code: def call(self, inputs):
      x, a = inputs
      x = self.mask(x)
      x = self.conv1([x, a])
      x_pool, a_pool = self.pool([x, a])
      x_pool = self.conv2([x_pool, a_pool])
      output = self.global_pool(x_pool)
      output = self.dense1(output)
  
      return output
  
file_path: spektral/examples/graph_prediction/tud_mincut.py
imports: import numpy
  from tensorflow.keras.callbacks import EarlyStopping
  from tensorflow.keras.layers import Dense
  from tensorflow.keras.models import Model
  from tensorflow.keras.optimizers import Adam
  from spektral.data import BatchLoader
  from spektral.datasets import TUDataset
  from spektral.layers import GCSConv, GlobalSumPool, GraphMasking, MinCutPool
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