

'''simple docstring'''







from __future__ import annotations
def    UpperCAmelCase__     (   UpperCAmelCase__,							UpperCAmelCase__					)      ->      list[int]:
       A_						       =   0
       A_						       =   len(UpperCAmelCase__					) - 1

       while i < j:
              if nums[i] + nums[j] == target:
                     return [i, j]
              elif nums[i] + nums[j] < target:
                     A_						       =   i + 1
              else:
                     A_						       =   j - 1

       return []


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      print(f"""{two_pointer([2, 7, 11, 15], 9) = }""")



'''simple docstring'''







from ...configuration_utils import PretrainedConfig


class        A__   (   _snake_case      ):
    lowercase						       =		"bert-generation"



    def __init__(       self		,					UpperCamelCase__=50358		,					UpperCamelCase__=1024		,					UpperCamelCase__=24		,					UpperCamelCase__=16		,					UpperCamelCase__=4096		,					UpperCamelCase__="gelu"		,					UpperCamelCase__=0.1		,					UpperCamelCase__=0.1		,					UpperCamelCase__=512		,					UpperCamelCase__=0.02		,					UpperCamelCase__=1e-1_2		,					UpperCamelCase__=0		,					UpperCamelCase__=2		,					UpperCamelCase__=1		,					UpperCamelCase__="absolute"		,					UpperCamelCase__=True		,					**UpperCamelCase__		,					)    ->   Any:





           '''simple docstring'''
           super().__init__(pad_token_id=UpperCamelCase__		,					bos_token_id=UpperCamelCase__		,					eos_token_id=UpperCamelCase__		,					**UpperCamelCase__							)

           A_						       =   vocab_size
           A_						       =   hidden_size
           A_						       =   num_hidden_layers
           A_						       =   num_attention_heads
           A_						       =   hidden_act
           A_						       =   intermediate_size
           A_						       =   hidden_dropout_prob
           A_						       =   attention_probs_dropout_prob
           A_						       =   max_position_embeddings
           A_						       =   initializer_range
           A_						       =   layer_norm_eps
           A_						       =   position_embedding_type
           A_						       =   use_cache
