Changing CustomDataParallel to DistributedDataParallel #487
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zylo117
reviewed
Aug 25, 2020
| @@ -315,7 +320,7 @@ def freeze_backbone(m): | |||
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| def save_checkpoint(model, name): | |||
| if isinstance(model, CustomDataParallel): | |||
| if isinstance(model, torch.nn.parallel.DistributedDataParallel): | |||
| torch.save(model.module.model.state_dict(), os.path.join(opt.saved_path, name)) | |||
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I'm not sure if DDP's module is the real model like DP
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ASAIK, it's model.model.state_dict() for DDP like the ordinary model. Or both are ok?
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Hi, thanks for your contribution. |
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It's a pleasure. You did a great job. Yes. I've tested in the afternoon, but I'm training a big model now. Tomorrow I will do more tests to see; this model is running on my machine (job). |
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Changing the previous CustomDataParallel to DistributedDataParallel to improve the training speed.