code: def __init__(self, n_hidden):
      super(Discriminator, self).__init__()
      uinit = tf.keras.initializers.RandomUniform(
          -1.0 / math.sqrt(n_hidden), 1.0 / math.sqrt(n_hidden)
      )
      self.weight = tf.Variable(
          initial_value=uinit(
              shape=(n_hidden, n_hidden), dtype="float32"
          ),
          trainable=True,
      )
  
imports: import math
  import numpy
  import tensorflow
  from gcn import GCN
  from tensorflow.keras import layers
label_desc: Use image node_id 1 to create a new Discriminator object from inherited base classes: layers with example: obj = Discriminator(n_hidden)