code: def _dict_hash(config, precision):
      flatconfig = flatten_dict(config)
      for param, value in flatconfig.items():
          if isinstance(value, float):
              flatconfig[param] = "{:.{digits}f}".format(
                  value, digits=precision
              )
  
      hashed = json.dumps(flatconfig, sort_keys=True, default=str)
      return hashed
  
imports: from collections import defaultdict
  import logging
  import pickle
  import json
  from typing import Dict, List, Optional, Tuple, Any, TYPE_CHECKING
  from ray.tune.result import DEFAULT_METRIC
  from ray.tune.search.sample import Domain, Float, Quantized, Uniform
  from ray.tune.search import UNRESOLVED_SEARCH_SPACE, UNDEFINED_METRIC_MODE, UNDEFINED_SEARCH_SPACE, Searcher
  from ray.tune.search.variant_generator import parse_spec_vars
  from ray.tune.utils.util import is_nan_or_inf, unflatten_dict
  from ray.tune.utils import flatten_dict
label_desc: Use image node_id 1 for calling a global function with example usage: _dict_hash(config, precision) and returns: hashed