It’s pred in the training loop. So far I have seen tensor with only 0, only 1, 0 or 1, but never a value in between…
I collected it this way:
predictions = []
...
for batch, (X, y) in enumerate(dataloader):
        # Compute prediction and loss
        pred = model(X)
        predictions.append(pred)
        loss = loss_fn(pred, y)
        ....