code: def testSampleOnly(self, dist_name, data):
      def eligibility_filter(name):
          # We use this eligibility filter to focus the test's attention
          # on sub-distributions that are not already tested by the sample
          # and log_prob test.  However, we also include some relatively
          # widely used distributions to make sure that at least one legal
          # sub-distribution exists for every meta-distribution we may be
          # testing.
          return (
              name in NO_NANS_TEST_BLOCK_LIST
              or name in dhps.QUANTIZED_BASE_DISTS
          ) and name not in NANS_EVEN_IN_SAMPLE_LIST
  
      dist = data.draw(
          dhps.distributions(
              dist_name=dist_name,
              enable_vars=False,
              eligibility_filter=eligibility_filter,
          )
      )
      self.check_samples_not_nan(dist)
  
imports: import collections
  from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import numerics_testing
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math.psd_kernels import hypothesis_testlib
label_desc: Use image node_id 2 for calling the NoNansTest obj's underlying member method code with example usage: obj.testSampleOnly(dist_name, data) and returns: unknown