code: def report_bad_trial(objective=1e10, name="objective", data=None):
      """Report a bad trial with large objective to Oríon.
  
      This is especially useful if some parameter values lead to exceptions such as out of memory.
      Reporting a large objective from such trials will push algorithms towards valid
      configurations.
  
      .. warning::
  
         To be called only once in order to report a final evaluation of a particular trial.
  
      .. warning::
  
         Oríon is only minimizing. Make sure to report a metric that you seek to minimize.
  
      .. note::
  
         In case that user's script is not running in a orion's context,
         this function will act as a Python `print` function.
  
      Parameters
      ----------
      objective: float
          Objective the return to Oríon for the current trial. The default objective is 1e10.
          This may not be valid for some metrics and this value should be overridden accordingly. In
          the case of error rates for instance, the value should be 1.0.
      name: str, optional
          Name of the objective. Default is 'objective'.
      data: list of dict, optional
          A list of dictionary representing the results in the form
          dict(name=result_name, type='statistic', value=0). The types supported are
          'contraint', 'gradient' and 'statistic'.
  
      """
      if data is None:
          data = []
      report_results(
          [dict(name=name, type="objective", value=objective)] + data
      )
  
imports: import os
  import sys
  from orion.core import config
label_desc: Use image node_id 3 for calling a global function with example usage: report_bad_trial(objective, name, data) without return types