Remove dead ScheduleBatch fields and avoid inplace seq_lens bump (#30669)

2026-07-15 14:23:31 +08:00
parent a3194d3585
commit 861d97d24d
4 changed files with 92 additions and 31 deletions
@@ -0,0 +1,86 @@
+import types
+import unittest
+from unittest.mock import patch
+
+import torch
+
+from sglang.test.ci.ci_register import register_cpu_ci
+from sglang.test.test_utils import maybe_stub_sgl_kernel
+
+maybe_stub_sgl_kernel()
+
+from sglang.srt.managers.schedule_batch import ScheduleBatch  # noqa: E402
+
+register_cpu_ci(est_time=5, suite="base-a-test-cpu")
+
+
+def _make_req():
+    return types.SimpleNamespace(
+        decode_batch_idx=0,
+        kv_committed_len=3,
+        kv_allocated_len=3,
+    )
+
+
+def _make_decode_batch():
+    batch = ScheduleBatch(reqs=[_make_req(), _make_req()])
+    batch.device = "cpu"
+    batch.model_config = types.SimpleNamespace(is_encoder_decoder=False)
+    batch.enable_overlap = False
+    batch.spec_algorithm = types.SimpleNamespace(is_none=lambda: True)
+    batch.sampling_info = types.SimpleNamespace(
+        penalizer_orchestrator=types.SimpleNamespace(is_required=False)
+    )
+    batch.hisparse_coordinator = None
+    batch.seq_lens = torch.tensor([3, 5], dtype=torch.int64)
+    batch.seq_lens_cpu = torch.tensor([3, 5], dtype=torch.int64)
+    batch.orig_seq_lens = torch.tensor([3, 5], dtype=torch.int32)
+    return batch
+
+
+class TestPrepareForDecodeSeqLensOwnership(unittest.TestCase):
+    def test_decode_seq_lens_bump_is_out_of_place(self):
+        """Each prepare_for_decode call rebinds seq-lens tensors to new +1 objects without mutating the old ones."""
+        batch = _make_decode_batch()
+
+        server_args = types.SimpleNamespace(
+            enable_mamba_extra_buffer=lambda: False,
+        )
+        with (
+            patch(
+                "sglang.srt.managers.schedule_batch.alloc_for_decode",
+                return_value=torch.tensor([6, 7], dtype=torch.int64),
+            ),
+            patch(
+                "sglang.srt.managers.schedule_batch.get_server_args",
+                return_value=server_args,
+            ),
+        ):
+            for step in range(1, 3):
+                prev_seq_lens = batch.seq_lens
+                prev_seq_lens_cpu = batch.seq_lens_cpu
+                prev_orig_seq_lens = batch.orig_seq_lens
+                prev_values = (
+                    prev_seq_lens.clone(),
+                    prev_seq_lens_cpu.clone(),
+                    prev_orig_seq_lens.clone(),
+                )
+
+                batch.prepare_for_decode()
+
+                self.assertIsNot(batch.seq_lens, prev_seq_lens)
+                self.assertIsNot(batch.seq_lens_cpu, prev_seq_lens_cpu)
+                self.assertIsNot(batch.orig_seq_lens, prev_orig_seq_lens)
+                expected = torch.tensor([3 + step, 5 + step], dtype=torch.int64)
+                self.assertTrue(torch.equal(batch.seq_lens, expected))
+                self.assertTrue(torch.equal(batch.seq_lens_cpu, expected))
+                self.assertTrue(
+                    torch.equal(batch.orig_seq_lens, expected.to(torch.int32))
+                )
+                self.assertTrue(torch.equal(prev_seq_lens, prev_values[0]))
+                self.assertTrue(torch.equal(prev_seq_lens_cpu, prev_values[1]))
+                self.assertTrue(torch.equal(prev_orig_seq_lens, prev_values[2]))
+
+
+if __name__ == "__main__":
+    unittest.main()