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hyperopt / hyperopt-sklearn

Hyper-parameter optimization for sklearn
hyperopt.github.io/hyperopt-sklearn
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error：The "freeze_support()" line can be omitted if the program is not going to be frozen to produce an executable. #207

Open yitai000 opened 3 months ago

yitai000 commented 3 months ago

job exception: An attempt has been made to start a new process before the current process has finished its bootstrapping phase.

    This probably means that you are not using fork to start your
    child processes and you have forgotten to use the proper idiom
    in the main module:

        if __name__ == '__main__':
            freeze_support()
            ...

    The "freeze_support()" line can be omitted if the program
    is not going to be frozen to produce an executable.

    To fix this issue, refer to the "Safe importing of main module"
    section in https://docs.python.org/3/library/multiprocessing.html

Traceback (most recent call last): File "", line 1, in File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\spawn.py", line 122, in spawn_main exitcode = _main(fd, parent_sentinel) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\spawn.py", line 131, in _main prepare(preparation_data) File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\spawn.py", line 246, in prepare _fixup_main_from_path(data['init_main_from_path']) File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\spawn.py", line 297, in _fixup_main_from_path main_content = runpy.run_path(main_path, ^^^^^^^^^^^^^^^^^^^^^^^^^ File "", line 291, in run_path File "", line 98, in _run_module_code File "", line 88, in _run_code File "D:\projects\pycharmProjects\EXP\XGB\XGB_classifier.py", line 39, in estimator.fit(x_train, y_train) File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hpsklearn\estimator\estimator.py", line 480, in fit fit_iter.send(increment) File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hpsklearn\estimator\estimator.py", line 347, in fit_iter hyperopt.fmin(_fn_with_timeout, File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hyperopt\fmin.py", line 540, in fmin return trials.fmin( ^^^^^^^^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hyperopt\base.py", line 671, in fmin return fmin( ^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hyperopt\fmin.py", line 586, in fmin rval.exhaust() File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hyperopt\fmin.py", line 364, in exhaust self.run(self.max_evals - n_done, block_until_done=self.asynchronous) File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hyperopt\fmin.py", line 300, in run self.serial_evaluate() File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hyperopt\fmin.py", line 178, in serial_evaluate result = self.domain.evaluate(spec, ctrl) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hyperopt\base.py", line 892, in evaluate rval = self.fn(pyll_rval) ^^^^^^^^^^^^^^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\site-packages\hpsklearn\estimator\estimator.py", line 304, in _fn_with_timeout th.start() File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\process.py", line 121, in start self._popen = self._Popen(self) ^^^^^^^^^^^^^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\context.py", line 336, in _Popen return Popen(process_obj) ^^^^^^^^^^^^^^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\popen_spawn_win32.py", line 46, in init prep_data = spawn.get_preparation_data(process_obj._name) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\spawn.py", line 164, in get_preparation_data _check_not_importing_main() File "D:\app\anaconda3\envs\hyperopt\Lib\multiprocessing\spawn.py", line 140, in _check_not_importing_main raise RuntimeError(''' RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase.

    This probably means that you are not using fork to start your
    child processes and you have forgotten to use the proper idiom
    in the main module:

        if __name__ == '__main__':
            freeze_support()
            ...

    The "freeze_support()" line can be omitted if the program
    is not going to be frozen to produce an executable.

    To fix this issue, refer to the "Safe importing of main module"
    section in https://docs.python.org/3/library/multiprocessing.html