





import copy

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


__lowerCAmelCase     =			logging.get_logger(__name__)

__lowerCAmelCase     =			{}




class   _UpperCAmelCase	(   _lowercase					):
					__A          =   "fsmt_decoder"




					def __init__(						self    ,      __lowerCAmelCase=0    ,      __lowerCAmelCase=0       )						->  Optional[int]:
							super().__init__()
							UpperCamelCase__         =	vocab_size
							UpperCamelCase__         =	bos_token_id




class   _UpperCAmelCase	(   _lowercase					):
					__A          =   "fsmt"
					__A          =   {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}




					def __init__(						self    ,      __lowerCAmelCase=["en", "de"]    ,      __lowerCAmelCase=42_024    ,      __lowerCAmelCase=42_024    ,      __lowerCAmelCase="relu"    ,      __lowerCAmelCase=1_024    ,      __lowerCAmelCase=200    ,      __lowerCAmelCase=1_024    ,      __lowerCAmelCase=4_096    ,      __lowerCAmelCase=12    ,      __lowerCAmelCase=16    ,      __lowerCAmelCase=0.0    ,      __lowerCAmelCase=4_096    ,      __lowerCAmelCase=12    ,      __lowerCAmelCase=16    ,      __lowerCAmelCase=0.0    ,      __lowerCAmelCase=0.0    ,      __lowerCAmelCase=0.1    ,      __lowerCAmelCase=0.0    ,      __lowerCAmelCase=0.0_2    ,      __lowerCAmelCase=2    ,      __lowerCAmelCase=True    ,      __lowerCAmelCase=True    ,      __lowerCAmelCase=False    ,      __lowerCAmelCase=5    ,      __lowerCAmelCase=1.0    ,      __lowerCAmelCase=False    ,      __lowerCAmelCase=True    ,      __lowerCAmelCase=1    ,      __lowerCAmelCase=0    ,      __lowerCAmelCase=2    ,      __lowerCAmelCase=2    ,      **__lowerCAmelCase    ,      )						->  Optional[Any]:
							UpperCamelCase__         =	langs
							UpperCamelCase__         =	src_vocab_size
							UpperCamelCase__         =	tgt_vocab_size
							UpperCamelCase__         =	d_model  # encoder_embed_dim and decoder_embed_dim

							UpperCamelCase__         =	encoder_ffn_dim
							UpperCamelCase__         =	UpperCamelCase__         =	encoder_layers
							UpperCamelCase__         =	encoder_attention_heads
							UpperCamelCase__         =	encoder_layerdrop
							UpperCamelCase__         =	decoder_layerdrop
							UpperCamelCase__         =	decoder_ffn_dim
							UpperCamelCase__         =	decoder_layers
							UpperCamelCase__         =	decoder_attention_heads
							UpperCamelCase__         =	max_position_embeddings
							UpperCamelCase__         =	init_std  # Normal(0, this parameter)
							UpperCamelCase__         =	activation_function

							UpperCamelCase__         =	DecoderConfig(vocab_size=__lowerCAmelCase    ,      bos_token_id=__lowerCAmelCase       )
							if "decoder" in common_kwargs:
									del common_kwargs["decoder"]

							UpperCamelCase__         =	scale_embedding  # scale factor will be sqrt(d_model) if True

							# 3 Types of Dropout
							UpperCamelCase__         =	attention_dropout
							UpperCamelCase__         =	activation_dropout
							UpperCamelCase__         =	dropout

							UpperCamelCase__         =	use_cache
							super().__init__(
							    pad_token_id=__lowerCAmelCase    ,      bos_token_id=__lowerCAmelCase    ,      eos_token_id=__lowerCAmelCase    ,      decoder_start_token_id=__lowerCAmelCase    ,      is_encoder_decoder=__lowerCAmelCase    ,      tie_word_embeddings=__lowerCAmelCase    ,      forced_eos_token_id=__lowerCAmelCase    ,      max_length=__lowerCAmelCase    ,      num_beams=__lowerCAmelCase    ,      length_penalty=__lowerCAmelCase    ,      early_stopping=__lowerCAmelCase    ,      **__lowerCAmelCase    ,      )




					def 	snake_case_		(						self       )						->  str:
							UpperCamelCase__         =	copy.deepcopy(self.__dict__       )
							UpperCamelCase__         =	self.decoder.to_dict()
							UpperCamelCase__         =	self.__class__.model_type
							return output












def     a						(      _lowercase   :     int ,						_lowercase   :     int       )     ->int:
		UpperCamelCase__         =	1.0
		for i in range(1 ,						r + 1       ):
				ret *= (n + 1 - i) / i
		return round(_lowercase       )

def     a						(      _lowercase   :     int       )     ->int:
		return choose(8 + n ,						_lowercase       ) + choose(9 + n ,						_lowercase       ) - 1_0

def     a						(      _lowercase   :     int       )     ->int:
		return sum(non_bouncy_exact(_lowercase       ) for i in range(1 ,						n + 1       )       )

def     a						(      _lowercase   :     int = 1_0_0       )     ->int:
		return non_bouncy_upto(_lowercase       )


if __name__ == "__main__":
				print(f"""{solution() = }""")





