code: def test_sample_xla(self):
      self.skip_if_no_xla()
      if not tf.executing_eagerly():
          return  # jit_compile is eager-only
  
      df = np.random.rand(4, 3).astype(np.float32)
      nc = np.random.rand(4, 3).astype(np.float32)
  
      nc_chi2 = noncentral_chi2.NoncentralChi2(
          df=df, noncentrality=nc, validate_args=True
      )
  
      self.evaluate(
          tf.function(
              lambda: nc_chi2.sample(seed=test_util.test_seed()),
              jit_compile=True,
          )()
      )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow
  from tensorflow_probability.python.distributions import noncentral_chi2
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 2 for calling the NoncentralChi2SamplingTest obj's underlying member method code with example usage: obj.test_sample_xla() without return types