


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


snake_case_  :     int							  =							logging.get_logger(__name__)

snake_case_  :     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   A__							(						UpperCamelCase__					):
						UpperCAmelCase     =  "pegasus_x"
						UpperCAmelCase     =  ["past_key_values"]
						UpperCAmelCase     =  {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}




						def __init__(    self   : int			,      _a   : Optional[Any]=9_6103			,      _a   : int=1_6384			,      _a   : Any=16			,      _a   : Optional[int]=4096			,      _a   : Optional[int]=16			,      _a   : Dict=16			,      _a   : int=4096			,      _a   : Optional[int]=16			,      _a   : Union[str, Any]=0.0			,      _a   : Optional[Any]=0.0			,      _a   : Any=True			,      _a   : Union[str, Any]=True			,      _a   : Optional[Any]="gelu"			,      _a   : Union[str, Any]=1024			,      _a   : Tuple=0.1			,      _a   : int=0.0			,      _a   : Optional[Any]=0.0			,      _a   : int=0.02			,      _a   : int=0			,      _a   : Tuple=True			,      _a   : int=0			,      _a   : Dict=1			,      _a   : List[Any]=1			,      _a   : Any=32			,      _a   : Dict=512			,      _a   : Any=True			,      **_a   : Dict			,      )							->       Any:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=vocab_size
										_SCREAMING_SNAKE_CASE     					=max_position_embeddings
										_SCREAMING_SNAKE_CASE     					=d_model
										_SCREAMING_SNAKE_CASE     					=encoder_ffn_dim
										_SCREAMING_SNAKE_CASE     					=encoder_layers
										_SCREAMING_SNAKE_CASE     					=encoder_attention_heads
										_SCREAMING_SNAKE_CASE     					=decoder_ffn_dim
										_SCREAMING_SNAKE_CASE     					=decoder_layers
										_SCREAMING_SNAKE_CASE     					=decoder_attention_heads
										_SCREAMING_SNAKE_CASE     					=dropout
										_SCREAMING_SNAKE_CASE     					=attention_dropout
										_SCREAMING_SNAKE_CASE     					=activation_dropout
										_SCREAMING_SNAKE_CASE     					=activation_function
										_SCREAMING_SNAKE_CASE     					=init_std
										_SCREAMING_SNAKE_CASE     					=encoder_layerdrop
										_SCREAMING_SNAKE_CASE     					=decoder_layerdrop
										_SCREAMING_SNAKE_CASE     					=use_cache
										_SCREAMING_SNAKE_CASE     					=encoder_layers
										_SCREAMING_SNAKE_CASE     					=scale_embedding  # scale factor will be sqrt(d_model) if True

										_SCREAMING_SNAKE_CASE     					=num_global_tokens
										_SCREAMING_SNAKE_CASE     					=block_size
										_SCREAMING_SNAKE_CASE     					=stagger_local_blocks

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




						@property
						def 							__UpperCamelCase			(    self   : Dict					)							->       int:


										"""simple docstring"""





										return self.encoder_attention_heads




						@property
						def 							__UpperCamelCase			(    self   : Optional[int]					)							->       int:


										"""simple docstring"""





										return self.d_model



import math







def   lowerCamelCase(				a__):
				_SCREAMING_SNAKE_CASE     					=math.log(2		,10) * number
				_SCREAMING_SNAKE_CASE     					=round((log_number - int(a__))		,15)

				return difference







def   lowerCamelCase(				a__ = 67_8910):
				_SCREAMING_SNAKE_CASE     					=90
				_SCREAMING_SNAKE_CASE     					=0

				_SCREAMING_SNAKE_CASE     					=math.log(1.23		,10)
				_SCREAMING_SNAKE_CASE     					=math.log(1.24		,10)
				_SCREAMING_SNAKE_CASE     					=0

				while position < number:
								_SCREAMING_SNAKE_CASE     					=log_difference(a__)

								if difference >= upper_limit:
												power_iterator += 93

								elif difference < lower_limit:
												power_iterator += 196

								else:
												_SCREAMING_SNAKE_CASE     					=power_iterator
												power_iterator += 196
												position += 1

				return previous_power


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							print(f"""{solution() = }""")