Add again the DistributedDataParallel types that were lost when distributed.pyi was removed.

torch/nn/parallel/distributed.py

@@ -12,10 +12,21 @@ from collections import defaultdict, deque
 from contextlib import contextmanager
 from dataclasses import dataclass, fields, is_dataclass
 from enum import auto, Enum
-from typing import Any, Callable, Optional, TYPE_CHECKING
+from typing import (
+    Any,
+    Callable,
+    List,
+    Optional,
+    Sequence,
+    Tuple,
+    Type,
+    TYPE_CHECKING,
+    Union,
+)
 
 import torch
 import torch.distributed as dist
+from torch import device
 from torch._utils import _get_device_index
 from torch.autograd import Function, Variable
 from torch.distributed.algorithms.join import Join, Joinable, JoinHook
@@ -633,23 +644,23 @@ class DistributedDataParallel(Module, Joinable):
 
     def __init__(
         self,
-        module,
-        device_ids=None,
-        output_device=None,
-        dim=0,
-        broadcast_buffers=True,
+        module: Module,
+        device_ids: Optional[Sequence[Union[int, device]]] = None,
+        output_device: Optional[Union[int, device]] = None,
+        dim: int = 0,
+        broadcast_buffers: bool = True,
         init_sync=True,
-        process_group=None,
-        bucket_cap_mb=None,
-        find_unused_parameters=False,
-        check_reduction=False,
-        gradient_as_bucket_view=False,
-        static_graph=False,
+        process_group: Optional[Any] = None,
+        bucket_cap_mb: float = 25,
+        find_unused_parameters: bool = False,
+        check_reduction: bool = False,
+        gradient_as_bucket_view: bool = False,
+        static_graph: bool = False,
         delay_all_reduce_named_params=None,
         param_to_hook_all_reduce=None,
         mixed_precision: Optional[_MixedPrecision] = None,
         device_mesh=None,
-    ):
+    ) -> None:
         super().__init__()
         Joinable.__init__(self)
         self.logger: Optional[dist.Logger] = None