

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 					__lowerCamelCase							(      __snake_case    ,				__snake_case      ):
      lowerCamelCase_      : Tuple  			=   'mel_config.json'







      @register_to_config
      def __init__(	self				,    lowerCamelCase = 256				,    lowerCamelCase = 256				,    lowerCamelCase = 22050				,    lowerCamelCase = 2048				,    lowerCamelCase = 512				,    lowerCamelCase = 80				,    lowerCamelCase = 32				,    )		->			Any:
        snake_case_					= hop_length
        snake_case_					= sample_rate
        snake_case_					= n_fft
        snake_case_					= top_db
        snake_case_					= n_iter
        self.set_resolution(lowerCamelCase				,    lowerCamelCase  )
        snake_case_					= None

        if not _librosa_can_be_imported:
          raise ValueError(_import_error  )







      def       lowerCAmelCase_       (	self				,    lowerCamelCase				,    lowerCamelCase  )		->			int:
        snake_case_					= x_res
        snake_case_					= y_res
        snake_case_					= self.y_res
        snake_case_					= self.x_res * self.hop_length - 1







      def       lowerCAmelCase_       (	self				,    lowerCamelCase = None				,    lowerCamelCase = None  )		->			Optional[Any]:
        if audio_file is not None:
          snake_case_					= librosa.load(lowerCamelCase				,    mono=lowerCamelCase				,    sr=self.sr  )
        else:
          snake_case_					= raw_audio

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







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







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







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







      def       lowerCAmelCase_       (	self				,    lowerCamelCase  )		->			Image.Image:
        snake_case_					= 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  )
        snake_case_					= librosa.power_to_db(lowerCamelCase				,    ref=np.max				,    top_db=self.top_db  )
        snake_case_					= (((log_S + self.top_db) * 255 / self.top_db).clip(0				,    255  ) + 0.5).astype(np.uinta  )
        snake_case_					= Image.fromarray(lowerCamelCase  )
        return image







      def       lowerCAmelCase_       (	self				,    lowerCamelCase  )		->			np.ndarray:
        snake_case_					= np.frombuffer(image.tobytes()				,    dtype="""uint8"""  ).reshape((image.height, image.width)  )
        snake_case_					= bytedata.astype("""float"""  ) * self.top_db / 255 - self.top_db
        snake_case_					= librosa.db_to_power(lowerCamelCase  )
        snake_case_					= 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







class 					_A						:



   '''simple docstring'''






   def __init__(	self	:					Any					, lowerCamelCase	:					int						)->	None:
          snake_case__					:	Optional[int]          =					value
          snake_case__					:	Node | None          =					None
          snake_case__					:	Node | None          =					None







class 					_A						:



   '''simple docstring'''






   _lowercase    						= 42




   def __init__(	self	:					str						)->	None:
          snake_case__					:	int          =					0




   def   __lowerCAmelCase						(	self	:					Tuple					, lowerCamelCase	:					Node | None					, lowerCamelCase	:					int						)->	None:
          if node is None:
                 return

          if path_sum == self.target:
                 self.paths += 1

          if node.left:
                 self.depth_first_search(node.left					, path_sum + node.left.value						)
          if node.right:
                 self.depth_first_search(node.right					, path_sum + node.right.value						)




   def   __lowerCAmelCase						(	self	:					Tuple					, lowerCamelCase	:					Node | None					, lowerCamelCase	:					int | None = None						)->	int:
          if node is None:
                 return 0
          if target is not None:
                 snake_case__					:	Dict          =					target

          self.depth_first_search(lowerCamelCase					, node.value						)
          self.path_sum(node.left						)
          self.path_sum(node.right						)

          return self.paths


if __name__ == "__main__":
     import doctest

     doctest.testmod()




