 16]				,    lowerCamelCase=3				,    lowerCamelCase=1				,    lowerCamelCase=8				,    lowerCamelCase=768				,    lowerCamelCase=12				,    lowerCamelCase=12				,    lowerCamelCase=3072				,    lowerCamelCase="gelu"				,    lowerCamelCase=0.0				,    lowerCamelCase=0.0				,    lowerCamelCase=0.02				,    lowerCamelCase=1e-6				,    lowerCamelCase=True				,    lowerCamelCase=False				,    lowerCamelCase=16				,    lowerCamelCase=512				,    lowerCamelCase=8				,    lowerCamelCase=2048				,    lowerCamelCase=0.75				,    lowerCamelCase=0.15				,    lowerCamelCase="frame-level"				,    lowerCamelCase=True				,    lowerCamelCase=True				,    lowerCamelCase="classification"				,    **lowerCamelCase				,    )		->			Optional[Any]:
        super().__init__(**lowerCamelCase  )

        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}'''  )

        snake_case_					= image_size
        snake_case_					= spectrogram_length
        snake_case_					= frequency_length
        snake_case_					= image_patch_size
        snake_case_					= audio_patch_size
        snake_case_					= num_image_channels
        snake_case_					= num_audio_channels
        snake_case_					= num_frames

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

        snake_case_					= decoder_num_attention_heads
        snake_case_					= decoder_hidden_size
        snake_case_					= decoder_num_hidden_layers
        snake_case_					= decoder_intermediate_size
        snake_case_					= pixel_mask_ratio
        snake_case_					= audio_mask_ratio
        snake_case_					= audio_mask_type

        snake_case_					= task_matching
        snake_case_					= task_mae
        snake_case_					= loss_type


from math import pi



def   UpperCamelCase(   lowercase_				)      ->							float:





  '''simple docstring'''





  return degree / (180 / pi)


if __name__ == "__main__":
    from doctest import testmod

    testmod()