Fix typing errors in torch.distributed.nn.* directory. (#47533)

Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/47533

Test Plan: Imported from OSS

Reviewed By: walterddr

Differential Revision: D24952500

Pulled By: xuzhao9

fbshipit-source-id: 8e66784fd8f9f111b6329e0bb48d6cd61c690a4a

mypy.ini

@@ -62,6 +62,9 @@ ignore_errors = False
 [mypy-torch.distributed.distributed_c10d.*]
 ignore_errors = False
 
+[mypy-torch.distributed.nn.*]
+ignore_errors = False
+
 [mypy-torch.testing._internal.hypothesis_utils.*]
 ignore_errors = True
 

torch/distributed/nn/api/remote_module.py

@@ -20,6 +20,7 @@ from torch.distributed.nn.jit import instantiator
 from torch.distributed.rpc.utils import _parse_remote_device
 from torch.nn.parameter import Parameter
 from torch.utils.hooks import RemovableHandle
+from torch.nn import Module
 
 
 _grad_t = Union[Tuple[Tensor, ...], Tensor]
@@ -52,7 +53,7 @@ def _create_module(module_cls, args, kwargs, device="cpu", module_interface_cls=
 
 
 def _param_rrefs(module_rref, recurse):
-    ret = []
+    ret: List[rpc.RRef[Parameter]] = []
     for param in module_rref.local_value().parameters(recurse):
         ret.append(rpc.RRef(param))
     return ret
@@ -216,45 +217,45 @@ class _RemoteModule(nn.Module):
     def register_parameter(self, name: str, param: Optional[Parameter]) -> None:
         _raise_not_supported(self.register_parameter.__name__)
 
-    def add_module(self, name: str, module: Optional["Module"]) -> None:
+    def add_module(self, name: str, module: Optional[Module]) -> None:
         _raise_not_supported(self.add_module.__name__)
 
-    def apply(self: T, fn: Callable[["Module"], None]) -> T:
+    def apply(self: T, fn: Callable[[Module], None]) -> T:  # type: ignore[return]
         _raise_not_supported(self.apply.__name__)
 
-    def cuda(self: T, device: Optional[Union[int, device]] = None) -> T:
+    def cuda(self: T, device: Optional[Union[int, device]] = None) -> T:  # type: ignore[return]
         _raise_not_supported(self.cuda.__name__)
 
-    def cpu(self: T) -> T:
+    def cpu(self: T) -> T:  # type: ignore[return]
         _raise_not_supported(self.cpu.__name__)
 
-    def type(self: T, dst_type: Union[dtype, str]) -> T:
+    def type(self: T, dst_type: Union[dtype, str]) -> T:  # type: ignore[return]
         _raise_not_supported(self.type.__name__)
 
-    def float(self: T) -> T:
+    def float(self: T) -> T:  # type: ignore[return]
         _raise_not_supported(self.float.__name__)
 
-    def double(self: T) -> T:
+    def double(self: T) -> T:  # type: ignore[return]
         _raise_not_supported(self.double.__name__)
 
-    def half(self: T) -> T:
+    def half(self: T) -> T:  # type: ignore[return]
         _raise_not_supported(self.half.__name__)
 
-    def bfloat16(self: T) -> T:
+    def bfloat16(self: T) -> T:  # type: ignore[return]
         _raise_not_supported(self.bfloat16.__name__)
 
-    def to(self, *args, **kwargs):
+    def to(self, *args, **kwargs) -> T:  # type: ignore[return]
         _raise_not_supported(self.to.__name__)
 
-    def register_backward_hook(
-        self, hook: Callable[["Module", _grad_t, _grad_t], Union[None, Tensor]]
+    def register_backward_hook(  # type: ignore[return]
+        self, hook: Callable[[Module, _grad_t, _grad_t], Union[None, Tensor]]
     ) -> RemovableHandle:
         _raise_not_supported(self.register_backward_hook.__name__)
 
-    def register_forward_pre_hook(self, hook: Callable[..., None]) -> RemovableHandle:
+    def register_forward_pre_hook(self, hook: Callable[..., None]) -> RemovableHandle:  # type: ignore[return]
         _raise_not_supported(self.register_forward_pre_hook.__name__)
 
