code: def test_get_gaussian_likelihood_with_gamma_prior(self):
      for batch_shape in (None, torch.Size([2])):
          likelihood = get_gaussian_likelihood_with_gamma_prior(
              batch_shape=batch_shape
          )
          self.assertIsInstance(likelihood, GaussianLikelihood)
          expected_shape = (batch_shape or torch.Size([])) + (1,)
          self.assertEqual(likelihood.raw_noise.shape, expected_shape)
          prior = likelihood.noise_covar.noise_prior
          self.assertIsInstance(prior, GammaPrior)
          self.assertAllClose(prior.concentration.item(), 1.1)
          self.assertAllClose(prior.rate.item(), 0.05)
          constraint = likelihood.noise_covar.raw_noise_constraint
          self.assertIsInstance(constraint, GreaterThan)
          self.assertAllClose(
              constraint.lower_bound.item(), MIN_INFERRED_NOISE_LEVEL
          )
          self.assertIsNone(constraint._transform)
          self.assertAllClose(constraint.initial_value.item(), 2.0)
  
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 2 for calling the TestGPyTorchModules obj's underlying member method code with example usage: obj.test_get_gaussian_likelihood_with_gamma_prior() without return types