docstr: Checks that you get finite values given unconstrained samples.
  
  We check `unnormalized_log_prob` as well as the values of the sample
  transformations.
  
  Args:
    num_test_points: Number of test points.
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",".","Args",":","num_test_points",":","Number","of","test","points","."]
code: def testBasic(self, num_test_points):
      """Checks that you get finite values given unconstrained samples.
  
      We check `unnormalized_log_prob` as well as the values of the sample
      transformations.
  
      Args:
        num_test_points: Number of test points.
      """
      num_features = 5
      model = probit_regression.ProbitRegression(
          **_test_dataset(num_features, num_test_points)
      )
      self.validate_log_prob_and_transforms(
          model,
          sample_transformation_shapes=dict(
              identity=[num_features + 1],
              test_nll=[],
              per_example_test_nll=[num_test_points],
          ),
      )
  
file_path: probability/spinoffs/inference_gym/inference_gym/targets/probit_regression_test.py
imports: from absl.testing import parameterized
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from inference_gym.internal import test_util
  from inference_gym.targets import probit_regression
label_desc: Use image node_id 1 for calling the ProbitRegressionTest obj's underlying member method code with example usage: obj.testBasic(num_test_points) without return types