




'''simple docstring'''







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				:		List[str]				      =    logging.get_logger(__name__)

_lowerCamelCase				:		List[Any]				      =    {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
}

_lowerCamelCase				:		str				      =    {
    '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				:		Tuple				      =    {
    'openai-gpt': 512,
}






def 						_lowercase						(      lowercase_    ):



		'''simple docstring'''







		_snake_case      			=			text.strip()
		if not text:
				return []
		_snake_case      			=			text.split()
		return tokens





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					def __init__(       self,    __UpperCamelCase=True,    __UpperCamelCase=None,    __UpperCamelCase=True,    __UpperCamelCase=None,    __UpperCamelCase=True,    ):

							if never_split is None:
									_snake_case      			=			[]
							_snake_case      			=			do_lower_case
							_snake_case      			=			set(__UpperCamelCase					)
							_snake_case      			=			tokenize_chinese_chars
							_snake_case      			=			strip_accents
							_snake_case      			=			do_split_on_punc






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase,    __UpperCamelCase=None					):
							_snake_case      			=			self.never_split.union(set(__UpperCamelCase					)					) if never_split else self.never_split
							_snake_case      			=			self._clean_text(__UpperCamelCase					)

							# 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      			=			self._tokenize_chinese_chars(__UpperCamelCase					)
							# prevents treating the same character with different unicode codepoints as different characters
							_snake_case      			=			unicodedata.normalize("NFC",    __UpperCamelCase					)
							_snake_case      			=			whitespace_tokenize(__UpperCamelCase					)
							_snake_case      			=			[]
							for token in orig_tokens:
									if token not in never_split:
											if self.do_lower_case:
													_snake_case      			=			token.lower()
													if self.strip_accents is not False:
															_snake_case      			=			self._run_strip_accents(__UpperCamelCase					)
											elif self.strip_accents:
													_snake_case      			=			self._run_strip_accents(__UpperCamelCase					)
									split_tokens.extend(self._run_split_on_punc(__UpperCamelCase,    __UpperCamelCase					)					)

							_snake_case      			=			whitespace_tokenize(" ".join(__UpperCamelCase					)					)
							return output_tokens






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase					):
							_snake_case      			=			unicodedata.normalize("NFD",    __UpperCamelCase					)
							_snake_case      			=			[]
							for char in text:
									_snake_case      			=			unicodedata.category(__UpperCamelCase					)
									if cat == "Mn":
											continue
									output.append(__UpperCamelCase					)
							return "".join(__UpperCamelCase					)






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase,    __UpperCamelCase=None					):

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

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






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase					):
							_snake_case      			=			[]
							for char in text:
									_snake_case      			=			ord(__UpperCamelCase					)
									if self._is_chinese_char(__UpperCamelCase					):
											output.append(" "					)
											output.append(__UpperCamelCase					)
											output.append(" "					)
									else:
											output.append(__UpperCamelCase					)
							return "".join(__UpperCamelCase					)






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase					):

							if (
							    (cp >= 0X4e_00 and cp <= 0X9f_ff)
							    or (cp >= 0X34_00 and cp <= 0X4d_bf)  #
							    or (cp >= 0X2_00_00 and cp <= 0X2_a6_df)  #
							    or (cp >= 0X2_a7_00 and cp <= 0X2_b7_3f)  #
							    or (cp >= 0X2_b7_40 and cp <= 0X2_b8_1f)  #
							    or (cp >= 0X2_b8_20 and cp <= 0X2_ce_af)  #
							    or (cp >= 0Xf9_00 and cp <= 0Xfa_ff)
							    or (cp >= 0X2_f8_00 and cp <= 0X2_fa_1f)  #
							):  #
									return True

							return False






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase					):
							_snake_case      			=			[]
							for char in text:
									_snake_case      			=			ord(__UpperCamelCase					)
									if cp == 0 or cp == 0Xff_fd or _is_control(__UpperCamelCase					):
											continue
									if _is_whitespace(__UpperCamelCase					):
											output.append(" "					)
									else:
											output.append(__UpperCamelCase					)
							return "".join(__UpperCamelCase					)






def 						_lowercase						(      lowercase_    ):



		'''simple docstring'''







		_snake_case      			=			set()
		_snake_case      			=			word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)    )
				_snake_case      			=			char
		return pairs






def 						_lowercase						(      lowercase_    ):



		'''simple docstring'''







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





class 	lowerCamelCase_				(			UpperCAmelCase_				):




