code: 
  
  
  
  
  
  
  from dataclasses import dataclass
  from typing import List, Optional, Union
  
  import numpy as np
  import PIL
  from PIL import Image
  
  from ...utils import is_torch_available, is_transformers_available
  
  
  if is_transformers_available() and is_torch_available():
   from .image_encoder import PaintByExampleImageEncoder
   from .pipeline_paint_by_example import PaintByExamplePipeline
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  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			:							List[str]       =True
   lowerCamelCase			:							Dict       =''''''
  except Exception as e:
   lowerCamelCase			:							str       =False
   lowerCamelCase			:							List[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     __a						(					A__ ,     A__ ):
   _lowerCAmelCase : Optional[Any] 				=				'''mel_config.json'''
  
  
  
  
  
  
  
   @register_to_config
   def __init__(	self      :     Any							,     SCREAMING_SNAKE_CASE      :     int = 2_56							,     SCREAMING_SNAKE_CASE      :     int = 2_56							,     SCREAMING_SNAKE_CASE      :     int = 2_20_50							,     SCREAMING_SNAKE_CASE      :     int = 20_48							,     SCREAMING_SNAKE_CASE      :     int = 5_12							,     SCREAMING_SNAKE_CASE      :     int = 80							,     SCREAMING_SNAKE_CASE      :     int = 32							,     ):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     str        =						hop_length
        UpperCamelCase__    :     Optional[Any]        =						sample_rate
        UpperCamelCase__    :     Dict        =						n_fft
        UpperCamelCase__    :     str        =						top_db
        UpperCamelCase__    :     Optional[Any]        =						n_iter
        self.set_resolution(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE		)
        UpperCamelCase__    :     str        =						None
  
        if not _librosa_can_be_imported:
             raise ValueError(_import_error		)
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Tuple							,     SCREAMING_SNAKE_CASE      :     int							,     SCREAMING_SNAKE_CASE      :     int		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     Dict        =						x_res
        UpperCamelCase__    :     Dict        =						y_res
        UpperCamelCase__    :     Dict        =						self.y_res
        UpperCamelCase__    :     Any        =						self.x_res * self.hop_length - 1
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     str							,     SCREAMING_SNAKE_CASE      :     str = None							,     SCREAMING_SNAKE_CASE      :     np.ndarray = None		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        if audio_file is not None:
             UpperCamelCase__       ,  UpperCamelCase__    :     int        =						librosa.load(SCREAMING_SNAKE_CASE							,     mono=SCREAMING_SNAKE_CASE							,     sr=self.sr		)
        else:
             UpperCamelCase__    :     List[Any]        =						raw_audio
  
        # Pad with silence if necessary.
        if len(self.audio		) < self.x_res * self.hop_length:
             UpperCamelCase__    :     List[Any]        =						np.concatenate([self.audio, np.zeros((self.x_res * self.hop_length - len(self.audio		),)		)]		)
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     List[Any]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        return len(self.audio		) // self.slice_size
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     int							,     SCREAMING_SNAKE_CASE      :     int = 0		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        return self.audio[self.slice_size * slice : self.slice_size * (slice + 1)]
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Tuple		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        return self.sr
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Union[str, Any]							,     SCREAMING_SNAKE_CASE      :     int		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     Optional[int]        =						librosa.feature.melspectrogram(
            y=self.get_audio_slice(SCREAMING_SNAKE_CASE		)							,     sr=self.sr							,     n_fft=self.n_fft							,     hop_length=self.hop_length							,     n_mels=self.n_mels		)
        UpperCamelCase__    :     Tuple        =						librosa.power_to_db(SCREAMING_SNAKE_CASE							,     ref=np.max							,     top_db=self.top_db		)
        UpperCamelCase__    :     Optional[Any]        =						(((log_S + self.top_db) * 2_55 / self.top_db).clip(0							,     2_55		) + 0.5).astype(np.uinta		)
        UpperCamelCase__    :     Optional[Any]        =						Image.fromarray(SCREAMING_SNAKE_CASE		)
        return image
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     List[Any]							,     SCREAMING_SNAKE_CASE      :     Image.Image		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     Optional[Any]        =						np.frombuffer(image.tobytes()							,     dtype="uint8"		).reshape((image.height, image.width)		)
        UpperCamelCase__    :     str        =						bytedata.astype("float"		) * self.top_db / 2_55 - self.top_db
        UpperCamelCase__    :     Any        =						librosa.db_to_power(SCREAMING_SNAKE_CASE		)
        UpperCamelCase__    :     Tuple        =						librosa.feature.inverse.mel_to_audio(
            SCREAMING_SNAKE_CASE							,     sr=self.sr							,     n_fft=self.n_fft							,     hop_length=self.hop_length							,     n_iter=self.n_iter		)
        return audio