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 generate_parameters(self):
      self.cur_param_id += 1
      if self.core_type == "tuner":
          self.cur_param = self.core.generate_parameters(
              self.cur_param_id - 1
          )
          return self.cur_param_id - 1, self.cur_param
  
      elif self.core_type == "advisor":
          self.cur_param = self.core._get_one_trial_job()
          hyperparams = self.cur_param["parameters"].copy()
          # hyperparams.pop('TRIAL_BUDGET')
          return self.cur_param["parameter_id"], hyperparams
  
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 4 for calling the NNITuner obj's underlying member method code with example usage: obj.generate_parameters() and returns: unknown,  self, self,  hyperparams