code: def test_log_prior_for_uniform_prior() -> None:
      """
      If we assign a Uniform prior to a parameter, we should not expect the value of the prior density
      to change with the parameter value, even if it has a transform associated with it.
      """
  
      uniform_prior = Uniform(low=np.float64(0), high=np.float64(100))
      param = gpflow.Parameter(
          1.0,
          transform=gpflow.utilities.positive(),
          prior=uniform_prior,
      )
      low_value = param.log_prior_density().numpy()
      param.assign(10.0)
      high_value = param.log_prior_density().numpy()
  
      assert np.isclose(low_value, high_value)
  
imports: from typing import Any, Tuple, Type
  import numpy
  import pytest
  import tensorflow
  import tensorflow_probability
  from tensorflow_probability.python.bijectors import Exp
  from tensorflow_probability.python.distributions import Uniform
  import gpflow
  from gpflow.base import AnyNDArray, PriorOn
  from gpflow.config import set_default_float
  from gpflow.utilities import to_default_float
label_desc: Use image node_id 3 for calling a global function with example usage: test_log_prior_for_uniform_prior() without return types