


from typing import List, Union

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


snake_case_  :     str							  =							logging.get_logger(__name__)

snake_case_  :     Optional[int]							  =							{
    '''allenai/led-base-16384''': '''https://huggingface.co/allenai/led-base-16384/resolve/main/config.json''',
    # See all LED models at https://huggingface.co/models?filter=led
}

class   A__							(						UpperCamelCase__					):
						UpperCAmelCase     =  "led"
						UpperCAmelCase     =  {
						    "num_attention_heads": "encoder_attention_heads",
						    "hidden_size": "d_model",
						    "attention_probs_dropout_prob": "attention_dropout",
						    "initializer_range": "init_std",
						}




						def __init__(    self   : Any			,      _a   : Tuple=5_0265			,      _a   : List[str]=1_6384			,      _a   : List[str]=1024			,      _a   : Dict=12			,      _a   : Tuple=4096			,      _a   : Optional[Any]=16			,      _a   : Tuple=12			,      _a   : Any=4096			,      _a   : List[Any]=16			,      _a   : str=0.0			,      _a   : Optional[int]=0.0			,      _a   : Dict=True			,      _a   : Dict=True			,      _a   : Optional[int]="gelu"			,      _a   : Dict=1024			,      _a   : List[str]=0.1			,      _a   : Union[str, Any]=0.0			,      _a   : Tuple=0.0			,      _a   : str=0.02			,      _a   : str=2			,      _a   : Union[str, Any]=0.0			,      _a   : Optional[Any]=1			,      _a   : Optional[int]=0			,      _a   : Optional[int]=2			,      _a   : Union[List[int], int] = 512			,      **_a   : Optional[int]			,      )							->       int:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=vocab_size
										_SCREAMING_SNAKE_CASE     					=max_encoder_position_embeddings
										_SCREAMING_SNAKE_CASE     					=max_decoder_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     					=classifier_dropout
										_SCREAMING_SNAKE_CASE     					=use_cache
										_SCREAMING_SNAKE_CASE     					=encoder_layers
										_SCREAMING_SNAKE_CASE     					=attention_window

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



import math

class   A__							:




						def __init__(    self   : Optional[int]			,      _a   : int			,      _a   : List[Any]			,      _a   : int					)							->       Optional[int]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=x
										_SCREAMING_SNAKE_CASE     					=y
										_SCREAMING_SNAKE_CASE     					=z




						def __repr__(    self   : List[str]					)							->       str:


										"""simple docstring"""





										return f"Point({self.x}, {self.y}, {self.z})"







def   lowerCamelCase(				a__		,a__):
				return math.sqrt(abs((b.x - a.x) ** 2 + (b.y - a.y) ** 2 + (b.z - a.z) ** 2))


if __name__ == "__main__":
							import doctest

							doctest.testmod()