





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:
				SCREAMING_SNAKE_CASE_      :			int		  =      None


SCREAMING_SNAKE_CASE_      :			Optional[int]		  =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_      :			Any		  =      {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

SCREAMING_SNAKE_CASE_      :			Union[str, Any]		  =      {
    '''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'''
        ),
    },
}

SCREAMING_SNAKE_CASE_      :			str		  =      {
    '''facebook/mbart-large-50-one-to-many-mmt''': 1024,
}

# fmt: off
SCREAMING_SNAKE_CASE_      :			int		  =      ['''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 		snake_case_      (       UpperCAmelCase_	):







	'''simple docstring'''
	__UpperCamelCase        =		VOCAB_FILES_NAMES
	__UpperCamelCase        =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__UpperCamelCase        =		PRETRAINED_VOCAB_FILES_MAP
	__UpperCamelCase        =		['''input_ids''', '''attention_mask''']
	__UpperCamelCase        =		MBartaaTokenizer

	__UpperCamelCase        =		[]
	__UpperCamelCase        =		[]




	def __init__(	self       :    int				,			__lowerCamelCase       :    Dict=None				,			__lowerCamelCase       :    Optional[Any]=None				,			__lowerCamelCase       :    str=None				,			__lowerCamelCase       :    Tuple=None				,			__lowerCamelCase       :    Tuple="</s>"				,			__lowerCamelCase       :    int="</s>"				,			__lowerCamelCase       :    Optional[int]="<s>"				,			__lowerCamelCase       :    str="<unk>"				,			__lowerCamelCase       :    Optional[int]="<pad>"				,			__lowerCamelCase       :    Tuple="<mask>"				,			**__lowerCamelCase       :    List[Any]				,			)					->   List[Any]:

			'''simple docstring'''




			__lowercase					=    AddedToken(__lowerCamelCase				,			lstrip=__lowerCamelCase				,			rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase				,			__lowerCamelCase      ) else mask_token

			__lowercase					=    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__(
			    __lowerCamelCase				,			src_lang=__lowerCamelCase				,			tgt_lang=__lowerCamelCase				,			tokenizer_file=__lowerCamelCase				,			eos_token=__lowerCamelCase				,			sep_token=__lowerCamelCase				,			cls_token=__lowerCamelCase				,			unk_token=__lowerCamelCase				,			pad_token=__lowerCamelCase				,			mask_token=__lowerCamelCase				,			**__lowerCamelCase				,			)

			__lowercase					=    vocab_file
			__lowercase					=    False if not self.vocab_file else True

			__lowercase					=    {
			    lang_code: self.convert_tokens_to_ids(__lowerCamelCase      ) for lang_code in FAIRSEQ_LANGUAGE_CODES
			}

			__lowercase					=    src_lang if src_lang is not None else 'en_XX'
			__lowercase					=    tgt_lang
			__lowercase					=    self.lang_code_to_id[self._src_lang]
			self.set_src_lang_special_tokens(self._src_lang      )




	@property
	def       UpperCAmelCase (	self       :    int      )					->   str:

			'''simple docstring'''




			return self._src_lang




	@src_lang.setter
	def       UpperCAmelCase (	self       :    Optional[int]				,			__lowerCamelCase       :    str      )					->   None:

			'''simple docstring'''




			__lowercase					=    new_src_lang
			self.set_src_lang_special_tokens(self._src_lang      )




	def       UpperCAmelCase (	self       :    Dict				,			__lowerCamelCase       :    List[int]				,			__lowerCamelCase       :    Optional[List[int]] = None      )					->   List[int]:

			'''simple docstring'''




			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       UpperCAmelCase (	self       :    str				,			__lowerCamelCase       :    List[str]				,			__lowerCamelCase       :    str = "en_XX"				,			__lowerCamelCase       :    Optional[List[str]] = None				,			__lowerCamelCase       :    str = "ro_RO"				,			**__lowerCamelCase       :    Tuple				,			)					->   BatchEncoding:

			'''simple docstring'''




			__lowercase					=    src_lang
			__lowercase					=    tgt_lang
			return super().prepare_seqaseq_batch(__lowerCamelCase				,			__lowerCamelCase				,			**__lowerCamelCase      )




	def       UpperCAmelCase (	self       :    List[Any]      )					->   Tuple:

			'''simple docstring'''




			return self.set_src_lang_special_tokens(self.src_lang      )




	def       UpperCAmelCase (	self       :    Tuple      )					->   str:

			'''simple docstring'''




			return self.set_tgt_lang_special_tokens(self.tgt_lang      )




	def       UpperCAmelCase (	self       :    Tuple				,			__lowerCamelCase       :    str      )					->   None:

			'''simple docstring'''




			__lowercase					=    self.convert_tokens_to_ids(__lowerCamelCase      )
			__lowercase					=    [self.cur_lang_code_id]
			__lowercase					=    [self.eos_token_id]

			__lowercase					=    self.convert_ids_to_tokens(self.prefix_tokens      )
			__lowercase					=    self.convert_ids_to_tokens(self.suffix_tokens      )

			__lowercase					=    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       UpperCAmelCase (	self       :    List[Any]				,			__lowerCamelCase       :    str      )					->   None:

			'''simple docstring'''




			__lowercase					=    self.convert_tokens_to_ids(__lowerCamelCase      )
			__lowercase					=    [self.cur_lang_code_id]
			__lowercase					=    [self.eos_token_id]

			__lowercase					=    self.convert_ids_to_tokens(self.prefix_tokens      )
			__lowercase					=    self.convert_ids_to_tokens(self.suffix_tokens      )

			__lowercase					=    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       UpperCAmelCase (	self       :    List[str]				,			__lowerCamelCase       :    str				,			__lowerCamelCase       :    str				,			__lowerCamelCase       :    Optional[str]				,			__lowerCamelCase       :    Optional[str]				,			**__lowerCamelCase       :    List[str]      )					->   Optional[int]:

			'''simple docstring'''




			if src_lang is None or tgt_lang is None:
					raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'      )
			__lowercase					=    src_lang
			__lowercase					=    self(__lowerCamelCase				,			add_special_tokens=__lowerCamelCase				,			return_tensors=__lowerCamelCase				,			**__lowerCamelCase      )
			__lowercase					=    self.convert_tokens_to_ids(__lowerCamelCase      )
			__lowercase					=    tgt_lang_id
			return inputs






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

			'''simple docstring'''




			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(__lowerCamelCase      ):
					logger.error(F"Vocabulary path ({save_directory}) should be a directory"      )
					return
			__lowercase					=    os.path.join(
			    __lowerCamelCase				,			(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )

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

			return (out_vocab_file,)











from math import floor, sqrt



def    SCREAMING_SNAKE_CASE							(			snake_case       )		->						int:
		__lowercase					=    0.0
		__lowercase					=    1.0
		__lowercase					=    int(sqrt(snake_case       )       )
		__lowercase					=    root
		__lowercase					=    0
		while integer_part != 2 * root:
				__lowercase					=    denominator * integer_part - numerator
				__lowercase					=    (n - numerator**2) / denominator
				__lowercase					=    int((root + numerator) / denominator       )
				period += 1
		return period



def    SCREAMING_SNAKE_CASE							(			snake_case = 10_000       )		->						int:
		__lowercase					=    0
		for i in range(2	,      n + 1       ):
				__lowercase					=    sqrt(snake_case       )
				if sr - floor(snake_case       ) != 0 and continuous_fraction_period(snake_case       ) % 2 == 1:
						count_odd_periods += 1
		return count_odd_periods


if __name__ == "__main__":
		print(F"""{solution(int(input().strip()))}""")




