





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_												=       logging.get_logger(__name__)

lowerCAmelCase_												=       {
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
}

lowerCAmelCase_												=       {
    '''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_												=       {
    '''openai-gpt''': 5_1_2,
}






def   lowerCamelCase_		(       _UpperCamelCase				)	->		List[Any]:






				"""simple docstring"""


				snake_case_		:					Optional[int]			    =						text.strip()
				if not text:
								return []
				snake_case_		:					Tuple			    =						text.split()
				return tokens



class       __lowerCAmelCase (    _a  ):






			def __init__(self      ,							__magic_name__=True      ,							__magic_name__=None      ,							__magic_name__=True      ,							__magic_name__=None      ,							__magic_name__=True      ,							)  ->     List[Any]:


							'''simple docstring'''



							if never_split is None:
											snake_case_		:					List[Any]			    =						[]
							snake_case_		:					int			    =						do_lower_case
							snake_case_		:					List[str]			    =						set(__magic_name__					)
							snake_case_		:					List[Any]			    =						tokenize_chinese_chars
							snake_case_		:					Dict			    =						strip_accents
							snake_case_		:					Any			    =						do_split_on_punc






			def     lowerCamelCase						(self      ,							__magic_name__      ,							__magic_name__=None					)  ->     Dict:


							'''simple docstring'''



							snake_case_		:					str			    =						self.never_split.union(set(__magic_name__					)					) if never_split else self.never_split
							snake_case_		:					Any			    =						self._clean_text(__magic_name__					)

							# 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:
											snake_case_		:					int			    =						self._tokenize_chinese_chars(__magic_name__					)
							# prevents treating the same character with different unicode codepoints as different characters
							snake_case_		:					List[str]			    =						unicodedata.normalize('''NFC'''      ,							__magic_name__					)
							snake_case_		:					Union[str, Any]			    =						whitespace_tokenize(__magic_name__					)
							snake_case_		:					Dict			    =						[]
							for token in orig_tokens:
											if token not in never_split:
															if self.do_lower_case:
																			snake_case_		:					Dict			    =						token.lower()
																			if self.strip_accents is not False:
																							snake_case_		:					Optional[int]			    =						self._run_strip_accents(__magic_name__					)
															elif self.strip_accents:
																			snake_case_		:					str			    =						self._run_strip_accents(__magic_name__					)
											split_tokens.extend(self._run_split_on_punc(__magic_name__      ,							__magic_name__					)					)

							snake_case_		:					str			    =						whitespace_tokenize(''' '''.join(__magic_name__					)					)
							return output_tokens






			def     lowerCamelCase						(self      ,							__magic_name__					)  ->     int:


							'''simple docstring'''



							snake_case_		:					Optional[int]			    =						unicodedata.normalize('''NFD'''      ,							__magic_name__					)
							snake_case_		:					int			    =						[]
							for char in text:
											snake_case_		:					int			    =						unicodedata.category(__magic_name__					)
											if cat == "Mn":
															continue
											output.append(__magic_name__					)
							return "".join(__magic_name__					)






			def     lowerCamelCase						(self      ,							__magic_name__      ,							__magic_name__=None					)  ->     int:


							'''simple docstring'''



							if not self.do_split_on_punc or (never_split is not None and text in never_split):
											return [text]
							snake_case_		:					Optional[Any]			    =						list(__magic_name__					)
							snake_case_		:					Optional[int]			    =						0
							snake_case_		:					List[Any]			    =						True
							snake_case_		:					List[Any]			    =						[]
							while i < len(__magic_name__					):
											snake_case_		:					int			    =						chars[i]
											if _is_punctuation(__magic_name__					):
															output.append([char]					)
															snake_case_		:					int			    =						True
											else:
															if start_new_word:
																			output.append([]					)
															snake_case_		:					Optional[int]			    =						False
															output[-1].append(__magic_name__					)
											i += 1

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






			def     lowerCamelCase						(self      ,							__magic_name__					)  ->     Optional[int]:


							'''simple docstring'''



							snake_case_		:					List[Any]			    =						[]
							for char in text:
											snake_case_		:					Dict			    =						ord(__magic_name__					)
											if self._is_chinese_char(__magic_name__					):
															output.append(''' '''					)
															output.append(__magic_name__					)
															output.append(''' '''					)
											else:
															output.append(__magic_name__					)
							return "".join(__magic_name__					)






			def     lowerCamelCase						(self      ,							__magic_name__					)  ->     Union[str, Any]:


							'''simple docstring'''



							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     lowerCamelCase						(self      ,							__magic_name__					)  ->     Union[str, Any]:


							'''simple docstring'''



							snake_case_		:					Tuple			    =						[]
							for char in text:
											snake_case_		:					List[str]			    =						ord(__magic_name__					)
											if cp == 0 or cp == 0XFFFD or _is_control(__magic_name__					):
															continue
											if _is_whitespace(__magic_name__					):
															output.append(''' '''					)
											else:
															output.append(__magic_name__					)
							return "".join(__magic_name__					)






def   lowerCamelCase_		(       _UpperCamelCase				)	->		List[str]:






				"""simple docstring"""


				snake_case_		:					Union[str, Any]			    =						set()
				snake_case_		:					List[Any]			    =						word[0]
				for char in word[1:]:
								pairs.add((prev_char, char)				)
								snake_case_		:					int			    =						char
				return pairs






def   lowerCamelCase_		(       _UpperCamelCase				)	->		Tuple:






