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Link full code example for LightningLite (#12568) 

Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
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Aniket Maurya 2022-04-04 12:59:14 +05:30 committed by GitHub
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docs/source/starter/lightning_lite.rst
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@ -69,7 +69,6 @@ The ``run`` function contains custom training loop used to train ``MyModel`` on
run(args)
----------
@ -124,7 +123,7 @@ Here are five required steps to convert to :class:`~pytorch_lightning.lite.Light
Lite(...).run(args)
That's all. You can now train on any kind of device and scale your training.
That's all. You can now train on any kind of device and scale your training. Check out `this <https://github.com/PyTorchLightning/pytorch-lightning/blob/master/pl_examples/basic_examples/mnist_examples/image_classifier_2_lite.py>`_ full MNIST training example with LightningLite.
:class:`~pytorch_lightning.lite.LightningLite` takes care of device management, so you don't have to.
You should remove any device-specific logic within your code.