code: def __init__(self):
      super().__init__()
      self.conv1 = GCSConv(32, activation="relu")
      self.conv2 = GCSConv(32, activation="relu")
      self.conv3 = GCSConv(32, activation="relu")
      self.global_pool = GlobalAvgPool()
      self.dense = Dense(data.n_labels, activation="softmax")
  
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 1 to create a new Net object from inherited base classes: Model with example: obj = Net()