code: def _test_tracin_identity_regression_setup(self, tmpdir: str):
      num_features = 7
      dataset = IdentityDataset(num_features)
      net = CoefficientNet()
  
      num_checkpoints = 5
  
      for i in range(num_checkpoints):
          net.fc1.weight.data = torch.rand((1, num_features)) * 100
          checkpoint_name = "-".join(["checkpoint-reg", str(i) + ".pt"])
          torch.save(
              net.state_dict(), os.path.join(tmpdir, checkpoint_name)
          )
  
      return dataset, net
  
file_path: captum/tests/influence/_core/test_tracin_regression.py
imports: import os
  import tempfile
  from typing import Callable, cast, Optional
  import torch
  import torch.nn
  from captum.influence._core.arnoldi_influence_function import ArnoldiInfluenceFunction
  from captum.influence._core.influence_function import NaiveInfluenceFunction
  from captum.influence._core.tracincp import TracInCP
  from captum.influence._core.tracincp_fast_rand_proj import TracInCPFast, TracInCPFastRandProj
  from parameterized import parameterized
  from tests.helpers.basic import assertTensorAlmostEqual, BaseTest
  from tests.influence._utils.common import _isSorted, _wrap_model_in_dataparallel, build_test_name_func, CoefficientNet, DataInfluenceConstructor, IdentityDataset, RangeDataset
label_desc: Use image node_id 4 for calling the TestTracInRegression obj's underlying member method code with example usage: obj._test_tracin_identity_regression_setup(tmpdir) and returns: dataset,  net