


import json
import os
import re
import unicodedata
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer, _is_control, _is_punctuation, _is_whitespace
from ...utils import logging


_lowerCAmelCase:	str      							=					logging.get_logger(__name__)

_lowerCAmelCase:	Union[str, Any]      							=					{
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
}

_lowerCAmelCase:	List[Any]      							=					{
    'vocab_file': {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/vocab.json'},
    'merges_file': {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/merges.txt'},
}

_lowerCAmelCase:	Union[str, Any]      							=					{
    'openai-gpt': 512,
}






def      _lowercase(				__a							:	int    ):
       a__     						=text.strip()
       if not text:
              return []
       a__     						=text.split()
       return tokens




class 			lowercase_				(lowercase__      ):





    def __init__(							self					,     lowercase_=True					,     lowercase_=None					,     lowercase_=True					,     lowercase_=None					,     lowercase_=True					,     )     ->   int:
           if never_split is None:
                  a__     						=[]
           a__     						=do_lower_case
           a__     						=set(lowercase_)
           a__     						=tokenize_chinese_chars
           a__     						=strip_accents
           a__     						=do_split_on_punc





    def 	__UpperCamelCase						(							self					,     lowercase_					,     lowercase_=None)     ->   List[Any]:
           a__     						=self.never_split.union(set(lowercase_)) if never_split else self.never_split
           a__     						=self._clean_text(lowercase_)

           # This was added on November 1st, 2018 for the multilingual and Chinese
           # models. This is also applied to the English models now, but it doesn't
           # matter since the English models were not trained on any Chinese data
           # and generally don't have any Chinese data in them (there are Chinese
           # characters in the vocabulary because Wikipedia does have some Chinese
           # words in the English Wikipedia.).
           if self.tokenize_chinese_chars:
                  a__     						=self._tokenize_chinese_chars(lowercase_)
           # prevents treating the same character with different unicode codepoints as different characters
           a__     						=unicodedata.normalize('NFC'					,     lowercase_)
           a__     						=whitespace_tokenize(lowercase_)
           a__     						=[]
           for token in orig_tokens:
                  if token not in never_split:
                         if self.do_lower_case:
                                a__     						=token.lower()
                                if self.strip_accents is not False:
                                       a__     						=self._run_strip_accents(lowercase_)
                         elif self.strip_accents:
                                a__     						=self._run_strip_accents(lowercase_)
                  split_tokens.extend(self._run_split_on_punc(lowercase_					,     lowercase_))

           a__     						=whitespace_tokenize(' '.join(lowercase_))
           return output_tokens





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   int:
           a__     						=unicodedata.normalize('NFD'					,     lowercase_)
           a__     						=[]
           for char in text:
                  a__     						=unicodedata.category(lowercase_)
                  if cat == "Mn":
                         continue
                  output.append(lowercase_)
           return "".join(lowercase_)





    def 	__UpperCamelCase						(							self					,     lowercase_					,     lowercase_=None)     ->   Optional[int]:
           if not self.do_split_on_punc or (never_split is not None and text in never_split):
                  return [text]
           a__     						=list(lowercase_)
           a__     						=0
           a__     						=True
           a__     						=[]
           while i < len(lowercase_):
                  a__     						=chars[i]
                  if _is_punctuation(lowercase_):
                         output.append([char])
                         a__     						=True
                  else:
                         if start_new_word:
                                output.append([])
                         a__     						=False
                         output[-1].append(lowercase_)
                  i += 1

           return ["".join(lowercase_) for x in output]





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   Any:
           a__     						=[]
           for char in text:
                  a__     						=ord(lowercase_)
                  if self._is_chinese_char(lowercase_):
                         output.append(' ')
                         output.append(lowercase_)
                         output.append(' ')
                  else:
                         output.append(lowercase_)
           return "".join(lowercase_)





