class_docstr: Apply SpecAugment to a Spectrogram. For more info, check the original paper at:
  https://arxiv.org/abs/1904.08779
  
  Args:
      freq_mask_param (`int`): Frequency Mask Parameter (F in the paper)
      time_mask_param (ìnt`): Time Mask Parameter (T in the paper)
      n_freq_masks (`int`): Number of frequency masks to apply (mF in the paper). By default is 1.
      n_time_masks (`int`): Number of time masks to apply (mT in the paper). By default is 1.
      mask_value (`float`): Value of the applied masks. By default is 0.
      data_format (`str`): specifies the data format of batch input/output
      **kwargs: Keyword args for the parent keras layer (e.g., `name`)
  
  Example:
      ::
  
          input_shape = (2048, 1)  # mono signal
  
          # We compute the Mel Spectrogram of the input signal
          melgram = kapre.composed.get_melspectrogram_layer(input_shape=input_shape,
                                                n_fft=1024,
                                                return_decibel=True,
                                                n_mels=256,
                                                input_data_format='channels_last',
                                                output_data_format='channels_last')
  
  
          # Now we define the SpecAugment layer. It will apply 5 masks in the frequency axis,
          # 3 masks in the time axis. The frequency mask param is 5 and the time mask param
          # is 10.
          spec_augment = SpecAugment(freq_mask_param=5,
                                     time_mask_param=10,
                                     n_freq_masks=5,
                                     n_time_masks=3)
  
          model = Sequential()
          model.add(melgram)
  
          # Add the spec_augment layer for augmentation
          model.add(spec_augment)
      ::
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code: def get_config(self):
      config = super(SpecAugment, self).get_config()
      config.update(
          {
              "freq_mask_param": self.freq_mask_param,
              "time_mask_param": self.time_mask_param,
              "n_freq_masks": self.n_freq_masks,
              "n_time_masks": self.n_time_masks,
              "mask_value": self.mask_value,
              "data_format": self.data_format,
          }
      )
      return config
  
file_path: kapre/kapre/augmentation.py
imports: import tensorflow
  from tensorflow.keras.layers import Layer
  from tensorflow.keras import backend
  from .None import backend
  from .backend import _CH_FIRST_STR, _CH_LAST_STR, _CH_DEFAULT_STR
  import numpy
label_desc: Use image node_id 6 for calling the SpecAugment obj's underlying member method code with example usage: obj.get_config() and returns: config