-    def register_forward_hook(self, hook: Callable[..., None]) -> RemovableHandle:
+    def register_forward_hook(self, hook: Callable[..., None]) -> RemovableHandle:  # type: ignore[return]
         _raise_not_supported(self.register_forward_hook.__name__)
 
     def state_dict(self, destination=None, prefix="", keep_vars=False):
@@ -272,47 +273,47 @@ class _RemoteModule(nn.Module):
             "Method ``parameters`` not supported for RemoteModule. Please use ``remote_parameters`` instead."
         )
 
-    def named_parameters(
+    def named_parameters(  # type: ignore[return]
         self, prefix: str = "", recurse: bool = True
     ) -> Iterator[Tuple[str, Tensor]]:
         _raise_not_supported(self.named_parameters.__name__)
 
-    def buffers(self, recurse: bool = True) -> Iterator[Tensor]:
+    def buffers(self, recurse: bool = True) -> Iterator[Tensor]:  # type: ignore[return]
         _raise_not_supported(self.buffers.__name__)
 
-    def named_buffers(
+    def named_buffers(  # type: ignore[return]
         self, prefix: str = "", recurse: bool = True
     ) -> Iterator[Tuple[str, Tensor]]:
         _raise_not_supported(self.named_buffers.__name__)
 
-    def children(self) -> Iterator["Module"]:
+    def children(self) -> Iterator[Module]:  # type: ignore[return]
         _raise_not_supported(self.children.__name__)
 
-    def named_children(self) -> Iterator[Tuple[str, "Module"]]:
+    def named_children(self) -> Iterator[Tuple[str, Module]]:  # type: ignore[return]
         _raise_not_supported(self.named_children.__name__)
 
-    def modules(self) -> Iterator["Module"]:
+    def modules(self) -> Iterator[Module]:  # type: ignore[return]
         _raise_not_supported(self.modules.__name__)
 
-    def named_modules(self, memo: Optional[Set["Module"]] = None, prefix: str = ""):
+    def named_modules(self, memo: Optional[Set[Module]] = None, prefix: str = ""):
         _raise_not_supported(self.named_modules.__name__)
 
-    def train(self: T, mode: bool = True) -> T:
+    def train(self: T, mode: bool = True) -> T:  # type: ignore[return]
         _raise_not_supported(self.train.__name__)
 
-    def eval(self: T) -> T:
+    def eval(self: T) -> T:  # type: ignore[return]
         _raise_not_supported(self.eval.__name__)
 
-    def requires_grad_(self: T, requires_grad: bool = True) -> T:
+    def requires_grad_(self: T, requires_grad: bool = True) -> T:  # type: ignore[return]
         _raise_not_supported(self.requires_grad_.__name__)
 
-    def zero_grad(self) -> None:
+    def zero_grad(self, set_to_none: bool = False) -> None:
         _raise_not_supported(self.zero_grad.__name__)
 
-    def share_memory(self: T) -> T:
+    def share_memory(self: T) -> T:  # type: ignore[return]
         _raise_not_supported(self.share_memory.__name__)
 
-    def extra_repr(self) -> str:
+    def extra_repr(self) -> str:  # type: ignore[return]
         _raise_not_supported(self.extra_repr.__name__)
 
 

torch/distributed/nn/jit/instantiator.py

@@ -6,6 +6,7 @@ import sys
 import tempfile
 
 import torch
+from typing import Optional
 from torch.distributed.nn.jit.templates.remote_module_template import (
     REMOTE_MODULE_TEMPLATE,
 )
@@ -37,11 +38,12 @@ def get_arg_return_types_from_interface(module_interface):
 
     arg_str_list = []
     arg_type_str_list = []
+    assert method_schema is not None
     for argument in method_schema.arguments:
         arg_str_list.append(argument.name)
 
         if argument.has_default_value():
-            default_value_str = " = {}".format(argument.default)
+            default_value_str = " = {}".format(argument.default_value)
         else:
             default_value_str = ""
         arg_type_str = "{name}: {type}{default_value}".format(
@@ -63,6 +65,7 @@ def get_arg_return_types_from_interface(module_interface):
 
 
 def _write(out_path, text):
+    old_text: Optional[str]
     try:
         with open(out_path, "r") as f:
             old_text = f.read()