






'''simple docstring'''



import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union

import numpy as np

from ...utils import is_tf_available, is_torch_available, logging


if TYPE_CHECKING:
     if is_torch_available():
          import torch
     if is_tf_available():
          import tensorflow as tf

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_codegen import CodeGenTokenizer


SCREAMING_SNAKE_CASE						=	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE						=	{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

SCREAMING_SNAKE_CASE						=	{
    'vocab_file': {
        'Salesforce/codegen-350M-mono': 'https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/vocab.json',
    },
    'merges_file': {
        'Salesforce/codegen-350M-mono': 'https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'Salesforce/codegen-350M-mono': (
            'https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/tokenizer.json'
        ),
    },
}

SCREAMING_SNAKE_CASE						=	{
    'Salesforce/codegen-350M-mono': 2_048,
}
class UpperCAmelCase_					(    __A				):




      """simple docstring"""




      UpperCamelCase_								=			VOCAB_FILES_NAMES
      UpperCamelCase_								=			PRETRAINED_VOCAB_FILES_MAP
      UpperCamelCase_								=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCamelCase_								=			['''input_ids''', '''attention_mask''']
      UpperCamelCase_								=			CodeGenTokenizer






      def __init__( self			:		Any     ,      UpperCAmelCase			:		Union[str, Any]=None     ,      UpperCAmelCase			:		Any=None     ,      UpperCAmelCase			:		Union[str, Any]=None     ,      UpperCAmelCase			:		str="<|endoftext|>"     ,      UpperCAmelCase			:		Dict="<|endoftext|>"     ,      UpperCAmelCase			:		Any="<|endoftext|>"     ,      UpperCAmelCase			:		Optional[int]=False     ,      **UpperCAmelCase			:		Union[str, Any]     ,      )  ->  List[Any]:


       '''simple docstring'''

       super().__init__(
           UpperCAmelCase     ,      UpperCAmelCase     ,      tokenizer_file=UpperCAmelCase     ,      unk_token=UpperCAmelCase     ,      bos_token=UpperCAmelCase     ,      eos_token=UpperCAmelCase     ,      add_prefix_space=UpperCAmelCase     ,      **UpperCAmelCase     ,      )

       if kwargs.pop('''add_bos_token'''     ,      UpperCAmelCase		):
        lowercase					:   List[str]				  =kwargs.pop('''name_or_path'''     ,      ''''''		)
        raise ValueError(
            '''Currenty GPT2\'s fast tokenizer does NOT support adding a BOS token.'''
            '''Instead you should use GPT2\'s slow tokenizer class `CodeGenTokenizer` as follows: \n'''
            f'`CodeGenTokenizer.from_pretrained(\'{model_id}\')`\nor\n'
            f'`AutoTokenizer.from_pretrained(\'{model_id}\', use_fast=False)`\n'
            '''This issue will be fixed soon, see: https://github.com/huggingface/tokenizers/pull/1005.'''
            ''' so that the fast tokenizer works correctly.'''		)

       lowercase					:   List[str]				  =json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()		)
       if pre_tok_state.get('''add_prefix_space'''     ,      UpperCAmelCase		) != add_prefix_space:
        lowercase					:   List[Any]				  =getattr(UpperCAmelCase     ,      pre_tok_state.pop('''type'''		)		)
        lowercase					:   Tuple				  =add_prefix_space
        lowercase					:   Union[str, Any]				  =pre_tok_class(**UpperCAmelCase		)

       lowercase					:   str				  =add_prefix_space






      def 				A__      ( self			:		Tuple     ,      *UpperCAmelCase			:		Optional[int]     ,      **UpperCAmelCase			:		str		)  ->  BatchEncoding:


       '''simple docstring'''

       lowercase					:   List[str]				  =kwargs.get('''is_split_into_words'''     ,      UpperCAmelCase		)
       assert self.add_prefix_space or not is_split_into_words, (
           f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
           "to use it with pretokenized inputs."
       )

       return super()._batch_encode_plus(*UpperCAmelCase     ,      **UpperCAmelCase		)






      def 				A__      ( self			:		Optional[int]     ,      *UpperCAmelCase			:		Any     ,      **UpperCAmelCase			:		str		)  ->  BatchEncoding:


