code: def testWeibullStd(self):
      concentration = np.array([1.3], dtype=self.dtype)
      scale = np.array([2.7], dtype=self.dtype)
  
      dist = weibull.Weibull(
          concentration=self.make_input(concentration),
          scale=self.make_input(scale),
          validate_args=True,
      )
  
      stddev = dist.stddev()
      self.assertAllClose(
          self.evaluate(stddev),
          stats.weibull_min.std(c=concentration, scale=scale),
          atol=1e-5,
          rtol=1e-5,
      )  # relaxed tol for fp32 in JAX
      self.assertEqual(
          self.evaluate(dist.batch_shape_tensor()), stddev.shape
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import weibull
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 9 for calling the _WeibullTest obj's underlying member method code with example usage: obj.testWeibullStd() without return types