code: def test_clone_graph_model():
      in1 = Input(shape=(2,))
      in2 = Input(shape=(3,))
      x = Dense(8)(Concatenate()([in1, in2]))
      graph = Model([in1, in2], x)
      graph.compile(optimizer="sgd", loss="mse")
  
      clone = clone_model(graph)
      clone.compile(optimizer="sgd", loss="mse")
  
      ins = [np.random.random((4, 2)), np.random.random((4, 3))]
      y_pred_graph = graph.predict_on_batch(ins)
      y_pred_clone = clone.predict_on_batch(ins)
      assert y_pred_graph.shape == y_pred_clone.shape
      assert_allclose(y_pred_graph, y_pred_clone)
  
file_path: keras-rl/tests/rl/test_util.py
imports: from __future__ import division
  import pytest
  import numpy
  from numpy.testing import assert_allclose
  from keras.models import Model, Sequential
  from keras.layers import Input, Dense, Concatenate
  from keras.optimizers import SGD
  import keras.backend
  from rl.util import clone_optimizer, clone_model, huber_loss, WhiteningNormalizer
label_desc: Use image node_id 2 for calling a global function with example usage: test_clone_graph_model() without return types