class_docstr: Function Caller for NN evaluations. 
class_docstr_tok: ["Function","Caller","for","NN","evaluations","."]
docstr: Constructor for train params. 
docstr_tok: ["Constructor","for","train","params","."]
code: def __init__(
      self,
      config,
      train_params,
      descr="",
      debug_mode=False,
      reporter="silent",
  ):
      """Constructor for train params."""
      constructor_args = _get_cpfc_args_from_config(config)
      super(NNFunctionCaller, self).__init__(
          None,
          descr=descr,
          fidel_cost_func=self._fidel_cost,
          **constructor_args,
      )
      self.train_params = deepcopy(train_params)
      self.debug_mode = debug_mode
      self.reporter = get_reporter(reporter)
  
file_path: dragonfly/examples/nas/nn_function_caller.py
imports: from copy import deepcopy
  import numpy
  from time import sleep
  from dragonfly.exd.experiment_caller import CPFunctionCaller
  from dragonfly.exd.exd_core import EVAL_ERROR_CODE
  from dragonfly.utils.reporters import get_reporter
label_desc: Use image node_id 1 to create a new NNFunctionCaller object from inherited base classes: CPFunctionCaller with example: obj = NNFunctionCaller(config, train_params, descr, debug_mode, reporter)