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This repository has been archived by the owner on Sep 19, 2022. It is now read-only.
Hello!
I'm setting up training with PyTorchJobs. I have the problem: if one of the pods (doesn't matter, master or worker) reloads, the whole process hangs. The reason for reloading can be different, usually, it's due to Google Cloud Engine node rescheduling. Also, I tried to kill pods myself - the behavior was the same.
Can I avoid this behavior and make training tolerant to pods' reloading?
The text was updated successfully, but these errors were encountered:
Hello!
I'm setting up training with PyTorchJobs. I have the problem: if one of the pods (doesn't matter, master or worker) reloads, the whole process hangs. The reason for reloading can be different, usually, it's due to Google Cloud Engine node rescheduling. Also, I tried to kill pods myself - the behavior was the same.
Can I avoid this behavior and make training tolerant to pods' reloading?
The text was updated successfully, but these errors were encountered: