code: def test_load_saved_model(self):
      with tempfile.NamedTemporaryFile() as snapshot_file:
          train_data = tests_module.test_file("train_data_tiny.tsv")
          eval_data = tests_module.test_file("test_data_tiny.tsv")
          config = PyTextConfig(
              task=DocumentClassificationTask.Config(
                  data=Data.Config(
                      source=TSVDataSource.Config(
                          train_filename=train_data,
                          eval_filename=eval_data,
                          field_names=["label", "slots", "text"],
                      )
                  )
              ),
              version=LATEST_VERSION,
              save_snapshot_path=snapshot_file.name,
          )
          task = create_task(config.task)
          model = task.model
  
          save(
              config,
              model,
              meta=None,
              tensorizers=task.data.tensorizers,
          )
          task2, config2, training_state_none = load(snapshot_file.name)
          self.assertEqual(config.export, config2.export)
          self.assertEqual(config.export_list, config2.export_list)
          self.assertEqual(config.task, config2.task)
          self.assertEqual(config, config2)
          self.assertModulesEqual(model, task2.model)
          self.assertIsNone(training_state_none)
          model.eval()
          task2.model.eval()
  
          inputs = torch.LongTensor([[1, 2, 3]]), torch.LongTensor([3])
          self.assertEqual(
              model(*inputs).tolist(), task2.model(*inputs).tolist()
          )
  
imports: import itertools
  import tempfile
  import unittest
  import torch
  from pytext.common.constants import Stage
  from pytext.config import LATEST_VERSION, PyTextConfig
  from pytext.config.component import create_optimizer, create_scheduler
  from pytext.data import Data
  from pytext.data.sources.tsv import BlockShardedTSVDataSource, TSVDataSource
  from pytext.optimizer import Adam
  from pytext.optimizer.scheduler import Scheduler
  from pytext.task import create_task
  from pytext.task.serialize import get_latest_checkpoint_path, load, save
  from pytext.task.tasks import DocumentClassificationTask
  from pytext.trainers.training_state import TrainingState
  from pytext.utils import test
label_desc: Use image node_id 2 for calling the TaskLoadSaveTest obj's underlying member method code with example usage: obj.test_load_saved_model() without return types