



'''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

					snake_case_				:			Any						 =						True
					snake_case_				:			List[Any]						 =						''
except Exception as e:
					snake_case_				:			Any						 =						False
					snake_case_				:			str						 =						(
					    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 							lowercase__			(							lowercase		,      lowercase     ):
	lowercase__						       =    """mel_config.json"""





	@register_to_config
	def __init__(				self      :       Dict				,lowerCamelCase__      :       int = 256				,lowerCamelCase__      :       int = 256				,lowerCamelCase__      :       int = 22050				,lowerCamelCase__      :       int = 2048				,lowerCamelCase__      :       int = 512				,lowerCamelCase__      :       int = 80				,lowerCamelCase__      :       int = 32				,):







							'''simple docstring'''
							_UpperCamelCase      :	Union[str, Any]				       =     hop_length
							_UpperCamelCase      :	int				       =     sample_rate
							_UpperCamelCase      :	Any				       =     n_fft
							_UpperCamelCase      :	Dict				       =     top_db
							_UpperCamelCase      :	Optional[int]				       =     n_iter
							self.set_resolution(lowerCamelCase__				,lowerCamelCase__				)
							_UpperCamelCase      :	List[Any]				       =     None

							if not _librosa_can_be_imported:
													raise ValueError(_import_error				)





	def 			UpperCamelCase_						(				self      :       Any				,lowerCamelCase__      :       int				,lowerCamelCase__      :       int				):







							'''simple docstring'''
							_UpperCamelCase      :	Union[str, Any]				       =     x_res
							_UpperCamelCase      :	int				       =     y_res
							_UpperCamelCase      :	str				       =     self.y_res
							_UpperCamelCase      :	Tuple				       =     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:
													_UpperCamelCase       ,    _UpperCamelCase      :	List[str]				       =     librosa.load(lowerCamelCase__				,mono=lowerCamelCase__				,sr=self.sr				)
							else:
													_UpperCamelCase      :	int				       =     raw_audio

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





	def 			UpperCamelCase_						(				self      :       Optional[Any]				):







							'''simple docstring'''
							return len(self.audio				) // self.slice_size





	def 			UpperCamelCase_						(				self      :       Optional[Any]				,lowerCamelCase__      :       int = 0				):







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





	def 			UpperCamelCase_						(				self      :       List[str]				):







							'''simple docstring'''
							return self.sr





	def 			UpperCamelCase_						(				self      :       Tuple				,lowerCamelCase__      :       int				):







							'''simple docstring'''
							_UpperCamelCase      :	Optional[int]				       =     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				)
							_UpperCamelCase      :	Union[str, Any]				       =     librosa.power_to_db(lowerCamelCase__				,ref=np.max				,top_db=self.top_db				)
							_UpperCamelCase      :	Tuple				       =     (((log_S + self.top_db) * 255 / self.top_db).clip(0				,255				) + 0.5).astype(np.uinta				)
							_UpperCamelCase      :	Union[str, Any]				       =     Image.fromarray(lowerCamelCase__				)
							return image





	def 			UpperCamelCase_						(				self      :       Dict				,lowerCamelCase__      :       Image.Image				):







							'''simple docstring'''
							_UpperCamelCase      :	Optional[Any]				       =     np.frombuffer(image.tobytes()				,dtype='uint8'				).reshape((image.height, image.width)				)
							_UpperCamelCase      :	Tuple				       =     bytedata.astype('float'				) * self.top_db / 255 - self.top_db
							_UpperCamelCase      :	Union[str, Any]				       =     librosa.db_to_power(lowerCamelCase__				)
							_UpperCamelCase      :	Any				       =     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

from queue import Queue






class 							lowercase__			:





	def __init__(				self      :       int				):







							'''simple docstring'''
							_UpperCamelCase      :	dict[int, list[int]]				       =     {}





	def 			UpperCamelCase_						(				self      :       int				):







							'''simple docstring'''
							for i in self.vertices:
													print(lowerCamelCase__				,' : '				,' -> '.join([str(lowerCamelCase__				) for j in self.vertices[i]]				)				)





	def 			UpperCamelCase_						(				self      :       Optional[Any]				,lowerCamelCase__      :       int				,lowerCamelCase__      :       int				):







							'''simple docstring'''
							if from_vertex in self.vertices:
													self.vertices[from_vertex].append(lowerCamelCase__				)
							else:
													_UpperCamelCase      :	Any				       =     [to_vertex]





	def 			UpperCamelCase_						(				self      :       int				,lowerCamelCase__      :       int				):







							'''simple docstring'''
							_UpperCamelCase      :	Dict				       =     set()

							# create a first in first out queue to store all the vertices for BFS
							_UpperCamelCase      :	Queue				       =     Queue()

							# mark the source node as visited and enqueue it
							visited.add(lowerCamelCase__				)
							queue.put(lowerCamelCase__				)

							while not queue.empty():
													_UpperCamelCase      :	Optional[Any]				       =     queue.get()

													# loop through all adjacent vertex and enqueue it if not yet visited
													for adjacent_vertex in self.vertices[vertex]:
																			if adjacent_vertex not in visited:
																									queue.put(lowerCamelCase__				)
																									visited.add(lowerCamelCase__				)
							return visited


if __name__ == "__main__":
					from doctest import testmod

					testmod(verbose=True)

					snake_case_				:			int						 =						Graph()
					g.add_edge(0, 1)
					g.add_edge(0, 2)
					g.add_edge(1, 2)
					g.add_edge(2, 0)
					g.add_edge(2, 3)
					g.add_edge(3, 3)

					g.print_graph()
					# 0  :  1 -> 2
					# 1  :  2
					# 2  :  0 -> 3
					# 3  :  3

					assert sorted(g.bfs(2)) == [0, 1, 2, 3]


