class_docstr: This abstract RepresentationGraph allows you to use Keras layers as a representation function by overriding the
  create_layers() method.
code: def connect_representation_graph(
      self, tf_features, n_components, n_features, node_name_ending
  ):
      layers = self.create_layers(
          n_features=n_features, n_components=n_components
      )
  
      weights = []
      last_layer = tf_features
  
      # Iterate through layers, connecting each one and extracting weights/biases
      for layer in layers:
          last_layer = layer(last_layer)
          if hasattr(layer, "weights"):
              weights.extend(layer.weights)
  
      return last_layer, weights
  
imports: import abc
  import tensorflow
label_desc: Use image node_id 1 for calling the AbstractKerasRepresentationGraph obj's underlying member method code with example usage: obj.connect_representation_graph(tf_features, n_components, n_features, node_name_ending) and returns: last_layer,  weights