code: def should_save_model(self) -> bool:
      if self.save_every_steps == 0:
          return False
      return (
          self.train_state.global_steps + 1
      ) % self.save_every_steps == 0
  
imports: from dataclasses import dataclass
  from typing import Dict
  import torch.nn
  import jiant.proj.main.runner
  import jiant.proj.main.components.task_sampler
  from jiant.shared.runner import save_model_with_metadata, compare_steps_max_steps
  from jiant.utils.python.datastructures import ExtendedDataClassMixin
  from jiant.utils.python.functional import always_false
  from jiant.utils.torch_utils import copy_state_dict, CPU_DEVICE, get_model_for_saving
  from jiant.utils.zlog import BaseZLogger, PRINT_LOGGER
  from jiant.shared.metarunner import AbstractMetarunner
label_desc: Use image node_id 4 for calling the JiantMetarunner obj's underlying member method code with example usage: obj.should_save_model() and returns: unknown, False