code: def test_half_cauchy_prior_batch_log_prob(self, cuda=False):
      device = torch.device("cuda") if cuda else torch.device("cpu")
      prior = HalfCauchyPrior(0.1)
      dist = HalfCauchy(0.1)
      t = torch.ones(2, device=device)
      self.assertTrue(torch.equal(prior.log_prob(t), dist.log_prob(t)))
      t = torch.ones(2, 2, device=device)
      self.assertTrue(torch.equal(prior.log_prob(t), dist.log_prob(t)))
  
      scale = torch.tensor([0.1, 1.0], device=device)
      prior = HalfCauchyPrior(scale)
      dist = HalfCauchy(scale)
      t = torch.ones(2, device=device)
      self.assertTrue(torch.equal(prior.log_prob(t), dist.log_prob(t)))
      t = torch.ones(2, 2, device=device)
      self.assertTrue(torch.equal(prior.log_prob(t), dist.log_prob(t)))
      with self.assertRaises(ValueError):
          prior.log_prob(torch.ones(3, device=device))
      with self.assertRaises(ValueError):
          prior.log_prob(torch.ones(2, 3, device=device))
  
file_path: gpytorch/test/priors/test_half_cauchy_prior.py
imports: import unittest
  import torch
  from torch.distributions import HalfCauchy
  from gpytorch.priors import HalfCauchyPrior
  from gpytorch.test.utils import least_used_cuda_device
label_desc: Use image node_id 7 for calling the TestHalfCauchyPrior obj's underlying member method code with example usage: obj.test_half_cauchy_prior_batch_log_prob(cuda) without return types