
'''simple docstring'''







import copy

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


_lowercase				:						List[Any]												= logging.get_logger(__name__)

_lowercase				:						Any												= {}






class 				lowerCAmelCase__     (						lowerCamelCase_  ):
					lowerCAmelCase_       =  '''fsmt_decoder'''






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE=0       ,							__SCREAMING_SNAKE_CASE=0	):


											"""simple docstring"""





											super().__init__()
											lowercase_			:  Optional[int]									= vocab_size
											lowercase_			:  Dict									= bos_token_id







class 				lowerCAmelCase__     (						lowerCamelCase_  ):
					lowerCAmelCase_       =  '''fsmt'''
					lowerCAmelCase_       =  {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE=["en", "de"]       ,							__SCREAMING_SNAKE_CASE=4_20_24       ,							__SCREAMING_SNAKE_CASE=4_20_24       ,							__SCREAMING_SNAKE_CASE="relu"       ,							__SCREAMING_SNAKE_CASE=10_24       ,							__SCREAMING_SNAKE_CASE=2_00       ,							__SCREAMING_SNAKE_CASE=10_24       ,							__SCREAMING_SNAKE_CASE=40_96       ,							__SCREAMING_SNAKE_CASE=12       ,							__SCREAMING_SNAKE_CASE=16       ,							__SCREAMING_SNAKE_CASE=0.0       ,							__SCREAMING_SNAKE_CASE=40_96       ,							__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=0.02       ,							__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       ,							):


											"""simple docstring"""





											lowercase_			:  Union[str, Any]									= langs
											lowercase_			:  Union[str, Any]									= src_vocab_size
											lowercase_			:  int									= tgt_vocab_size
											lowercase_			:  Union[str, Any]									= d_model  # encoder_embed_dim and decoder_embed_dim

											lowercase_			:  Tuple									= encoder_ffn_dim
											lowercase_			:  Union[str, Any]									= encoder_layers
											lowercase_			:  Tuple									= encoder_attention_heads
											lowercase_			:  Tuple									= encoder_layerdrop
											lowercase_			:  int									= decoder_layerdrop
											lowercase_			:  Any									= decoder_ffn_dim
											lowercase_			:  Tuple									= decoder_layers
											lowercase_			:  Dict									= decoder_attention_heads
											lowercase_			:  Optional[Any]									= max_position_embeddings
											lowercase_			:  int									= init_std  # Normal(0, this parameter)
											lowercase_			:  Union[str, Any]									= activation_function

											lowercase_			:  Union[str, Any]									= DecoderConfig(vocab_size=__SCREAMING_SNAKE_CASE       ,							bos_token_id=__SCREAMING_SNAKE_CASE	)
											if "decoder" in common_kwargs:
																	del common_kwargs["decoder"]

											lowercase_			:  Optional[int]									= scale_embedding  # scale factor will be sqrt(d_model) if True

											# 3 Types of Dropout
											lowercase_			:  Tuple									= attention_dropout
											lowercase_			:  List[Any]									= activation_dropout
											lowercase_			:  Optional[Any]									= dropout

											lowercase_			:  Dict									= 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 			_snake_case					(     self	):


											"""simple docstring"""





											lowercase_			:  int									= copy.deepcopy(self.__dict__	)
											lowercase_			:  List[str]									= self.decoder.to_dict()
											lowercase_			:  List[str]									= self.__class__.model_type
											return output





'''simple docstring'''







def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int = 1000							):



						"""simple docstring"""





						lowercase_			:  List[Any]									= 0
						for i in range(__SCREAMING_SNAKE_CASE							):
												if i % 3 == 0 or i % 5 == 0:
																		result += i
						return result


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



