Split callbacks (#849)

* add .vscode in .gitignore

* Split callbacks in individual files + add a  property to Callback for easy trainer instance access

* formatting

* Add a conda env file for quick and easy env setup to develop on PL

* Adress comments

* add fix to kth_best_model

* add some typing to callbacks

* fix typo

* add autopep8 config to pyproject.toml

* format again

* format

* fix toml

* fix toml again

* consistent max line length in all config files

* remove conda env file

* Update pytorch_lightning/callbacks/early_stopping.py

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

* Update pytorch_lightning/callbacks/model_checkpoint.py

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

* docstring

* Update pytorch_lightning/callbacks/model_checkpoint.py

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

* Update pytorch_lightning/callbacks/model_checkpoint.py

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

* fix logic error

* format

* simplify if/else

* format

* fix linting issue in changelog

* edit changelog about new callback mechanism

* fix remaining formating issue on CHANGELOG

* remove lambda function because it's compatible with pickle (used during ddp)

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>

pytorch_lightning/callbacks/__init__.py

@@ -1,6 +1,11 @@
-from .pt_callbacks import EarlyStopping, ModelCheckpoint, GradientAccumulationScheduler
+from .base import Callback
+from .early_stopping import EarlyStopping
+from .model_checkpoint import ModelCheckpoint
+from .gradient_accumulation_scheduler import GradientAccumulationScheduler
+
 
 __all__ = [
+    'Callback',
     'EarlyStopping',
     'ModelCheckpoint',
     'GradientAccumulationScheduler',