sgl-project · zhyncs · Jul 10, 2025 · May 21, 2025 · Jun 2, 2025 · Jun 25, 2025
@@ -418,6 +418,7 @@ async def start_profile_async(obj: Optional[ProfileReqInput] = None):
 
     await _global_state.tokenizer_manager.start_profile(
         output_dir=obj.output_dir,
+        start_step=obj.start_step,
         num_steps=obj.num_steps,
         activities=obj.activities,
         with_stack=obj.with_stack,

@@ -905,6 +905,7 @@ class ProfileReqInput:
     # If set, it profile as many as this number of steps.
     # If it is set, profiling is automatically stopped after this step, and
     # the caller doesn't need to run stop_profile.
+    start_step: Optional[int] = None
     num_steps: Optional[int] = None
     activities: Optional[List[str]] = None
     profile_by_stage: bool = False
@@ -932,6 +933,7 @@ class ExpertDistributionReqOutput:
 class ProfileReq:
     type: ProfileReqType
     output_dir: Optional[str] = None
+    start_step: Optional[int] = None
     num_steps: Optional[int] = None
     activities: Optional[List[str]] = None
     profile_by_stage: bool = False

@@ -485,6 +485,8 @@ def __init__(
             enable=server_args.enable_memory_saver
         )
         self.init_profier()
+
+        # Init metrics stats
         self.init_metrics()
         self.init_kv_events(server_args.kv_events_config)
 
@@ -628,6 +630,7 @@ def init_profier(self):
         self.torch_profiler_output_dir: Optional[str] = None
         self.profiler_activities: Optional[List[str]] = None
         self.profile_id: Optional[str] = None
+        self.profiler_start_forward_ct: Optional[int] = None
         self.profiler_target_forward_ct: Optional[int] = None
         self.profiler_target_prefill_ct: Optional[int] = None
         self.profiler_target_decode_ct: Optional[int] = None
@@ -2389,9 +2392,10 @@ def slow_down(self, recv_req: SlowDownReqInput):
 
     def profile(self, recv_req: ProfileReq):
         if recv_req.type == ProfileReqType.START_PROFILE:
-            if recv_req.profile_by_stage:
+            if recv_req.profile_by_stage or recv_req.start_step:
                 return self.init_profile(
                     recv_req.output_dir,
+                    recv_req.start_step,
                     recv_req.num_steps,
                     recv_req.activities,
                     recv_req.with_stack,
@@ -2402,6 +2406,7 @@ def profile(self, recv_req: ProfileReq):
             else:
                 self.init_profile(
                     recv_req.output_dir,
+                    recv_req.start_step,
                     recv_req.num_steps,
                     recv_req.activities,
                     recv_req.with_stack,
@@ -2416,6 +2421,7 @@ def profile(self, recv_req: ProfileReq):
     def init_profile(
         self,
         output_dir: Optional[str],
+        start_step: Optional[int],
         num_steps: Optional[int],
         activities: Optional[List[str]],
         with_stack: Optional[bool],
@@ -2442,13 +2448,20 @@ def init_profile(
         self.profiler_activities = activities
         self.profile_id = profile_id
 
+        if start_step:
+            self.profiler_start_forward_ct = max(start_step, self.forward_ct + 1)
+
         if num_steps:
             self.profile_steps = num_steps
             if self.profile_by_stage:
                 self.profiler_target_prefill_ct = num_steps
                 self.profiler_target_decode_ct = num_steps
                 self.profiler_prefill_ct = 0
                 self.profiler_decode_ct = 0
+            elif start_step:
+                self.profiler_target_forward_ct = (
+                    self.profiler_start_forward_ct + num_steps
+                )
             else:
                 self.profiler_target_forward_ct = self.forward_ct + num_steps
             # The caller will be notified when reaching profiler_target_forward_ct
@@ -2521,6 +2534,7 @@ def start_profile(
 
         if "CUDA_PROFILER" in activities:
             torch.cuda.cudart().cudaProfilerStart()
+            self.profile_in_progress = True
 
         return ProfileReqOutput(success=True, message="Succeeded")
 
@@ -2584,6 +2598,7 @@ def stop_profile(
         )
         self.torch_profiler = None
         self.profile_in_progress = False
+        self.profiler_start_forward_ct = None
 
         return ProfileReqOutput(success=True, message="Succeeded.")
 
