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@ -30,7 +30,7 @@ Keras and fast.ai are too abstract for researchers. Lightning abstracts the full
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Because you want to use best practices and get gpu training, multi-node training, checkpointing, mixed-precision, etc... for free, but still want granular control of the meat of the training, validation and testing loops.
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Because you want to use best practices and get gpu training, multi-node training, checkpointing, mixed-precision, etc... for free, but still want granular control of the meat of the training, validation and testing loops.
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To use lightning do 2 things:
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To use lightning do 2 things:
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1. [Define a Trainer](https://github.com/williamFalcon/pytorch-lightning/blob/master/examples/new_project_templates/trainer_cpu_template.py) (which will run ALL your models).
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1. [Define a Trainer](https://github.com/williamFalcon/pytorch-lightning/blob/master/examples/new_project_templates/trainer_cpu_template.py).
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2. [Define a LightningModel](https://github.com/williamFalcon/pytorch-lightning/blob/master/examples/new_project_templates/lightning_module_template.py).
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2. [Define a LightningModel](https://github.com/williamFalcon/pytorch-lightning/blob/master/examples/new_project_templates/lightning_module_template.py).
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## What does lightning control for me?
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## What does lightning control for me?
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