Can't setup batch transforms from TfmdDL

[slawekslex]

The Transform.setup() is called before the TfmdDL super constructor here As the result the transform wont have access to the data. See for example:

class foo(Transform):
    def setup(self, items):
        n = len(items)
test_ds = DataSource(L(range(10)))
test_dl = TfmdDL(test_ds,bs=2,after_batch=[foo])

[sgugger]

What is your use case? I think they should be passed self.dataset for the setup but want to be sure that's what you need.

[slawekslex]

Getting the dataset sounds good.

[sgugger]

Just fixed this, the setup gets passed the full DataLoader in the end. Pipelines are setup in the logical order: after_item, before_batch and after_batch.