
from __future__ import annotations

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

_SCREAMING_SNAKE_CASE     :   Tuple							 =      TypeVar('T', bound=bool)







class 			UpperCamelCase__		(     Generic[T] ):







	'''simple docstring'''





	def __init__(      self					,							UpperCamelCase__		):
					A__	:						T								=				value
					A__	:						RandomizedHeapNode[T] | None								=				None
					A__	:						RandomizedHeapNode[T] | None								=				None





	@property
	def 	__snake_case					(      self		):
					return self._value





	@staticmethod
	def 	__snake_case					(      UpperCamelCase__					,							UpperCamelCase__		):
					if not roota:
									return roota

					if not roota:
									return roota

					if roota.value > roota.value:
									A__							,				A__	:						Tuple								=				roota, roota

					if random.choice([True, False]		):
									A__							,				A__	:						Optional[Any]								=				roota.right, roota.left

					A__	:						Any								=				RandomizedHeapNode.merge(roota.left					,							UpperCamelCase__		)

					return roota







class 			UpperCamelCase__		(     Generic[T] ):







	'''simple docstring'''





	def __init__(      self					,							UpperCamelCase__ = ()		):
					A__	:						RandomizedHeapNode[T] | None								=				None

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





	def 	__snake_case					(      self					,							UpperCamelCase__		):
					A__	:						Tuple								=				RandomizedHeapNode.merge(self._root					,							RandomizedHeapNode(UpperCamelCase__		)		)





	def 	__snake_case					(      self		):
					A__	:						List[Any]								=				self.top()

					if self._root is None:
									return None

					A__	:						Dict								=				RandomizedHeapNode.merge(self._root.left					,							self._root.right		)

					return result





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





	def 	__snake_case					(      self		):
					A__	:						Union[str, Any]								=				None





	def 	__snake_case					(      self		):
					A__	:						Optional[Any]								=				[]
					while self:
									result.append(self.pop()		)

					return result





	def __bool__(      self		):
					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

					_SCREAMING_SNAKE_CASE     :   Tuple							 =      True
					_SCREAMING_SNAKE_CASE     :   List[Any]							 =      ''
except Exception as e:
					_SCREAMING_SNAKE_CASE     :   Optional[Any]							 =      False
					_SCREAMING_SNAKE_CASE     :   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 			UpperCamelCase__		(     SCREAMING_SNAKE_CASE_,      SCREAMING_SNAKE_CASE_ ):







	'''simple docstring'''
	_lowerCAmelCase											=					"mel_config.json"





	@register_to_config
	def __init__(      self					,							UpperCamelCase__ = 256					,							UpperCamelCase__ = 256					,							UpperCamelCase__ = 2_2050					,							UpperCamelCase__ = 2048					,							UpperCamelCase__ = 512					,							UpperCamelCase__ = 80					,							UpperCamelCase__ = 32					,							):
					A__	:						Any								=				hop_length
					A__	:						List[Any]								=				sample_rate
					A__	:						Union[str, Any]								=				n_fft
					A__	:						Optional[int]								=				top_db
					A__	:						Optional[Any]								=				n_iter
					self.set_resolution(UpperCamelCase__					,							UpperCamelCase__		)
					A__	:						str								=				None

					if not _librosa_can_be_imported:
									raise ValueError(_import_error		)





	def 	__snake_case					(      self					,							UpperCamelCase__					,							UpperCamelCase__		):
					A__	:						int								=				x_res
					A__	:						List[Any]								=				y_res
					A__	:						List[str]								=				self.y_res
					A__	:						int								=				self.x_res * self.hop_length - 1





	def 	__snake_case					(      self					,							UpperCamelCase__ = None					,							UpperCamelCase__ = None		):
					if audio_file is not None:
									A__							,				A__	:						Union[str, Any]								=				librosa.load(UpperCamelCase__					,							mono=UpperCamelCase__					,							sr=self.sr		)
					else:
									A__	:						Tuple								=				raw_audio

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





	def 	__snake_case					(      self		):
					return len(self.audio		) // self.slice_size





	def 	__snake_case					(      self					,							UpperCamelCase__ = 0		):
					return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]





	def 	__snake_case					(      self		):
					return self.sr





	def 	__snake_case					(      self					,							UpperCamelCase__		):
					A__	:						Optional[Any]								=				librosa.feature.melspectrogram(
					    y=self.get_audio_slice(UpperCamelCase__		)					,							sr=self.sr					,							n_fft=self.n_fft					,							hop_length=self.hop_length					,							n_mels=self.n_mels		)
					A__	:						str								=				librosa.power_to_db(UpperCamelCase__					,							ref=np.max					,							top_db=self.top_db		)
					A__	:						str								=				(((log_S + self.top_db) * 255 / self.top_db).clip(0					,							255		) + 0.5).astype(np.uinta		)
					A__	:						Dict								=				Image.fromarray(UpperCamelCase__		)
					return image





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