code: def test_get_matern_kernel_with_gamma_prior(self):
      for batch_shape in (None, torch.Size([2])):
          kernel = get_matern_kernel_with_gamma_prior(
              ard_num_dims=2, batch_shape=batch_shape
          )
          self.assertIsInstance(kernel, ScaleKernel)
          self.assertEqual(
              kernel.batch_shape, batch_shape or torch.Size([])
          )
          prior = kernel.outputscale_prior
          self.assertIsInstance(prior, GammaPrior)
          self.assertAllClose(prior.concentration.item(), 2.0)
          self.assertAllClose(prior.rate.item(), 0.15)
          base_kernel = kernel.base_kernel
          self.assertIsInstance(base_kernel, MaternKernel)
          self.assertEqual(
              base_kernel.batch_shape, batch_shape or torch.Size([])
          )
          self.assertEqual(base_kernel.ard_num_dims, 2)
          prior = base_kernel.lengthscale_prior
          self.assertIsInstance(prior, GammaPrior)
          self.assertAllClose(prior.concentration.item(), 3.0)
          self.assertAllClose(prior.rate.item(), 6.0)
  
file_path: botorch/test/models/utils/test_gpytorch_modules.py
imports: import torch
  from botorch.models.utils.gpytorch_modules import get_gaussian_likelihood_with_gamma_prior, get_matern_kernel_with_gamma_prior, MIN_INFERRED_NOISE_LEVEL
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.constraints.constraints import GreaterThan
  from gpytorch.kernels.matern_kernel import MaternKernel
  from gpytorch.kernels.scale_kernel import ScaleKernel
  from gpytorch.likelihoods.gaussian_likelihood import GaussianLikelihood
  from gpytorch.priors.torch_priors import GammaPrior
label_desc: Use image node_id 1 for calling the TestGPyTorchModules obj's underlying member method code with example usage: obj.test_get_matern_kernel_with_gamma_prior() without return types