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   Optional[int]:
           # This defines a "chinese character" as anything in the CJK Unicode block:
           #   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
           #
           # Note that the CJK Unicode block is NOT all Japanese and Korean characters,
           # despite its name. The modern Korean Hangul alphabet is a different block,
           # as is Japanese Hiragana and Katakana. Those alphabets are used to write
           # space-separated words, so they are not treated specially and handled
           # like the all of the other languages.
           if (
               (cp >= 0X4E00 and cp <= 0X9FFF)
               or (cp >= 0X3400 and cp <= 0X4DBF)  #
               or (cp >= 0X20000 and cp <= 0X2A6DF)  #
               or (cp >= 0X2A700 and cp <= 0X2B73F)  #
               or (cp >= 0X2B740 and cp <= 0X2B81F)  #
               or (cp >= 0X2B820 and cp <= 0X2CEAF)  #
               or (cp >= 0XF900 and cp <= 0XFAFF)
               or (cp >= 0X2F800 and cp <= 0X2FA1F)  #
           ):  #
                  return True

           return False





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   Union[str, Any]:
           a__     						=[]
           for char in text:
                  a__     						=ord(lowercase_)
                  if cp == 0 or cp == 0XFFFD or _is_control(lowercase_):
                         continue
                  if _is_whitespace(lowercase_):
                         output.append(' ')
                  else:
                         output.append(lowercase_)
           return "".join(lowercase_)







def      _lowercase(				__a							:	str    ):
       a__     						=set()
       a__     						=word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)    )
              a__     						=char
       return pairs






def      _lowercase(				__a							:	List[Any]    ):
       a__     						=text.replace('—'						,    '-'    )
       a__     						=text.replace('–'						,    '-'    )
       a__     						=text.replace('―'						,    '-'    )
       a__     						=text.replace('…'						,    '...'    )
       a__     						=text.replace('´'						,    '\''    )
       a__     						=re.sub(r'(-+|~+|!+|"+|;+|\?+|\++|,+|\)+|\(+|\\+|\/+|\*+|\[+|\]+|}+|{+|\|+|_+)'						,    r' \1 '						,    __a    )
       a__     						=re.sub(r'\s*\n\s*'						,    ' \n '						,    __a    )
       a__     						=re.sub(r'[^\S\n]+'						,    ' '						,    __a    )
       return text.strip()







class 			lowercase_				(lowercase__      ):
    snake_case  						=VOCAB_FILES_NAMES
    snake_case  						=PRETRAINED_VOCAB_FILES_MAP
    snake_case  						=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    snake_case  						=['input_ids', 'attention_mask']





    def __init__(							self					,     lowercase_					,     lowercase_					,     lowercase_="<unk>"					,     **lowercase_)     ->   Union[str, Any]:
           super().__init__(unk_token=lowercase_					,     **lowercase_)

           try:
                  import ftfy
                  from spacy.lang.en import English

                  a__     						=English()
                  a__     						=_nlp.tokenizer
                  a__     						=ftfy.fix_text
           except ImportError:
                  logger.warning('ftfy or spacy is not installed using BERT BasicTokenizer instead of SpaCy & ftfy.')
                  a__     						=BasicTokenizer(do_lower_case=lowercase_)
                  a__     						=None

           with open(lowercase_					,     encoding='utf-8') as vocab_handle:
                  a__     						=json.load(lowercase_)
           a__     						={v: k for k, v in self.encoder.items()}
           with open(lowercase_					,     encoding='utf-8') as merges_handle:
                  a__     						=merges_handle.read().split('\n')[1:-1]
           a__     						=[tuple(merge.split()) for merge in merges]
           a__     						=dict(zip(lowercase_					,     range(len(lowercase_))))
           a__     						={}





    @property
    def 	__UpperCamelCase						(							self)     ->   Optional[int]:
           return True





    @property
    def 	__UpperCamelCase						(							self)     ->   Union[str, Any]:
           return len(self.encoder)





    def 	__UpperCamelCase						(							self)     ->   Optional[int]:
           return dict(self.encoder					,     **self.added_tokens_encoder)





