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

After recovering our model’s state, we can finally use it to make predictions for
new inputs:
Notebook Cell 2.10
new_inputs = torch.tensor([[.20], [.34], [.57]])
model.eval() # always use EVAL for fully trained models! 1
model(new_inputs.to(device))
1 Never forget to set the mode!
Output
tensor([[1.4185],
[1.6908],
[2.1381]], device='cuda:0', grad_fn=<AddmmBackward>)
Since Model Configuration V3 created a model and sent it automatically to our
device, we need to do the same with our new inputs.
After loading a fully trained model for deployment / to make
predictions, make sure you ALWAYS set it to evaluation mode:
model.eval()
Congratulations, you "deployed" your first model :-)
Setting the Model’s Mode
I know, I am probably a bit obsessive about this, but here we go one more time:
After loading the model, DO NOT FORGET to SET THE MODE:
• checkpointing: model.train()
• deploying / making predictions: model.eval()
Saving and Loading Models | 169