code: def test_variable_workload_size(self, tmp_path: pathlib.Path) -> None:
      tensorboard_path = tmp_path.joinpath("tensorboard")
  
      (
          trial,
          controller,
      ) = pytorch_utils.create_trial_and_trial_controller(
          trial_class=pytorch_onevar_model.OneVarTrial,
          hparams=self.hparams,
          trial_seed=self.trial_seed,
          max_batches=100,
          min_validation_batches=10,
          min_checkpoint_batches=sys.maxsize,
          tensorboard_path=tensorboard_path,
      )
  
      training_metrics = []
      total_steps, total_batches_processed = 10, 0
      for step_id in range(1, total_steps):
          num_batches = step_id
          train_steps, metrics = controller._train_with_boundaries(
              training_enumerator=enumerate(
                  controller.training_iterator
              ),
              train_boundaries=[
                  pytorch._TrainBoundary(
                      step_type=pytorch._TrainBoundaryType.TRAIN,
                      unit=pytorch.Batch(num_batches),
                  )
              ],
          )
          assert len(train_steps) == 1, "unexpected train step count"
          assert train_steps[
              0
          ].limit_reached, "train step did not reach expected limit"
          assert (
              len(metrics) == num_batches
          ), "did not run for expected num_batches"
          training_metrics.extend(metrics)
          total_batches_processed += num_batches
  
      assert total_batches_processed == sum(
          range(1, total_steps)
      ), "total batches did not match expected"
  
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 14 for calling the TestPyTorchTrial obj's underlying member method code with example usage: obj.test_variable_workload_size(tmp_path) without return types