


from typing import Callable, Optional, Union

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


SCREAMING_SNAKE_CASE__     					=			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__     					=			{
    "microsoft/xprophetnet-large-wiki100-cased": (
        "https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json"
    ),
}



class 						_UpperCAmelCase      (     lowercase							):
		lowerCamelCase_	:			Union[str, Any]       			=  """xlm-prophetnet"""
		lowerCamelCase_	:			List[str]       			=  ["""past_key_values"""]
		lowerCamelCase_	:			Dict       			=  {
		    """num_attention_heads""": """num_encoder_attention_heads""",
		}






		def __init__(						self				:     List[str]   ,  UpperCAmelCase				:     Optional[float] = 0.1   ,  UpperCAmelCase				:     Optional[Union[str, Callable]] = "gelu"   ,  UpperCAmelCase				:     Optional[int] = 3_05_22   ,  UpperCAmelCase				:     Optional[int] = 10_24   ,  UpperCAmelCase				:     Optional[int] = 40_96   ,  UpperCAmelCase				:     Optional[int] = 12   ,  UpperCAmelCase				:     Optional[int] = 16   ,  UpperCAmelCase				:     Optional[int] = 40_96   ,  UpperCAmelCase				:     Optional[int] = 12   ,  UpperCAmelCase				:     Optional[int] = 16   ,  UpperCAmelCase				:     Optional[float] = 0.1   ,  UpperCAmelCase				:     Optional[float] = 0.1   ,  UpperCAmelCase				:     Optional[int] = 5_12   ,  UpperCAmelCase				:     Optional[float] = 0.02   ,  UpperCAmelCase				:     Optional[bool] = True   ,  UpperCAmelCase				:     Optional[bool] = True   ,  UpperCAmelCase				:     Optional[int] = 0   ,  UpperCAmelCase				:     Optional[int] = 2   ,  UpperCAmelCase				:     Optional[int] = 32   ,  UpperCAmelCase				:     Optional[int] = 1_28   ,  UpperCAmelCase				:     Optional[bool] = False   ,  UpperCAmelCase				:     Optional[float] = 0.0   ,  UpperCAmelCase				:     Optional[bool] = True   ,  UpperCAmelCase				:     Optional[int] = 0   ,  UpperCAmelCase				:     Optional[int] = 1   ,  UpperCAmelCase				:     Optional[int] = 2   ,  **UpperCAmelCase				:     Any   ,  ):
				SCREAMING_SNAKE_CASE_				:Dict				     =						vocab_size
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						hidden_size
				SCREAMING_SNAKE_CASE_				:int				     =						encoder_ffn_dim
				SCREAMING_SNAKE_CASE_				:str				     =						num_encoder_layers
				SCREAMING_SNAKE_CASE_				:Dict				     =						num_encoder_attention_heads
				SCREAMING_SNAKE_CASE_				:Dict				     =						decoder_ffn_dim
				SCREAMING_SNAKE_CASE_				:str				     =						num_decoder_layers
				SCREAMING_SNAKE_CASE_				:int				     =						num_decoder_attention_heads
				SCREAMING_SNAKE_CASE_				:Tuple				     =						max_position_embeddings
				SCREAMING_SNAKE_CASE_				:Any				     =						init_std  # Normal(0, this parameter)
				SCREAMING_SNAKE_CASE_				:int				     =						activation_function

				# parameters for xlmprophetnet
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						ngram
				SCREAMING_SNAKE_CASE_				:Tuple				     =						num_buckets
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						relative_max_distance
				SCREAMING_SNAKE_CASE_				:Any				     =						disable_ngram_loss
				SCREAMING_SNAKE_CASE_				:Optional[Any]				     =						eps

				# 3 Types of Dropout
				SCREAMING_SNAKE_CASE_				:Dict				     =						attention_dropout
				SCREAMING_SNAKE_CASE_				:Any				     =						activation_dropout
				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						dropout

				SCREAMING_SNAKE_CASE_				:Optional[int]				     =						use_cache

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






		@property
		def _snake_case		(						self				:     Any):
				return self.num_encoder_layers + self.num_decoder_layers







		@num_hidden_layers.setter
		def _snake_case		(						self				:     Dict   ,  UpperCAmelCase				:     Optional[Any]):
				raise NotImplementedError(
				    "This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"
				    " `num_decoder_layers`.")










from __future__ import annotations

import math


def     lowercase	(    a     , a ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:List[Any]				     =						u
		for i in range(1     , a ):
				SCREAMING_SNAKE_CASE_				:Union[str, Any]				     =						temp * (u - i)
		return temp


def     lowercase	(    ):



		'''simple docstring'''




		SCREAMING_SNAKE_CASE_				:int				     =						int(input("enter the numbers of values: " ) )
		SCREAMING_SNAKE_CASE_				:list[list[float]]				     =						[]
		for _ in range(a ):
				y.append([] )
		for i in range(a ):
				for j in range(a ):
						y[i].append(a )
						SCREAMING_SNAKE_CASE_				:Any				     =						0

		print("enter the values of parameters in a list: " )
		SCREAMING_SNAKE_CASE_				:Dict				     =						list(map(a     , input().split() ) )

		print("enter the values of corresponding parameters: " )
		for i in range(a ):
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						float(input() )

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

		# for calculating forward difference table

		for i in range(1     , a ):
				for j in range(n - i ):
						SCREAMING_SNAKE_CASE_				:List[str]				     =						y[j + 1][i - 1] - y[j][i - 1]

		SCREAMING_SNAKE_CASE_				:Tuple				     =						y[0][0]
		for i in range(1     , a ):
				summ += (ucal(a     , a ) * y[0][i]) / math.factorial(a )

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


if __name__ == "__main__":
		main()






