code: def testPdfXProper(self):
      a = [[1.0, 2, 3]]
      b = [[2.0, 4, 3]]
      dist = beta_lib.Beta(a, b, 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("sample must be positive"):
          self.evaluate(dist.prob([-1.0, 0.1, 0.5]))
      with self.assertRaisesOpError("sample must be positive"):
          self.evaluate(dist.prob([0.0, 0.1, 0.5]))
      with self.assertRaisesOpError("sample must be less than `1`"):
          self.evaluate(dist.prob([0.1, 0.2, 1.2]))
      with self.assertRaisesOpError("sample must be less than `1`"):
          self.evaluate(dist.prob([0.1, 0.2, 1.0]))
  
imports: import importlib
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.distributions import beta
  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 6 for calling the BetaTest obj's underlying member method code with example usage: obj.testPdfXProper() without return types