code: def save(self, finetune_obj, path, mkdir=True):
      if self.variables is None:
          raise FinetuneError(
              "Cowardly refusing to save default model."
          )
      if self.exclude_matches is not None:
          variables = {
              k: v
              for k, v in self.variables.items()
              if self.exclude_matches not in k
          }
      else:
          variables = self.variables
  
      names, values = variables.keys(), variables.values()
      if isinstance(path, str):
          folder = os.path.dirname(path)
          os.makedirs(folder, exist_ok=True)
      if self.save_dtype is not None:
          LOGGER.info(
              "Saving with {} precision.".format(
                  self.save_dtype.__name__
              )
          )
          values = [a.astype(self.save_dtype) for a in values]
  
      var_names_reduced, vals_reduced = self.remove_unchanged(
          names, values, self.fallback
      )
      var_dict = dict(zip(var_names_reduced, vals_reduced))
      assert (
          len(vals_reduced) == len(var_names_reduced) == len(var_dict)
      )
      joblib.dump((var_dict, finetune_obj), path)
  
imports: import os
  from concurrent.futures import ThreadPoolExecutor
  import logging
  import sys
  import re
  import joblib
  import numpy
  import tensorflow
  from tensorflow.compat.v1.train import SessionRunHook
  from tensorflow_estimator.python.estimator.early_stopping import _StopOnPredicateHook
  from finetune.errors import FinetuneError
  from finetune.config import get_config
  from finetune.util.metrics import read_eval_metrics
label_desc: Use image node_id 6 for calling the Saver obj's underlying member method code with example usage: obj.save(finetune_obj, path, mkdir) without return types