





import copy

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


_UpperCAmelCase										=					logging.get_logger(__name__)

_UpperCAmelCase										=					{}



class 				_UpperCamelCase       (						lowercase_  ):
       _UpperCamelCase					:       Union[str, Any]       = '''fsmt_decoder'''

       def __init__(		self:			Optional[int]       , _SCREAMING_SNAKE_CASE:			Tuple=0       , _SCREAMING_SNAKE_CASE:			List[str]=0		)							->			str:




              """simple docstring"""


              super().__init__()
              UpperCamelCase_ 							=	vocab_size
              UpperCamelCase_ 							=	bos_token_id



class 				_UpperCamelCase       (						lowercase_  ):
       _UpperCamelCase					:       List[str]       = '''fsmt'''
       _UpperCamelCase					:       Tuple       = {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}

       def __init__(		self:			Dict       , _SCREAMING_SNAKE_CASE:			List[str]=["en", "de"]       , _SCREAMING_SNAKE_CASE:			List[str]=42024       , _SCREAMING_SNAKE_CASE:			Dict=42024       , _SCREAMING_SNAKE_CASE:			Tuple="relu"       , _SCREAMING_SNAKE_CASE:			Optional[Any]=1024       , _SCREAMING_SNAKE_CASE:			Dict=200       , _SCREAMING_SNAKE_CASE:			Optional[Any]=1024       , _SCREAMING_SNAKE_CASE:			Optional[Any]=4096       , _SCREAMING_SNAKE_CASE:			Union[str, Any]=12       , _SCREAMING_SNAKE_CASE:			Dict=16       , _SCREAMING_SNAKE_CASE:			Optional[Any]=0.0       , _SCREAMING_SNAKE_CASE:			Dict=4096       , _SCREAMING_SNAKE_CASE:			Dict=12       , _SCREAMING_SNAKE_CASE:			str=16       , _SCREAMING_SNAKE_CASE:			Any=0.0       , _SCREAMING_SNAKE_CASE:			str=0.0       , _SCREAMING_SNAKE_CASE:			List[Any]=0.1       , _SCREAMING_SNAKE_CASE:			List[Any]=0.0       , _SCREAMING_SNAKE_CASE:			str=0.02       , _SCREAMING_SNAKE_CASE:			List[str]=2       , _SCREAMING_SNAKE_CASE:			Union[str, Any]=True       , _SCREAMING_SNAKE_CASE:			Optional[Any]=True       , _SCREAMING_SNAKE_CASE:			int=False       , _SCREAMING_SNAKE_CASE:			List[str]=5       , _SCREAMING_SNAKE_CASE:			Optional[int]=1.0       , _SCREAMING_SNAKE_CASE:			List[str]=False       , _SCREAMING_SNAKE_CASE:			Any=True       , _SCREAMING_SNAKE_CASE:			List[str]=1       , _SCREAMING_SNAKE_CASE:			int=0       , _SCREAMING_SNAKE_CASE:			str=2       , _SCREAMING_SNAKE_CASE:			Dict=2       , **_SCREAMING_SNAKE_CASE:			Optional[int]       , )							->			int:




              """simple docstring"""


              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=__UpperCamelCase       , bos_token_id=__UpperCamelCase		)
              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=__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 lowercase			(		self:			List[str]		)							->			Optional[int]:




              """simple docstring"""


              UpperCamelCase_ 							=	copy.deepcopy(self.__dict__		)
              UpperCamelCase_ 							=	self.decoder.to_dict()
              UpperCamelCase_ 							=	self.__class__.model_type
              return output








"""simple docstring"""
from __future__ import annotations






def    A__							(     UpperCamelCase			):
							A						=    42
							A						=    list(UpperCamelCase			)
							A,      A						=    _vector[:-1], int(_vector[-1]			)
							A						=    [int(UpperCamelCase			) for digit in __vector]

							vector.reverse()
							for i, digit in enumerate(UpperCamelCase			):
														if i & 1 == 0:
																					A						=    digit * 2
																					if doubled > 9:
																												doubled -= 9
																					check_digit += doubled
														else:
																					check_digit += digit

							return check_digit % 10 == 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		assert is_luhn('79927398713')
		assert not is_luhn('79927398714')


