
"""simple docstring"""





from __future__ import annotations

import math







def 	__a     (		__lowerCamelCase,		__lowerCamelCase  ):
   UpperCAmelCase_					:					Any			     =    u
   for i in range(1,		__lowerCamelCase  ):
      UpperCAmelCase_					:					int			     =    temp * (u - i)
   return temp







def 	__a     (		):
   UpperCAmelCase_					:					str			     =    int(input("enter the numbers of values: "  )  )
   UpperCAmelCase_					:					list[list[float]]			     =    []
   for _ in range(__lowerCamelCase  ):
      y.append([]  )
   for i in range(__lowerCamelCase  ):
      for j in range(__lowerCamelCase  ):
         y[i].append(__lowerCamelCase  )
         UpperCAmelCase_					:					Tuple			     =    0

   print("enter the values of parameters in a list: "  )
   UpperCAmelCase_					:					Union[str, Any]			     =    list(map(__lowerCamelCase,		input().split()  )  )

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

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

   # for calculating forward difference table

   for i in range(1,		__lowerCamelCase  ):
      for j in range(n - i  ):
         UpperCAmelCase_					:					Union[str, Any]			     =    y[j + 1][i - 1] - y[j][i - 1]

   UpperCAmelCase_					:					Optional[int]			     =    y[0][0]
   for i in range(1,		__lowerCamelCase  ):
      summ += (ucal(__lowerCamelCase,		__lowerCamelCase  ) * y[0][i]) / math.factorial(__lowerCamelCase  )

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


if __name__ == "__main__":
    main()




"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


_a		       =							{
    'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
    'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/config.json',
    'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/config.json',
    'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json',
    'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/config.json',
    'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/config.json',
    'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/config.json',
    'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json',
}


class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						Optional[Any]       =		"""albert"""







  def __init__(		self				,   lowercase_=3_0000				,   lowercase_=128				,   lowercase_=4096				,   lowercase_=12				,   lowercase_=1				,   lowercase_=64				,   lowercase_=1_6384				,   lowercase_=1				,   lowercase_="gelu_new"				,   lowercase_=0				,   lowercase_=0				,   lowercase_=512				,   lowercase_=2				,   lowercase_=0.02				,   lowercase_=1E-1_2				,   lowercase_=0.1				,   lowercase_="absolute"				,   lowercase_=0				,   lowercase_=2				,   lowercase_=3				,   **lowercase_				,   ):

     """simple docstring"""
     super().__init__(pad_token_id=lowercase_				,   bos_token_id=lowercase_				,   eos_token_id=lowercase_				,   **lowercase_  )

     UpperCAmelCase_					:					int			     =    vocab_size
     UpperCAmelCase_					:					Optional[int]			     =    embedding_size
     UpperCAmelCase_					:					List[str]			     =    hidden_size
     UpperCAmelCase_					:					Optional[int]			     =    num_hidden_layers
     UpperCAmelCase_					:					Union[str, Any]			     =    num_hidden_groups
     UpperCAmelCase_					:					Dict			     =    num_attention_heads
     UpperCAmelCase_					:					Any			     =    inner_group_num
     UpperCAmelCase_					:					Union[str, Any]			     =    hidden_act
     UpperCAmelCase_					:					Union[str, Any]			     =    intermediate_size
     UpperCAmelCase_					:					List[str]			     =    hidden_dropout_prob
     UpperCAmelCase_					:					Union[str, Any]			     =    attention_probs_dropout_prob
     UpperCAmelCase_					:					Optional[Any]			     =    max_position_embeddings
     UpperCAmelCase_					:					Any			     =    type_vocab_size
     UpperCAmelCase_					:					List[str]			     =    initializer_range
     UpperCAmelCase_					:					Optional[int]			     =    layer_norm_eps
     UpperCAmelCase_					:					List[Any]			     =    classifier_dropout_prob
     UpperCAmelCase_					:					Tuple			     =    position_embedding_type




class A_	(lowercase__      ):




  '''simple docstring'''







  @property
  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     if self.task == "multiple-choice":
        UpperCAmelCase_					:					int			     =    {0: "batch", 1: "choice", 2: "sequence"}
     else:
        UpperCAmelCase_					:					Optional[Any]			     =    {0: "batch", 1: "sequence"}
     return OrderedDict(
         [
             ("input_ids", dynamic_axis),
             ("attention_mask", dynamic_axis),
             ("token_type_ids", dynamic_axis),
         ]  )


