Rename master_params to main_params

CHANGELOG.md

@@ -423,6 +423,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Deprecated passing `resume_from_checkpoint` to the `Trainer` constructor in favor of `trainer.fit(ckpt_path=)` ([#10061](https://github.com/PyTorchLightning/pytorch-lightning/pull/10061))
 
 
+
+- Deprecated `PrecisionPlugin.master_params()` in favor of `PrecisionPlugin.main_params()` ([#10105](https://github.com/PyTorchLightning/pytorch-lightning/pull/10105))
+
+
 ### Removed
 
 - Removed deprecated `metrics` ([#8586](https://github.com/PyTorchLightning/pytorch-lightning/pull/8586/))

pytorch_lightning/plugins/precision/apex_amp.py

@@ -43,7 +43,7 @@ def __init__(self, amp_level: str = "O2") -> None:
         self.amp_level = amp_level
         self._connected = False
 
-    def master_params(self, optimizer: Optimizer) -> _PARAMETERS:
+    def main_params(self, optimizer: Optimizer) -> _PARAMETERS:
         return amp.master_params(optimizer)
 
     def dispatch(self, trainer: "pl.Trainer") -> None:

pytorch_lightning/plugins/precision/precision_plugin.py

@@ -21,7 +21,7 @@
 
 import pytorch_lightning as pl
 from pytorch_lightning.core.hooks import CheckpointHooks
-from pytorch_lightning.utilities import GradClipAlgorithmType
+from pytorch_lightning.utilities import GradClipAlgorithmType, rank_zero_deprecation
 from pytorch_lightning.utilities.types import _PARAMETERS
 
 
@@ -34,7 +34,19 @@ class PrecisionPlugin(CheckpointHooks):
     precision: Union[str, int] = 32
 
     def master_params(self, optimizer: Optimizer) -> _PARAMETERS:
-        """The master params of the model.
+        """The main params of the model.
+
+        .. deprecated:: v1.5     This method is deprecated in v1.5 and will be removed in v1.6. Use :meth:`main_params`
+        instead.
+        """
+        rank_zero_deprecation(
+            f"`{self.__class__.__name__}.master_params` was deprecated in v1.5 and will be removed in v1.6."
+            f" Use `main_params` instead."
+        )
+        return self.main_params(optimizer)
+
+    def main_params(self, optimizer: Optimizer) -> _PARAMETERS:
+        """The main params of the model.
 
         Returns the plain model params here. Maybe different in other precision plugins.
         """
@@ -126,12 +138,12 @@ def clip_gradients(
 
     def clip_grad_by_value(self, optimizer: Optimizer, clip_val: Union[int, float]) -> None:
         """Clip gradients by value."""
-        parameters = self.master_params(optimizer)
+        parameters = self.main_params(optimizer)
         torch.nn.utils.clip_grad_value_(parameters, clip_value=clip_val)
 
     def clip_grad_by_norm(self, optimizer: Optimizer, clip_val: Union[int, float]) -> None:
         """Clip gradients by norm."""
-        parameters = self.master_params(optimizer)
+        parameters = self.main_params(optimizer)
         torch.nn.utils.clip_grad_norm_(parameters, clip_val)
 
     def pre_dispatch(self) -> None:

tests/deprecated_api/test_remove_1-6.py

@@ -16,10 +16,12 @@
 
 import pytest
 import torch
+from torch.optim import Optimizer
 
 from pytorch_lightning import Trainer
 from pytorch_lightning.callbacks import ModelCheckpoint
 from pytorch_lightning.callbacks.early_stopping import EarlyStopping
+from pytorch_lightning.plugins import PrecisionPlugin
 from pytorch_lightning.plugins.training_type import DDPPlugin, DDPSpawnPlugin
 from pytorch_lightning.utilities.distributed import rank_zero_deprecation, rank_zero_warn
 from pytorch_lightning.utilities.model_helpers import is_overridden
@@ -421,3 +423,8 @@ def test_v1_6_0_is_slurm_managing_tasks():
 
     with pytest.deprecated_call(match=r"`AcceleratorConnector.is_slurm_managing_tasks` was deprecated in v1.5"):
         trainer._accelerator_connector.is_slurm_managing_tasks = False
+
+
+def test_v1_6_0_master_params():
+    with pytest.deprecated_call(match="`PrecisionPlugin.master_params` was deprecated in v1.5"):
+        PrecisionPlugin().master_params(Mock(spec=Optimizer))