






from __future__ import annotations

import random

class 					snake_case_							:







   """simple docstring"""



   __lowerCAmelCase      =						6

   def __init__(    self:	Optional[Any]	)  ->		Any:


       """simple docstring"""



       _lowercase     =	list(range(1   ,       Dice.NUM_SIDES + 1	)	)

   def 			SCREAMING_SNAKE_CASE__				(    self:	int	)  ->		Union[str, Any]:


       """simple docstring"""



       return random.choice(self.sides	)






def        UpperCAmelCase      (   _lowercase,      _lowercase = 2      ):


    '''simple docstring'''



    _lowercase     =	[Dice() for i in range(_lowercase      )]
    _lowercase     =	[0] * (len(_lowercase      ) * Dice.NUM_SIDES + 1)
    for _ in range(_lowercase      ):
        count_of_sum[sum(dice.roll() for dice in dices      )] += 1
    _lowercase     =	[round((count * 100) / num_throws,      2      ) for count in count_of_sum]
    return probability[num_dice:]  # remove probability of sums that never appear


if __name__ == "__main__":
   import doctest

   doctest.testmod()








from typing import List, Union

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


lowerCamelCase										=  logging.get_logger(__name__)

lowerCamelCase										=  {
    '''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 					snake_case_							(       lowercase_      ):







   """simple docstring"""



   __lowerCAmelCase      =						"""led"""
   __lowerCAmelCase      =						{
       """num_attention_heads""": """encoder_attention_heads""",
       """hidden_size""": """d_model""",
       """attention_probs_dropout_prob""": """attention_dropout""",
       """initializer_range""": """init_std""",
   }

   def __init__(    self:	int   ,       snake_case__:	str=50_265   ,       snake_case__:	Dict=16_384   ,       snake_case__:	str=1_024   ,       snake_case__:	Tuple=12   ,       snake_case__:	int=4_096   ,       snake_case__:	Union[str, Any]=16   ,       snake_case__:	int=12   ,       snake_case__:	Union[str, Any]=4_096   ,       snake_case__:	Optional[Any]=16   ,       snake_case__:	str=0.0   ,       snake_case__:	Optional[Any]=0.0   ,       snake_case__:	List[Any]=True   ,       snake_case__:	List[Any]=True   ,       snake_case__:	List[Any]="gelu"   ,       snake_case__:	Optional[int]=1_024   ,       snake_case__:	List[Any]=0.1   ,       snake_case__:	int=0.0   ,       snake_case__:	List[str]=0.0   ,       snake_case__:	List[str]=0.02   ,       snake_case__:	Dict=2   ,       snake_case__:	int=0.0   ,       snake_case__:	Optional[int]=1   ,       snake_case__:	Tuple=0   ,       snake_case__:	Union[str, Any]=2   ,       snake_case__:	Union[List[int], int] = 512   ,       **snake_case__:	int   ,       )  ->		List[Any]:


       """simple docstring"""



       _lowercase     =	vocab_size
       _lowercase     =	max_encoder_position_embeddings
       _lowercase     =	max_decoder_position_embeddings
       _lowercase     =	d_model
       _lowercase     =	encoder_ffn_dim
       _lowercase     =	encoder_layers
       _lowercase     =	encoder_attention_heads
       _lowercase     =	decoder_ffn_dim
       _lowercase     =	decoder_layers
       _lowercase     =	decoder_attention_heads
       _lowercase     =	dropout
       _lowercase     =	attention_dropout
       _lowercase     =	activation_dropout
       _lowercase     =	activation_function
       _lowercase     =	init_std
       _lowercase     =	encoder_layerdrop
       _lowercase     =	decoder_layerdrop
       _lowercase     =	classifier_dropout
       _lowercase     =	use_cache
       _lowercase     =	encoder_layers
       _lowercase     =	attention_window

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