code: def test_gamma_prior_log_prob_log_transform(self, cuda=False):
      device = torch.device("cuda") if cuda else torch.device("cpu")
      concentration = torch.tensor(1.0, device=device)
      rate = torch.tensor(1.0, device=device)
      prior = GammaPrior(concentration, rate, transform=torch.exp)
      dist = Gamma(concentration, rate)
  
      t = torch.tensor(0.0, device=device)
      self.assertTrue(
          torch.equal(prior.log_prob(t), dist.log_prob(t.exp()))
      )
      t = torch.tensor([-1, 0.5], device=device)
      self.assertTrue(
          torch.equal(prior.log_prob(t), dist.log_prob(t.exp()))
      )
      t = torch.tensor([[-1, 0.5], [0.1, -2.0]], device=device)
      self.assertTrue(
          torch.equal(prior.log_prob(t), dist.log_prob(t.exp()))
      )
  
file_path: gpytorch/test/priors/test_gamma_prior.py
imports: import unittest
  import torch
  from torch.distributions import Gamma
  from gpytorch.priors import GammaPrior
  from gpytorch.test.utils import least_used_cuda_device
label_desc: Use image node_id 5 for calling the TestGammaPrior obj's underlying member method code with example usage: obj.test_gamma_prior_log_prob_log_transform(cuda) without return types