code: def keras_model():
      def get_model():
          # Create a simple model.
          inputs = keras.Input(shape=(32,))
          outputs = keras.layers.Dense(1)(inputs)
          model = keras.Model(inputs, outputs)
          model.compile(optimizer="adam", loss="mean_squared_error")
          return model
  
      model = get_model()
  
      # Train the model.
      test_input = np.random.random((128, 32))
      test_target = np.random.random((128, 1))
      model.fit(test_input, test_target)
  
      return model
  
imports: import pytest
label_desc: Use image node_id 3 for calling a global function with example usage: keras_model() and returns: model, model