				"""simple docstring"""


				snake_case_		:					str			    =						text.replace('''—'''				,       '''-'''				)
				snake_case_		:					int			    =						text.replace('''–'''				,       '''-'''				)
				snake_case_		:					Optional[int]			    =						text.replace('''―'''				,       '''-'''				)
				snake_case_		:					int			    =						text.replace('''…'''				,       '''...'''				)
				snake_case_		:					Tuple			    =						text.replace('''´'''				,       '''\''''				)
				snake_case_		:					Optional[Any]			    =						re.sub(R'''(-+|~+|!+|"+|;+|\?+|\++|,+|\)+|\(+|\\+|\/+|\*+|\[+|\]+|}+|{+|\|+|_+)'''				,       R''' \1 '''				,       _UpperCamelCase				)
				snake_case_		:					List[str]			    =						re.sub(R'''\s*\n\s*'''				,       ''' \n '''				,       _UpperCamelCase				)
				snake_case_		:					List[str]			    =						re.sub(R'''[^\S\n]+'''				,       ''' '''				,       _UpperCamelCase				)
				return text.strip()





class       __lowerCAmelCase (    _a  ):
			lowerCamelCase_  :  Union[str, Any]     =   VOCAB_FILES_NAMES
			lowerCamelCase_  :  Union[str, Any]     =   PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase_  :  str     =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase_  :  Union[str, Any]     =   ['''input_ids''', '''attention_mask''']






			def __init__(self      ,							__magic_name__      ,							__magic_name__      ,							__magic_name__="<unk>"      ,							**__magic_name__					)  ->     Dict:


							'''simple docstring'''



							super().__init__(unk_token=__magic_name__      ,							**__magic_name__					)

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

											snake_case_		:					Any			    =						English()
											snake_case_		:					Dict			    =						_nlp.tokenizer
											snake_case_		:					Optional[int]			    =						ftfy.fix_text
							except ImportError:
											logger.warning('''ftfy or spacy is not installed using BERT BasicTokenizer instead of SpaCy & ftfy.'''					)
											snake_case_		:					Dict			    =						BasicTokenizer(do_lower_case=__magic_name__					)
											snake_case_		:					Optional[Any]			    =						None

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






			@property
			def     lowerCamelCase						(self					)  ->     Dict:


							'''simple docstring'''



							return True






			@property
			def     lowerCamelCase						(self					)  ->     int:


							'''simple docstring'''



							return len(self.encoder					)






			def     lowerCamelCase						(self					)  ->     List[Any]:


							'''simple docstring'''



							return dict(self.encoder      ,							**self.added_tokens_encoder					)






			def     lowerCamelCase						(self      ,							__magic_name__					)  ->     int:


							'''simple docstring'''



							snake_case_		:					Dict			    =						tuple(token[:-1]					) + (token[-1] + '''</w>''',)
							if token in self.cache:
											return self.cache[token]
							snake_case_		:					Optional[int]			    =						get_pairs(__magic_name__					)

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

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

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






			def     lowerCamelCase						(self      ,							__magic_name__					)  ->     str:


							'''simple docstring'''



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






			def     lowerCamelCase						(self      ,							__magic_name__					)  ->     Optional[int]:


							'''simple docstring'''



							return self.encoder.get(__magic_name__      ,							self.encoder.get(self.unk_token					)					)






			def     lowerCamelCase						(self      ,							__magic_name__					)  ->     str:


							'''simple docstring'''



							return self.decoder.get(__magic_name__      ,							self.unk_token					)






			def     lowerCamelCase						(self      ,							__magic_name__					)  ->     Union[str, Any]:


							'''simple docstring'''



							snake_case_		:					Optional[int]			    =						''''''.join(__magic_name__					).replace('''</w>'''      ,							''' '''					).strip()
							return out_string






			def     lowerCamelCase						(self      ,							__magic_name__      ,							__magic_name__ = None					)  ->     Tuple[str]:


							'''simple docstring'''



							if not os.path.isdir(__magic_name__					):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''					)
											return
							snake_case_		:					Any			    =						os.path.join(
							    __magic_name__      ,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)
							snake_case_		:					List[str]			    =						os.path.join(
							    __magic_name__      ,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']					)

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

							snake_case_		:					List[str]			    =						0
							with open(__magic_name__      ,							'''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 __magic_name__					: 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!'''					)
																			snake_case_		:					Optional[int]			    =						token_index
															writer.write(''' '''.join(__magic_name__					) + '''\n'''					)
															index += 1

							return vocab_file, merge_file







def   lowerCamelCase_		(       _UpperCamelCase				)	->		int:






				"""simple docstring"""


				barcode //= 10  # exclude the last digit
				snake_case_		:					str			    =						False
				snake_case_		:					str			    =						0

				# extract and check each digit
				while barcode != 0:
								snake_case_		:					Any			    =						1 if checker else 3
								s += mult * (barcode % 10)
								barcode //= 10
								snake_case_		:					Tuple			    =						not checker

				return (10 - (s % 10)) % 10






def   lowerCamelCase_		(       _UpperCamelCase				)	->		bool:






				"""simple docstring"""


				return len(str(_UpperCamelCase				)				) == 13 and get_check_digit(_UpperCamelCase				) == barcode % 10






def   lowerCamelCase_		(       _UpperCamelCase				)	->		int:






				"""simple docstring"""


				if str(_UpperCamelCase				).isalpha():
								snake_case_		:					Optional[Any]			    =						f'''Barcode \'{barcode}\' has alphabetic characters.'''
								raise ValueError(_UpperCamelCase				)
				elif int(_UpperCamelCase				) < 0:
								raise ValueError('''The entered barcode has a negative value. Try again.'''				)
				else:
								return int(_UpperCamelCase				)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	lowerCAmelCase_												=       get_barcode(input('''Barcode: ''').strip())

	if is_valid(barcode):
		print(F'''\'{barcode}\' is a valid barcode.''')
	else:
		print(F'''\'{barcode}\' is NOT a valid barcode.''')
