code: def test_draw_from_base_covar(self):
      # grab a posterior
      posterior = self.post_list[0][2]
  
      base_samples = torch.randn(4, 30, 1, device=self.device)
      base_mat = torch.randn(30, 30, device=self.device)
      sym_mat = base_mat.matmul(base_mat.t())
  
      # base, non-lt case
      res = posterior._draw_from_base_covar(sym_mat, base_samples)
      self.assertIsInstance(res, torch.Tensor)
  
      # too many samples works
      base_samples = torch.randn(4, 50, 1, device=self.device)
      res = posterior._draw_from_base_covar(sym_mat, base_samples)
      self.assertIsInstance(res, torch.Tensor)
  
      # too few samples fails
      base_samples = torch.randn(4, 10, 1, device=self.device)
      with self.assertRaises(RuntimeError):
          res = posterior._draw_from_base_covar(sym_mat, base_samples)
  
file_path: botorch/test/posteriors/test_multitask.py
imports: import numpy
  import torch
  from botorch.exceptions.errors import BotorchTensorDimensionError
  from botorch.models.multitask import KroneckerMultiTaskGP
  from botorch.posteriors.multitask import MultitaskGPPosterior
  from botorch.sampling.normal import IIDNormalSampler
  from botorch.utils.testing import BotorchTestCase
label_desc: Use image node_id 3 for calling the TestMultitaskGPPosterior obj's underlying member method code with example usage: obj.test_draw_from_base_covar() without return types