       '''simple docstring'''

       lowercase					:   str				  =kwargs.get('''is_split_into_words'''     ,      UpperCAmelCase		)

       assert self.add_prefix_space or not is_split_into_words, (
           f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
           "to use it with pretokenized inputs."
       )

       return super()._encode_plus(*UpperCAmelCase     ,      **UpperCAmelCase		)






      def 				A__      ( self			:		int     ,      UpperCAmelCase			:		str     ,      UpperCAmelCase			:		Optional[str] = None		)  ->  Tuple[str]:


       '''simple docstring'''

       lowercase					:   Union[str, Any]				  =self._tokenizer.model.save(UpperCAmelCase     ,      name=UpperCAmelCase		)
       return tuple(UpperCAmelCase		)






      def 				A__      ( self			:		Optional[int]     ,      UpperCAmelCase			:		Union[int, List[int], "np.ndarray", "torch.Tensor", "tf.Tensor"]     ,      UpperCAmelCase			:		bool = False     ,      UpperCAmelCase			:		bool = None     ,      UpperCAmelCase			:		Optional[List[str]] = None     ,      **UpperCAmelCase			:		Dict     ,      )  ->  str:


       '''simple docstring'''

       lowercase					:   str				  =super().decode(
           token_ids=UpperCAmelCase     ,      skip_special_tokens=UpperCAmelCase     ,      clean_up_tokenization_spaces=UpperCAmelCase     ,      **UpperCAmelCase     ,      )

       if truncate_before_pattern is not None and len(UpperCAmelCase		) > 0:
        lowercase					:   List[str]				  =self.truncate(UpperCAmelCase     ,      UpperCAmelCase		)

       return decoded_text






      def 				A__      ( self			:		int     ,      UpperCAmelCase			:		Tuple     ,      UpperCAmelCase			:		List[Any]		)  ->  Optional[int]:


       '''simple docstring'''

       def find_re(UpperCAmelCase			:		Dict     ,      UpperCAmelCase			:		Optional[int]     ,      UpperCAmelCase			:		int		):
        lowercase					:   Union[str, Any]				  =pattern.search(UpperCAmelCase     ,      UpperCAmelCase		)
        return m.start() if m else -1

       lowercase					:   str				  =[re.compile(UpperCAmelCase     ,      re.MULTILINE		) for pattern in truncate_before_pattern]

       lowercase					:   Any				  =list(re.finditer('''^print'''     ,      UpperCAmelCase     ,      re.MULTILINE		)		)

       if len(UpperCAmelCase		) > 1:
        lowercase					:   List[str]				  =completion[: prints[1].start()]

       lowercase					:   Optional[int]				  =list(re.finditer('''^def'''     ,      UpperCAmelCase     ,      re.MULTILINE		)		)

       if len(UpperCAmelCase		) > 1:
        lowercase					:   Optional[Any]				  =completion[: defs[1].start()]

       lowercase					:   Any				  =0

       lowercase					:   int				  =[
           pos for pos in [find_re(UpperCAmelCase     ,      UpperCAmelCase     ,      UpperCAmelCase		) for terminal in terminals] if pos != -1
       ]

       if len(UpperCAmelCase		) > 0:
        return completion[: min(UpperCAmelCase		)]
       else:
        return completion











'''simple docstring'''



from __future__ import annotations

import math


def 							lowercase_				(    __A :       float					,      __A :       int			)       ->      float:



 """simple docstring"""




 lowercase					:   str				  =u
 for i in range(1					,      __A			):
  lowercase					:   Any				  =temp * (u - i)
 return temp


def 							lowercase_				(    )       ->      None:



 """simple docstring"""




 lowercase					:   List[str]				  =int(input('''enter the numbers of values: '''			)			)
 lowercase					:   list[list[float]]				  =[]
 for _ in range(__A			):
  y.append([]			)
 for i in range(__A			):
  for j in range(__A			):
   y[i].append(__A			)
   lowercase					:   List[Any]				  =0

 print('''enter the values of parameters in a list: '''			)
 lowercase					:   Optional[int]				  =list(map(__A					,      input().split()			)			)

 print('''enter the values of corresponding parameters: '''			)
 for i in range(__A			):
  lowercase					:   str				  =float(input()			)

 lowercase					:   int				  =int(input('''enter the value to interpolate: '''			)			)
 lowercase					:   Union[str, Any]				  =(value - x[0]) / (x[1] - x[0])

 # for calculating forward difference table

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

 lowercase					:   Any				  =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()



