With the PyTorch Distributed training model, code changes affect running applications

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I noticed two strange things,
First, when I used Distributed for training, I modified the code. After a while, the application reported an error when RUNNING because of my modification.
Second, I added print to the code, and after a while, the program that was already running will start to print accordingly

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@ckx506772099 Sorry for the late reply! Please see DDP is affected by code modification, this is a python multiprocessing module behavior instead of DDP.