code: import copy
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowercase__    :       Any						=			logging.get_logger(__name__)
  
  lowercase__    :       int						=			{}
  
  
  
  
  class      lowercase_						(						a_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      Dict     =       'fsmt_decoder'
  
  
  	def __init__(							self	,    __SCREAMING_SNAKE_CASE=0	,    __SCREAMING_SNAKE_CASE=0       )		->Union[str, Any]:
  								super().__init__()
  								lowerCAmelCase				=	vocab_size
  								lowerCAmelCase				=	bos_token_id
  
  
  
  
  class      lowercase_						(						a_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      Tuple     =       'fsmt'
  	UpperCAmelCase_						:      List[str]     =       {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}
  
  
  	def __init__(							self	,    __SCREAMING_SNAKE_CASE=["en", "de"]	,    __SCREAMING_SNAKE_CASE=42024	,    __SCREAMING_SNAKE_CASE=42024	,    __SCREAMING_SNAKE_CASE="relu"	,    __SCREAMING_SNAKE_CASE=1024	,    __SCREAMING_SNAKE_CASE=200	,    __SCREAMING_SNAKE_CASE=1024	,    __SCREAMING_SNAKE_CASE=4096	,    __SCREAMING_SNAKE_CASE=12	,    __SCREAMING_SNAKE_CASE=16	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=4096	,    __SCREAMING_SNAKE_CASE=12	,    __SCREAMING_SNAKE_CASE=16	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=0.1	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=0.0_2	,    __SCREAMING_SNAKE_CASE=2	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=5	,    __SCREAMING_SNAKE_CASE=1.0	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=1	,    __SCREAMING_SNAKE_CASE=0	,    __SCREAMING_SNAKE_CASE=2	,    __SCREAMING_SNAKE_CASE=2	,    **__SCREAMING_SNAKE_CASE	,    )		->Tuple:
  								lowerCAmelCase				=	langs
  								lowerCAmelCase				=	src_vocab_size
  								lowerCAmelCase				=	tgt_vocab_size
  								lowerCAmelCase				=	d_model  # encoder_embed_dim and decoder_embed_dim
  
  								lowerCAmelCase				=	encoder_ffn_dim
  								lowerCAmelCase				=	encoder_layers
  								lowerCAmelCase				=	encoder_attention_heads
  								lowerCAmelCase				=	encoder_layerdrop
  								lowerCAmelCase				=	decoder_layerdrop
  								lowerCAmelCase				=	decoder_ffn_dim
  								lowerCAmelCase				=	decoder_layers
  								lowerCAmelCase				=	decoder_attention_heads
  								lowerCAmelCase				=	max_position_embeddings
  								lowerCAmelCase				=	init_std  # Normal(0, this parameter)
  								lowerCAmelCase				=	activation_function
  
  								lowerCAmelCase				=	DecoderConfig(vocab_size=__SCREAMING_SNAKE_CASE	,    bos_token_id=__SCREAMING_SNAKE_CASE       )
  								if "decoder" in common_kwargs:
  															del common_kwargs["decoder"]
  
  								lowerCAmelCase				=	scale_embedding  # scale factor will be sqrt(d_model) if True
  
  								# 3 Types of Dropout
  								lowerCAmelCase				=	attention_dropout
  								lowerCAmelCase				=	activation_dropout
  								lowerCAmelCase				=	dropout
  
  								lowerCAmelCase				=	use_cache
  								super().__init__(
  								    pad_token_id=__SCREAMING_SNAKE_CASE	,    bos_token_id=__SCREAMING_SNAKE_CASE	,    eos_token_id=__SCREAMING_SNAKE_CASE	,    decoder_start_token_id=__SCREAMING_SNAKE_CASE	,    is_encoder_decoder=__SCREAMING_SNAKE_CASE	,    tie_word_embeddings=__SCREAMING_SNAKE_CASE	,    forced_eos_token_id=__SCREAMING_SNAKE_CASE	,    max_length=__SCREAMING_SNAKE_CASE	,    num_beams=__SCREAMING_SNAKE_CASE	,    length_penalty=__SCREAMING_SNAKE_CASE	,    early_stopping=__SCREAMING_SNAKE_CASE	,    **__SCREAMING_SNAKE_CASE	,    )
  
  
  
  
  	def     SCREAMING_SNAKE_CASE_       (							self       )		->int:
  								lowerCAmelCase				=	copy.deepcopy(self.__dict__       )
  								lowerCAmelCase				=	self.decoder.to_dict()
  								lowerCAmelCase				=	self.__class__.model_type
  								return output
  
  
  
  
style_context: import math
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__							)  ->			float:
  							lowerCAmelCase				=	math.log(2     ,						1_0							) * number
  							lowerCAmelCase				=	round((log_number - int(snake_case__							))     ,						1_5							)
  
  							return difference
  
  def      SCREAMING_SNAKE_CASE_  (		snake_case__ = 6_7_8_9_1_0							)  ->			int:
  							lowerCAmelCase				=	9_0
  							lowerCAmelCase				=	0
  
  							lowerCAmelCase				=	math.log(1.23     ,						1_0							)
  							lowerCAmelCase				=	math.log(1.24     ,						1_0							)
  							lowerCAmelCase				=	0
  
  							while position < number:
  														lowerCAmelCase				=	log_difference(snake_case__							)
  
  														if difference >= upper_limit:
  																					power_iterator += 9_3
  
  														elif difference < lower_limit:
  																					power_iterator += 1_9_6
  
  														else:
  																					lowerCAmelCase				=	power_iterator
  																					power_iterator += 1_9_6
  																					position += 1
  
  							return previous_power
  
  
  if __name__ == "__main__":
  	import doctest
  
  	doctest.testmod()
  
  	print(f'{solution() = }')
  
  
  
  