code: def testPmfAndCdfExtremeProbs(self):
      n = 5.0
      p = [0.0, 1.0]
      counts = [[0.0], [3.0], [5.0]]
      binom = binomial_lib.Binomial(
          total_count=n, probs=p, validate_args=True
      )
      self.assertAllClose(
          self.evaluate(binom.prob(counts)),
          [[1.0, 0.0], [0.0, 0.0], [0.0, 1.0]],
      )
      self.assertAllClose(
          self.evaluate(binom.cdf(counts)),
          [[1.0, 0.0], [1.0, 0.0], [1.0, 1.0]],
      )
  
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 11 for calling the BinomialTest obj's underlying member method code with example usage: obj.testPmfAndCdfExtremeProbs() without return types