"""simple docstring"""







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

						SCREAMING_SNAKE_CASE						=    True
						SCREAMING_SNAKE_CASE						=    ''
except Exception as e:
						SCREAMING_SNAKE_CASE						=    False
						SCREAMING_SNAKE_CASE						=    (
						    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      (__lowerCamelCase    ,				__lowerCamelCase  ):
				_snake_case  =	"mel_config.json"







				@register_to_config
				def __init__(			self     :							Optional[Any]      ,       lowerCamelCase_     :							int = 2_5_6      ,       lowerCamelCase_     :							int = 2_5_6      ,       lowerCamelCase_     :							int = 2_2_0_5_0      ,       lowerCamelCase_     :							int = 2_0_4_8      ,       lowerCamelCase_     :							int = 5_1_2      ,       lowerCamelCase_     :							int = 8_0      ,       lowerCamelCase_     :							int = 3_2      ,       ):

					"""simple docstring"""






					_lowercase			:     Tuple      					=				hop_length
					_lowercase			:     Union[str, Any]      					=				sample_rate
					_lowercase			:     str      					=				n_fft
					_lowercase			:     str      					=				top_db
					_lowercase			:     int      					=				n_iter
					self.set_resolution(lowerCamelCase_      ,       lowerCamelCase_    )
					_lowercase			:     str      					=				None

					if not _librosa_can_be_imported:
						raise ValueError(_import_error    )







				def 				__UpperCAmelCase       (			self     :							Any      ,       lowerCamelCase_     :							int      ,       lowerCamelCase_     :							int    ):

					"""simple docstring"""






					_lowercase			:     str      					=				x_res
					_lowercase			:     str      					=				y_res
					_lowercase			:     Optional[int]      					=				self.y_res
					_lowercase			:     Optional[Any]      					=				self.x_res * self.hop_length - 1







				def 				__UpperCAmelCase       (			self     :							List[Any]      ,       lowerCamelCase_     :							str = None      ,       lowerCamelCase_     :							np.ndarray = None    ):

					"""simple docstring"""






					if audio_file is not None:
						_lowercase					,   _lowercase			:     Any      					=				librosa.load(lowerCamelCase_      ,       mono=lowerCamelCase_      ,       sr=self.sr    )
					else:
						_lowercase			:     int      					=				raw_audio

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







				def 				__UpperCAmelCase       (			self     :							List[Any]    ):

					"""simple docstring"""






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







				def 				__UpperCAmelCase       (			self     :							Optional[int]      ,       lowerCamelCase_     :							int = 0    ):

					"""simple docstring"""






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







				def 				__UpperCAmelCase       (			self     :							Dict    ):

					"""simple docstring"""






					return self.sr







				def 				__UpperCAmelCase       (			self     :							Union[str, Any]      ,       lowerCamelCase_     :							int    ):

					"""simple docstring"""






					_lowercase			:     Optional[Any]      					=				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    )
					_lowercase			:     str      					=				librosa.power_to_db(lowerCamelCase_      ,       ref=np.max      ,       top_db=self.top_db    )
					_lowercase			:     List[Any]      					=				(((log_S + self.top_db) * 2_5_5 / self.top_db).clip(0      ,       2_5_5    ) + 0.5).astype(np.uinta    )
					_lowercase			:     str      					=				Image.fromarray(lowerCamelCase_    )
					return image







				def 				__UpperCAmelCase       (			self     :							Tuple      ,       lowerCamelCase_     :							Image.Image    ):

					"""simple docstring"""






					_lowercase			:     Any      					=				np.frombuffer(image.tobytes()      ,       dtype='uint8'    ).reshape((image.height, image.width)    )
					_lowercase			:     Tuple      					=				bytedata.astype('float'    ) * self.top_db / 2_5_5 - self.top_db
					_lowercase			:     Optional[int]      					=				librosa.db_to_power(lowerCamelCase_    )
					_lowercase			:     Optional[int]      					=				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




"""simple docstring"""







from __future__ import annotations

import math
import random


def   __lowerCAmelCase(		__UpperCAmelCase  ,__UpperCAmelCase  ,__UpperCAmelCase      ):






	"""simple docstring"""





	_lowercase			:     Optional[int]      					=				d * e - 1
	_lowercase			:     int      					=				0
	_lowercase			:     Union[str, Any]      					=				0
	while p == 0:
		_lowercase			:     int      					=				random.randint(2  ,n - 1      )
		_lowercase			:     str      					=				k
		while True:
			if t % 2 == 0:
				_lowercase			:     List[Any]      					=				t // 2
				_lowercase			:     int      					=				(g**t) % n
				_lowercase			:     Tuple      					=				math.gcd(x - 1  ,__UpperCAmelCase      )
				if x > 1 and y > 1:
					_lowercase			:     List[str]      					=				y
					_lowercase			:     str      					=				n // y
					break  # find the correct factors
			else:
				break  # t is not divisible by 2, break and choose another g
	return sorted([p, q]      )


if __name__ == "__main__":
						import doctest

						doctest.testmod()



