code: def test_huber_loss():
      a = np.array([1.0, 1.5, 2.0, 4.0])
      b = np.array([1.5, 1.0, 4.0, 2.0])
      assert_allclose(
          K.eval(huber_loss(a, b, 1.0)),
          np.array([0.125, 0.125, 1.5, 1.5]),
      )
      assert_allclose(
          K.eval(huber_loss(a, b, 3.0)),
          np.array([0.125, 0.125, 2.0, 2.0]),
      )
      assert_allclose(
          K.eval(huber_loss(a, b, np.inf)),
          np.array([0.125, 0.125, 2.0, 2.0]),
      )
  
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 5 for calling a global function with example usage: test_huber_loss() without return types