


"""simple docstring"""


from typing import Callable, Optional, Union

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


__lowerCamelCase      :Optional[Any]	    =		logging.get_logger(__name__)

__lowerCamelCase      :Optional[Any]	    =		{
    'microsoft/xprophetnet-large-wiki100-cased': (
        'https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'
    ),
}


class 			A__	(						__lowercase):


     """simple docstring"""
     snake_case__	:					Optional[int]													='''xlm-prophetnet'''
     snake_case__	:					Any													=['''past_key_values''']
     snake_case__	:					Dict													={
         '''num_attention_heads''': '''num_encoder_attention_heads''',
     }

     def __init__(	self:						List[str]     ,		__a:						Optional[float] = 0.1     ,		__a:						Optional[Union[str, Callable]] = "gelu"     ,		__a:						Optional[int] = 30_522     ,		__a:						Optional[int] = 1_024     ,		__a:						Optional[int] = 4_096     ,		__a:						Optional[int] = 12     ,		__a:						Optional[int] = 16     ,		__a:						Optional[int] = 4_096     ,		__a:						Optional[int] = 12     ,		__a:						Optional[int] = 16     ,		__a:						Optional[float] = 0.1     ,		__a:						Optional[float] = 0.1     ,		__a:						Optional[int] = 512     ,		__a:						Optional[float] = 0.02     ,		__a:						Optional[bool] = True     ,		__a:						Optional[bool] = True     ,		__a:						Optional[int] = 0     ,		__a:						Optional[int] = 2     ,		__a:						Optional[int] = 32     ,		__a:						Optional[int] = 128     ,		__a:						Optional[bool] = False     ,		__a:						Optional[float] = 0.0     ,		__a:						Optional[bool] = True     ,		__a:						Optional[int] = 0     ,		__a:						Optional[int] = 1     ,		__a:						Optional[int] = 2     ,		**__a:						Dict     ,		)->    int:
           lowerCamelCase					:					Optional[int]        =	vocab_size
           lowerCamelCase					:					Dict        =	hidden_size
           lowerCamelCase					:					str        =	encoder_ffn_dim
           lowerCamelCase					:					int        =	num_encoder_layers
           lowerCamelCase					:					Any        =	num_encoder_attention_heads
           lowerCamelCase					:					Dict        =	decoder_ffn_dim
           lowerCamelCase					:					Dict        =	num_decoder_layers
           lowerCamelCase					:					Dict        =	num_decoder_attention_heads
           lowerCamelCase					:					Optional[Any]        =	max_position_embeddings
           lowerCamelCase					:					Union[str, Any]        =	init_std  # Normal(0, this parameter)
           lowerCamelCase					:					Optional[Any]        =	activation_function

           # parameters for xlmprophetnet
           lowerCamelCase					:					Dict        =	ngram
           lowerCamelCase					:					Tuple        =	num_buckets
           lowerCamelCase					:					Optional[int]        =	relative_max_distance
           lowerCamelCase					:					Tuple        =	disable_ngram_loss
           lowerCamelCase					:					List[str]        =	eps

           # 3 Types of Dropout
           lowerCamelCase					:					Optional[int]        =	attention_dropout
           lowerCamelCase					:					str        =	activation_dropout
           lowerCamelCase					:					Tuple        =	dropout

           lowerCamelCase					:					Optional[int]        =	use_cache

           super().__init__(
               pad_token_id=__a     ,		bos_token_id=__a     ,		eos_token_id=__a     ,		is_encoder_decoder=__a     ,		add_cross_attention=__a     ,		decoder_start_token_id=__a     ,		**__a     ,		)

     @property
     def 		a__						(	self:						Optional[Any]	)->    int:
           return self.num_encoder_layers + self.num_decoder_layers







     @num_hidden_layers.setter
     def 		a__						(	self:						List[str]     ,		__a:						Any	)->    Union[str, Any]:
           raise NotImplementedError(
               """This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"""
               """ `num_decoder_layers`."""	)










"""simple docstring"""


from __future__ import annotations

import math




def   snake_case		(     UpperCamelCase__       :						float			,				UpperCamelCase__       :						int    )   ->      float:
      lowerCamelCase					:					Dict        =	u
      for i in range(1			,				UpperCamelCase__    ):
            lowerCamelCase					:					List[str]        =	temp * (u - i)
      return temp




def   snake_case		(     )   ->      None:
      lowerCamelCase					:					List[Any]        =	int(input("""enter the numbers of values: """    )    )
      lowerCamelCase					:					list[list[float]]        =	[]
      for _ in range(UpperCamelCase__    ):
            y.append([]    )
      for i in range(UpperCamelCase__    ):
            for j in range(UpperCamelCase__    ):
                  y[i].append(UpperCamelCase__    )
                  lowerCamelCase					:					Union[str, Any]        =	0

      print("""enter the values of parameters in a list: """    )
      lowerCamelCase					:					Any        =	list(map(UpperCamelCase__			,				input().split()    )    )

      print("""enter the values of corresponding parameters: """    )
      for i in range(UpperCamelCase__    ):
            lowerCamelCase					:					int        =	float(input()    )

      lowerCamelCase					:					Dict        =	int(input("""enter the value to interpolate: """    )    )
      lowerCamelCase					:					List[Any]        =	(value - x[0]) / (x[1] - x[0])

      # for calculating forward difference table

      for i in range(1			,				UpperCamelCase__    ):
            for j in range(n - i    ):
                  lowerCamelCase					:					str        =	y[j + 1][i - 1] - y[j][i - 1]

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

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


if __name__ == "__main__":
    main()




