code: def testSampleGPU(self):
      # Debugging tip: --vmodule=implementation_selector=2,function_api_info=3
      # helps debug errors like: Skipping optimization due to error while loading
      # function libraries: Invalid argument: Functions
      # '__inference__binomial_cpu_1184' and '__inference__binomial_noncpu_2305'
      # both implement 'binomial_76a77701-978a-4299-ad23-ff0d5c7598cb' but their
      # signatures do not match.
      if not tf.test.is_gpu_available():
          self.skipTest("no GPU")
      with tf.device("GPU"):
          _, runtime = self.evaluate(
              binomial_lib._random_binomial(
                  shape=tf.constant([], dtype=tf.int32),
                  counts=tf.constant(10.0),
                  probs=tf.constant(0.5),
                  seed=test_util.test_seed(),
              )
          )
      self.assertEqual(
          implementation_selection._RUNTIME_DEFAULT, runtime
      )
  
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 2 for calling the BinomialSamplingTest obj's underlying member method code with example usage: obj.testSampleGPU() without return types