






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

				UpperCamelCase__						:      str								=					True
				UpperCamelCase__						:      int								=					""""""
except Exception as e:
				UpperCamelCase__						:      Optional[int]								=					False
				UpperCamelCase__						:      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 				lowerCamelCase_     (	a_ ,						a_     ):
							SCREAMING_SNAKE_CASE_						     =			'mel_config.json'
							@register_to_config
							def __init__(						self		:					List[str]							,__lowerCamelCase		:					int = 2_56							,__lowerCamelCase		:					int = 2_56							,__lowerCamelCase		:					int = 2_20_50							,__lowerCamelCase		:					int = 20_48							,__lowerCamelCase		:					int = 5_12							,__lowerCamelCase		:					int = 80							,__lowerCamelCase		:					int = 32							,):





								'''simple docstring'''



								a		=			hop_length
								a		=			sample_rate
								a		=			n_fft
								a		=			top_db
								a		=			n_iter
								self.set_resolution(__lowerCamelCase							,__lowerCamelCase					)
								a		=			None

								if not _librosa_can_be_imported:
									raise ValueError(_import_error					)
							def  SCREAMING_SNAKE_CASE_ (						self		:					Optional[Any]							,__lowerCamelCase		:					int							,__lowerCamelCase		:					int					):





								'''simple docstring'''



								a		=			x_res
								a		=			y_res
								a		=			self.y_res
								a		=			self.x_res * self.hop_length - 1
							def  SCREAMING_SNAKE_CASE_ (						self		:					Tuple							,__lowerCamelCase		:					str = None							,__lowerCamelCase		:					np.ndarray = None					):





								'''simple docstring'''



								if audio_file is not None:
									a	, a		=			librosa.load(__lowerCamelCase							,mono=__lowerCamelCase							,sr=self.sr					)
								else:
									a		=			raw_audio

								# Pad with silence if necessary.
								if len(self.audio					) < self.x_res * self.hop_length:
									a		=			np.concatenate([self.audio, np.zeros((self.x_res * self.hop_length - len(self.audio					),)					)]					)
							def  SCREAMING_SNAKE_CASE_ (						self		:					int					):





								'''simple docstring'''



								return len(self.audio					) // self.slice_size
							def  SCREAMING_SNAKE_CASE_ (						self		:					int							,__lowerCamelCase		:					int = 0					):





								'''simple docstring'''



								return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]
							def  SCREAMING_SNAKE_CASE_ (						self		:					Optional[Any]					):





								'''simple docstring'''



								return self.sr
							def  SCREAMING_SNAKE_CASE_ (						self		:					Dict							,__lowerCamelCase		:					int					):





								'''simple docstring'''



								a		=			librosa.feature.melspectrogram(
								    y=self.get_audio_slice(__lowerCamelCase					)							,sr=self.sr							,n_fft=self.n_fft							,hop_length=self.hop_length							,n_mels=self.n_mels					)
								a		=			librosa.power_to_db(__lowerCamelCase							,ref=np.max							,top_db=self.top_db					)
								a		=			(((log_S + self.top_db) * 2_55 / self.top_db).clip(0							,2_55					) + 0.5).astype(np.uinta					)
								a		=			Image.fromarray(__lowerCamelCase					)
								return image




							def  SCREAMING_SNAKE_CASE_ (						self		:					Tuple							,__lowerCamelCase		:					Image.Image					):





								'''simple docstring'''



								a		=			np.frombuffer(image.tobytes()							,dtype='''uint8'''					).reshape((image.height, image.width)					)
								a		=			bytedata.astype('''float'''					) * self.top_db / 2_55 - self.top_db
								a		=			librosa.db_to_power(__lowerCamelCase					)
								a		=			librosa.feature.inverse.mel_to_audio(
								    __lowerCamelCase							,sr=self.sr							,n_fft=self.n_fft							,hop_length=self.hop_length							,n_iter=self.n_iter					)
								return audio













UpperCamelCase__						:      Dict								=					10**8





def   SCREAMING_SNAKE_CASE__						(   snake_case_  )   ->  bool:


	"""simple docstring"""



	if n % 1_0 == 0:
		return False
	a		=			str(snake_case_  )
	return s == s[::-1]





def   SCREAMING_SNAKE_CASE__						(   )   ->  int:


	"""simple docstring"""



	a		=			set()
	a		=			1
	a		=			5
	while sum_squares < LIMIT:
		a		=			first_square + 1
		while sum_squares < LIMIT:
			if is_palindrome(snake_case_  ):
				answer.add(snake_case_  )
			last_square += 1
			sum_squares += last_square**2
		first_square += 1
		a		=			first_square**2 + (first_square + 1) ** 2

	return sum(snake_case_  )


if __name__ == "__main__":
				print(solution())





