class_docstr: Function Caller for NN evaluations. 
class_docstr_tok: ["Function","Caller","for","NN","evaluations","."]
docstr: Fidelity cost function. 
docstr_tok: ["Fidelity","cost","function","."]
code: def _raw_fidel_cost(cls, raw_fidel):
      """Fidelity cost function."""
      # The first (and only) fidelity argument is the number of batch loops, and the cost
      # is linear in the number of loops. The multiplication by a scalar does not change
      # relative costs.
      return raw_fidel[0] / 100.0
  
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 4 for calling the NNFunctionCaller obj's underlying member method code with example usage: obj._raw_fidel_cost(cls, raw_fidel) and returns: unknown