code: 
  """simple docstring"""
  
  
  
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  SCREAMING_SNAKE_CASE_     				=   {
      'configuration_bart': ['BART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BartConfig', 'BartOnnxConfig'],
      'tokenization_bart': ['BartTokenizer'],
  }
  
  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    SCREAMING_SNAKE_CASE_     				=   ['BartTokenizerFast']
  
  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    SCREAMING_SNAKE_CASE_     				=   [
        'BART_PRETRAINED_MODEL_ARCHIVE_LIST',
        'BartForCausalLM',
        'BartForConditionalGeneration',
        'BartForQuestionAnswering',
        'BartForSequenceClassification',
        'BartModel',
        'BartPretrainedModel',
        'PretrainedBartModel',
    ]
  
  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    SCREAMING_SNAKE_CASE_     				=   [
        'TFBartForConditionalGeneration',
        'TFBartForSequenceClassification',
        'TFBartModel',
        'TFBartPretrainedModel',
    ]
  
  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    SCREAMING_SNAKE_CASE_     				=   [
        'FlaxBartDecoderPreTrainedModel',
        'FlaxBartForCausalLM',
        'FlaxBartForConditionalGeneration',
        'FlaxBartForQuestionAnswering',
        'FlaxBartForSequenceClassification',
        'FlaxBartModel',
        'FlaxBartPreTrainedModel',
    ]
  
  if TYPE_CHECKING:
    from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
    from .tokenization_bart import BartTokenizer
  
    try:
      if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
      pass
    else:
      from .tokenization_bart_fast import BartTokenizerFast
  
    try:
      if not is_torch_available():
        raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
      pass
    else:
      from .modeling_bart import (
          BART_PRETRAINED_MODEL_ARCHIVE_LIST,
          BartForCausalLM,
          BartForConditionalGeneration,
          BartForQuestionAnswering,
          BartForSequenceClassification,
          BartModel,
          BartPretrainedModel,
          PretrainedBartModel,
      )
  
    try:
      if not is_tf_available():
        raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
      pass
    else:
      from .modeling_tf_bart import (
          TFBartForConditionalGeneration,
          TFBartForSequenceClassification,
          TFBartModel,
          TFBartPretrainedModel,
      )
  
    try:
      if not is_flax_available():
        raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
      pass
    else:
      from .modeling_flax_bart import (
          FlaxBartDecoderPreTrainedModel,
          FlaxBartForCausalLM,
          FlaxBartForConditionalGeneration,
          FlaxBartForQuestionAnswering,
          FlaxBartForSequenceClassification,
          FlaxBartModel,
          FlaxBartPreTrainedModel,
      )
  
  else:
    import sys
  
    SCREAMING_SNAKE_CASE_     				=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
style_context: 
  """simple docstring"""
  
  
  
  
  
  
  
  from math import floor, sqrt
  def 			__UpperCAmelCase		(		a_			:		int				)     ->       int:
     _UpperCAmelCase   	=					0.0
     _UpperCAmelCase   	=					1.0
     _UpperCAmelCase   	=					int(sqrt(a_				)				)
     _UpperCAmelCase   	=					root
     _UpperCAmelCase   	=					0
     while integer_part != 2 * root:
        _UpperCAmelCase   	=					denominator * integer_part - numerator
        _UpperCAmelCase   	=					(n - numerator**2) / denominator
        _UpperCAmelCase   	=					int((root + numerator) / denominator				)
        period += 1
     return period
  def 			__UpperCAmelCase		(		a_			:		int = 1_00_00				)     ->       int:
     _UpperCAmelCase   	=					0
     for i in range(2    ,  n + 1				):
        _UpperCAmelCase   	=					sqrt(a_				)
        if sr - floor(a_				) != 0 and continuous_fraction_period(a_				) % 2 == 1:
           count_odd_periods += 1
     return count_odd_periods
  
  
  if __name__ == "__main__":
    print(f'''{solution(int(input().strip()))}''')
  
  