Fix Ego4D target compatibility in local baselines

test_ego4d_local_workflow.py

@@ -181,6 +181,30 @@ class Ego4DLocalWorkflowTests(unittest.TestCase):
             if name != "baseline_seed0":
                 self.assertEqual(train[train.index("--local-modalities") + 1], name.split("_")[0])
 
+    def test_ego4d_noncanonical_binary_rows_are_preserved(self):
+        target_path = self.root / "targets" / f"{self.names[0]}.npy"
+        targets = np.load(target_path)
+        targets[3] = 0
+        targets[4] = [1, 1, 0]
+        np.save(target_path, targets)
+
+        data = load_session_data(
+            self.root / "features",
+            self.root / "targets",
+            self.names[0],
+            dataset="ego4d",
+            expected_mode="open-stream-replay",
+        )
+        self.assertTrue(torch.equal(data.targets[3], torch.zeros(3)))
+        self.assertTrue(
+            torch.equal(data.targets[4], torch.tensor([1.0, 1.0, 0.0]))
+        )
+        self.assertEqual(data.feature_metadata["num_noncanonical_target_rows"], 2)
+        output = io.StringIO()
+        with contextlib.redirect_stdout(output):
+            runner.preflight(runner.parse_args(self.runner_args(["--variants", "baseline"])))
+        self.assertIn("constraint: 2/60 ([0,0,0]=1, [1,1,0]=1)", output.getvalue())
+
     def test_family_preflight_catches_missing_test_sidecar_before_training(self):
         (self.root / "local" / f"{self.names[1]}.pt").unlink()
         with patch("run_ego4d_local_baselines.subprocess.run") as run:
@@ -219,6 +243,13 @@ class Ego4DLocalWorkflowTests(unittest.TestCase):
         self.assertFalse((self.root / "checkpoints").exists())
 
     def test_full_cpu_family_round_trip_and_summary(self):
+        # EgoSpeak's LSTR MCE consumes the released Ego4D rows as binary
+        # weights.  Preserve noncanonical rows, and do not derive transitions
+        # when that auxiliary objective is disabled.
+        target_path = self.root / "targets" / f"{self.names[0]}.npy"
+        targets = np.load(target_path)
+        targets[3] = 0
+        np.save(target_path, targets)
         self.split_feature_layout()
         env = dict(os.environ, OMP_NUM_THREADS="1", MKL_NUM_THREADS="1", OPENBLAS_NUM_THREADS="1")
         completed = subprocess.run([sys.executable, str(runner.REPO / "run_ego4d_local_baselines.py"),