Remove the Trainer.prediction_writer_callbacks property

src/lightning/pytorch/CHANGELOG.md

@@ -255,6 +255,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed the `Trainer.data_parallel` property. Use `isinstance(trainer.strategy, ParallelStrategy)` instead ([#16703](https://github.com/Lightning-AI/lightning/pull/16703))
 
 
+- Removed the `Trainer.prediction_writer_callbacks` property ([#16759](https://github.com/Lightning-AI/lightning/pull/16759))
+
+
 - Removed support for multiple optimizers in automatic optimization mode ([#16539](https://github.com/Lightning-AI/lightning/pull/16539))
   * Removed `opt_idx` argument from `BaseFinetuning.finetune_function` callback method
   * Removed `opt_idx` argument from `Callback.on_before_optimizer_step` callback method

src/lightning/pytorch/loops/epoch/prediction_epoch_loop.py

@@ -4,6 +4,7 @@
 import torch
 
 from lightning.fabric.utilities import move_data_to_device
+from lightning.pytorch.callbacks import BasePredictionWriter
 from lightning.pytorch.loops.loop import _Loop
 from lightning.pytorch.loops.progress import Progress
 from lightning.pytorch.overrides.distributed import IndexBatchSamplerWrapper
@@ -36,7 +37,8 @@ def done(self) -> bool:
     @property
     def should_store_predictions(self) -> bool:
         """Whether the predictions should be stored for later usage (e.g. aggregation or returning)"""
-        any_pred = any(cb.interval.on_epoch for cb in self.trainer.prediction_writer_callbacks)
+        prediction_writers = [cb for cb in self.trainer.callbacks if isinstance(cb, BasePredictionWriter)]
+        any_pred = any(cb.interval.on_epoch for cb in prediction_writers)
         return self.return_predictions or any_pred
 
     def run(

src/lightning/pytorch/trainer/trainer.py

@@ -41,7 +41,6 @@
 from lightning.fabric.utilities.warnings import PossibleUserWarning
 from lightning.pytorch.accelerators import Accelerator
 from lightning.pytorch.callbacks import Callback, Checkpoint, EarlyStopping, ProgressBarBase
-from lightning.pytorch.callbacks.prediction_writer import BasePredictionWriter
 from lightning.pytorch.core.datamodule import LightningDataModule
 from lightning.pytorch.loggers import Logger
 from lightning.pytorch.loggers.tensorboard import TensorBoardLogger
@@ -1305,12 +1304,6 @@ def early_stopping_callbacks(self) -> List[EarlyStopping]:
         the Trainer.callbacks list."""
         return [c for c in self.callbacks if isinstance(c, EarlyStopping)]
 
-    @property
-    def prediction_writer_callbacks(self) -> List[BasePredictionWriter]:
-        """A list of all instances of :class:`~lightning.pytorch.callbacks.prediction_writer.BasePredictionWriter`
-        found in the Trainer.callbacks list."""
-        return [cb for cb in self.callbacks if isinstance(cb, BasePredictionWriter)]
-
     @property
     def checkpoint_callback(self) -> Optional[Checkpoint]:
         """The first :class:`~lightning.pytorch.callbacks.model_checkpoint.ModelCheckpoint` callback in the