





'''simple docstring'''







from __future__ import annotations

import random
from collections.abc import Iterable
from typing import Any, Generic, TypeVar

snake_case_  :							Dict            =	TypeVar("T", bound=bool)


class        __a   (Generic[T]  ):

							def __init__(				self				:  Optional[int]							,  __magic_name__				:  T )       ->							None:







													"""simple docstring"""
													UpperCAmelCase_      :   T      =	value
													UpperCAmelCase_      :   RandomizedHeapNode[T] | None      =	None
													UpperCAmelCase_      :   RandomizedHeapNode[T] | None      =	None

							@property
							def      UpperCAmelCase__						(				self				:  List[str] )       ->							T:







													"""simple docstring"""
													return self._value



							@staticmethod
							def      UpperCAmelCase__						(				__magic_name__				:  RandomizedHeapNode[T] | None							,  __magic_name__				:  RandomizedHeapNode[T] | None )       ->							RandomizedHeapNode[T] | None:







													"""simple docstring"""
													if not roota:
																			return roota

													if not roota:
																			return roota

													if roota.value > roota.value:
																			UpperCAmelCase_    ,							UpperCAmelCase_      :   Dict      =	roota, roota

													if random.choice([True, False] ):
																			UpperCAmelCase_    ,							UpperCAmelCase_      :   Tuple      =	roota.right, roota.left

													UpperCAmelCase_      :   Optional[Any]      =	RandomizedHeapNode.merge(roota.left							,  __magic_name__ )

													return roota





class        __a   (Generic[T]  ):

							def __init__(				self				:  Dict							,  __magic_name__				:  Iterable[T] | None = () )       ->							None:







													"""simple docstring"""
													UpperCAmelCase_      :   RandomizedHeapNode[T] | None      =	None

													if data:
																			for item in data:
																									self.insert(__magic_name__ )

							def      UpperCAmelCase__						(				self				:  Optional[Any]							,  __magic_name__				:  T )       ->							None:







													"""simple docstring"""
													UpperCAmelCase_      :   Optional[Any]      =	RandomizedHeapNode.merge(self._root							,  RandomizedHeapNode(__magic_name__ ) )

							def      UpperCAmelCase__						(				self				:  List[Any] )       ->							T | None:







													"""simple docstring"""
													UpperCAmelCase_      :   List[str]      =	self.top()

													if self._root is None:
																			return None

													UpperCAmelCase_      :   Tuple      =	RandomizedHeapNode.merge(self._root.left							,  self._root.right )

													return result

							def      UpperCAmelCase__						(				self				:  Dict )       ->							T:







													"""simple docstring"""
													if not self._root:
																			raise IndexError('''Can\'t get top element for the empty heap.''' )
													return self._root.value

							def      UpperCAmelCase__						(				self				:  Optional[Any] )       ->							None:







													"""simple docstring"""
													UpperCAmelCase_      :   Dict      =	None

							def      UpperCAmelCase__						(				self				:  int )       ->							list[Any]:







													"""simple docstring"""
													UpperCAmelCase_      :   Tuple      =	[]
													while self:
																			result.append(self.pop() )

													return result



							def __bool__(				self				:  List[Any] )       ->							bool:







													"""simple docstring"""
													return self._root is not None


if __name__ == "__main__":
					import doctest

					doctest.testmod()













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						= True
						__lowerCamelCase						= ''
except Exception as e:
						__lowerCamelCase						= False
						__lowerCamelCase						= (
						    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      UpperCamelCase_							(				UpperCamelCase ,       UpperCamelCase       ):
						lowercase									=  '''mel_config.json'''




						@register_to_config
						def __init__(    self		,	lowercase = 256		,	lowercase = 256		,	lowercase = 22_050		,	lowercase = 2_048		,	lowercase = 512		,	lowercase = 80		,	lowercase = 32		,	)			->						Optional[Any]:
													_a  :    Tuple			=						hop_length
													_a  :    Dict			=						sample_rate
													_a  :    Dict			=						n_fft
													_a  :    List[str]			=						top_db
													_a  :    Optional[int]			=						n_iter
													self.set_resolution(lowercase		,	lowercase       )
													_a  :    Optional[int]			=						None

													if not _librosa_can_be_imported:
																				raise ValueError(_import_error       )




						def      snake_case__(    self		,	lowercase		,	lowercase       )			->						Any:
													_a  :    Any			=						x_res
													_a  :    Optional[Any]			=						y_res
													_a  :    List[Any]			=						self.y_res
													_a  :    Tuple			=						self.x_res * self.hop_length - 1




						def      snake_case__(    self		,	lowercase = None		,	lowercase = None       )			->						Union[str, Any]:
													if audio_file is not None:
																				_a		,					_a  :    str			=						librosa.load(lowercase		,	mono=lowercase		,	sr=self.sr       )
													else:
																				_a  :    Any			=						raw_audio

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




						def      snake_case__(    self       )			->						int:
													return len(self.audio       ) // self.slice_size




						def      snake_case__(    self		,	lowercase = 0       )			->						np.ndarray:
													return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]




						def      snake_case__(    self       )			->						int:
													return self.sr




						def      snake_case__(    self		,	lowercase       )			->						Image.Image:
													_a  :    int			=						librosa.feature.melspectrogram(
													    y=self.get_audio_slice(lowercase       )		,	sr=self.sr		,	n_fft=self.n_fft		,	hop_length=self.hop_length		,	n_mels=self.n_mels       )
													_a  :    List[str]			=						librosa.power_to_db(lowercase		,	ref=np.max		,	top_db=self.top_db       )
													_a  :    List[str]			=						(((log_S + self.top_db) * 255 / self.top_db).clip(0		,	255       ) + 0.5).astype(np.uinta       )
													_a  :    Any			=						Image.fromarray(lowercase       )
													return image







						def      snake_case__(    self		,	lowercase       )			->						np.ndarray:
													_a  :    Any			=						np.frombuffer(image.tobytes()		,	dtype='''uint8'''       ).reshape((image.height, image.width)       )
													_a  :    Any			=						bytedata.astype('''float'''       ) * self.top_db / 255 - self.top_db
													_a  :    Dict			=						librosa.db_to_power(lowercase       )
													_a  :    List[str]			=						librosa.feature.inverse.mel_to_audio(
													    lowercase		,	sr=self.sr		,	n_fft=self.n_fft		,	hop_length=self.hop_length		,	n_iter=self.n_iter       )
													return audio