




from math import gcd
def        __lowerCAmelCase (UpperCAmelCase_ = 12_000		)     ->   Dict:
    a__      =       0
    for d in range(max_d + 1		):
        for n in range(d // 3 + 1   ,    (d + 1) // 2		):
            if gcd(UpperCAmelCase_   ,    UpperCAmelCase_		) == 1:
                fractions_number += 1
    return fractions_number


if __name__ == "__main__":
 print(F"{solution() = }")












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE_						:					str			   =       {
    '''configuration_wav2vec2_conformer''': [
        '''WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Wav2Vec2ConformerConfig''',
    ],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_						:					Optional[int]			   =       [
     '''WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''Wav2Vec2ConformerForAudioFrameClassification''',
     '''Wav2Vec2ConformerForCTC''',
     '''Wav2Vec2ConformerForPreTraining''',
     '''Wav2Vec2ConformerForSequenceClassification''',
     '''Wav2Vec2ConformerForXVector''',
     '''Wav2Vec2ConformerModel''',
     '''Wav2Vec2ConformerPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_wavaveca_conformer import (
     WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
     WavaVecaConformerConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_wavaveca_conformer import (
      WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      WavaVecaConformerForAudioFrameClassification,
      WavaVecaConformerForCTC,
      WavaVecaConformerForPreTraining,
      WavaVecaConformerForSequenceClassification,
      WavaVecaConformerForXVector,
      WavaVecaConformerModel,
      WavaVecaConformerPreTrainedModel,
  )

else:
 import sys

 SCREAMING_SNAKE_CASE_						:					Optional[int]			   =       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






