






"""simple docstring"""


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


_UpperCamelCase   :						str     						= logging.get_logger(__name__)

_UpperCamelCase   :						Tuple     						= {
    """uw-madison/yoso-4096""": """https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json""",
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}






class __a   (   snake_case_				):
  __lowercase    :    str						=					'yoso'



  def __init__(self  :		int				,			lowercase_  :		Optional[Any]=50_265				,			lowercase_  :		Tuple=768				,			lowercase_  :		Tuple=12				,			lowercase_  :		Dict=12				,			lowercase_  :		Union[str, Any]=3_072				,			lowercase_  :		Union[str, Any]="gelu"				,			lowercase_  :		Union[str, Any]=0.1				,			lowercase_  :		Tuple=0.1				,			lowercase_  :		Optional[Any]=4_096				,			lowercase_  :		List[str]=1				,			lowercase_  :		Optional[int]=0.02				,			lowercase_  :		int=1E-12				,			lowercase_  :		int="absolute"				,			lowercase_  :		List[Any]=True				,			lowercase_  :		List[Any]=9				,			lowercase_  :		List[str]=64				,			lowercase_  :		Optional[int]=None				,			lowercase_  :		Union[str, Any]=True				,			lowercase_  :		str=True				,			lowercase_  :		int=1				,			lowercase_  :		List[Any]=0				,			lowercase_  :		Optional[Any]=2				,			**lowercase_  :		Tuple				,			)		->							Union[str, Any]:
   super().__init__(pad_token_id=lowercase_				,			bos_token_id=lowercase_				,			eos_token_id=lowercase_				,			**lowercase_   )

   __A	:       Optional[Any]       =	vocab_size
   __A	:       Optional[int]       =	max_position_embeddings
   __A	:       str       =	hidden_size
   __A	:       Any       =	num_hidden_layers
   __A	:       Optional[int]       =	num_attention_heads
   __A	:       Tuple       =	intermediate_size
   __A	:       Dict       =	hidden_act
   __A	:       List[Any]       =	hidden_dropout_prob
   __A	:       Optional[int]       =	attention_probs_dropout_prob
   __A	:       str       =	initializer_range
   __A	:       Union[str, Any]       =	type_vocab_size
   __A	:       int       =	layer_norm_eps
   __A	:       List[str]       =	position_embedding_type
   __A	:       Tuple       =	use_expectation
   __A	:       Optional[int]       =	hash_code_len
   __A	:       Any       =	num_hash
   __A	:       str       =	conv_window
   __A	:       Optional[Any]       =	use_fast_hash
   __A	:       Dict       =	lsh_backward













"""simple docstring"""


def 				a (     UpperCamelCase_							:				list     ,	UpperCamelCase_							:				int		)  ->		int:
 for index, item in enumerate(UpperCamelCase_		):
  if item == target:
   return index
 return -1




def 				a (     UpperCamelCase_							:				list     ,	UpperCamelCase_							:				int     ,	UpperCamelCase_							:				int     ,	UpperCamelCase_							:				int		)  ->		int:
 if not (0 <= high < len(UpperCamelCase_		) and 0 <= low < len(UpperCamelCase_		)):
  raise Exception('Invalid upper or lower bound!'		)
 if high < low:
  return -1
 if sequence[low] == target:
  return low
 if sequence[high] == target:
  return high
 return rec_linear_search(UpperCamelCase_     ,	low + 1     ,	high - 1     ,	UpperCamelCase_		)


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

   _UpperCamelCase   :						List[str]     						= int(input("""Enter a single number to be found in the list:\n""").strip())
   _UpperCamelCase   :						List[Any]     						= linear_search(sequence, target)
   if result != -1:
      print(f'''linear_search({sequence}, {target}) = {result}''')
   else:
      print(f'''{target} was not found in {sequence}''')





