code: def is_fast_enough(self, max_single_prediction_time):
      # dont need to check
      if max_single_prediction_time is None:
          return True
  
      # no iformation about prediction time
      if self._single_prediction_time is None:
          return True
  
      return self._single_prediction_time < max_single_prediction_time
  
imports: import copy
  import json
  import logging
  import operator
  import os
  import time
  import uuid
  import numpy
  import pandas
  from supervised.algorithms.algorithm import BaseAlgorithm
  from supervised.algorithms.registry import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, REGRESSION
  from supervised.exceptions import NotTrainedException
  from supervised.model_framework import ModelFramework
  from supervised.utils.additional_metrics import AdditionalMetrics
  from supervised.utils.config import LOG_LEVEL
  from supervised.utils.metric import Metric
  from supervised.utils.jsonencoder import MLJSONEncoder
  import matplotlib.pyplot
  from tabulate import tabulate
  from supervised.utils.learning_curves import LearningCurves
label_desc: Use image node_id 5 for calling the Ensemble obj's underlying member method code with example usage: obj.is_fast_enough(max_single_prediction_time) and returns: unknown, True, True