fix pyre error (#2993)

Summary:
Pull Request resolved: #2993

# context
* add/remove pyre-ignores to fix pyre error
* probably due to pyre checker version change somewhere

Reviewed By: iamzainhuda

Differential Revision: D74944268

fbshipit-source-id: 18a71a2a49aa9ee778a914d9dfba574435fda7b7

Author: TroyGarden

torchrec/distributed/test_utils/test_input.py

@@ -319,10 +319,10 @@ def generate(
             # the `_to_copy` (host-to-device) data transfer still blocks cpu execution
             float_features = float_features.pin_memory()
             label = label.pin_memory()
-            idlist_features: Optional[KeyedJaggedTensor] = (
+            idlist_features = (
                 None if idlist_features is None else idlist_features.pin_memory()
             )
-            idscore_features: Optional[KeyedJaggedTensor] = (
+            idscore_features = (
                 None if idscore_features is None else idscore_features.pin_memory()
             )
         return ModelInput(

torchrec/quant/embedding_modules.py

@@ -419,7 +419,6 @@ def __init__(
 
             emb_module = IntNBitTableBatchedEmbeddingBagsCodegen(
                 embedding_specs=embedding_specs,
-                # pyre-ignore
                 pooling_mode=pooling_type_to_pooling_mode(pooling),
                 weight_lists=weight_lists,
                 device=device,

torchrec/quant/tests/test_embedding_modules.py

@@ -289,7 +289,7 @@ def __init__(self, m: torch.nn.Module) -> None:
         )
         self.assertTrue(isinstance(qebc.m, QuantEmbeddingBagCollection))
         # feature name should be consistent with the order of grouped embeddings
-        self.assertEqual(qebc.m._feature_names, ["f1", "f3", "f2"])
+        self.assertEqual(qebc.m._feature_names, ["f1", "f3", "f2"])  # pyre-ignore[16]
 
         features = KeyedJaggedTensor(
             keys=["f1", "f2", "f3"],
@@ -822,7 +822,7 @@ def __init__(self, m: torch.nn.Module) -> None:
         )
         self.assertTrue(isinstance(qec.m, QuantEmbeddingCollection))
         # feature name should be consistent with the order of grouped embeddings
-        self.assertEqual(qec.m._feature_names, ["f1", "f3", "f2"])
+        self.assertEqual(qec.m._feature_names, ["f1", "f3", "f2"])  # pyre-ignore[16]
 
         # pyre-fixme[29]: `Union[Tensor, Module]` is not a function.
         configs = model.m.embedding_configs()

torchrec/quant/utils.py

@@ -33,7 +33,7 @@ def populate_fx_names(
         ):
             table_names = []
             for config in emb_configs:
-                table_names.append(config.name)
+                table_names.append(config.name)  # pyre-ignore[16]
             joined_table_names = ",".join(table_names)
             # pyre-fixme[16]: `Module` has no attribute `_fx_path`.
             emb_module._fx_path = f"emb_module.{joined_table_names}"