[checkpointio]support asyncio for all models #6152
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checkpoint benchmark |
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| @@ -216,15 +244,31 @@ def save_sharded_model( | |||
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| # Then collect the sharded parameters & buffers along tp_group. | |||
| # Only devices with tp_rank == 0 are responsible for model saving. | |||
| state_dict_shard = HybridParallelCheckpointIO._model_sharder(model, size_per_shard=size_per_shard) | |||
| control_saving = self.tp_rank == 0 | |||
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| # exception for fsdp, part[1] isn't param_id | ||
| idx = parts[1] |
| plugin = TorchDDPPlugin() | ||
| booster = Booster(plugin=plugin) | ||
| model = resnet18() | ||
| criterion = lambda x: x.mean() | ||
| optimizer = SGD((model.parameters()), lr=0.001) | ||
| optimizer = SGD((model.parameters()), lr=0.001, momentum=0.5) |
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keep momentum=0 to test corner case
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