docstr: Update random state of :attr:`model_init_params` according to :attr:`current_seed`
docstr_tok: ["Update","random","state","of",":","attr",":","`","model_init_params","`","according","to",":","attr",":","`","current_seed","`"]
code: def _update_model_params(self):
      """Update random state of :attr:`model_init_params` according to :attr:`current_seed`"""
      # TODO: Add this to some workflow in Experiment class. For now it is never used, unless the subclass decides to...
      # `model_init_params` initialized to all algorithm hyperparameters - Works even if 'random_state' not explicitly given
      try:
          if "random_state" in self.model_init_params:
              self.model_init_params["random_state"] = self.current_seed
          elif "seed" in self.model_init_params:
              self.model_init_params["seed"] = self.current_seed
          else:
              G.debug(
                  "WARNING: Model has no random_state/seed parameter to update"
              )
              # FLAG: HIGH PRIORITY BELOW
              # TODO: BELOW IS NOT THE CASE IF MODEL IS NN - SETTING THE GLOBAL RANDOM SEED DOES SOMETHING
              # TODO: If this is logged, there is no reason to execute multiple-run-averaging, so don't
              # TODO: ... Either 1) Set `runs` = 1 (this would mess with the environment key), or...
              # TODO: ... 2) Set the results of all subsequent runs to the results of the first run (this could be difficult)
              # FLAG: HIGH PRIORITY ABOVE
      except Exception as _ex:
          G.log(
              "WARNING: Failed to update model's random_state     {}".format(
                  _ex.__repr__()
              )
          )
  
imports: from hyperparameter_hunter.algorithm_handlers import identify_algorithm, identify_algorithm_hyperparameters
  from hyperparameter_hunter.data import TrainDataset, OOFDataset, HoldoutDataset, TestDataset
  from hyperparameter_hunter.experiment_core import ExperimentMeta
  from hyperparameter_hunter.feature_engineering import FeatureEngineer
  from hyperparameter_hunter.i_o.exceptions import EnvironmentInactiveError, EnvironmentInvalidError, RepeatedExperimentError
  from hyperparameter_hunter.i_o.recorders import RecorderList
  from hyperparameter_hunter.keys.makers import HyperparameterKeyMaker
  from hyperparameter_hunter.metrics import ScoringMixIn, get_formatted_target_metric
  from hyperparameter_hunter.models import model_selector
  from hyperparameter_hunter.settings import G
  from hyperparameter_hunter.utils.file_utils import RetryMakeDirs
  from abc import abstractmethod
  from copy import deepcopy
  from inspect import isclass
  import numpy
  import pandas
  import random
  import shutil
  from sys import exc_info
  from uuid import uuid4
  import warnings
  import sklearn.utils
label_desc: Use image node_id 18 for calling the BaseExperiment obj's underlying member method code with example usage: obj._update_model_params() without return types