




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


__lowerCAmelCase		:    Optional[int]	      =		logging.get_logger(__name__)

__lowerCAmelCase		:    List[Any]	      =		{
    'google/pegasus-x-base': 'https://huggingface.co/google/pegasus-x-base/resolve/main/config.json',
    'google/pegasus-x-large': 'https://huggingface.co/google/pegasus-x-large/resolve/main/config.json',
    # See all PEGASUS-X models at https://huggingface.co/models?filter=pegasus-x
}




class    snake_case__							(_UpperCamelCase       ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_	:							Dict										= """pegasus_x"""
				SCREAMING_SNAKE_CASE_	:							Any										= ["""past_key_values"""]
				SCREAMING_SNAKE_CASE_	:							Dict										= {"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}





				def __init__(				self    :					Union[str, Any] ,				__lowerCamelCase    :					List[str]=9_61_03 ,				__lowerCamelCase    :					List[Any]=1_63_84 ,				__lowerCamelCase    :					str=16 ,				__lowerCamelCase    :					Tuple=40_96 ,				__lowerCamelCase    :					str=16 ,				__lowerCamelCase    :					Tuple=16 ,				__lowerCamelCase    :					str=40_96 ,				__lowerCamelCase    :					str=16 ,				__lowerCamelCase    :					Union[str, Any]=0.0 ,				__lowerCamelCase    :					Dict=0.0 ,				__lowerCamelCase    :					Optional[Any]=True ,				__lowerCamelCase    :					List[Any]=True ,				__lowerCamelCase    :					List[Any]="gelu" ,				__lowerCamelCase    :					Tuple=10_24 ,				__lowerCamelCase    :					Dict=0.1 ,				__lowerCamelCase    :					Any=0.0 ,				__lowerCamelCase    :					Optional[int]=0.0 ,				__lowerCamelCase    :					List[Any]=0.02 ,				__lowerCamelCase    :					Optional[int]=0 ,				__lowerCamelCase    :					List[Any]=True ,				__lowerCamelCase    :					str=0 ,				__lowerCamelCase    :					List[str]=1 ,				__lowerCamelCase    :					str=1 ,				__lowerCamelCase    :					str=32 ,				__lowerCamelCase    :					Union[str, Any]=5_12 ,				__lowerCamelCase    :					Dict=True ,				**__lowerCamelCase    :					Any ,				) ->					int:
							a   =      vocab_size
							a   =      max_position_embeddings
							a   =      d_model
							a   =      encoder_ffn_dim
							a   =      encoder_layers
							a   =      encoder_attention_heads
							a   =      decoder_ffn_dim
							a   =      decoder_layers
							a   =      decoder_attention_heads
							a   =      dropout
							a   =      attention_dropout
							a   =      activation_dropout
							a   =      activation_function
							a   =      init_std
							a   =      encoder_layerdrop
							a   =      decoder_layerdrop
							a   =      use_cache
							a   =      encoder_layers
							a   =      scale_embedding  # scale factor will be sqrt(d_model) if True

							a   =      num_global_tokens
							a   =      block_size
							a   =      stagger_local_blocks

							super().__init__(
							    pad_token_id=__lowerCamelCase ,				eos_token_id=__lowerCamelCase ,				is_encoder_decoder=__lowerCamelCase ,				decoder_start_token_id=__lowerCamelCase ,				forced_eos_token_id=__lowerCamelCase ,				**__lowerCamelCase ,				)





				@property
				def 							__UpperCAmelCase							(				self    :					str							) ->					int:
							return self.encoder_attention_heads





				@property
				def 							__UpperCAmelCase							(				self    :					List[Any]							) ->					int:
							return self.d_model












def       __magic_name__    (			A		: float       ):






			'''simple docstring'''







			return -num if num < 0 else num




def       __magic_name__    (			A		: list[int]       ):






			'''simple docstring'''







			if len(A       ) == 0:
						raise ValueError("abs_min() arg is an empty sequence"       )
			a   =      x[0]
			for i in x:
						if abs_val(A       ) < abs_val(A       ):
									a   =      i
			return j




def       __magic_name__    (			A		: list[int]       ):






			'''simple docstring'''







			if len(A       ) == 0:
						raise ValueError("abs_max() arg is an empty sequence"       )
			a   =      x[0]
			for i in x:
						if abs(A       ) > abs(A       ):
									a   =      i
			return j




def       __magic_name__    (			A		: list[int]       ):






			'''simple docstring'''







			if len(A       ) == 0:
						raise ValueError("abs_max_sort() arg is an empty sequence"       )
			return sorted(A,  key=A       )[-1]




def       __magic_name__    (			):






			'''simple docstring'''







			assert abs_val(0       ) == 0
			assert abs_val(34       ) == 34
			assert abs_val(-100000000000       ) == 100000000000

			a   =      [-3, -1, 2, -11]
			assert abs_max(A       ) == -11
			assert abs_max_sort(A       ) == -11
			assert abs_min(A       ) == -1


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		test_abs_val()
		print(abs_val(-34))  # --> 34






