Prune deprecated Trainer(checkpoint_callback=ModelCheckpoint()) (#6166)

CHANGELOG.md

@@ -26,6 +26,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed support for passing a bool value to `profiler` argument of Trainer ([#6164](https://github.com/PyTorchLightning/pytorch-lightning/pull/6164))
 
 
+- Removed passing a `ModelCheckpoint` instance to `Trainer(checkpoint_callback)` ([#6166](https://github.com/PyTorchLightning/pytorch-lightning/pull/6166))
+
+
 - Removed deprecated Trainer argument `enable_pl_optimizer` and `automatic_optimization` ([#6163](https://github.com/PyTorchLightning/pytorch-lightning/pull/6163))
 
 

pytorch_lightning/trainer/connectors/callback_connector.py

@@ -16,7 +16,7 @@
 
 from pytorch_lightning.callbacks import Callback, ModelCheckpoint, ProgressBar, ProgressBarBase
 from pytorch_lightning.core.lightning import LightningModule
-from pytorch_lightning.utilities import rank_zero_info, rank_zero_warn
+from pytorch_lightning.utilities import rank_zero_info
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 
 
@@ -63,15 +63,6 @@ def on_trainer_init(
  self.trainer.callbacks = self._reorder_callbacks(self.trainer.callbacks)
 
  def configure_checkpoint_callbacks(self, checkpoint_callback: Union[ModelCheckpoint, bool]):
- if isinstance(checkpoint_callback, ModelCheckpoint):
- # TODO: deprecated, remove this block in v1.3.0
- rank_zero_warn(
- "Passing a ModelCheckpoint instance to Trainer(checkpoint_callbacks=...)"
- " is deprecated since v1.1 and will no longer be supported in v1.3."
- " Use `callbacks` argument instead.", DeprecationWarning
- )
- self.trainer.callbacks.append(checkpoint_callback)
-
  if self._trainer_has_checkpoint_callbacks() and checkpoint_callback is False:
  raise MisconfigurationException(
  "Trainer was configured with checkpoint_callback=False but found ModelCheckpoint"

pytorch_lightning/trainer/trainer.py

@@ -177,9 +177,6 @@ def __init__(
  It will configure a default ModelCheckpoint callback if there is no user-defined ModelCheckpoint in
  :paramref:`~pytorch_lightning.trainer.trainer.Trainer.callbacks`.
 
- .. warning:: Passing a ModelCheckpoint instance to this argument is deprecated since
- v1.1 and will be unsupported from v1.3. Use `callbacks` argument instead.
-
  check_val_every_n_epoch: Check val every n train epochs.
 
  default_root_dir: Default path for logs and weights when no logger/ckpt_callback passed.

tests/checkpointing/test_model_checkpoint.py

@@ -899,16 +899,6 @@ def test_configure_model_checkpoint(tmpdir):
  assert trainer.checkpoint_callback == callback1
  assert trainer.checkpoint_callbacks == [callback1, callback2]
 
- with pytest.warns(DeprecationWarning, match='will no longer be supported in v1.3'):
- trainer = Trainer(checkpoint_callback=callback1, **kwargs)
- assert [c for c in trainer.callbacks if isinstance(c, ModelCheckpoint)] == [callback1]
- assert trainer.checkpoint_callback == callback1
-
- with pytest.warns(DeprecationWarning, match="will no longer be supported in v1.3"):
- trainer = Trainer(checkpoint_callback=callback1, callbacks=[callback2], **kwargs)
- assert trainer.checkpoint_callback == callback2
- assert trainer.checkpoint_callbacks == [callback2, callback1]
-
  with pytest.raises(MisconfigurationException, match="checkpoint_callback=False but found ModelCheckpoint"):
  Trainer(checkpoint_callback=False, callbacks=[callback1], **kwargs)