code: def run_with_continue(cl_args):
      run_args = RunConfiguration.default_run_cli(cl_args=cl_args)
      if not run_args.force_overwrite and (
          os.path.exists(os.path.join(run_args.output_dir, "done_file"))
          or os.path.exists(
              os.path.join(run_args.output_dir, "val_metrics.json")
          )
      ):
          print("Already Done")
          return
      elif run_args.save_checkpoint_every_steps and os.path.exists(
          os.path.join(run_args.output_dir, "checkpoint.p")
      ):
          print("Resuming")
          resume(os.path.join(run_args.output_dir, "checkpoint.p"))
      else:
          print("Running from start")
          run_loop(args=run_args)
  
imports: import os
  import torch
  import jiant.proj.main.modeling.model_setup
  import jiant.proj.main.runner
  import jiant.proj.main.components.container_setup
  import jiant.proj.main.metarunner
  import jiant.proj.main.components.evaluate
  import jiant.shared.initialization
  import jiant.shared.distributed
  import jiant.shared.model_setup
  import jiant.utils.python.io
  import jiant.utils.zconf
label_desc: Use image node_id 5 for calling a global function with example usage: run_with_continue(cl_args) without return types