Split test_piecewise_cuda_graph.py to optimize CI resource usage

test/srt/run_suite.py

@@ -87,6 +87,8 @@
         TestFile("test_original_logprobs.py", 41),
         TestFile("test_page_size.py", 60),
         TestFile("test_penalty.py", 82),
+        TestFile("test_piecewise_cuda_graph_1_gpu_a.py", 460),
+        TestFile("test_piecewise_cuda_graph_1_gpu_b.py", 480),
         TestFile("test_priority_scheduling.py", 130),
         TestFile("test_pytorch_sampling_backend.py", 66),
         TestFile("test_radix_attention.py", 105),
@@ -117,7 +119,7 @@
         TestFile("test_triton_sliding_window.py", 84),
         TestFile("test_utils_update_weights.py", 29),
         TestFile("test_video_utils.py", 5),
-        TestFile("test_vision_chunked_prefill.py", 117),
+        TestFile("test_vision_chunked_prefill.py", 150),
         TestFile("test_vision_openai_server_a.py", 778),
         TestFile("test_vlm_input_format.py", 166),
         TestFile("test_modelopt_export.py", 9),
@@ -137,6 +139,7 @@
         TestFile("test_dp_attention.py", 350),
         TestFile("test_load_weights_from_remote_instance.py", 72),
         TestFile("test_patch_torch.py", 19),
+        TestFile("test_piecewise_cuda_graph_2_gpu.py", 200),
         TestFile("test_eagle_dp_attention.py", 200),
     ],
     "per-commit-4-gpu": [
@@ -145,7 +148,6 @@
         TestFile("test_local_attn.py", 411),
         TestFile("test_multi_instance_release_memory_occupation.py", 64),
         TestFile("test_pp_single_node.py", 500),
-        TestFile("test_piecewise_cuda_graph.py", 1260),
         TestFile("test_epd_disaggregation.py", 150),
     ],
     "per-commit-8-gpu-h200": [

test/srt/test_piecewise_cuda_graph_1_gpu_a.py

@@ -0,0 +1,175 @@
+import unittest
+
+from sglang.srt.utils import get_device_sm, kill_process_tree
+from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
+from sglang.test.run_eval import run_eval
+from sglang.test.test_utils import (
+    DEFAULT_MODEL_NAME_FOR_TEST,
+    DEFAULT_MODEL_NAME_FOR_TEST_MLA,
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    CustomTestCase,
+    SimpleNamespace,
+    popen_launch_server,
+    run_bench_one_batch,
+)
+
+
+class TestPiecewiseCudaGraphCorrectness(CustomTestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEFAULT_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=["--enable-piecewise-cuda-graph"],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(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)
+        self.assertGreaterEqual(metrics["score"], 0.65)
+
+
+class TestPiecewiseCudaGraphBenchmark(CustomTestCase):
+
+    def test_latency(self):
+        prefill_latency, _, _ = run_bench_one_batch(
+            DEFAULT_MODEL_NAME_FOR_TEST,
+            other_args=["--enable-piecewise-cuda-graph"],
+        )
+        self.assertLess(prefill_latency, 0.015)
+
+
+@unittest.skipIf(get_device_sm() < 100, "Test requires CUDA SM 100 or higher")
+class TestPiecewiseCudaGraphLlama31FP4(CustomTestCase):
+    """MGSM test: piecewise CUDA graph with NVFP4 Llama3.1 8B on Blackwell."""
+
+    @classmethod
+    def setUpClass(cls):
+        cls.model = "nvidia/Llama-3.1-8B-Instruct-FP4"
+        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=[
+                "--enable-piecewise-cuda-graph",
+                "--quantization",
+                "modelopt_fp4",
+                "--mem-fraction-static",
+                "0.8",
+            ],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_mgsm_accuracy(self):
+        num_examples = 1319
+        args = SimpleNamespace(
+            base_url=self.base_url,
+            model=self.model,
+            eval_name="mgsm_en",
+            num_examples=num_examples,
+            num_threads=min(num_examples, 1024),
+        )
+        metrics = run_eval(args)
+        print(f"MGSM Accuracy: {metrics['score']:.3f}")
+        self.assertGreaterEqual(metrics["score"], 0.78)
+
+
+class TestPiecewiseCudaGraphQwen3MoE(CustomTestCase):
+    """Test piecewise CUDA graph with Qwen3-Coder-30B-A3B-Instruct MoE model"""
+
+    @classmethod
+    def setUpClass(cls):
+        cls.model = "Qwen/Qwen3-Coder-30B-A3B-Instruct"
+        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=[
+                "--enable-piecewise-cuda-graph",
+                "--piecewise-cuda-graph-compiler",
+                "eager",
+            ],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_gsm8k_accuracy(self):
+        """Test GSM8K accuracy with 8-shot setting"""
+        num_examples = 2000
+
+        args = SimpleNamespace(
+            base_url=self.base_url,
+            model=self.model,
+            eval_name="mgsm_en",
+            num_examples=num_examples,
+            num_threads=min(num_examples, 1024),
+        )
+
+        metrics = run_eval(args)
+        print(f"GSM8K Accuracy: {metrics['score']:.3f}")
+
+        self.assertGreaterEqual(metrics["score"], 0.90)
+
+
+class TestPiecewiseCudaGraphDeepSeek(CustomTestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEFAULT_MODEL_NAME_FOR_TEST_MLA
+        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=[
+                "--enable-piecewise-cuda-graph",
+                "--piecewise-cuda-graph-compiler",
+                "eager",
+                "--piecewise-cuda-graph-max-tokens",
+                "4096",  # should less than max_context_len
+            ],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_gsm8k(self):
+        args = SimpleNamespace(
+            num_shots=5,
+            data_path=None,
+            num_questions=200,
+            max_new_tokens=512,
+            parallel=128,
+            host="http://127.0.0.1",
+            port=int(self.base_url.split(":")[-1]),
+        )
+        metrics = run_eval_few_shot_gsm8k(args)
+        print(metrics)
+
+        self.assertGreater(metrics["accuracy"], 0.62)
+
+
+if __name__ == "__main__":
+    unittest.main()