





"""simple docstring"""






from __future__ import annotations

import math

def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE,SCREAMING_SNAKE_CASE							)		->       float:






       """simple docstring"""




       _UpperCAmelCase     =     u
       for i in range(1,__UpperCAmelCase							):
              _UpperCAmelCase     =     temp * (u - i)
       return temp

def       __lowerCamelCase    (       )		->       None:






       """simple docstring"""




       _UpperCAmelCase     =     int(input('enter the numbers of values: '							)							)
       _UpperCAmelCase     =     []
       for _ in range(__UpperCAmelCase							):
              y.append([]							)
       for i in range(__UpperCAmelCase							):
              for j in range(__UpperCAmelCase							):
                     y[i].append(__UpperCAmelCase							)
                     _UpperCAmelCase     =     0

       print('enter the values of parameters in a list: '							)
       _UpperCAmelCase     =     list(map(__UpperCAmelCase,input().split()							)							)

       print('enter the values of corresponding parameters: '							)
       for i in range(__UpperCAmelCase							):
              _UpperCAmelCase     =     float(input()							)

       _UpperCAmelCase     =     int(input('enter the value to interpolate: '							)							)
       _UpperCAmelCase     =     (value - x[0]) / (x[1] - x[0])

       # for calculating forward difference table

       for i in range(1,__UpperCAmelCase							):
              for j in range(n - i							):
                     _UpperCAmelCase     =     y[j + 1][i - 1] - y[j][i - 1]

       _UpperCAmelCase     =     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()













"""simple docstring"""






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


lowerCAmelCase_			=							logging.get_logger(__name__)

lowerCAmelCase_			=							{
    '''microsoft/trocr-base-handwritten''': (
        '''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}



class 	lowerCAmelCase					(      snake_case							):
       lowerCAmelCase__						 =  """trocr"""
       lowerCAmelCase__						 =  ["""past_key_values"""]
       lowerCAmelCase__						 =  {
           """num_attention_heads""": """decoder_attention_heads""",
           """hidden_size""": """d_model""",
           """num_hidden_layers""": """decoder_layers""",
       }






       def __init__(   self    ,  a__=5_02_65    ,  a__=10_24    ,  a__=12    ,  a__=16    ,  a__=40_96    ,  a__="gelu"    ,  a__=5_12    ,  a__=0.1    ,  a__=0.0    ,  a__=0.0    ,  a__=2    ,  a__=0.02    ,  a__=0.0    ,  a__=True    ,  a__=False    ,  a__=True    ,  a__=True    ,  a__=1    ,  a__=0    ,  a__=2    ,  **a__    ,  ):
              _UpperCAmelCase     =     vocab_size
              _UpperCAmelCase     =     d_model
              _UpperCAmelCase     =     decoder_layers
              _UpperCAmelCase     =     decoder_attention_heads
              _UpperCAmelCase     =     decoder_ffn_dim
              _UpperCAmelCase     =     activation_function
              _UpperCAmelCase     =     max_position_embeddings
              _UpperCAmelCase     =     dropout
              _UpperCAmelCase     =     attention_dropout
              _UpperCAmelCase     =     activation_dropout
              _UpperCAmelCase     =     init_std
              _UpperCAmelCase     =     decoder_layerdrop
              _UpperCAmelCase     =     use_cache
              _UpperCAmelCase     =     scale_embedding
              _UpperCAmelCase     =     use_learned_position_embeddings
              _UpperCAmelCase     =     layernorm_embedding

              super().__init__(
                  pad_token_id=a__    ,  bos_token_id=a__    ,  eos_token_id=a__    ,  decoder_start_token_id=a__    ,  **a__    ,  )






