code: def setup_method(self) -> None:
      # This training setup is not guaranteed to converge in general,
      # but has been tested with this random seed.  If changing this
      # random seed, verify the initial conditions converge.
      self.trial_seed = 17
      self.hparams = {
          "hidden_size": 2,
          "learning_rate": 0.5,
          "global_batch_size": 4,
          "lr_scheduler_step_mode": pytorch.LRScheduler.StepMode.MANUAL_STEP.value,
          "dataloader_type": "determined",
          "disable_dataset_reproducibility_checks": False,
      }
  
imports: import contextlib
  import importlib
  import io
  import os
  import pathlib
  import sys
  import typing
  from unittest import mock
  import numpy
  import pytest
  import torch
  from _pytest import monkeypatch
  from torch.distributed import launcher
  import determined
  from determined import pytorch
  from tests.experiment import pytorch_utils, utils
  from tests.experiment.fixtures import pytorch_onevar_model
label_desc: Use image node_id 1 for calling the TestPyTorchTrial obj's underlying member method code with example usage: obj.setup_method() without return types