code: def test_clone_sequential_model():
      seq = Sequential()
      seq.add(Dense(8, input_shape=(3,)))
      seq.compile(optimizer="sgd", loss="mse")
  
      clone = clone_model(seq)
      clone.compile(optimizer="sgd", loss="mse")
  
      ins = np.random.random((4, 3))
      y_pred_seq = seq.predict_on_batch(ins)
      y_pred_clone = clone.predict_on_batch(ins)
      assert y_pred_seq.shape == y_pred_clone.shape
      assert_allclose(y_pred_seq, 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 1 for calling a global function with example usage: test_clone_sequential_model() without return types