code: def test_get_frozen_and_tunable_parameter_names(self):
      model = torch.nn.Sequential(
          OrderedDict(
              [
                  ("conv", torch.nn.Conv1d(5, 5, 5)),
                  ("linear", torch.nn.Linear(5, 10)),
              ]
          )
      )
      named_parameters = dict(model.named_parameters())
      named_parameters["linear.weight"].requires_grad_(False)
      named_parameters["linear.bias"].requires_grad_(False)
      (
          frozen_parameter_names,
          tunable_parameter_names,
      ) = util.get_frozen_and_tunable_parameter_names(model)
      assert set(frozen_parameter_names) == {
          "linear.weight",
          "linear.bias",
      }
      assert set(tunable_parameter_names) == {
          "conv.weight",
          "conv.bias",
      }
  
imports: from datetime import timedelta
  import sys
  from collections import OrderedDict
  import pytest
  import torch
  from allennlp.common import util
  from allennlp.common.testing import AllenNlpTestCase
  from allennlp.common.util import push_python_path
label_desc: Use image node_id 7 for calling the TestCommonUtils obj's underlying member method code with example usage: obj.test_get_frozen_and_tunable_parameter_names() without return types