code: def testGammaStd(self):
      concentration_v = np.array([1.0, 3.0, 2.5])
      rate_v = np.array([1.0, 4.0, 5.0])
      gamma = gamma_lib.Gamma(
          concentration=concentration_v, rate=rate_v, validate_args=True
      )
      gamma_lr = gamma_lib.Gamma(
          concentration=concentration_v,
          log_rate=np.log(rate_v),
          validate_args=True,
      )
      self.assertEqual(gamma.stddev().shape, (3,))
      expected_stddev = sp_stats.gamma.std(
          concentration_v, scale=1.0 / rate_v
      )
      self.assertAllClose(
          self.evaluate(gamma.stddev()), expected_stddev
      )
      self.assertAllClose(
          self.evaluate(gamma_lr.stddev()), expected_stddev
      )
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  from scipy import misc
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 15 for calling the GammaTest obj's underlying member method code with example usage: obj.testGammaStd() without return types