					'''simple docstring'''






					lowercase__       =					VOCAB_FILES_NAMES
					lowercase__       =					PRETRAINED_VOCAB_FILES_MAP
					lowercase__       =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__       =					["""input_ids""", """attention_mask"""]






					def __init__(       self,    __UpperCamelCase,    __UpperCamelCase,    __UpperCamelCase="<unk>",    **__UpperCamelCase					):
							super().__init__(unk_token=__UpperCamelCase,    **__UpperCamelCase					)

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

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

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






					@property
					def 							__SCREAMING_SNAKE_CASE      (       self					):
							return True






					@property
					def 							__SCREAMING_SNAKE_CASE      (       self					):
							return len(self.encoder					)






					def 							__SCREAMING_SNAKE_CASE      (       self					):
							return dict(self.encoder,    **self.added_tokens_encoder					)






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase					):
							_snake_case      			=			tuple(token[:-1]					) + (token[-1] + "</w>",)
							if token in self.cache:
									return self.cache[token]
							_snake_case      			=			get_pairs(__UpperCamelCase					)

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

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

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






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






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase					):
							return self.encoder.get(__UpperCamelCase,    self.encoder.get(self.unk_token					)					)






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase					):
							return self.decoder.get(__UpperCamelCase,    self.unk_token					)






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase					):
							_snake_case      			=			"".join(__UpperCamelCase					).replace("</w>",    " "					).strip()
							return out_string






					def 							__SCREAMING_SNAKE_CASE      (       self,    __UpperCamelCase,    __UpperCamelCase = None					):

							if not os.path.isdir(__UpperCamelCase					):
									logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''					)
									return
							_snake_case      			=			os.path.join(
							    __UpperCamelCase,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)
							_snake_case      			=			os.path.join(
							    __UpperCamelCase,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]					)

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

							_snake_case      			=			0
							with open(__UpperCamelCase,    "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 __UpperCamelCase					: 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      			=			token_index
											writer.write(" ".join(__UpperCamelCase					) + "\n"					)
											index += 1

							return vocab_file, merge_file






"""simple docstring"""
import math
from collections.abc import Generator





def  lowerCAmelCase__     (      _UpperCamelCase							:					int       )       ->					Generator[int, None, None]:





						"""simple docstring"""






						snake_case             =      (i for i in range(1			,      (max_n + 1)       ))
						for i in (n for n in numbers if n > 1):
												for j in range(2			,      _UpperCamelCase       ):
																		if (i % j) == 0:
																								break
												else:
																		yield i





def  lowerCAmelCase__     (      _UpperCamelCase							:					int       )       ->					Generator[int, None, None]:





						"""simple docstring"""






						snake_case             =      (i for i in range(1			,      (max_n + 1)       ))
						for i in (n for n in numbers if n > 1):
												# only need to check for factors up to sqrt(i)
												snake_case             =      int(math.sqrt(_UpperCamelCase       )       ) + 1
												for j in range(2			,      _UpperCamelCase       ):
																		if (i % j) == 0:
																								break
												else:
																		yield i





def  lowerCAmelCase__     (      _UpperCamelCase							:					int       )       ->					Generator[int, None, None]:





						"""simple docstring"""






						snake_case             =      (i for i in range(1			,      (max_n + 1)			,      2       ))
						# It's useless to test even numbers as they will not be prime
						if max_n > 2:
												yield 2  # Because 2 will not be tested, it's necessary to yield it now
						for i in (n for n in numbers if n > 1):
												snake_case             =      int(math.sqrt(_UpperCamelCase       )       ) + 1
												for j in range(3			,      _UpperCamelCase			,      2       ):
																		# As we removed the even numbers, we don't need them now
																		if (i % j) == 0:
																								break
												else:
																		yield i





def  lowerCAmelCase__     (      )       ->					List[str]:





						"""simple docstring"""






						from timeit import timeit

						snake_case             =      'from __main__ import slow_primes, primes, fast_primes'
						print(timeit('slow_primes(1_000_000_000_000)'			,      setup=_UpperCamelCase			,      number=1_0_0_0_0_0_0       )       )
						print(timeit('primes(1_000_000_000_000)'			,      setup=_UpperCamelCase			,      number=1_0_0_0_0_0_0       )       )
						print(timeit('fast_primes(1_000_000_000_000)'			,      setup=_UpperCamelCase			,      number=1_0_0_0_0_0_0       )       )


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE__       =	int(input("Calculate primes up to:\n>> ").strip())
					for ret in primes(number):
										print(ret)
					benchmark()


