code: def testPdfXProper(self):
      alpha = [[1.0, 2, 3]]
      dist = dirichlet_lib.Dirichlet(alpha, validate_args=True)
      self.evaluate(dist.prob([0.1, 0.3, 0.6]))
      self.evaluate(dist.prob([0.2, 0.3, 0.5]))
      # Either condition can trigger.
      with self.assertRaisesOpError("samples must be positive"):
          self.evaluate(dist.prob([-1.0, 1.5, 0.5]))
      with self.assertRaisesOpError("samples must be positive"):
          self.evaluate(dist.prob([0.0, 0.1, 0.9]))
      with self.assertRaisesOpError(
          "sample last-dimension must sum to `1`"
      ):
          self.evaluate(dist.prob([0.1, 0.2, 0.8]))
  
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 4 for calling the DirichletTest obj's underlying member method code with example usage: obj.testPdfXProper() without return types