Changed the way the optimizer is saved: only its state_dict is pickled #772
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| path, pickle_module=pickle_module, **kwargs) | ||
| attributes = {item: getattr(self, item) for item in self.PRESERVE if item != "optimizer"} | ||
| optimizer = getattr(self, "optimizer") | ||
| attributes["optimizer"] = optimizer.state_dict() |
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But how do we load the optimizer from that state if we need to? In the current implementation we dump Optimizer instance and can deserialize it to use.
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Optimizer cannot be pickled in later PyTorch version directly - their
optimizer.state_dict()object must be saved instead. This little change ensures thatoptimizerattribute saves onlystate_dict