code: def testSample(self):
      if not tf.test.is_gpu_available():
          self.skipTest("no GPU")
      with tf.device("GPU"):
          self.evaluate(
              exp_gamma_lib.random_exp_gamma(
                  shape=tf.constant([], dtype=tf.int32),
                  concentration=tf.constant(1.0),
                  seed=test_util.test_seed(),
              )
          )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import misc
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.distributions import exp_gamma
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 1 for calling the GammaSamplingTest obj's underlying member method code with example usage: obj.testSample() without return types