Remove deprecated sync_batchnorm and num_nodes attributes in DDP plugins

CHANGELOG.md

@@ -72,8 +72,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed deprecated `has_prepared_data`, `has_setup_fit`, `has_setup_validate`, `has_setup_test`, `has_setup_predict`, `has_teardown_fit`, `has_teardown_validate`, `has_teardown_test` and `has_teardown_predict` datamodule lifecycle properties  ([#10350](https://github.com/PyTorchLightning/pytorch-lightning/pull/10350))
 
 
-- Removed deprecated property `is_slurm_managing_tasks` from AcceleratorConnector ([#10353](https://github.com/PyTorchLightning/pytorch-lightning/pull/10353))
+- Removed deprecated arguments `num_nodes` and `sync_batchnorm` from `DDPPlugin`, `DDPSpawnPlugin`, `DeepSpeedPlugin` ([#10357](https://github.com/PyTorchLightning/pytorch-lightning/pull/10357))
+
 
+- Removed deprecated property `is_slurm_managing_tasks` from AcceleratorConnector ([#10353](https://github.com/PyTorchLightning/pytorch-lightning/pull/10353))
 
 
 ### Fixed

pytorch_lightning/plugins/training_type/ddp.py

@@ -94,10 +94,8 @@ class DDPPlugin(ParallelPlugin):
     def __init__(
         self,
         parallel_devices: Optional[List[torch.device]] = None,
-        num_nodes: Optional[int] = None,
         cluster_environment: Optional[ClusterEnvironment] = None,
         checkpoint_io: Optional[CheckpointIO] = None,
-        sync_batchnorm: Optional[bool] = None,
         ddp_comm_state: Optional[object] = None,
         ddp_comm_hook: Optional[callable] = None,
         ddp_comm_wrapper: Optional[callable] = None,
@@ -110,18 +108,8 @@ def __init__(
             checkpoint_io=checkpoint_io,
         )
         self.interactive_ddp_procs = []
-        if num_nodes is not None:
-            rank_zero_deprecation(
-                "Argument `num_nodes` in `DDPPlugin` is deprecated in v1.4, and will be removed in v1.6."
-                " Notice that it will be overriden by the trainer setting."
-            )
-        self._num_nodes = num_nodes or 1
-        if sync_batchnorm is not None:
-            rank_zero_deprecation(
-                "Argument `sync_batchnorm` in `DDPPlugin` is deprecated in v1.4, and will be removed in v1.6."
-                " Notice that it will be overriden by the trainer setting."
-            )
-        self._sync_batchnorm = sync_batchnorm or False
+        self._num_nodes = 1
+        self._sync_batchnorm = False
         self.num_processes = len(self.parallel_devices) if self.parallel_devices is not None else 0
         self._ddp_kwargs = kwargs
         self._task_idx = None

pytorch_lightning/plugins/training_type/ddp_spawn.py

@@ -32,12 +32,7 @@
 from pytorch_lightning.plugins.io.checkpoint_plugin import CheckpointIO
 from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
 from pytorch_lightning.trainer.states import TrainerFn
-from pytorch_lightning.utilities import (
-    _TORCH_GREATER_EQUAL_1_7,
-    _TORCH_GREATER_EQUAL_1_8,
-    rank_zero_deprecation,
-    rank_zero_warn,
-)
+from pytorch_lightning.utilities import _TORCH_GREATER_EQUAL_1_7, _TORCH_GREATER_EQUAL_1_8, rank_zero_warn
 from pytorch_lightning.utilities.apply_func import apply_to_collection, move_data_to_device
 from pytorch_lightning.utilities.cloud_io import atomic_save
 from pytorch_lightning.utilities.cloud_io import load as pl_load
@@ -69,10 +64,8 @@ class DDPSpawnPlugin(ParallelPlugin):
     def __init__(
         self,
         parallel_devices: Optional[List[torch.device]] = None,
-        num_nodes: Optional[int] = None,
         cluster_environment: Optional[ClusterEnvironment] = None,
         checkpoint_io: Optional[CheckpointIO] = None,
-        sync_batchnorm: Optional[bool] = None,
         ddp_comm_state: Optional[object] = None,
         ddp_comm_hook: Optional[callable] = None,
         ddp_comm_wrapper: Optional[callable] = None,
@@ -83,18 +76,8 @@ def __init__(
             cluster_environment=cluster_environment,
             checkpoint_io=checkpoint_io,
         )
-        if num_nodes is not None:
-            rank_zero_deprecation(
-                "Argument `num_nodes` in `DDPSpawnPlugin` is deprecated in v1.4, and will be removed in v1.6. "
-                "Notice that it will be overriden by the trainer setting."
-            )
-        self._num_nodes = num_nodes or 1
-        if sync_batchnorm is not None:
-            rank_zero_deprecation(
-                "Argument `sync_batchnorm` in `DDPSpawnPlugin` is deprecated in v1.4, and will be removed in v1.6. "
-                "Notice that it will be overriden by the trainer setting."
-            )
-        self._sync_batchnorm = sync_batchnorm or False
+        self._num_nodes = 1
+        self._sync_batchnorm = False
         self._ddp_kwargs = kwargs
         self.num_processes = len(parallel_devices) if parallel_devices is not None else 0
         self.mp_queue = None

pytorch_lightning/plugins/training_type/deepspeed.py

@@ -116,7 +116,6 @@ def __init__(
         logging_batch_size_per_gpu: Union[str, int] = "auto",
         config: Optional[Union[Path, str, dict]] = None,
         logging_level: int = logging.WARN,
-        num_nodes: Optional[int] = None,
         parallel_devices: Optional[List[torch.device]] = None,
         cluster_environment: Optional[ClusterEnvironment] = None,
         loss_scale: float = 0,
@@ -273,7 +272,6 @@ def __init__(
 
         super().__init__(
             parallel_devices=parallel_devices,
-            num_nodes=num_nodes,
             cluster_environment=cluster_environment,
         )
 

tests/deprecated_api/test_remove_1-6.py

@@ -22,7 +22,7 @@
 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.plugins.training_type import DDPPlugin
 from pytorch_lightning.utilities.distributed import rank_zero_deprecation, rank_zero_warn
 from pytorch_lightning.utilities.model_helpers import is_overridden
 from pytorch_lightning.utilities.model_summary import ModelSummary
@@ -40,26 +40,6 @@ def transfer_batch_to_device(self, batch, device):
         trainer.fit(OldModel())
 
 
-def test_v1_6_0_ddp_num_nodes():
-    with pytest.deprecated_call(match="Argument `num_nodes` in `DDPPlugin` is deprecated in v1.4"):
-        DDPPlugin(num_nodes=1)
-
-
-def test_v1_6_0_ddp_sync_batchnorm():
-    with pytest.deprecated_call(match="Argument `sync_batchnorm` in `DDPPlugin` is deprecated in v1.4"):
-        DDPPlugin(sync_batchnorm=False)
-
-
-def test_v1_6_0_ddp_spawn_num_nodes():
-    with pytest.deprecated_call(match="Argument `num_nodes` in `DDPSpawnPlugin` is deprecated in v1.4"):
-        DDPSpawnPlugin(num_nodes=1)
-
-
-def test_v1_6_0_ddp_spawn_sync_batchnorm():
-    with pytest.deprecated_call(match="Argument `sync_batchnorm` in `DDPSpawnPlugin` is deprecated in v1.4"):
-        DDPSpawnPlugin(sync_batchnorm=False)
-
-
 def test_v1_6_0_reload_dataloaders_every_epoch(tmpdir):
     model = BoringModel()