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import torch
if __name__ == '__main__':
model_path = "saved_model/11/model.pth"
output_path = "saved_model/11/model1.pth"
checkpoint_dict = torch.load(model_path, map_location='cpu')
checkpoint_dict_new = {}
for k, v in checkpoint_dict.items():
if k == "optimizer":
print("remove optimizer")
continue
checkpoint_dict_new[k] = v
torch.save(checkpoint_dict_new, output_path)
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