code: def model():
      inp = keras.Input(shape=(10,))
      x = Dense(10, name="dense1")(inp)
      y = Dense(10, name="dense2")(inp)
      model = keras.Model(inp, [x, y])
      return model
  
file_path: hls4ml/test/pytest/test_multiout_network.py
imports: from pathlib import Path
  import numpy
  import pytest
  from keras.layers import Dense
  from tensorflow import keras
  from hls4ml.converters import convert_from_keras_model
label_desc: Use image node_id 1 for calling a global function with example usage: model() and returns: model