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you basically need to do the same as in tensorflow. That is, when you store a network, only the parameters (i.e. the trainable objects in your network) will be stored, but not the "glue", that is all the logic you need to use a trained model. So if you have a .pth.tar file, you can load it, thereby overriding the parameter values of a model already defined. That means that the general ...
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