




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


SCREAMING_SNAKE_CASE_    :       Any       =							logging.get_logger(__name__)

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







class 		__UpperCAmelCase(		lowercase__			):





     """simple docstring"""



     __UpperCAmelCase						:			Union[str, Any]							=     """tvlt"""

     def __init__(   self			:							str    ,					A			:							int=2_24    ,					A			:							Optional[int]=20_48    ,					A			:							List[Any]=1_28    ,					A			:							Optional[int]=[16, 16]    ,					A			:							Union[str, Any]=[16, 16]    ,					A			:							Optional[Any]=3    ,					A			:							str=1    ,					A			:							Optional[Any]=8    ,					A			:							str=7_68    ,					A			:							Any=12    ,					A			:							Any=12    ,					A			:							Optional[int]=30_72    ,					A			:							Dict="gelu"    ,					A			:							Any=0.0    ,					A			:							Dict=0.0    ,					A			:							Optional[int]=0.0_2    ,					A			:							Optional[Any]=1E-6    ,					A			:							Tuple=True    ,					A			:							Optional[int]=False    ,					A			:							str=16    ,					A			:							Any=5_12    ,					A			:							Dict=8    ,					A			:							List[str]=20_48    ,					A			:							Union[str, Any]=0.7_5    ,					A			:							Optional[int]=0.1_5    ,					A			:							str="frame-level"    ,					A			:							Optional[Any]=True    ,					A			:							int=True    ,					A			:							Optional[int]="classification"    ,					**A			:							str    ,					)      ->      int:






         """simple docstring"""
         super().__init__(**A     )

         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__  			=							image_size
         a__  			=							spectrogram_length
         a__  			=							frequency_length
         a__  			=							image_patch_size
         a__  			=							audio_patch_size
         a__  			=							num_image_channels
         a__  			=							num_audio_channels
         a__  			=							num_frames

         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__  			=							pixel_mask_ratio
         a__  			=							audio_mask_ratio
         a__  			=							audio_mask_type

         a__  			=							task_matching
         a__  			=							task_mae
         a__  			=							loss_type












from __future__ import annotations

import sys
def 							__lowerCAmelCase			(UpperCAmelCase_		):
    if n < 0:
        raise ValueError("""Negative arguments are not supported"""		)
    return _fib(UpperCAmelCase_		)[0]
def 							__lowerCAmelCase			(UpperCAmelCase_		):
    if n == 0:  # (F(0), F(1))
        return (0, 1)

    # F(2n) = F(n)[2F(n+1) − F(n)]
    # F(2n+1) = F(n+1)^2+F(n)^2
    a__			,		a__  			=							_fib(n // 2		)
    a__  			=							a * (b * 2 - a)
    a__  			=							a * a + b * b
    return (d, c + d) if n % 2 else (c, d)


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE_    :       Dict       =							int(sys.argv[1])
 print(F"fibonacci({n}) is {fibonacci(n)}")






