class_docstr: A specialized wrapper for the automlbenchmark framework.
  Abstracts the different behaviors of tuners and advisors into a tuner API. 
class_docstr_tok: ["A","specialized","wrapper","for","the","automlbenchmark","framework",".","Abstracts","the","different","behaviors","of","tuners","and","advisors","into","a","tuner","API","."]
code: def receive_trial_result(self, parameter_id, parameters, value):
      if self.core_type == "tuner":
          return self.core.receive_trial_result(
              parameter_id, parameters, value
          )
  
      elif self.core_type == "advisor":
          metric_report = {}
          metric_report["parameter_id"] = parameter_id
          metric_report["trial_job_id"] = self.cur_param_id
          metric_report["type"] = MetricType.FINAL
          metric_report["value"] = str(value)
          metric_report["sequence"] = self.cur_param_id
          return self.core.handle_report_metric_data(metric_report)
  
file_path: nni/examples/trials/benchmarking/automlbenchmark/nni/extensions/NNI/tuners.py
imports: import os
  import yaml
  import importlib
  import nni
  from nni.runtime.config import get_config_file
  from nni.utils import MetricType
  from nni.tuner import Tuner
  from nni.runtime.msg_dispatcher_base import MsgDispatcherBase
  from amlb.benchmark import TaskConfig
label_desc: Use image node_id 5 for calling the NNITuner obj's underlying member method code with example usage: obj.receive_trial_result(parameter_id, parameters, value) and returns: self, self