code: def testDeterministicGammaKL(self):
      batch_size = 2
      a_loc = np.array([0.5] * batch_size, dtype=np.float32)
      b_concentration = np.array([3.2] * batch_size, dtype=np.float32)
      b_rate = np.array([4.1] * batch_size, dtype=np.float32)
  
      a = det.Deterministic(loc=a_loc, validate_args=True)
      b = gamma.Gamma(concentration=b_concentration, rate=b_rate)
  
      expected_kl = -b.log_prob(a_loc)
      actual_kl = kullback_leibler.kl_divergence(a, b)
      expected_kl_, actual_kl_ = self.evaluate([expected_kl, actual_kl])
      self.assertAllEqual(expected_kl_, actual_kl_)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 21 for calling the DeterministicTest obj's underlying member method code with example usage: obj.testDeterministicGammaKL() without return types