Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Deploying / Making Predictions
Again, if we’re starting fresh (as if we had just turned on the computer and started
Jupyter), we have to set the stage before actually loading the model. But, this time,
we only need to configure the model:
Notebook Cell 2.8
%run -i model_configuration/v3.py
Once again, we have an untrained model at this point. The loading procedure is
simpler, though:
• load the dictionary back using torch.load()
• load model state dictionary back using its method load_state_dict()
Since the model is fully trained, we don’t need to load the optimizer or anything
else.
Notebook Cell 2.9 - Loading a fully trained model to make predictions
checkpoint = torch.load('model_checkpoint.pth')
model.load_state_dict(checkpoint['model_state_dict'])
print(model.state_dict())
Output
OrderedDict([('0.weight', tensor([[1.9448]], device='cuda:0')),
('0.bias', tensor([1.0295], device='cuda:0'))])
168 | Chapter 2: Rethinking the Training Loop