move dead sglang.test files to test/manual (#25316)

test/manual/vlm/test_mm_utils.py

@@ -0,0 +1,50 @@
+import unittest
+from unittest.mock import Mock, patch
+
+import torch
+
+from sglang.srt.managers import mm_utils, schedule_batch
+from sglang.srt.managers.schedule_batch import (
+    Modality,
+    MultimodalDataItem,
+    MultimodalInputs,
+)
+
+
+def _make_proxy_with_reconstruct_result(tensor: torch.Tensor):
+    proxy = mm_utils.CudaIpcTensorTransportProxy.__new__(
+        mm_utils.CudaIpcTensorTransportProxy
+    )
+    proxy.reconstruct_on_target_device = Mock(return_value=tensor)
+    return proxy
+
+
+class TestMultimodalInputsFromDict(unittest.TestCase):
+    def test_materialize_proxy(self):
+        feature_tensor = torch.tensor([[7.0], [8.0]], dtype=torch.float32)
+        proxy_feature = _make_proxy_with_reconstruct_result(feature_tensor)
+        mm_item = MultimodalDataItem(
+            modality=Modality.IMAGE,
+            offsets=[(0, 1), (1, 2)],
+            feature=proxy_feature,
+            model_specific_data={"image_grid_thw": [[1, 1, 1], [1, 1, 1]]},
+        )
+
+        with (
+            patch.object(schedule_batch.torch.cuda, "is_available", return_value=True),
+            patch.object(schedule_batch.torch.cuda, "current_device", return_value=0),
+            patch.object(
+                schedule_batch.envs.SGLANG_MM_BUFFER_SIZE_MB, "get", return_value=0
+            ),
+        ):
+            mm_inputs = MultimodalInputs.from_dict({"mm_items": [mm_item]})
+
+        # Splitting happens at the processor layer, not in from_dict.
+        # from_dict just reconstructs and passes through.
+        self.assertEqual(len(mm_inputs.mm_items), 1)
+        self.assertTrue(torch.equal(mm_inputs.mm_items[0].feature, feature_tensor))
+        proxy_feature.reconstruct_on_target_device.assert_called_once_with(0)
+
+
+if __name__ == "__main__":
+    unittest.main(verbosity=2)