code: def testPdfUniformZeroBatch(self):
      # This is equivalent to a uniform distribution
      a = 1.0
      b = 1.0
      x = np.array([0.1, 0.2, 0.3, 0.5, 0.8], dtype=np.float32)
      dist = beta_lib.Beta(a, b)
      pdf = dist.prob(x)
      self.assertAllClose([1.0] * 5, self.evaluate(pdf))
      self.assertEqual((5,), pdf.get_shape())
  
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 9 for calling the BetaTest obj's underlying member method code with example usage: obj.testPdfUniformZeroBatch() without return types