class_docstr: A class for performing operations on the AutoML algorithm runtime at the API level
  
  :param time_for_automl: time for AutoML algorithms in minutes
docstr: Based on time spend for composing and initial pipeline fit determine
  how much time and how many iterations are needed for tuning
docstr_tok: ["Based","on","time","spend","for","composing","and","initial","pipeline","fit","determine","how","much","time","and","how","many","iterations","are","needed","for","tuning"]
code: def determine_resources_for_tuning(self):
      """
      Based on time spend for composing and initial pipeline fit determine
      how much time and how many iterations are needed for tuning
  
      """
      all_spend_time = (
          self.composing_spend_time + self.assumption_fit_spend_time
      )
  
      if self.time_for_automl is not None:
          all_timeout = float(self.time_for_automl)
          timeout_in_sec = datetime.timedelta(
              minutes=all_timeout
          ).total_seconds()
          timeout_for_tuning = (
              timeout_in_sec - all_spend_time.total_seconds()
          )
      else:
          timeout_for_tuning = all_spend_time.total_seconds()
      return timeout_for_tuning
  
file_path: FEDOT/fedot/api/time.py
imports: import datetime
  from contextlib import contextmanager
  from typing import Optional
  from fedot.core.constants import COMPOSING_TUNING_PROPORTION, MINIMAL_PIPELINE_NUMBER_FOR_EVALUATION, MINIMAL_SECONDS_FOR_TUNING, MIN_NUMBER_OF_GENERATIONS
label_desc: Use image node_id 9 for calling the ApiTime obj's underlying member method code with example usage: obj.determine_resources_for_tuning() and returns: timeout_for_tuning