code: def dense_block(
      tensor, n_filters, n_layers=2, activation=layers.ReLU(), seed=None
  ):
      initializer = tf.keras.initializers.GlorotUniform(seed=seed)
      for _ in range(n_layers):
          tensor = layers.Dense(
              n_filters,
              activation=activation,
              kernel_initializer=initializer,
          )(tensor)
      return tensor
  
label_desc: Use image node_id 1 for calling a global function with example usage: dense_block(tensor, n_filters, n_layers, activation, seed) and returns: tensor