code: def testSampleExtremeValues(self):
      total_count = tf.constant(17.0, dtype=tf.float32)
      probs = tf.constant([0.0, 1.0], dtype=tf.float32)
      dist = binomial_lib.Binomial(
          total_count=total_count, probs=probs, validate_args=True
      )
      samples, expected_samples = self.evaluate(
          (dist.sample(seed=test_util.test_seed()), total_count * probs)
      )
      self.assertAllEqual(samples, expected_samples)
  
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 24 for calling the BinomialTest obj's underlying member method code with example usage: obj.testSampleExtremeValues() without return types