docstr: 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 testBasic(self):
      """Checks that you get finite values given unconstrained samples.
  
      We check `unnormalized_log_prob` as well as the values of the sample
      transformations.
      """
      model = log_gaussian_cox_process.LogGaussianCoxProcess(
          **_test_dataset()
      )
      self.validate_log_prob_and_transforms(
          model,
          sample_transformation_shapes=dict(
              identity={
                  "amplitude": [],
                  "length_scale": [],
                  "log_intensity": [10],
              },
          ),
      )
  
file_path: probability/spinoffs/inference_gym/inference_gym/targets/log_gaussian_cox_process_test.py
imports: 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 log_gaussian_cox_process
label_desc: Use image node_id 1 for calling the LogGaussianCoxProcessTest obj's underlying member method code with example usage: obj.testBasic() without return types