docstr: Checks that you get finite values given unconstrained samples.
  
  We check `unnormalized_log_prob` as well as the values of the sample
  transformations.
docstr_tok: ["Checks","that","you","get","finite","values","given","unconstrained","samples",".","We","check","`","unnormalized_log_prob","`","as","well","as","the","values","of","the","sample","transformations","."]
code: def testSP500Small(self):
      """Checks that you get finite values given unconstrained samples.
  
      We check `unnormalized_log_prob` as well as the values of the sample
      transformations.
      """
      if BACKEND == "backend_jax":
          self.skipTest("Too slow.")
      model = (
          vectorized_stochastic_volatility.VectorizedStochasticVolatilitySP500Small()
      )
      self.validate_log_prob_and_transforms(
          model,
          sample_transformation_shapes=dict(
              identity={
                  "persistence_of_volatility": [],
                  "mean_log_volatility": [],
                  "white_noise_shock_scale": [],
                  "log_volatility": [100],
              }
          ),
          check_ground_truth_mean_standard_error=True,
          check_ground_truth_mean=True,
          check_ground_truth_standard_deviation=True,
      )
  
imports: import functools
  from absl import logging
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  import tensorflow_probability
  from tensorflow_probability.python.internal import test_util
  from inference_gym.internal import test_util
  from inference_gym.targets import vectorized_stochastic_volatility
  from tensorflow.python.util import nest
label_desc: Use image node_id 6 for calling the VectorizedStochasticVolatilityTest obj's underlying member method code with example usage: obj.testSP500Small() without return types