hyperopt 오류

안녕하세요 , 항상 고생많으십니다.

다름이 아니라 , hyperopt 마지막 실습 중에 다음의 코드에서 오류가 발생합니다. hyperopt version도 실습과 같은데, 왜 이런 오류가 발생하는지 몰라서 질문드립니다.

from hyperopt import fmin, tpe, Trials

trial_val = Trials()
best = fmin(fn=objective_func,
            space=xgb_search_space,
            algo=tpe.suggest,
            max_evals=50, # 최대 반복 횟수를 지정합니다.
            trials=trial_val, rstate=np.random.default_rng(seed=9))
print('best:', best)

오류문
---------------------------------------------------------------------------
AllTrialsFailed                           Traceback (most recent call last)
Cell In[21], line 4
      1 from hyperopt import fmin, tpe, Trials
      3 trial_val = Trials()
----> 4 best = fmin(fn=objective_func,
      5             space=xgb_search_space,
      6             algo=tpe.suggest,
      7             max_evals=50, # 최대 반복 횟수를 지정합니다.
      8             trials=trial_val, rstate=np.random.default_rng(seed=9))
      9 print('best:', best)

File ~\anaconda3\envs\sklearn_env\lib\site-packages\hyperopt\fmin.py:540, in fmin(fn, space, algo, max_evals, timeout, loss_threshold, trials, rstate, allow_trials_fmin, pass_expr_memo_ctrl, catch_eval_exceptions, verbose, return_argmin, points_to_evaluate, max_queue_len, show_progressbar, early_stop_fn, trials_save_file)
    537     fn = __objective_fmin_wrapper(fn)
    539 if allow_trials_fmin and hasattr(trials, "fmin"):
--> 540     return trials.fmin(
    541         fn,
    542         space,
    543         algo=algo,
    544         max_evals=max_evals,
    545         timeout=timeout,
    546         loss_threshold=loss_threshold,
    547         max_queue_len=max_queue_len,
    548         rstate=rstate,
    549         pass_expr_memo_ctrl=pass_expr_memo_ctrl,
    550         verbose=verbose,
    551         catch_eval_exceptions=catch_eval_exceptions,
    552         return_argmin=return_argmin,
    553         show_progressbar=show_progressbar,
    554         early_stop_fn=early_stop_fn,
    555         trials_save_file=trials_save_file,
    556     )
    558 if trials is None:
    559     if os.path.exists(trials_save_file):

File ~\anaconda3\envs\sklearn_env\lib\site-packages\hyperopt\base.py:671, in Trials.fmin(self, fn, space, algo, max_evals, timeout, loss_threshold, max_queue_len, rstate, verbose, pass_expr_memo_ctrl, catch_eval_exceptions, return_argmin, show_progressbar, early_stop_fn, trials_save_file)
    666 # -- Stop-gap implementation!
    667 #    fmin should have been a Trials method in the first place
    668 #    but for now it's still sitting in another file.
    669 from .fmin import fmin
--> 671 return fmin(
    672     fn,
    673     space,
    674     algo=algo,
    675     max_evals=max_evals,
    676     timeout=timeout,
    677     loss_threshold=loss_threshold,
    678     trials=self,
    679     rstate=rstate,
    680     verbose=verbose,
    681     max_queue_len=max_queue_len,
    682     allow_trials_fmin=False,  # -- prevent recursion
    683     pass_expr_memo_ctrl=pass_expr_memo_ctrl,
    684     catch_eval_exceptions=catch_eval_exceptions,
    685     return_argmin=return_argmin,
    686     show_progressbar=show_progressbar,
    687     early_stop_fn=early_stop_fn,
    688     trials_save_file=trials_save_file,
    689 )

File ~\anaconda3\envs\sklearn_env\lib\site-packages\hyperopt\fmin.py:593, in fmin(fn, space, algo, max_evals, timeout, loss_threshold, trials, rstate, allow_trials_fmin, pass_expr_memo_ctrl, catch_eval_exceptions, verbose, return_argmin, points_to_evaluate, max_queue_len, show_progressbar, early_stop_fn, trials_save_file)
    589     if len(trials.trials) == 0:
    590         raise Exception(
    591             "There are no evaluation tasks, cannot return argmin of task losses."
    592         )
--> 593     return trials.argmin
    594 if len(trials) > 0:
    595     # Only if there are some successful trail runs, return the best point in
    596     # the evaluation space
    597     return space_eval(space, trials.argmin)

File ~\anaconda3\envs\sklearn_env\lib\site-packages\hyperopt\base.py:620, in Trials.argmin(self)
    618 @property
    619 def argmin(self):
--> 620     best_trial = self.best_trial
    621     vals = best_trial["misc"]["vals"]
    622     # unpack the one-element lists to values
    623     # and skip over the 0-element lists

File ~\anaconda3\envs\sklearn_env\lib\site-packages\hyperopt\base.py:611, in Trials.best_trial(self)
    605 candidates = [
    606     t
    607     for t in self.trials
    608     if t["result"]["status"] == STATUS_OK and not np.isnan(t["result"]["loss"])
    609 ]
    610 if not candidates:
--> 611     raise AllTrialsFailed
    612 losses = [float(t["result"]["loss"]) for t in candidates]
    613 if len(losses) == 0:

AllTrialsFailed: