Remove the precision attribute from LightningModule

changelog

fix

Author: awaelchli

src/pytorch_lightning/CHANGELOG.md

@@ -107,6 +107,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Removed
 
+- Removed the `LightningModule.precision` attribute ([#16203](https://github.com/Lightning-AI/lightning/pull/16203))
+
+
 - Removed deprecated `pytorch_lightning.utilities.memory.get_gpu_memory_map` in favor of `pytorch_lightning.accelerators.cuda.get_nvidia_gpu_stats` ([#15617](https://github.com/Lightning-AI/lightning/pull/15617))
 
 

src/pytorch_lightning/core/module.py

@@ -110,9 +110,6 @@ def __init__(self, *args: Any, **kwargs: Any) -> None:
         # pointer to the trainer object
         self._trainer: Optional["pl.Trainer"] = None
 
-        # the precision used
-        self.precision: Union[int, str] = 32
-
         # optionally can be set by user
         self._example_input_array: Optional[Union[Tensor, Tuple, Dict]] = None
         self._current_fx_name: Optional[str] = None

src/pytorch_lightning/trainer/connectors/data_connector.py

@@ -144,13 +144,8 @@ def attach_data(
         elif self.trainer.state.fn == TrainerFn.PREDICTING:
             _check_dataloader_none(predict_dataloaders, self._predict_dataloader_source, self.trainer.state.fn)
 
-        # set local properties on the model
-        self._copy_trainer_model_properties(model)
-
-    def _copy_trainer_model_properties(self, model: "pl.LightningModule") -> None:
+        # Attach the trainer to the LightningModule
         model.trainer = proxy(self.trainer)
-        # for backward compatibility
-        model.precision = int(self.trainer.precision) if self.trainer.precision != "bf16" else "bf16"
 
     def attach_dataloaders(
         self,

src/pytorch_lightning/utilities/model_summary/model_summary.py

@@ -189,7 +189,7 @@ def __init__(self, model: "pl.LightningModule", max_depth: int = 1) -> None:
         self._layer_summary = self.summarize()
         # 1 byte -> 8 bits
         # TODO: how do we compute precision_megabytes in case of mixed precision?
-        precision = self._model.precision if isinstance(self._model.precision, int) else 32
+        precision = self._model.trainer.precision if isinstance(self._model.trainer.precision, int) else 32
         self._precision_megabytes = (precision / 8.0) * 1e-6
 
     @property