code: def testPmfAndCdfBothZeroBatches(self):
      # Both zero-batches.  No broadcast
      p = 0.5
      counts = 1.0
      binom = binomial_lib.Binomial(
          total_count=1.0, probs=p, validate_args=True
      )
      pmf = binom.prob(counts)
      cdf = binom.cdf(counts)
      self.assertAllClose(0.5, self.evaluate(pmf))
      self.assertAllClose(
          stats.binom.cdf(counts, n=1, p=p), self.evaluate(cdf)
      )
      self.assertEqual((), pmf.shape)
      self.assertEqual((), cdf.shape)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 12 for calling the BinomialTest obj's underlying member method code with example usage: obj.testPmfAndCdfBothZeroBatches() without return types