






"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowercase_								=	{
    'configuration_esm': ['ESM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'EsmConfig'],
    'tokenization_esm': ['EsmTokenizer'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_								=	[
           'ESM_PRETRAINED_MODEL_ARCHIVE_LIST',
           'EsmForMaskedLM',
           'EsmForSequenceClassification',
           'EsmForTokenClassification',
           'EsmModel',
           'EsmPreTrainedModel',
       ]
       lowercase_								=	['EsmForProteinFolding', 'EsmFoldPreTrainedModel']

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_								=	[
           'TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST',
           'TFEsmForMaskedLM',
           'TFEsmForSequenceClassification',
           'TFEsmForTokenClassification',
           'TFEsmModel',
           'TFEsmPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_esm import ESM_PRETRAINED_CONFIG_ARCHIVE_MAP, EsmConfig
       from .tokenization_esm import EsmTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_esm import (
                  ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  EsmForMaskedLM,
                  EsmForSequenceClassification,
                  EsmForTokenClassification,
                  EsmModel,
                  EsmPreTrainedModel,
              )
              from .modeling_esmfold import EsmFoldPreTrainedModel, EsmForProteinFolding

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_esm import (
                  TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFEsmForMaskedLM,
                  TFEsmForSequenceClassification,
                  TFEsmForTokenClassification,
                  TFEsmModel,
                  TFEsmPreTrainedModel,
              )


else:
       import sys

       lowercase_								=	_LazyModule(__name__, globals()['__file__'], _import_structure)









'''simple docstring'''


from math import floor, sqrt






def 			UpperCAmelCase_							(		lowercase__							):


     '''simple docstring'''







     a_									=0.0
     a_									=1.0
     a_									=int(sqrt(lowercase__							)							)
     a_									=root
     a_									=0
     while integer_part != 2 * root:
          a_									=denominator * integer_part - numerator
          a_									=(n - numerator**2) / denominator
          a_									=int((root + numerator) / denominator							)
          period += 1
     return period






def 			UpperCAmelCase_							(		lowercase__ = 1_0_0_0_0							):


     '''simple docstring'''







     a_									=0
     for i in range(2							,						n + 1							):
          a_									=sqrt(lowercase__							)
          if sr - floor(lowercase__							) != 0 and continuous_fraction_period(lowercase__							) % 2 == 1:
               count_odd_periods += 1
     return count_odd_periods


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


