code: def testStd(self):
      concentration_v = np.array([1.0, 3.0, 2.5])
      rate_v = np.array([1.0, 4.0, 5.0])
      d = exp_gamma_lib.ExpGamma(
          concentration=concentration_v, rate=rate_v, validate_args=True
      )
      d_lr = exp_gamma_lib.ExpGamma(
          concentration=concentration_v,
          log_rate=np.log(rate_v),
          validate_args=True,
      )
      self.assertEqual(d.stddev().shape, (3,))
      expected_stddev = sp_stats.loggamma.std(
          concentration_v, loc=-np.log(rate_v)
      )
      self.assertAllClose(self.evaluate(d.stddev()), expected_stddev)
      self.assertAllClose(self.evaluate(d_lr.stddev()), expected_stddev)
  
imports: 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 exp_gamma
  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 test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 10 for calling the ExpGammaTest obj's underlying member method code with example usage: obj.testStd() without return types