Fix triton head num (#1482)

.github/workflows/pr-test.yml

@@ -233,6 +233,12 @@ jobs:
         run: |
           cd test/srt
           python3 test_moe_eval_accuracy_large.py
+      
+      - name: Evaluate MLA Accuracy (TP=2)
+        timeout-minutes: 10
+        run: |
+          cd test/srt
+          python3 -m unittest test_mla.TestMLA.test_mmlu
 
   finish:
     needs: [

python/sglang/srt/layers/attention_backend.py

@@ -346,7 +346,9 @@ class TritonAttnBackend(AttentionBackend):
 
         self.decode_attention_fwd = decode_attention_fwd
         self.extend_attention_fwd = extend_attention_fwd
-        self.num_head = model_runner.model_config.num_attention_heads
+        self.num_head = (
+            model_runner.model_config.num_attention_heads // model_runner.tp_size
+        )
 
         if global_server_args_dict.get("triton_attention_reduce_in_fp32", False):
             self.reduce_dtype = torch.float32

python/sglang/test/test_utils.py

@@ -25,6 +25,7 @@ from sglang.utils import get_exception_traceback
 DEFAULT_FP8_MODEL_NAME_FOR_TEST = "neuralmagic/Meta-Llama-3.1-8B-FP8"
 DEFAULT_MODEL_NAME_FOR_TEST = "meta-llama/Meta-Llama-3.1-8B-Instruct"
 DEFAULT_MOE_MODEL_NAME_FOR_TEST = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+DEFAULT_MLA_MODEL_NAME_FOR_TEST = "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct"
 DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH = 600
 DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_TP1 = "meta-llama/Meta-Llama-3.1-8B-Instruct,mistralai/Mistral-7B-Instruct-v0.3,deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct,google/gemma-2-27b-it"
 DEFAULT_MODEL_NAME_FOR_NIGHTLY_EVAL_TP2 = "meta-llama/Meta-Llama-3.1-70B-Instruct,mistralai/Mixtral-8x7B-Instruct-v0.1,Qwen/Qwen2-57B-A14B-Instruct"

test/srt/test_mla.py

@@ -0,0 +1,44 @@
+import unittest
+from types import SimpleNamespace
+
+from sglang.srt.utils import kill_child_process
+from sglang.test.run_eval import run_eval
+from sglang.test.test_utils import (
+    DEFAULT_MLA_MODEL_NAME_FOR_TEST,
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    popen_launch_server,
+)
+
+
+class TestMLA(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEFAULT_MLA_MODEL_NAME_FOR_TEST
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=["--tp", "2", "--trust-remote-code"],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_child_process(cls.process.pid)
+
+    def test_mmlu(self):
+        args = SimpleNamespace(
+            base_url=self.base_url,
+            model=self.model,
+            eval_name="mmlu",
+            num_examples=64,
+            num_threads=32,
+        )
+
+        metrics = run_eval(args)
+        assert metrics["score"] >= 0.5
+
+
+if __name__ == "__main__":
+    unittest.main()