class_docstr: NoneTrainer is a trainer that does not train a model, only runs evaluation.
class_docstr_tok: ["NoneTrainer","is","a","trainer","that","does","not","train","a","model",",","only","runs","evaluation","."]
code: def shutdown(self):
      pass
  
imports: import logging
  import os
  import time
  from typing import Callable, Dict, List, Optional, Union
  from torch.utils.tensorboard import SummaryWriter
  from ludwig.constants import MINIMUM_BATCH_SIZE, TEST, TRAINING, VALIDATION
  from ludwig.data.dataset.base import Dataset
  from ludwig.distributed.base import DistributedStrategy, LocalStrategy
  from ludwig.features.feature_utils import LudwigFeatureDict
  from ludwig.models.llm import LLM
  from ludwig.models.predictor import LlmFineTunePredictor, LlmPredictor
  from ludwig.modules.metric_modules import get_initial_validation_value
  from ludwig.schema.trainer import BaseTrainerConfig, FineTuneTrainerConfig, NoneTrainerConfig
  from ludwig.trainers.base import BaseTrainer
  from ludwig.trainers.registry import register_llm_ray_trainer, register_llm_trainer
  from ludwig.trainers.trainer import Trainer
  from ludwig.types import ModelConfigDict
  from ludwig.utils import time_utils
  from ludwig.utils.defaults import default_random_seed
  from ludwig.utils.metric_utils import TrainerMetric
  from ludwig.utils.metrics_printed_table import print_metrics_table
  from ludwig.utils.misc_utils import set_random_seed
  from ludwig.utils.torch_utils import get_torch_device
  from ludwig.utils.trainer_utils import append_metrics, get_new_progress_tracker, ProgressTracker
label_desc: Use image node_id 8 for calling the NoneTrainer obj's underlying member method code with example usage: obj.shutdown() without return types