class_docstr: A Wrapper to shield user from Optuna specific configurations and API      Later may support other HPO search engines.
class_docstr_tok: ["A","Wrapper","to","shield","user","from","Optuna","specific","configurations","and","API","Later","may","support","other","HPO","search","engines","."]
docstr: Generate the param config from a trial's sampled param set.
docstr_tok: ["Generate","the","param","config","from","a","trial","'s","sampled","param","set","."]
code: def gen_config(trial, automl_obj):
      """Generate the param config from a trial's sampled param set."""
      configspace = automl_obj.cs
      config = OptunaBackend.get_hpo_config(trial, configspace)
      other_kwargs = OptunaBackend.get_other_args(
          automl_obj.kwargs, automl_obj.kwspaces
      )
      config.update(other_kwargs)
      return config
  
file_path: BigDL/python/nano/src/bigdl/nano/deps/automl/optuna_backend.py
imports: from bigdl.nano.automl.hpo.backend import PrunerType, SamplerType
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.automl.hpo.space import SimpleSpace, NestedSpace, AutoObject
  from bigdl.nano.automl.hpo.space import AutoObject, Space, SingleParam, _get_hp_prefix
  import optuna
label_desc: Use image node_id 7 for calling the OptunaBackend obj's underlying member method code with example usage: obj.gen_config(trial, automl_obj) and returns: config