old_contents: """
      Augmenter that apply cropping operation to audio.
  """
  
  from nlpaug.augmenter.audio import AudioAugmenter
  import nlpaug.model.audio as nma
  from nlpaug.util import Action, WarningMessage
  
  
  class CropAug(AudioAugmenter):
      """
      :param int sampling_rate: Sampling rate of input audio. Mandatory if duration is provided.
      :param tuple zone: Assign a zone for augmentation. Default value is (0.2, 0.8) which means that no any
          augmentation will be applied in first 20% and last 20% of whole audio.
      :param float coverage: Portion of augmentation. Value should be between 0 and 1. If `0.1` is assigned, augment
          operation will be applied to target audio segment. For example, the audio duration is 60 seconds while
          zone and coverage are (0.2, 0.8) and 0.7 respectively. 42 seconds ((0.8-0.2)*0.7*60) audio will be
          augmented.
      :param int duration: Duration of augmentation (in second). Default value is None. If value is provided. `coverage`
          value will be ignored.
      :param str name: Name of this augmenter
  
      >>> import nlpaug.augmenter.audio as naa
      >>> aug = naa.CropAug(sampling_rate=44010)
      """
  
      def __init__(self, sampling_rate=None, zone=(0.2, 0.8), coverage=0.1, duration=None,
                   crop_range=(0.2, 0.8), crop_factor=2, name='Crop_Aug', verbose=0):
          super().__init__(
              action=Action.DELETE, name=name, device='cpu', verbose=verbose)
          self.model = self.get_model(sampling_rate, zone, coverage, duration)
  
          if crop_range != (0.2, 0.8):
              print(WarningMessage.DEPRECATED.format('crop_range', '0.0.12', 'zone'))
          if crop_factor != 2:
              print(WarningMessage.DEPRECATED.format('crop_factor', '0.0.12', 'temperature'))
  
      def delete(self, data):
          return self.model.manipulate(data)
  
      @classmethod
      def get_model(cls, sampling_rate, zone, coverage, duration):
          return nma.Crop(sampling_rate, zone=zone, coverage=coverage, duration=duration)
  
new_contents: """
      Augmenter that apply cropping operation to audio.
  """
  
  from nlpaug.augmenter.audio import AudioAugmenter
  import nlpaug.model.audio as nma
  from nlpaug.util import Action, WarningMessage
  
  
  class CropAug(AudioAugmenter):
      """
      :param int sampling_rate: Sampling rate of input audio. Mandatory if duration is provided.
      :param tuple zone: Assign a zone for augmentation. Default value is (0.2, 0.8) which means that no any
          augmentation will be applied in first 20% and last 20% of whole audio.
      :param float coverage: Portion of augmentation. Value should be between 0 and 1. If `0.1` is assigned, augment
          operation will be applied to target audio segment. For example, the audio duration is 60 seconds while
          zone and coverage are (0.2, 0.8) and 0.7 respectively. 25.2 seconds ((0.8-0.2)*0.7*60) audio will be
          augmented.
      :param int duration: Duration of augmentation (in second). Default value is None. If value is provided. `coverage`
          value will be ignored.
      :param str name: Name of this augmenter
  
      >>> import nlpaug.augmenter.audio as naa
      >>> aug = naa.CropAug(sampling_rate=44010)
      """
  
      def __init__(self, sampling_rate=None, zone=(0.2, 0.8), coverage=0.1, duration=None,
                   crop_range=(0.2, 0.8), crop_factor=2, name='Crop_Aug', verbose=0):
          super().__init__(
              action=Action.DELETE, name=name, device='cpu', verbose=verbose)
          self.model = self.get_model(sampling_rate, zone, coverage, duration)
  
          if crop_range != (0.2, 0.8):
              print(WarningMessage.DEPRECATED.format('crop_range', '0.0.12', 'zone'))
          if crop_factor != 2:
              print(WarningMessage.DEPRECATED.format('crop_factor', '0.0.12', 'temperature'))
  
      def delete(self, data):
          return self.model.manipulate(data)
  
      @classmethod
      def get_model(cls, sampling_rate, zone, coverage, duration):
          return nma.Crop(sampling_rate, zone=zone, coverage=coverage, duration=duration)
  
subject: Fix #134