code: def __init__(
      self, placeholders, input_dim, hidden1, weight_decay, **kwargs
  ):
      super(GCN, self).__init__(**kwargs)
  
      self.inputs = placeholders["features"]
      self.hidden1 = hidden1
      self.weight_decay = weight_decay
      self.input_dim = input_dim
      # self.input_dim = self.inputs.get_shape().as_list()[1]  # To be supported in future Tensorflow versions
      self.output_dim = placeholders["labels"].get_shape().as_list()[1]
      self.placeholders = placeholders
  
      self.optimizer = tf.train.AdamOptimizer(learning_rate=0.01)
  
      self.build()
  
imports: from .layers import *
  from .metrics import *
label_desc: Use image node_id 1 to create a new GCN object from inherited base classes: Model with example: obj = GCN(placeholders, input_dim, hidden1, weight_decay)