sync torchx .pyre_configuration.internal with external config and upg…

.github/workflows/pyre.yaml

@@ -8,7 +8,7 @@ on:
 
 jobs:
   pyre:
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-24.04
     steps:
       - name: Setup Python
         uses: actions/setup-python@v2

torchx/examples/apps/lightning/data.py

@@ -64,17 +64,17 @@ def __len__(self) -> int:
 # our trainer and other components that need to load data.
 
 
-# pyre-fixme[13]: Attribute `test_ds` is never initialized.
-# pyre-fixme[13]: Attribute `train_ds` is never initialized.
-# pyre-fixme[13]: Attribute `val_ds` is never initialized.
 class TinyImageNetDataModule(pl.LightningDataModule):
     """
     TinyImageNetDataModule is a pytorch LightningDataModule for the tiny
     imagenet dataset.
     """
 
+    # pyre-fixme[13]: Attribute `test_ds` is never initialized.
     train_ds: ImageFolderSamplesDataset
+    # pyre-fixme[13]: Attribute `train_ds` is never initialized.
     val_ds: ImageFolderSamplesDataset
+    # pyre-fixme[13]: Attribute `val_ds` is never initialized.
     test_ds: ImageFolderSamplesDataset
 
     def __init__(

torchx/examples/apps/tracker/main.py

@@ -99,6 +99,8 @@ def test(
         for data, target in test_loader:
             data, target = data.to(device), target.to(device)
             output = model(data)
+            # pyre-fixme[58]: `+` is not supported for operand types `int` and
+            #  `Union[bool, float, int]`.
             test_loss += F.nll_loss(
                 output, target, reduction="sum"
             ).item()  # sum up batch loss

torchx/pipelines/kfp/adapter.py

@@ -50,7 +50,9 @@ def component_spec_from_app(app: api.AppDef) -> Tuple[str, api.Role]:
 
     role = app.roles[0]
     assert (
-        role.num_replicas == 1
+        role.num_replicas
+        == 1
+        # pyre-fixme[16]: `AppDef` has no attribute `num_replicas`.
     ), f"KFP adapter only supports one replica, got {app.num_replicas}"
 
     command = [role.entrypoint, *role.args]

torchx/schedulers/aws_batch_scheduler.py

@@ -809,6 +809,8 @@ def _stream_events(
                     startFromHead=True,
                     **args,
                 )
+            # pyre-fixme[66]: Exception handler type annotation `unknown` must
+            #  extend BaseException.
             except self._log_client.exceptions.ResourceNotFoundException:
                 return []  # noqa: B901
             if response["nextForwardToken"] == next_token:

torchx/schedulers/aws_sagemaker_scheduler.py

@@ -267,9 +267,9 @@ def _submit_dryrun(
                 raise ValueError(
                     f"{key} is controlled by aws_sagemaker_scheduler and is set to {job_def[key]}"
                 )
-            value = cfg.get(key)  # pyre-ignore[26]
+            value = cfg.get(key)  # type: ignore
             if value is not None:
-                job_def[key] = value
+                job_def[key] = value  # type: ignore
 
         req = AWSSageMakerJob(
             job_name=job_name,

torchx/schedulers/ray/ray_driver.py

@@ -116,7 +116,7 @@ def load_actor_json(filename: str) -> List[RayActor]:
         return actors
 
 
-def create_placement_group_async(replicas: List[RayActor]) -> PlacementGroup:
+def create_placement_group_async(replicas: List[RayActor]) -> PlacementGroup:  # type: ignore
     """return a placement group reference, the corresponding placement group could be scheduled or pending"""
     bundles = []
     for replica in replicas: