Passing a parameter to model's forward pass on an event

First of all, I’d like to thank you for that great library.

However, I couldn’t achieve a solution of my problem. I should use a different approach during the training stage and the evaluation stage. In PyTorch I could do this like this:

for epoch in range(1, n_epochs + 1):
    model.train()
    for data, target in train_loader:
        #bla bla
        output = model(data, training = True)
        #bla bla
            
    model.eval()
    for data, target in valid_loader:
        #bla bla
        output = model(data, training = False)
        #bla bla

How can I achieve this using Ignite library?

[miguelvr]

@furkan-kucuk you’re welcome.

[iamkucuk]

@furkan-kucuk please take a look at the quickstart. For more details you can consult the implementations of create_supervised_trainer and create_supervised_evaluator.

If you find out the quickstart unclear or cumbersome, please post your feedback here.

Thank you for fast answer. I really admire your work and thankful for it!