fix distributed training after DataLoader change (device parameter)

[jaidmin]

fixes the distributed training issue introduces with the change from a Cuda callback to a device parameter on DataLoader reported in #57 and here in the forums.

The fix is simply passing the device parameter from the DataLoader to the DistributedDL when it is initialized.

Also fixes this error:

warn(f"You are setting an attribute ({name}) that also exists in the learner. Please be advised that you're not setting it in the learner but in the callback. Use `self.learn.{name}` if you would like to change it in the learner.")
/home/jaidmin/Software/Devel/forks/fastai2/fastai2/learner.py:30: UserWarning: You are setting an attribute (dl) that also exists in the learner. Please be advised that you're not setting it in the learner but in the callback. Use `self.learn.dl` if you would like to change it in the learner.

If this behavior is wanted, let me know and I'll change the PR

[sgugger]

Looking good, thanks!