code: def testSample(self):
      alpha = [1.0, 2]
      dirichlet = dirichlet_lib.Dirichlet(alpha)
      n = constant_op.constant(100000)
      samples = dirichlet.sample(n)
      sample_values = self.evaluate(samples)
      self.assertEqual(sample_values.shape, (100000, 2))
      self.assertTrue(np.all(sample_values > 0.0))
      if not stats:
          return
      self.assertLess(
          stats.kstest(
              # Beta is a univariate distribution.
              sample_values[:, 0],
              stats.beta(a=1.0, b=2.0).cdf,
          )[0],
          0.01,
      )
  
imports: import importlib
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.distributions import dirichlet
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 20 for calling the DirichletTest obj's underlying member method code with example usage: obj.testSample() without return types