





'''simple docstring'''



import math
from collections.abc import Generator




def       _lowerCAmelCase  ( lowerCamelCase_	:     int ):
			__lowercase   =							(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						,				lowerCamelCase_ ):
									if (i % j) == 0:
												break
						else:
									yield i




def       _lowerCAmelCase  ( lowerCamelCase_	:     int ):
			__lowercase   =							(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)
						__lowercase   =							int(math.sqrt(lowerCamelCase_ ) ) + 1
						for j in range(2						,				lowerCamelCase_ ):
									if (i % j) == 0:
												break
						else:
									yield i




def       _lowerCAmelCase  ( lowerCamelCase_	:     int ):
			__lowercase   =							(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):
						__lowercase   =							int(math.sqrt(lowerCamelCase_ ) ) + 1
						for j in range(3						,				lowerCamelCase_						,				2 ):
									# As we removed the even numbers, we don't need them now
									if (i % j) == 0:
												break
						else:
									yield i




def       _lowerCAmelCase  ( ):
			from timeit import timeit

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












"""simple docstring"""


import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_mbartaa import MBartaaTokenizer
else:
  lowerCamelCase__      =      None


lowerCamelCase__      =      logging.get_logger(__name__)

lowerCamelCase__      =      {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

lowerCamelCase__      =      {
    "vocab_file": {
        "facebook/mbart-large-50-one-to-many-mmt": (
            "https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-50-one-to-many-mmt": (
            "https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/tokenizer.json"
        ),
    },
}

lowerCamelCase__      =      {
    "facebook/mbart-large-50-one-to-many-mmt": 1024,
}

# fmt: off
lowerCamelCase__      =      ["ar_AR", "cs_CZ", "de_DE", "en_XX", "es_XX", "et_EE", "fi_FI", "fr_XX", "gu_IN", "hi_IN", "it_IT", "ja_XX", "kk_KZ", "ko_KR", "lt_LT", "lv_LV", "my_MM", "ne_NP", "nl_XX", "ro_RO", "ru_RU", "si_LK", "tr_TR", "vi_VN", "zh_CN", "af_ZA", "az_AZ", "bn_IN", "fa_IR", "he_IL", "hr_HR", "id_ID", "ka_GE", "km_KH", "mk_MK", "ml_IN", "mn_MN", "mr_IN", "pl_PL", "ps_AF", "pt_XX", "sv_SE", "sw_KE", "ta_IN", "te_IN", "th_TH", "tl_XX", "uk_UA", "ur_PK", "xh_ZA", "gl_ES", "sl_SI"]



class    __SCREAMING_SNAKE_CASE			(  _UpperCamelCase      ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:Tuple		   =    VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__							:List[Any]		   =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__							:Union[str, Any]		   =    PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__							:int		   =    ["input_ids", "attention_mask"]
  SCREAMING_SNAKE_CASE__							:Dict		   =    MBartaaTokenizer

  SCREAMING_SNAKE_CASE__							:List[int]		   =    []
  SCREAMING_SNAKE_CASE__							:List[int]		   =    []

  def __init__(						self      :				str    ,      __a      :				int=None    ,      __a      :				List[str]=None    ,      __a      :				Optional[Any]=None    ,      __a      :				List[str]=None    ,      __a      :				Tuple="</s>"    ,      __a      :				Union[str, Any]="</s>"    ,      __a      :				str="<s>"    ,      __a      :				Any="<unk>"    ,      __a      :				List[str]="<pad>"    ,      __a      :				Optional[Any]="<mask>"    ,      **__a      :				Any    ,      )						-> Union[str, Any]:
        # Mask token behave like a normal word, i.e. include the space before it
        _UpperCamelCase					:		Dict  =				AddedToken(__a    ,      lstrip=__a    ,      rstrip=__a		) if isinstance(__a    ,      __a		) else mask_token

        _UpperCamelCase					:		str  =				kwargs.get("additional_special_tokens"    ,      []		)
        kwargs["additional_special_tokens"] += [
            code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
        ]

        super().__init__(
            __a    ,      src_lang=__a    ,      tgt_lang=__a    ,      tokenizer_file=__a    ,      eos_token=__a    ,      sep_token=__a    ,      cls_token=__a    ,      unk_token=__a    ,      pad_token=__a    ,      mask_token=__a    ,      **__a    ,      )

        _UpperCamelCase					:		Optional[int]  =				vocab_file
        _UpperCamelCase					:		int  =				False if not self.vocab_file else True

        _UpperCamelCase					:		int  =				{
            lang_code: self.convert_tokens_to_ids(__a		) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

        _UpperCamelCase					:		List[str]  =				src_lang if src_lang is not None else "en_XX"
        _UpperCamelCase					:		Dict  =				tgt_lang
        _UpperCamelCase					:		int  =				self.lang_code_to_id[self._src_lang]
        self.set_src_lang_special_tokens(self._src_lang		)

