





def        lowerCAmelCase_       (							UpperCamelCase_    ,						UpperCamelCase_     )   ->						List[str]:
       sequence.append(UpperCamelCase_     )

       UpperCamelCase_      				=     0
       while sequence[index] != target:
              index += 1

       sequence.pop()

       if index == len(UpperCamelCase_     ):
              return None

       return index


if __name__ == "__main__":
     _UpperCAmelCase				       = input('Enter numbers separated by comma:\n').strip()
     _UpperCAmelCase				       = [int(item) for item in user_input.split(',')]

     _UpperCAmelCase				       = input('Enter a single number to be found in the list:\n')
     _UpperCAmelCase				       = int(target_input)
     _UpperCAmelCase				       = sentinel_linear_search(sequence, target)
     if result is not None:
          print(f'''{target} found at positions: {result}''')
     else:
          print('Not found')








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


_UpperCAmelCase				       = logging.get_logger(__name__)

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



class 							_UpperCamelCase    (		lowerCAmelCase_   ):
       _UpperCamelCase :    List[Any]   			=      '''videomae'''

       def __init__(						self:       Optional[Any]    ,      _SCREAMING_SNAKE_CASE:       List[str]=224    ,      _SCREAMING_SNAKE_CASE:       Dict=16    ,      _SCREAMING_SNAKE_CASE:       List[Any]=3    ,      _SCREAMING_SNAKE_CASE:       Tuple=16    ,      _SCREAMING_SNAKE_CASE:       Tuple=2    ,      _SCREAMING_SNAKE_CASE:       Optional[Any]=768    ,      _SCREAMING_SNAKE_CASE:       str=12    ,      _SCREAMING_SNAKE_CASE:       List[Any]=12    ,      _SCREAMING_SNAKE_CASE:       Dict=3072    ,      _SCREAMING_SNAKE_CASE:       Tuple="gelu"    ,      _SCREAMING_SNAKE_CASE:       List[Any]=0.0    ,      _SCREAMING_SNAKE_CASE:       List[Any]=0.0    ,      _SCREAMING_SNAKE_CASE:       Tuple=0.02    ,      _SCREAMING_SNAKE_CASE:       Optional[int]=1e-12    ,      _SCREAMING_SNAKE_CASE:       Dict=True    ,      _SCREAMING_SNAKE_CASE:       Dict=True    ,      _SCREAMING_SNAKE_CASE:       List[str]=6    ,      _SCREAMING_SNAKE_CASE:       Dict=384    ,      _SCREAMING_SNAKE_CASE:       Any=4    ,      _SCREAMING_SNAKE_CASE:       Dict=1536    ,      _SCREAMING_SNAKE_CASE:       Optional[int]=True    ,      **_SCREAMING_SNAKE_CASE:       str    ,      )				->       Dict:




              """simple docstring"""


              super().__init__(**_SCREAMING_SNAKE_CASE						)

              UpperCamelCase_      				=     image_size
              UpperCamelCase_      				=     patch_size
              UpperCamelCase_      				=     num_channels
              UpperCamelCase_      				=     num_frames
              UpperCamelCase_      				=     tubelet_size

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

              UpperCamelCase_      				=     decoder_num_attention_heads
              UpperCamelCase_      				=     decoder_hidden_size
              UpperCamelCase_      				=     decoder_num_hidden_layers
              UpperCamelCase_      				=     decoder_intermediate_size
              UpperCamelCase_      				=     norm_pix_loss

