code: def __init__(
      self,
      fallback_filename=None,
      exclude_matches=None,
      variable_transforms=None,
      save_dtype=None,
      restart_global_step=True,
      permit_uninitialized=None,
      add_tokens=None,
  ):
      self.variable_transforms = variable_transforms or []
      self.exclude_matches = exclude_matches
      self.variables = None
      self.save_dtype = save_dtype
      if fallback_filename is not None:
          self.set_fallback(fallback_filename)
      self.restart_global_step = restart_global_step
      self.permit_uninitialized = permit_uninitialized
      self.add_tokens = add_tokens
  
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 1 to create a new Saver object  with example: obj = Saver(fallback_filename, exclude_matches, variable_transforms, save_dtype, restart_global_step, permit_uninitialized, add_tokens)