class_docstr: Class for managing threads which run concurrent Spark jobs.
  
  This maintains a primary dispatcher thread, plus 1 thread per Hyperopt trial.
  Each trial's thread runs 1 Spark job with 1 task.
code: def _poll_new_tasks(self):
      new_task_list = []
      for trial in copy.copy(self.trials.trials):
          if trial["state"] == base.JOB_STATE_NEW:
              # check parallelism limit
              if self.running_trial_count() >= self.trials.parallelism:
                  break
              new_task_list.append(trial)
              self._begin_trial_run(trial)
      return new_task_list
  
imports: import copy
  import os
  import threading
  import time
  import timeit
  import traceback
  from hyperopt import base, fmin, Trials
  from hyperopt.base import validate_timeout, validate_loss_threshold, STATUS_OK
  from hyperopt.utils import coarse_utcnow, _get_logger, _get_random_id
label_desc: Use image node_id 12 for calling the _SparkFMinState obj's underlying member method code with example usage: obj._poll_new_tasks() and returns: new_task_list