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* docs

* docs
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10
pytorch_lightning/core/__init__.py
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@ -9,7 +9,7 @@ Notice a few things.
1. It's the SAME code. 1. It's the SAME code.
2. The PyTorch code IS NOT abstracted - just organized. 2. The PyTorch code IS NOT abstracted - just organized.
3. All the other code that didn't go in the LightningModule has been automated for you by the trainer 3. All the other code that not in the LightningModule has been automated for you by the trainer
.. code-block:: python .. code-block:: python
net = Net() net = Net()
@ -101,7 +101,7 @@ Which you can train by doing:
trainer.fit(model) trainer.fit(model)
--- ----------
Training loop structure Training loop structure
----------------------- -----------------------
@ -181,7 +181,7 @@ don't run your test data by accident. Instead you have to explicitly call:
trainer = Trainer() trainer = Trainer()
trainer.test(model) trainer.test(model)
--- ----------
Training_step_end method Training_step_end method
------------------------ ------------------------
@ -211,7 +211,7 @@ which allows you to operate on the pieces of the batch
# like calculate validation set accuracy or loss # like calculate validation set accuracy or loss
training_epoch_end(val_outs) training_epoch_end(val_outs)
--- ----------
Remove cuda calls Remove cuda calls
----------------- -----------------
@ -230,7 +230,7 @@ When you init a new tensor in your code, just use type_as
z = sample_noise() z = sample_noise()
z = z.type_as(x.type()) z = z.type_as(x.type())
--- ----------
Data preparation Data preparation
---------------- ----------------