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First of all, thank for your sharing.
Your experiment codes are perpectly working to reproduce your experiments.
But when I want to get the pruned model which is not trained for my custom experiment,
I get in trouble.
Referring your main script and other codes I found that if I want to load a pruned model in other code base,
I need to call all dependent modules for the neural network with unpickling the pruned weights.
Is there any detour to get a pruned model for using easily as like following ?
import torch model_path = "Pruned_model.pth" model = torch.load(model_path)
The text was updated successfully, but these errors were encountered:
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First of all, thank for your sharing.
Your experiment codes are perpectly working to reproduce your experiments.
But when I want to get the pruned model which is not trained for my custom experiment,
I get in trouble.
Referring your main script and other codes I found that if I want to load a pruned model in other code base,
I need to call all dependent modules for the neural network with unpickling the pruned weights.
Is there any detour to get a pruned model for using easily as like following ?
The text was updated successfully, but these errors were encountered: