Removing unused tests (#3555)

Summary:
Pull Request resolved: #3555

These test have been skipped for quite some time now and they don't seem to imapct much.

internal
torchrec/modules/tests:test_feature_processor_ - torchrec.modules.tests.test_feature_processor_.PositionWeightedModuleTest: test_rematerialize_from_meta (844425044832114) constantly skipping since 2025-05-29,
torchrec/modules/tests:test_feature_processor_ - torchrec.modules.tests.test_feature_processor_.PositionWeightedModuleTest: test_rematerialize_from_meta (562950069172161) constantly skipping since 2025-05-29

Reviewed By: kausv

Differential Revision: D87352762

fbshipit-source-id: d6f12fa9c9b1e87d099e45bea1b5372a2f589097

Author: aliafzal

torchrec/modules/tests/test_feature_processor_.py

@@ -61,23 +61,6 @@ def test_populate_weights(self) -> None:
             weighted_features.lengths(), weighted_features_gm_script.lengths()
         )
 
-    # TODO: this test is not being run
-    # pyre-ignore
-    @unittest.skipIf(
-        torch.cuda.device_count() <= 0,
-        "Not enough GPUs, this test requires at least one GPU",
-    )
-    def test_rematerialize_from_meta(self) -> None:
-        pw = PositionWeightedModule(max_feature_length=10, device=torch.device("meta"))
-        self.assertTrue(pw.position_weight.is_meta)
-
-        # Re-materialize on cuda
-        init_parameters(pw, torch.device("cuda"))
-        self.assertTrue(not pw.position_weight.is_meta)
-        torch.testing.assert_close(
-            pw.position_weight, torch.ones_like(pw.position_weight)
-        )
-
 
 class PositionWeightedCollectionModuleTest(unittest.TestCase):
     def test_populate_weights(self) -> None:
@@ -133,26 +116,6 @@ def test_populate_weights(self) -> None:
             empty_fp_kjt.length_per_key(), empty_fp_kjt_gm_script.length_per_key()
         )
 
-    # TODO: this test is not being run
-    # pyre-ignore
-    @unittest.skipIf(
-        torch.cuda.device_count() <= 0,
-        "Not enough GPUs, this test requires at least one GPU",
-    )
-    def test_rematerialize_from_meta(self) -> None:
-        pwmc = PositionWeightedModuleCollection(
-            max_feature_lengths={"f1": 10, "f2": 10},
-            device=torch.device("meta"),
-        )
-        self.assertTrue(all(param.is_meta for param in pwmc.position_weights.values()))
-
-        # Re-materialize on cuda
-        init_parameters(pwmc, torch.device("cuda"))
-        for key, param in pwmc.position_weights.items():
-            self.assertTrue(not param.is_meta)
-            self.assertTrue(pwmc.position_weights_dict[key] is param)
-            torch.testing.assert_close(param, torch.ones_like(param))
-
     # pyre-ignore
     @unittest.skipIf(
         torch.cuda.device_count() <= 0,