





import copy

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


UpperCAmelCase_												=   logging.get_logger(__name__)

UpperCAmelCase_												=   {}
class 	UpperCamelCase_						(     __lowerCAmelCase    ):
					lowerCAmelCase_							=		"""fsmt_decoder"""




					def __init__(						self ,  lowerCAmelCase_=0 ,  lowerCAmelCase_=0     )						->							List[str]:
										super().__init__()
										_snake_case													= vocab_size
										_snake_case													= bos_token_id





class 	UpperCamelCase_						(     __lowerCAmelCase    ):
					lowerCAmelCase_							=		"""fsmt"""
					lowerCAmelCase_							=		{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}




					def __init__(						self ,  lowerCAmelCase_=["en", "de"] ,  lowerCAmelCase_=4_2024 ,  lowerCAmelCase_=4_2024 ,  lowerCAmelCase_="relu" ,  lowerCAmelCase_=1024 ,  lowerCAmelCase_=200 ,  lowerCAmelCase_=1024 ,  lowerCAmelCase_=4096 ,  lowerCAmelCase_=12 ,  lowerCAmelCase_=16 ,  lowerCAmelCase_=0.0 ,  lowerCAmelCase_=4096 ,  lowerCAmelCase_=12 ,  lowerCAmelCase_=16 ,  lowerCAmelCase_=0.0 ,  lowerCAmelCase_=0.0 ,  lowerCAmelCase_=0.1 ,  lowerCAmelCase_=0.0 ,  lowerCAmelCase_=0.02 ,  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]:
										_snake_case													= langs
										_snake_case													= src_vocab_size
										_snake_case													= tgt_vocab_size
										_snake_case													= d_model  # encoder_embed_dim and decoder_embed_dim

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

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

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

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

										_snake_case													= 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 		lowerCAmelCase	(						self     )						->							int:
										_snake_case													= copy.deepcopy(self.__dict__     )
										_snake_case													= self.decoder.to_dict()
										_snake_case													= self.__class__.model_type
										return output










"""simple docstring"""


from __future__ import annotations





def 							a__	(     _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		,   )			->     list[float | int]:

 '''simple docstring'''






 if not all((nth_term, start_term_a, common_ratio_r)		):
  return []
 snake_case__										= []
 snake_case__										= 1
 snake_case__										= common_ratio_r
 for _ in range(int(_UpperCAmelCase		)		):
  if not series:
   series.append(_UpperCAmelCase		)
  else:
   power += 1
   series.append(float(start_term_a * multiple		)		)
   snake_case__										= pow(float(_UpperCAmelCase		)		,   _UpperCAmelCase		)
 return series


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   a__    :   int    						= float(input("""Enter the last number (n term) of the Geometric Series"""))
   a__    :   str    						= float(input("""Enter the starting term (a) of the Geometric Series"""))
   a__    :   str    						= float(
       input("""Enter the common ratio between two terms (r) of the Geometric Series""")
   )
   print("""Formula of Geometric Series => a + ar + ar^2 ... +ar^n""")
   print(geometric_series(nth_term, start_term_a, common_ratio_r))

