How to use trained pytorch model for prediction

Question

I have a pretrained pytorch model which is saved in .pth format. How can i use it for prediction on new dataset in a separate python file.

I need a detailed guide.

Answer 1

To use a pretrained model you should load the state on a new instance of the architecture as explained in the docs/tutorials:

Here models is imported beforehand:

model = models.vgg16()
model.load_state_dict(torch.load('model_weights.pth')) # This line uses .load() to read a .pth file and load the network weights on to the architecture.
model.eval() # enabling the eval mode to test with new samples.

If you are using a custom architecture you only need to change the first line.

model = MyCustomModel()

After enabling the eval mode, you can proceed as follows:

• Load your data into a Dataset instance and then in a DataLoader.
• Make your predictions with the data.
• Calculate metrics on the results.

More about Dataset and DataLoader here.