code: def __init__(self, filters, kernel_size, activation, **kwargs):
      super(ConvBNBlock, self).__init__(**kwargs)
      self.convolution1d = keras.layers.Conv1D(
          filters, kernel_size, padding="same", name="convolution1d"
      )
      self.batch_normalization = keras.layers.BatchNormalization(
          axis=2,
          momentum=0.90,
          epsilon=1e-5,
          name="batch_normalization",
      )
      self.dropout = keras.layers.Dropout(rate=0.5, name="dropout")
      self.activation = keras.layers.Activation(
          activation, name="activation"
      )
  
imports: import tensorflow
  from tensorflow import keras
  from TTS.tts.tf.utils.tf_utils import shape_list
  from TTS.tts.tf.layers.common_layers import Prenet, Attention
label_desc: Use image node_id 1 to create a new ConvBNBlock object from inherited base classes: keras.layers with example: obj = ConvBNBlock(filters, kernel_size, activation)