code: def test_get_data_loader(self):
      data_loader = get_data_loader(self.model)
      self.assertEqual(
          data_loader.batch_size, len(self.model.train_targets)
      )
  
      train_X, train_Y = next(iter(data_loader))
      self.assertTrue(self.model.train_inputs[0].equal(train_X))
      self.assertTrue(self.model.train_targets.equal(train_Y))
  
      _TensorDataset = MagicMock(return_value="foo")
      _DataLoader = MagicMock()
      with patch.multiple(
          model_utils,
          TensorDataset=_TensorDataset,
          DataLoader=_DataLoader,
      ):
          model_utils.get_data_loader(
              self.model, batch_size=2, shuffle=True
          )
          _DataLoader.assert_called_once_with(
              dataset="foo",
              batch_size=2,
              shuffle=True,
          )
  
imports: from __future__ import annotations
  import re
  import warnings
  from copy import deepcopy
  from string import ascii_lowercase
  from unittest.mock import MagicMock, patch
  import torch
  from botorch import settings
  from botorch.models import SingleTaskGP
  from botorch.optim.utils import get_data_loader, get_name_filter, get_parameters, get_parameters_and_bounds, model_utils, sample_all_priors
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.constraints import GreaterThan
  from gpytorch.kernels.matern_kernel import MaternKernel
  from gpytorch.kernels.scale_kernel import ScaleKernel
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.mlls.exact_marginal_log_likelihood import ExactMarginalLogLikelihood
  from gpytorch.priors import UniformPrior
  from gpytorch.priors.prior import Prior
  from gpytorch.priors.torch_priors import GammaPrior
label_desc: Use image node_id 2 for calling the TestGetDataLoader obj's underlying member method code with example usage: obj.test_get_data_loader() without return types