





from __future__ import annotations

import math
def      _A       (		SCREAMING_SNAKE_CASE     :   float       ,       SCREAMING_SNAKE_CASE     :   int						):





  """simple docstring"""



  a__	:					List[Any]										=u
  for i in range(1       ,       SCREAMING_SNAKE_CASE__						):
    a__	:					str										=temp * (u - i)
  return temp
def      _A       (		):





  """simple docstring"""



  a__	:					Union[str, Any]										=int(input("enter the numbers of values: "						)						)
  a__	:					List[Any]										=[]
  for _ in range(SCREAMING_SNAKE_CASE__						):
    y.append([]						)
  for i in range(SCREAMING_SNAKE_CASE__						):
    for j in range(SCREAMING_SNAKE_CASE__						):
      y[i].append(SCREAMING_SNAKE_CASE__						)
      a__	:					Optional[int]										=0

  print("enter the values of parameters in a list: "						)
  a__	:					List[Any]										=list(map(SCREAMING_SNAKE_CASE__       ,       input().split()						)						)

  print("enter the values of corresponding parameters: "						)
  for i in range(SCREAMING_SNAKE_CASE__						):
    a__	:					Optional[int]										=float(input()						)

  a__	:					Optional[int]										=int(input("enter the value to interpolate: "						)						)
  a__	:					int										=(value - x[0]) / (x[1] - x[0])

  # for calculating forward difference table

  for i in range(1       ,       SCREAMING_SNAKE_CASE__						):
    for j in range(n - i						):
      a__	:					List[Any]										=y[j + 1][i - 1] - y[j][i - 1]

  a__	:					Optional[Any]										=y[0][0]
  for i in range(1       ,       SCREAMING_SNAKE_CASE__						):
    summ += (ucal(SCREAMING_SNAKE_CASE__       ,       SCREAMING_SNAKE_CASE__						) * y[0][i]) / math.factorial(SCREAMING_SNAKE_CASE__						)

  print(f'''the value at {value} is {summ}'''						)


if __name__ == "__main__":
     main()










import warnings

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


_A		       =						logging.get_logger(__name__)

_A		       =						{
    'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}






class     UpperCAmelCase__       (					A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Optional[int]      =  "mvp"
    UpperCAmelCase__						:		Tuple      =  ["past_key_values"]
    UpperCAmelCase__						:		Union[str, Any]      =  {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}






    def __init__(			self					,   A_=50267					,   A_=1024					,   A_=12					,   A_=4096					,   A_=16					,   A_=12					,   A_=4096					,   A_=16					,   A_=0.0					,   A_=0.0					,   A_="gelu"					,   A_=1024					,   A_=0.1					,   A_=0.0					,   A_=0.0					,   A_=0.02					,   A_=0.0					,   A_=False					,   A_=True					,   A_=1					,   A_=0					,   A_=2					,   A_=True					,   A_=2					,   A_=2					,   A_=False					,   A_=100					,   A_=800					,   **A_					,   )  ->       Union[str, Any]:
         __UpperCamelCase    							=vocab_size
         __UpperCamelCase    							=max_position_embeddings
         __UpperCamelCase    							=d_model
         __UpperCamelCase    							=encoder_ffn_dim
         __UpperCamelCase    							=encoder_layers
         __UpperCamelCase    							=encoder_attention_heads
         __UpperCamelCase    							=decoder_ffn_dim
         __UpperCamelCase    							=decoder_layers
         __UpperCamelCase    							=decoder_attention_heads
         __UpperCamelCase    							=dropout
         __UpperCamelCase    							=attention_dropout
         __UpperCamelCase    							=activation_dropout
         __UpperCamelCase    							=activation_function
         __UpperCamelCase    							=init_std
         __UpperCamelCase    							=encoder_layerdrop
         __UpperCamelCase    							=decoder_layerdrop
         __UpperCamelCase    							=classifier_dropout
         __UpperCamelCase    							=use_cache
         __UpperCamelCase    							=encoder_layers
         __UpperCamelCase    							=scale_embedding  # scale factor will be sqrt(d_model) if True
         __UpperCamelCase    							=use_prompt
         __UpperCamelCase    							=prompt_length
         __UpperCamelCase    							=prompt_mid_dim

         super().__init__(
             pad_token_id=A_					,   bos_token_id=A_					,   eos_token_id=A_					,   is_encoder_decoder=A_					,   decoder_start_token_id=A_					,   forced_eos_token_id=A_					,   **A_					,   )

         if self.forced_bos_token_id is None and kwargs.get('force_bos_token_to_be_generated'					,   A_    ):
              __UpperCamelCase    							=self.bos_token_id
              warnings.warn(
                  f'Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '
                  'The config can simply be saved and uploaded again to be fixed.'    )





