Question

当我调用“ pool.apply（engine，args =（reminder_stream，streams_total，12，

reminder_duration，templates，templates_classes）“我遇到运行时错误”试图在启动新进程之前当前进程已完成其引导阶段。

这可能意味着您没有使用fork来启动子进程，并且忘记了在主模块中使用适当的习惯用法：if name ==' main >'：Frozen_support（）...如果不打算冻结程序以生成可执行文件，则可以省略“ freeze_support（）”行。”

```python
 def engine(stream_reminder, total_streams, stream_id, duration_reminder, templates, templates_classes):
        stream = get_stream_data(stream_id)
        if stream != "":
            optimized_stream, timestamps = optimize_stream(stream)
            if len(stream_reminder) != 0:
                optimized_stream = np.concatenate((stream_reminder, optimized_stream), axis=None)
                timestamps = np.concatenate((duration_reminder, timestamps), axis=None)
            stream_cuts, stream_reminder, stream_durations, duration_reminder = cut_stream(optimized_stream, 13, 125,
                                                                                           timestamps)
            if len(stream_cuts) > 0:
                submit_stream_cuts(stream_id, stream_cuts, stream_durations)
                total_streams = total_streams + stream_cuts
                print(len(total_streams))
                for i in range(len(stream_cuts)):
                    stream_cut_result = classifiy_stroke(templates,stream_cuts[i], templates_classes)
                    submit_stroke_result(stream_cut_result,stream_cuts[i])

    print(len(total_streams))
    threading.Timer(2.0, engine, [stream_reminder, total_streams, stream_id, duration_reminder, templates, templates_classes]).start()
```

reminder_stream = []
streams_total = []
reminder_duration = []

templates, templates_classes = get_stroke_templates()
for i in range(len(templates)):
    templates[i] = filter_stream(templates[i], False, False)
import multiprocessing as mp
pool = mp.Pool(mp.cpu_count())

results = [pool.apply(engine, args=(reminder_stream, streams_total ,12, reminder_duration,templates, templates_classes))]
pool.close()

python快速dtw多核freeze_support错误

0 个答案: