Depending on what you want, I’d probably try one of the following:

If the normalization is per example, add it to the dataset and keeping track of it in the dataset is the preferred way.
There are various other ways to achieve something similar to what @fmassa suggested (and even more variants when you search for “currying in python”). The lazy person’s way would be using default arguments:

dl = torch.utils.data.DataLoader(..., collate_fn = lambda b: my_collator_with_param(b, 3))

or, using the params argument in the lambda to fix the argument rather than having the lookup during execution
dl = torch.utils.data.DataLoader(..., collate_fn = lambda b, params=params: my_collator_with_param(b, params))

Between doing things in the dataset and having one of the collator variants from this thread, you should be able to do most things.
Best regards
Thomas