code: def call(self, inputs):
      x, a, i = inputs
      x = self.conv1([x, a])
      x = self.conv2([x, a])
      x = self.conv3([x, a])
      output = self.global_pool([x, i])
      output = self.dense(output)
  
      return output
  
imports: import numpy
  import scipy.sparse
  import tensorflow
  from tensorflow.keras.layers import Dense
  from tensorflow.keras.losses import CategoricalCrossentropy
  from tensorflow.keras.metrics import categorical_accuracy
  from tensorflow.keras.models import Model
  from tensorflow.keras.optimizers import Adam
  from spektral.data import Dataset, DisjointLoader, Graph
  from spektral.layers import GCSConv, GlobalAvgPool
  from spektral.transforms.normalize_adj import NormalizeAdj
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.call(inputs) and returns: output