  @property
  def       __SCREAMING_SNAKE_CASE (						self      :				Optional[int]		)						-> str:
        return self._src_lang

  @src_lang.setter
  def       __SCREAMING_SNAKE_CASE (						self      :				Union[str, Any]    ,      __a      :				str		)						-> None:
        _UpperCamelCase					:		int  =				new_src_lang
        self.set_src_lang_special_tokens(self._src_lang		)

  def       __SCREAMING_SNAKE_CASE (						self      :				Optional[int]    ,      __a      :				List[int]    ,      __a      :				Optional[List[int]] = None		)						-> List[int]:
        if token_ids_a is None:
              return self.prefix_tokens + token_ids_a + self.suffix_tokens
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens

  def       __SCREAMING_SNAKE_CASE (						self      :				Any    ,      __a      :				List[str]    ,      __a      :				str = "en_XX"    ,      __a      :				Optional[List[str]] = None    ,      __a      :				str = "ro_RO"    ,      **__a      :				Tuple    ,      )						-> BatchEncoding:
        _UpperCamelCase					:		List[Any]  =				src_lang
        _UpperCamelCase					:		Union[str, Any]  =				tgt_lang
        return super().prepare_seqaseq_batch(__a    ,      __a    ,      **__a		)

  def       __SCREAMING_SNAKE_CASE (						self      :				List[str]		)						-> int:
        return self.set_src_lang_special_tokens(self.src_lang		)

  def       __SCREAMING_SNAKE_CASE (						self      :				Tuple		)						-> Tuple:
        return self.set_tgt_lang_special_tokens(self.tgt_lang		)

  def       __SCREAMING_SNAKE_CASE (						self      :				List[str]    ,      __a      :				str		)						-> None:
        _UpperCamelCase					:		List[Any]  =				self.convert_tokens_to_ids(__a		)
        _UpperCamelCase					:		Union[str, Any]  =				[self.cur_lang_code_id]
        _UpperCamelCase					:		List[Any]  =				[self.eos_token_id]

        _UpperCamelCase					:		Union[str, Any]  =				self.convert_ids_to_tokens(self.prefix_tokens		)
        _UpperCamelCase					:		Union[str, Any]  =				self.convert_ids_to_tokens(self.suffix_tokens		)

        _UpperCamelCase					:		Optional[Any]  =				processors.TemplateProcessing(
            single=prefix_tokens_str + ["$A"] + suffix_tokens_str    ,      pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str    ,      special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str    ,      self.prefix_tokens + self.suffix_tokens		)		)    ,      )

  def       __SCREAMING_SNAKE_CASE (						self      :				Dict    ,      __a      :				str		)						-> None:
        _UpperCamelCase					:		Tuple  =				self.convert_tokens_to_ids(__a		)
        _UpperCamelCase					:		Union[str, Any]  =				[self.cur_lang_code_id]
        _UpperCamelCase					:		Optional[Any]  =				[self.eos_token_id]

        _UpperCamelCase					:		int  =				self.convert_ids_to_tokens(self.prefix_tokens		)
        _UpperCamelCase					:		Any  =				self.convert_ids_to_tokens(self.suffix_tokens		)

        _UpperCamelCase					:		Tuple  =				processors.TemplateProcessing(
            single=prefix_tokens_str + ["$A"] + suffix_tokens_str    ,      pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str    ,      special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str    ,      self.prefix_tokens + self.suffix_tokens		)		)    ,      )

  def       __SCREAMING_SNAKE_CASE (						self      :				Dict    ,      __a      :				Optional[int]    ,      __a      :				str    ,      __a      :				Optional[str]    ,      __a      :				Optional[str]    ,      **__a      :				int		)						-> List[str]:
        if src_lang is None or tgt_lang is None:
              raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"		)
        _UpperCamelCase					:		List[str]  =				src_lang
        _UpperCamelCase					:		List[str]  =				self(__a    ,      add_special_tokens=__a    ,      return_tensors=__a    ,      **__a		)
        _UpperCamelCase					:		str  =				self.convert_tokens_to_ids(__a		)
        _UpperCamelCase					:		str  =				tgt_lang_id
        return inputs


  def       __SCREAMING_SNAKE_CASE (						self      :				Union[str, Any]    ,      __a      :				str    ,      __a      :				Optional[str] = None		)						-> Tuple[str]:
        if not self.can_save_slow_tokenizer:
              raise ValueError(
                  "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                  "tokenizer."		)

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

        if os.path.abspath(self.vocab_file		) != os.path.abspath(__a		):
              copyfile(self.vocab_file    ,      __a		)

        return (out_vocab_file,)
