apply Black 2024 style in fbcode (4/16)

Differential Revision: D54447727

Pull Request resolved: #842

torchx/pipelines/kfp/adapter.py

@@ -74,8 +74,7 @@ class ContainerFactory(Protocol):
     kfp.dsl.ContainerOp.
     """
 
-    def __call__(self, *args: object, **kwargs: object) -> dsl.ContainerOp:
-        ...
+    def __call__(self, *args: object, **kwargs: object) -> dsl.ContainerOp: ...
 
 
 class KFPContainerFactory(ContainerFactory, Protocol):

torchx/runner/api.py

@@ -654,7 +654,7 @@ def _scheduler(self, scheduler: str) -> Scheduler:
     def _scheduler_app_id(
         self,
         app_handle: AppHandle,
-        check_session: bool = True
+        check_session: bool = True,
         # pyre-fixme[24]: SchedulerOpts is a generic, and we don't have access to the corresponding type
     ) -> Tuple[Scheduler, str, str]:
         """

torchx/schedulers/__init__.py

@@ -27,8 +27,7 @@
 
 class SchedulerFactory(Protocol):
     # pyre-fixme: Scheduler opts
-    def __call__(self, session_name: str, **kwargs: object) -> Scheduler:
-        ...
+    def __call__(self, session_name: str, **kwargs: object) -> Scheduler: ...
 
 
 def _defer_load_scheduler(path: str) -> SchedulerFactory:

torchx/schedulers/docker_scheduler.py

@@ -292,9 +292,9 @@ def _submit_dryrun(self, app: AppDef, cfg: DockerOpts) -> AppDryRunInfo[DockerJo
                 if resource.memMB >= 0:
                     # To support PyTorch dataloaders we need to set /dev/shm to
                     # larger than the 64M default.
-                    c.kwargs["mem_limit"] = c.kwargs[
-                        "shm_size"
-                    ] = f"{int(resource.memMB)}m"
+                    c.kwargs["mem_limit"] = c.kwargs["shm_size"] = (
+                        f"{int(resource.memMB)}m"
+                    )
                 if resource.cpu >= 0:
                     c.kwargs["nano_cpus"] = int(resource.cpu * 1e9)
                 if resource.gpu > 0:

torchx/schedulers/local_scheduler.py

@@ -271,21 +271,16 @@ class PopenProtocol(Protocol):
     """
 
     @property
-    def pid(self) -> int:
-        ...
+    def pid(self) -> int: ...
 
     @property
-    def returncode(self) -> int:
-        ...
+    def returncode(self) -> int: ...
 
-    def wait(self, timeout: Optional[float] = None) -> int:
-        ...
+    def wait(self, timeout: Optional[float] = None) -> int: ...
 
-    def poll(self) -> Optional[int]:
-        ...
+    def poll(self) -> Optional[int]: ...
 
-    def kill(self) -> None:
-        ...
+    def kill(self) -> None: ...
 
 
 @dataclass

torchx/schedulers/ray/ray_driver.py

@@ -148,12 +148,12 @@ def __init__(self, replicas: List[RayActor]) -> None:
         else:
             self.min_replicas = replicas[0].min_replicas  # pyre-ignore[8]
 
-        self.placement_groups: List[
-            PlacementGroup
-        ] = []  # all the placement groups, shall never change
-        self.actor_info_of_id: Dict[
-            str, ActorInfo
-        ] = {}  # store the info used to recover an actor
+        self.placement_groups: List[PlacementGroup] = (
+            []
+        )  # all the placement groups, shall never change
+        self.actor_info_of_id: Dict[str, ActorInfo] = (
+            {}
+        )  # store the info used to recover an actor
         self.active_tasks: List["ray.ObjectRef"] = []  # list of active tasks
 
         self.terminating: bool = False  # if the job has finished and being terminated

torchx/tracker/api.py

@@ -67,8 +67,7 @@ class AppRunTrackableSource:
     artifact_name: Optional[str]
 
 
-class Lineage:
-    ...
+class Lineage: ...
 
 
 class TrackerBase(ABC):
@@ -332,5 +331,4 @@ def sources(self) -> Iterable[AppRunTrackableSource]:
 
         return model_run_sources
 
-    def children(self) -> Iterable[AppRun]:
-        ...
+    def children(self) -> Iterable[AppRun]: ...