Allow Callback instance as an argument of `callbacks` in `Trainer` (#5446)

* fix

* Update CHANGELOG

* add test

* fix

* pep

* docs

Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com>

CHANGELOG.md

@@ -61,6 +61,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Changed `iou` [func] to allow float input ([#4704](https://github.com/PyTorchLightning/pytorch-lightning/pull/4704))
 
 
+- Changed `callbacks` argument in `Trainer` to allow `Callback` input ([#5446](https://github.com/PyTorchLightning/pytorch-lightning/pull/5446))
+
+
 ### Deprecated
 
 - `stat_scores_multiple_classes` is deprecated in favor of `stat_scores` ([#4839](https://github.com/PyTorchLightning/pytorch-lightning/pull/4839))

pytorch_lightning/trainer/connectors/callback_connector.py

@@ -14,7 +14,7 @@
 import os
 from typing import Union
 
-from pytorch_lightning.callbacks import ModelCheckpoint, ProgressBar, ProgressBarBase
+from pytorch_lightning.callbacks import Callback, ModelCheckpoint, ProgressBar, ProgressBarBase
 from pytorch_lightning.utilities import rank_zero_warn
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
@@ -41,6 +41,8 @@ class CallbackConnector:
         self.trainer._weights_save_path = weights_save_path or self.trainer._default_root_dir
 
         # init callbacks
+        if isinstance(callbacks, Callback):
+            callbacks = [callbacks]
         self.trainer.callbacks = callbacks or []
 
         # configure checkpoint callback

pytorch_lightning/trainer/trainer.py

@@ -85,7 +85,7 @@ class Trainer(
         self,
         logger: Union[LightningLoggerBase, Iterable[LightningLoggerBase], bool] = True,
         checkpoint_callback: bool = True,
-        callbacks: Optional[List[Callback]] = None,
+        callbacks: Optional[Union[List[Callback], Callback]] = None,
         default_root_dir: Optional[str] = None,
         gradient_clip_val: float = 0,
         process_position: int = 0,
@@ -169,7 +169,7 @@ class Trainer(
 
             benchmark: If true enables cudnn.benchmark.
 
-            callbacks: Add a list of callbacks.
+            callbacks: Add a callback or list of callbacks.
 
             checkpoint_callback: If ``True``, enable checkpointing.
                 It will configure a default ModelCheckpoint callback if there is no user-defined ModelCheckpoint in

tests/callbacks/test_callback_hook_outputs.py

@@ -11,11 +11,14 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from pytorch_lightning import Trainer, Callback
+import pytest
+
+from pytorch_lightning import Callback, Trainer
 from tests.base.boring_model import BoringModel
 
 
-def test_train_step_no_return(tmpdir):
+@pytest.mark.parametrize("single_cb", [False, True])
+def test_train_step_no_return(tmpdir, single_cb):
     """
     Tests that only training_step can be used
     """
@@ -53,7 +56,7 @@ def test_train_step_no_return(tmpdir):
     model = TestModel()
 
     trainer = Trainer(
-        callbacks=[CB()],
+        callbacks=CB() if single_cb else [CB()],
         default_root_dir=tmpdir,
         limit_train_batches=2,
         limit_val_batches=2,
@@ -62,4 +65,7 @@ def test_train_step_no_return(tmpdir):
         weights_summary=None,
     )
 
-    trainer.fit(model)
+    assert any(isinstance(c, CB) for c in trainer.callbacks)
+
+    results = trainer.fit(model)
+    assert results