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   Optional[int]:
           a__     						=tuple(token[:-1]) + (token[-1] + '</w>',)
           if token in self.cache:
                  return self.cache[token]
           a__     						=get_pairs(lowercase_)

           if not pairs:
                  return token + "</w>"

           while True:
                  a__     						=min(lowercase_					,     key=lambda lowercase_: self.bpe_ranks.get(lowercase_					,     float('inf')))
                  if bigram not in self.bpe_ranks:
                         break
                  a__						,    a__     						=bigram
                  a__     						=[]
                  a__     						=0
                  while i < len(lowercase_):
                         try:
                                a__     						=word.index(lowercase_					,     lowercase_)
                         except ValueError:
                                new_word.extend(word[i:])
                                break
                         else:
                                new_word.extend(word[i:j])
                                a__     						=j

                         if word[i] == first and i < len(lowercase_) - 1 and word[i + 1] == second:
                                new_word.append(first + second)
                                i += 2
                         else:
                                new_word.append(word[i])
                                i += 1
                  a__     						=tuple(lowercase_)
                  a__     						=new_word
                  if len(lowercase_) == 1:
                         break
                  else:
                         a__     						=get_pairs(lowercase_)
           a__     						=' '.join(lowercase_)
           if word == "\n  </w>":
                  a__     						='\n</w>'
           a__     						=word
           return word





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   List[Any]:
           a__     						=[]
           if self.fix_text is None:
                  # Using BERT's BasicTokenizer
                  a__     						=self.nlp.tokenize(lowercase_)
                  for token in text:
                         split_tokens.extend(list(self.bpe(lowercase_).split(' ')))
           else:
                  # Using SpaCy & ftfy (original tokenization process of OpenAI GPT)
                  a__     						=self.nlp(text_standardize(self.fix_text(lowercase_)))
                  for token in text:
                         split_tokens.extend(list(self.bpe(token.text.lower()).split(' ')))
           return split_tokens





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   int:
           return self.encoder.get(lowercase_					,     self.encoder.get(self.unk_token))





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   Dict:
           return self.decoder.get(lowercase_					,     self.unk_token)





    def 	__UpperCamelCase						(							self					,     lowercase_)     ->   Union[str, Any]:
           a__     						=''.join(lowercase_).replace('</w>'					,     ' ').strip()
           return out_string





    def 	__UpperCamelCase						(							self					,     lowercase_					,     lowercase_ = None)     ->   Tuple[str]:
           if not os.path.isdir(lowercase_):
                  logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
                  return
           a__     						=os.path.join(
               lowercase_					,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])
           a__     						=os.path.join(
               lowercase_					,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file'])

           with open(lowercase_					,     'w'					,     encoding='utf-8') as f:
                  f.write(json.dumps(self.encoder					,     indent=2					,     sort_keys=lowercase_					,     ensure_ascii=lowercase_) + '\n')

           a__     						=0
           with open(lowercase_					,     'w'					,     encoding='utf-8') as writer:
                  writer.write('#version: 0.2\n')
                  for bpe_tokens, token_index in sorted(self.bpe_ranks.items()					,     key=lambda lowercase_: kv[1]):
                         if index != token_index:
                                logger.warning(
                                    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
                                    ' Please check that the tokenizer is not corrupted!')
                                a__     						=token_index
                         writer.write(' '.join(lowercase_) + '\n')
                         index += 1

           return vocab_file, merge_file





from __future__ import annotations






def      _lowercase(				__a							:	float | int						,    __a							:	float | int						,    __a							:	float | int						,    ):
							if not all((nth_term, start_term_a, common_ratio_r)    ):
														return []
							a__     						=[]
							a__     						=1
							a__     						=common_ratio_r
							for _ in range(int(__a    )    ):
														if not series:
																					series.append(__a    )
														else:
																					power += 1
																					series.append(float(start_term_a * multiple    )    )
																					a__     						=pow(float(__a    )						,    __a    )
							return series


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	_lowerCAmelCase:	Tuple      							=					float(input('Enter the last number (n term) of the Geometric Series'))
	_lowerCAmelCase:	Optional[int]      							=					float(input('Enter the starting term (a) of the Geometric Series'))
	_lowerCAmelCase:	List[Any]      							=					float(
	    input('Enter the common ratio between two terms (r) of the Geometric Series')
	)
	print('Formula of Geometric Series => a + ar + ar^2 ... +ar^n')
	print(geometric_series(nth_term, start_term_a, common_ratio_r))

