code: def testExcessiveConcretizationInZeroArgPublicMethods(
      self, process_name, data
  ):
      tfp_hps.guitar_skip_if_matches(
          "VariationalGaussianProcess", process_name, "b/147770193"
      )
      # Check that standard statistics do not concretize variables/deferred
      # tensors more than the allowed amount.
      process = data.draw(
          stochastic_processes(process_name, enable_vars=True)
      )
      self.evaluate([var.initializer for var in process.variables])
  
      for stat in [
          "mean",
          "covariance",
          "stddev",
          "variance",
          "sample",
      ]:
          hp.note(
              "Testing excessive concretization in {}.{}".format(
                  process_name, stat
              )
          )
          try:
              with tfp_hps.assert_no_excessive_var_usage(
                  "method `{}` of `{}`".format(stat, process),
                  max_permissible=MAX_CONVERSIONS_BY_CLASS.get(
                      process_name, 1
                  ),
              ), kernel_hps.no_pd_errors():
                  getattr(process, stat)()
  
          except NotImplementedError:
              pass
  
imports: from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import six
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gaussian_process
  from tensorflow_probability.python.distributions import gaussian_process_regression_model
  from tensorflow_probability.python.distributions import student_t_process
  from tensorflow_probability.python.distributions import student_t_process_regression_model
  from tensorflow_probability.python.distributions import variational_gaussian_process
  from tensorflow_probability.python.experimental.distributions import marginal_fns
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  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 StochasticProcessParamsAreVarsTest obj's underlying member method code with example usage: obj.testExcessiveConcretizationInZeroArgPublicMethods(process_name, data) without return types