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.Beta(a, b, validate_args=True)
      pdf = dist.prob(x)
      self.assertAllClose([1.0] * 5, self.evaluate(pdf))
      self.assertEqual((5,), pdf.shape)
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
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