fix ds3.2 nsa backend prefill TBO (#14901)

python/sglang/srt/layers/attention/tbo_backend.py

@@ -185,6 +185,9 @@ class TboAttnBackend(AttentionBackend):
     def forward_decode(self, *args, **kwargs):
         return self.primary.forward_decode(*args, **kwargs)
 
+    def get_indexer_metadata(self, layer_id: int, forward_batch: "ForwardBatch"):
+        return self.primary.get_indexer_metadata(layer_id, forward_batch)
+
 
 def _init_forward_metadata_cuda_graph_split(
     fn_name: str,

python/sglang/srt/models/deepseek_v2.py

@@ -67,6 +67,7 @@ from sglang.srt.layers.attention.nsa.utils import (
     is_nsa_enable_prefill_cp,
     prepare_input_dp_with_cp_dsa,
 )
+from sglang.srt.layers.attention.tbo_backend import TboAttnBackend
 from sglang.srt.layers.attention.utils import concat_and_cast_mha_k_triton
 from sglang.srt.layers.communicator import (
     LayerCommunicator,
@@ -425,7 +426,10 @@ def handle_attention_nsa(attn, forward_batch):
     Dispatch logic is centralized in NativeSparseAttnBackend.set_nsa_prefill_impl and executed
     in init_forward_metadata. Read the decision from backend.use_mha.
     """
+
     backend = forward_batch.attn_backend
+    if isinstance(backend, TboAttnBackend):  # if enable tbo, get primary backend
+        backend = backend.primary
     if hasattr(backend, "use_mha") and backend.use_mha:
         return AttnForwardMethod.MHA_ONE_SHOT
     return AttnForwardMethod.MLA
@@ -2670,7 +2674,10 @@ class DeepseekV2AttentionMLA(nn.Module):
 
         Returns: (kv_a, k_pe) both in BF16
         """
-        kv_indices = forward_batch.attn_backend.forward_metadata.page_table_1_flattened
+        backend = forward_batch.attn_backend
+        if isinstance(backend, TboAttnBackend):  # if enable tbo, get primary backend
+            backend = backend.primary
+        kv_indices = backend.forward_metadata.page_table_1_flattened
         assert (
             kv_indices is not None
         ), "page_table_1_flattened should have been generated for FP8 MHA path"

python/sglang/srt/server_args.py

@@ -727,6 +727,9 @@ class ServerArgs:
         # Handle any other necessary validations.
         self._handle_other_validations()
 
+        # Handle two-batch overlap settings.
+        self._handle_two_batch_overlap()
+
     def _handle_deprecated_args(self):
         # Handle deprecated tool call parsers
         deprecated_tool_call_parsers = {"qwen25": "qwen", "glm45": "glm"}
@@ -2392,6 +2395,12 @@ class ServerArgs:
                     self.preferred_sampling_params
                 )
 
+    def _handle_two_batch_overlap(self):
+        if self.enable_two_batch_overlap and self.moe_a2a_backend == "none":
+            raise ValueError(
+                "When enabling two batch overlap, moe_a2a_backend cannot be 'none'."
+            )
+
     @staticmethod
     def add_cli_args(parser: argparse.ArgumentParser):
 

test/srt/ep/test_deepep_large.py

@@ -5,6 +5,7 @@ import requests
 
 from sglang.srt.utils import kill_process_tree
 from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
+from sglang.test.send_one import BenchArgs, send_one_prompt
 from sglang.test.test_utils import (
     DEFAULT_DEEPEP_MODEL_NAME_FOR_TEST,
     DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
@@ -13,6 +14,8 @@ from sglang.test.test_utils import (
     popen_launch_server,
 )
 
+DEEPSEEK_V32_MODEL_PATH = "deepseek-ai/DeepSeek-V3.2-Exp"
+
 
 class TestDeepseek(CustomTestCase):
     @classmethod
@@ -153,5 +156,57 @@ class TestDeepseekMTP(CustomTestCase):
         self.assertGreater(avg_spec_accept_length, 1.85)
 
 
+class TestDeepseekV32TBO(CustomTestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEEPSEEK_V32_MODEL_PATH
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        other_args = [
+            "--trust-remote-code",
+            "--tp",
+            "8",
+            "--dp",
+            "8",
+            "--enable-dp-attention",
+            "--enable-two-batch-overlap",
+            "--moe-a2a-backend",
+            "deepep",
+            "--cuda-graph-max-bs",
+            "32",
+        ]
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=other_args,
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_a_gsm8k(
+        self,
+    ):  # Append an "a" to make this test run first (alphabetically) to warm up the server
+        args = SimpleNamespace(
+            num_shots=20,
+            data_path=None,
+            num_questions=1400,
+            parallel=1400,
+            max_new_tokens=512,
+            host="http://127.0.0.1",
+            port=int(self.base_url.split(":")[-1]),
+        )
+        metrics = run_eval_few_shot_gsm8k(args)
+        print(f"{metrics=}")
+        self.assertGreater(metrics["accuracy"], 0.92)
+
+    def test_bs_1_speed(self):
+        args = BenchArgs(port=int(self.base_url.split(":")[-1]), max_new_tokens=2048)
+        acc_length, speed = send_one_prompt(args)
+
+        print(f"{speed=:.2f}")
+
+
 if __name__ == "__main__":
     unittest.main()

test/srt/run_suite.py

@@ -186,7 +186,7 @@ suites = {
         # TestFile("ep/test_mooncake_ep_small.py", 450),
     ],
     "per-commit-8-gpu-h200-deepep": [
-        TestFile("ep/test_deepep_large.py", 338),
+        TestFile("ep/test_deepep_large.py", 563),
     ],
     "quantization_test": [
         TestFile("quant/test_awq.py", 163),