Docs2 (#1028)

* added community examples

* added community examples

docs/source/callbacks.rst

@@ -35,10 +35,31 @@ Example
 
 We successfully extended functionality without polluting our super clean LightningModule research code
 
-Callback Class
---------------
+.. automodule:: pytorch_lightning.callbacks.base
+   :noindex:
+   :exclude-members:
+        _del_model,
+        _save_model,
+        _abc_impl,
+        check_monitor_top_k,
 
-.. automodule:: pytorch_lightning.callbacks
+.. automodule:: pytorch_lightning.callbacks.early_stopping
+   :noindex:
+   :exclude-members:
+        _del_model,
+        _save_model,
+        _abc_impl,
+        check_monitor_top_k,
+
+.. automodule:: pytorch_lightning.callbacks.model_checkpoint
+   :noindex:
+   :exclude-members:
+        _del_model,
+        _save_model,
+        _abc_impl,
+        check_monitor_top_k,
+
+.. automodule:: pytorch_lightning.callbacks.gradient_accumulation_scheduler
    :noindex:
    :exclude-members:
         _del_model,

pytorch_lightning/callbacks/base.py

@@ -1,15 +1,16 @@
-"""
-Callbacks
-=========
-
-Callbacks supported by Lightning
+r"""
+Callback Base
+==============
+    Abstract base class used to build new callbacks.
 """
 
 import abc
 
 
 class Callback(abc.ABC):
-    """Abstract base class used to build new callbacks."""
+    r"""
+    Abstract base class used to build new callbacks.
+    """
 
     def on_init_start(self, trainer):
         """Called when the trainer initialization begins, model has not yet been set."""

pytorch_lightning/callbacks/early_stopping.py

@@ -1,3 +1,10 @@
+r"""
+Early Stopping
+==============
+Stop training when a monitored quantity has stopped improving.
+
+"""
+
 import logging as log
 import warnings
 
@@ -8,7 +15,6 @@ from .base import Callback
 
 class EarlyStopping(Callback):
     r"""
-    Stop training when a monitored quantity has stopped improving.
 
     Args:
         monitor (str): quantity to be monitored. Default: ``'val_loss'``.

pytorch_lightning/callbacks/gradient_accumulation_scheduler.py

@@ -1,3 +1,9 @@
+r"""
+Gradient Accumulator
+====================
+Change gradient accumulation factor according to scheduling.
+"""
+
 import warnings
 
 from .base import Callback

pytorch_lightning/callbacks/model_checkpoint.py

@@ -1,3 +1,10 @@
+r"""
+Model Checkpoint
+==============
+Save the model as often as requested.
+
+"""
+
 import os
 import shutil
 import logging as log