code: def test_lnprob_and_grad_array():
      prior = GammaPrior(a=0.5, scale=1 / 2, loc=0, seed=1)
      val = np.array([-1, -1])
  
      with pytest.raises(NotImplementedError):
          prior.get_log_probability(val)
  
      with pytest.raises(NotImplementedError):
          prior.get_gradient(val)
  
imports: from functools import partial
  import numpy
  import pytest
  import scipy.optimize
  from smac.constants import VERY_SMALL_NUMBER
  from smac.model.gaussian_process.priors import GammaPrior, HorseshoePrior, LogNormalPrior, SoftTopHatPrior, TophatPrior
label_desc: Use image node_id 12 for calling a global function with example usage: test_lnprob_and_grad_array() without return types