code: def get_compiled_model():
      # Make a simple 2-layer densely-connected neural network.
      inputs = keras.Input(shape=(784,))
      x = keras.layers.Dense(256, activation="relu")(inputs)
      x = keras.layers.Dense(256, activation="relu")(x)
      outputs = keras.layers.Dense(10)(x)
      model = keras.Model(inputs, outputs)
      model.compile(
          optimizer=keras.optimizers.Adam(),
          loss=keras.losses.SparseCategoricalCrossentropy(
              from_logits=True
          ),
          metrics=[keras.metrics.SparseCategoricalAccuracy()],
      )
      return model
  
imports: import os
  import tensorflow
  import keras
label_desc: Use image node_id 1 for calling a global function with example usage: get_compiled_model() and returns: model