docstr: Checks that unconstrained parameters yield finite joint densities.
docstr_tok: ["Checks","that","unconstrained","parameters","yield","finite","joint","densities","."]
code: def testBasic(self, test_size):
      """Checks that unconstrained parameters yield finite joint densities."""
      num_counties = 3
      train_size = 20
      model = radon_contextual_effects.RadonContextualEffects(
          prior_scale=self.prior_scale,
          **_test_dataset(train_size, test_size, num_counties),
      )
      self.validate_log_prob_and_transforms(
          model,
          sample_transformation_shapes=dict(
              identity={
                  "county_effect_mean": [],
                  "county_effect_scale": [],
                  "county_effect": [num_counties],
                  "weight": [3],
                  "log_radon_scale": [],
              },
              test_nll=[],
              per_example_test_nll=[test_size],
          ),
      )
  
imports: import functools
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from inference_gym.internal import test_util
  from inference_gym.targets import radon_contextual_effects
label_desc: Use image node_id 1 for calling the _RadonContextualEffectsTest obj's underlying member method code with example usage: obj.testBasic(test_size) without return types