






import math
from decimal import Decimal, getcontext







def 	SCREAMING_SNAKE_CASE							(      __lowerCAmelCase = 400_0000    )				->			int:

     try:
          UpperCamelCase__    :     Tuple        =						int(__lowerCAmelCase    )
     except (TypeError, ValueError):
          raise TypeError("Parameter n must be int or castable to int."    )
     if n <= 0:
          raise ValueError("Parameter n must be greater than or equal to one."    )
     UpperCamelCase__    :     Dict        =						100
     UpperCamelCase__    :     Dict        =						(Decimal(5    ) ** Decimal(0.5    ) + 1) / Decimal(2    )

     UpperCamelCase__    :     Dict        =						(math.floor(math.log(n * (phi + 2)      ,					__lowerCAmelCase    ) - 1    ) // 3) * 3 + 2
     UpperCamelCase__    :     Tuple        =						Decimal(round(phi ** Decimal(index + 1    )    )    ) / (phi + 2)
     UpperCamelCase__    :     Union[str, Any]        =						num // 2
     return int(__lowerCAmelCase    )


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







import numpy as np  # noqa: E402

from ...configuration_utils import ConfigMixin, register_to_config
from ...schedulers.scheduling_utils import SchedulerMixin


try:
 import librosa  # noqa: E402

 lowerCamelCase			:							List[str]       =True
 lowerCamelCase			:							Dict       =''''''
except Exception as e:
 lowerCamelCase			:							str       =False
 lowerCamelCase			:							List[Any]       =(
     F"""Cannot import librosa because {e}. Make sure to correctly install librosa to be able to install it."""
 )


from PIL import Image  # noqa: E402





class     __a						(					A__ ,     A__ ):
 _lowerCAmelCase : Optional[Any] 				=				'''mel_config.json'''







 @register_to_config
 def __init__(	self      :     Any							,     SCREAMING_SNAKE_CASE      :     int = 2_56							,     SCREAMING_SNAKE_CASE      :     int = 2_56							,     SCREAMING_SNAKE_CASE      :     int = 2_20_50							,     SCREAMING_SNAKE_CASE      :     int = 20_48							,     SCREAMING_SNAKE_CASE      :     int = 5_12							,     SCREAMING_SNAKE_CASE      :     int = 80							,     SCREAMING_SNAKE_CASE      :     int = 32							,     ):


      '''simple docstring'''






      UpperCamelCase__    :     str        =						hop_length
      UpperCamelCase__    :     Optional[Any]        =						sample_rate
      UpperCamelCase__    :     Dict        =						n_fft
      UpperCamelCase__    :     str        =						top_db
      UpperCamelCase__    :     Optional[Any]        =						n_iter
      self.set_resolution(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE		)
      UpperCamelCase__    :     str        =						None

      if not _librosa_can_be_imported:
           raise ValueError(_import_error		)







 def       __lowercase      (	self      :     Tuple							,     SCREAMING_SNAKE_CASE      :     int							,     SCREAMING_SNAKE_CASE      :     int		):


      '''simple docstring'''






      UpperCamelCase__    :     Dict        =						x_res
      UpperCamelCase__    :     Dict        =						y_res
      UpperCamelCase__    :     Dict        =						self.y_res
      UpperCamelCase__    :     Any        =						self.x_res * self.hop_length - 1







 def       __lowercase      (	self      :     str							,     SCREAMING_SNAKE_CASE      :     str = None							,     SCREAMING_SNAKE_CASE      :     np.ndarray = None		):


      '''simple docstring'''






      if audio_file is not None:
           UpperCamelCase__       ,  UpperCamelCase__    :     int        =						librosa.load(SCREAMING_SNAKE_CASE							,     mono=SCREAMING_SNAKE_CASE							,     sr=self.sr		)
      else:
           UpperCamelCase__    :     List[Any]        =						raw_audio

      # Pad with silence if necessary.
      if len(self.audio		) < self.x_res * self.hop_length:
           UpperCamelCase__    :     List[Any]        =						np.concatenate([self.audio, np.zeros((self.x_res * self.hop_length - len(self.audio		),)		)]		)







 def       __lowercase      (	self      :     List[Any]		):


      '''simple docstring'''






      return len(self.audio		) // self.slice_size







 def       __lowercase      (	self      :     int							,     SCREAMING_SNAKE_CASE      :     int = 0		):


      '''simple docstring'''






      return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]







 def       __lowercase      (	self      :     Tuple		):


      '''simple docstring'''






      return self.sr







 def       __lowercase      (	self      :     Union[str, Any]							,     SCREAMING_SNAKE_CASE      :     int		):


      '''simple docstring'''






      UpperCamelCase__    :     Optional[int]        =						librosa.feature.melspectrogram(
          y=self.get_audio_slice(SCREAMING_SNAKE_CASE		)							,     sr=self.sr							,     n_fft=self.n_fft							,     hop_length=self.hop_length							,     n_mels=self.n_mels		)
      UpperCamelCase__    :     Tuple        =						librosa.power_to_db(SCREAMING_SNAKE_CASE							,     ref=np.max							,     top_db=self.top_db		)
      UpperCamelCase__    :     Optional[Any]        =						(((log_S + self.top_db) * 2_55 / self.top_db).clip(0							,     2_55		) + 0.5).astype(np.uinta		)
      UpperCamelCase__    :     Optional[Any]        =						Image.fromarray(SCREAMING_SNAKE_CASE		)
      return image







 def       __lowercase      (	self      :     List[Any]							,     SCREAMING_SNAKE_CASE      :     Image.Image		):


      '''simple docstring'''






      UpperCamelCase__    :     Optional[Any]        =						np.frombuffer(image.tobytes()							,     dtype="uint8"		).reshape((image.height, image.width)		)
      UpperCamelCase__    :     str        =						bytedata.astype("float"		) * self.top_db / 2_55 - self.top_db
      UpperCamelCase__    :     Any        =						librosa.db_to_power(SCREAMING_SNAKE_CASE		)
      UpperCamelCase__    :     Tuple        =						librosa.feature.inverse.mel_to_audio(
          SCREAMING_SNAKE_CASE							,     sr=self.sr							,     n_fft=self.n_fft							,     hop_length=self.hop_length							,     n_iter=self.n_iter		)
      return audio