docstr: Tests that the task runs when only a train dataset is specified.
code: def test_train_only_task(self):
      """
      Tests that the task runs when only a train dataset is specified.
      """
      test_config = get_fast_test_task_config()
  
      # delete the test dataset from the config
      del test_config["dataset"]["test"]
  
      task = build_task(test_config).set_hooks(
          [LossLrMeterLoggingHook()]
      )
      task.prepare()
  
      # verify the the task can still be trained
      trainer = LocalTrainer()
      trainer.train(task)
  
imports: import copy
  import itertools
  import shutil
  import tempfile
  import unittest
  import torch
  import torch.nn
  from classy_vision.dataset import build_dataset
  from classy_vision.generic.distributed_util import is_distributed_training_run
  from classy_vision.generic.util import get_checkpoint_dict, get_torch_version
  from classy_vision.hooks import CheckpointHook, LossLrMeterLoggingHook
  from classy_vision.losses import build_loss, ClassyLoss, register_loss
  from classy_vision.models import build_model, ClassyModel
  from classy_vision.optim import build_optimizer, SGD
  from classy_vision.tasks import build_task, ClassificationTask
  from classy_vision.trainer import LocalTrainer
  from test.generic.config_utils import get_fast_test_task_config, get_test_task_config
  from test.generic.utils import compare_model_state, compare_samples, compare_states, LimitedPhaseTrainer
label_desc: Use image node_id 15 for calling the TestClassificationTask obj's underlying member method code with example usage: obj.test_train_only_task() without return types