code: 
  
  import copy
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  A_:      Tuple        =			logging.get_logger(__name__)
  
  A_:      Dict        =			{}
  
  
  class _lowercase					(       _UpperCAmelCase						):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  							lowerCAmelCase__       =					'fsmt_decoder'
  
  
  
  							def __init__(    self     ,   UpperCAmelCase=0     ,   UpperCAmelCase=0  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														super().__init__()
  														_lowercase				=	vocab_size
  														_lowercase				=	bos_token_id
  
  
  
  
  
  
  class _lowercase					(       _UpperCAmelCase						):
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  							lowerCAmelCase__       =					'fsmt'
  							lowerCAmelCase__       =					{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}
  
  
  
  							def __init__(    self     ,   UpperCAmelCase=["en", "de"]     ,   UpperCAmelCase=42024     ,   UpperCAmelCase=42024     ,   UpperCAmelCase="relu"     ,   UpperCAmelCase=1024     ,   UpperCAmelCase=200     ,   UpperCAmelCase=1024     ,   UpperCAmelCase=4096     ,   UpperCAmelCase=12     ,   UpperCAmelCase=16     ,   UpperCAmelCase=0.0     ,   UpperCAmelCase=4096     ,   UpperCAmelCase=12     ,   UpperCAmelCase=16     ,   UpperCAmelCase=0.0     ,   UpperCAmelCase=0.0     ,   UpperCAmelCase=0.1     ,   UpperCAmelCase=0.0     ,   UpperCAmelCase=0.02     ,   UpperCAmelCase=2     ,   UpperCAmelCase=True     ,   UpperCAmelCase=True     ,   UpperCAmelCase=False     ,   UpperCAmelCase=5     ,   UpperCAmelCase=1.0     ,   UpperCAmelCase=False     ,   UpperCAmelCase=True     ,   UpperCAmelCase=1     ,   UpperCAmelCase=0     ,   UpperCAmelCase=2     ,   UpperCAmelCase=2     ,   **UpperCAmelCase     ,   ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	langs
  														_lowercase				=	src_vocab_size
  														_lowercase				=	tgt_vocab_size
  														_lowercase				=	d_model  # encoder_embed_dim and decoder_embed_dim
  
  														_lowercase				=	encoder_ffn_dim
  														_lowercase				=	_lowercase				=	encoder_layers
  														_lowercase				=	encoder_attention_heads
  														_lowercase				=	encoder_layerdrop
  														_lowercase				=	decoder_layerdrop
  														_lowercase				=	decoder_ffn_dim
  														_lowercase				=	decoder_layers
  														_lowercase				=	decoder_attention_heads
  														_lowercase				=	max_position_embeddings
  														_lowercase				=	init_std  # Normal(0, this parameter)
  														_lowercase				=	activation_function
  
  														_lowercase				=	DecoderConfig(vocab_size=UpperCAmelCase     ,   bos_token_id=UpperCAmelCase  )
  														if "decoder" in common_kwargs:
  																					del common_kwargs["decoder"]
  
  														_lowercase				=	scale_embedding  # scale factor will be sqrt(d_model) if True
  
  														# 3 Types of Dropout
  														_lowercase				=	attention_dropout
  														_lowercase				=	activation_dropout
  														_lowercase				=	dropout
  
  														_lowercase				=	use_cache
  														super().__init__(
  														    pad_token_id=UpperCAmelCase     ,   bos_token_id=UpperCAmelCase     ,   eos_token_id=UpperCAmelCase     ,   decoder_start_token_id=UpperCAmelCase     ,   is_encoder_decoder=UpperCAmelCase     ,   tie_word_embeddings=UpperCAmelCase     ,   forced_eos_token_id=UpperCAmelCase     ,   max_length=UpperCAmelCase     ,   num_beams=UpperCAmelCase     ,   length_penalty=UpperCAmelCase     ,   early_stopping=UpperCAmelCase     ,   **UpperCAmelCase     ,   )
  
  
  
  							def     _UpperCAmelCase       (    self  ):
  
  
  
  
  
  
  
  														'''simple docstring'''
  
  
  
  
  
  
  														_lowercase				=	copy.deepcopy(self.__dict__  )
  														_lowercase				=	self.decoder.to_dict()
  														_lowercase				=	self.__class__.model_type
  														return output
  
  
  
style_context: def 					__lowerCAmelCase			(  _A = 998_001					):
  
  
  
  							"""simple docstring"""
  
  
  							_lowercase				=	0
  							for i in range(999 ,99 ,-1					):  # 3 digit numbers range from 999 down to 100
  														for j in range(999 ,99 ,-1					):
  																					_lowercase				=	str(i * j					)
  																					if product_string == product_string[::-1] and i * j < n:
  																												_lowercase				=	max(_A ,i * j					)
  							return answer
  
  
  if __name__ == "__main__":
  				print(F'''{solution() = }''')
  
  
  