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Improved docs for callbacks (#1370)

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* improved docs for callbacks

* class references

* make doctest pass

* doctests

* fix lines too long

* fix line too long

* fix permission error in doctest

* Apply suggestions from code review

Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com>

* fix doctest

* fix default

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
This commit is contained in:
Adrian Wälchli
2020-04-05 09:38:52 +00:00
committed by GitHub
co-authored by Jirka Borovec
parent 22bedf9b57
commit 1f2da71069
6 changed files with 88 additions and 72 deletions
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docs/source/callbacks.rst
+20 -18
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@@ -7,7 +7,7 @@ Callbacks
=========
Lightning has a callback system to execute arbitrary code. Callbacks should capture NON-ESSENTIAL
logic that is NOT required for your LightningModule to run.
logic that is NOT required for your :class:`~pytorch_lightning.core.LightningModule` to run.
An overall Lightning system should have:
@@ -15,27 +15,29 @@ An overall Lightning system should have:
2. LightningModule for all research code.
3. Callbacks for non-essential code.
Example
.. code-block:: python
Example:
import pytorch_lightning as pl
.. doctest::
class MyPrintingCallback(pl.Callback):
>>> import pytorch_lightning as pl
>>> class MyPrintingCallback(pl.Callback):
...
... def on_init_start(self, trainer):
... print('Starting to init trainer!')
...
... def on_init_end(self, trainer):
... print('trainer is init now')
...
... def on_train_end(self, trainer, pl_module):
... print('do something when training ends')
...
>>> trainer = pl.Trainer(callbacks=[MyPrintingCallback()])
Starting to init trainer!
trainer is init now
def on_init_start(self, trainer):
print('Starting to init trainer!')
def on_init_end(self, trainer):
print('trainer is init now')
def on_train_end(self, trainer, pl_module):
print('do something when training ends')
# pass to trainer
trainer = pl.Trainer(callbacks=[MyPrintingCallback()])
We successfully extended functionality without polluting our super clean LightningModule research code
We successfully extended functionality without polluting our super clean
:class:`~pytorch_lightning.core.LightningModule` research code.
---------