@@ -2617,6 +2632,11 @@ def _profile_batch_predicate(self, batch):
                 and self.profiler_target_forward_ct <= self.forward_ct
             ):
                 self.stop_profile()
+            if (
+                self.profiler_start_forward_ct
+                and self.profiler_start_forward_ct == self.forward_ct
+            ):
+                self.start_profile()
 
     def expert_distribution_handle(self, recv_req: ExpertDistributionReq):
         if recv_req == ExpertDistributionReq.START_RECORD:

@@ -863,6 +863,7 @@ def abort_request(self, rid: str = "", abort_all: bool = False):
     async def start_profile(
         self,
         output_dir: Optional[str] = None,
+        start_step: Optional[int] = None,
         num_steps: Optional[int] = None,
         activities: Optional[List[str]] = None,
         with_stack: Optional[bool] = None,
@@ -875,6 +876,7 @@ async def start_profile(
         req = ProfileReq(
             type=ProfileReqType.START_PROFILE,
             output_dir=output_dir,
+            start_step=start_step,
             num_steps=num_steps,
             activities=activities,
             with_stack=with_stack,

diff --git a/test/srt/run_suite.py b/test/srt/run_suite.py
@@ -87,6 +87,7 @@ class TestFile:
         TestFile("test_skip_tokenizer_init.py", 117),
         TestFile("test_srt_engine.py", 261),
         TestFile("test_srt_endpoint.py", 130),
+        TestFile("test_start_profile.py", 60),
         TestFile("test_torch_compile.py", 76),
         TestFile("test_torch_compile_moe.py", 172),
         TestFile("test_torch_native_attention_backend.py", 123),

diff --git a/test/srt/test_start_profile.py b/test/srt/test_start_profile.py
@@ -0,0 +1,115 @@
+"""
+Usage:
+python3 -m unittest test_srt_engine.TestSRTEngine.test_4_sync_async_stream_combination
+"""
+
+import os
+import shutil
+import unittest
+
+import requests
+
+from sglang.srt.utils import kill_process_tree
+from sglang.test.test_utils import (
+    DEFAULT_SMALL_MODEL_NAME_FOR_TEST,
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    CustomTestCase,
+    popen_launch_server,
+)
+
+OUTPUT_DIR = "./profiler_dir"
+
+
+class TestStartProfile(CustomTestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEFAULT_SMALL_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,
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def setUp(self):
+        self._clear_profile_dir()
+
+    def test_start_profile_1(self):
+        """Test /start_profile with start_step and num_steps argument. This have to be the first test for start_step to work"""
+        response = self._start_profile(start_step="15", num_steps=5)
+
+        self._post_request()
+
+        self._check_non_empty_profile_dir()
+
+    def test_start_profile_2(self):
+        """Test /start_profile with no argument"""
+        response = self._start_profile()
+
+        self._post_request()
+
+        # Before /stop_profile, the profile directory should be empty
+        self._check_empty_profile_dir()
+
+        # Post /stop_profile and check the profile directory is non-empty
+        response = requests.post(
+            f"{DEFAULT_URL_FOR_TEST}/stop_profile",
+        )
+        self._check_non_empty_profile_dir()
+
+    def test_start_profile_3(self):
+        """Test /start_profile with num_steps argument"""
+        response = self._start_profile(num_steps=5)
+
+        self._post_request()
+
+        self._check_non_empty_profile_dir()
+
+    def _start_profile(self, **kwargs):
+        """Start profiling with optional parameters."""
+        response = requests.post(
+            f"{DEFAULT_URL_FOR_TEST}/start_profile",
+            json=kwargs if kwargs else None,
+        )
+        self.assertEqual(response.status_code, 200)
+
+    def _post_request(self):
+        response = requests.post(
+            f"{DEFAULT_URL_FOR_TEST}/generate",
+            json={
+                "text": "The capital of France is",
+                "sampling_params": {
+                    "temperature": 0,
+                    "max_new_tokens": 32,
+                },
+            },
+        )
+        self.assertEqual(response.status_code, 200)
+
+    def _clear_profile_dir(self):
+        if os.path.isdir(OUTPUT_DIR):
+            # Remove the directory and all its contents
+            shutil.rmtree(OUTPUT_DIR)
+
+    def _check_non_empty_profile_dir(self):
+        self.assertTrue(os.path.isdir(OUTPUT_DIR), "Output directory does not exist.")
+        self.assertNotEqual(
+            len(os.listdir(OUTPUT_DIR)), 0, "Output directory is empty!"
+        )
+
+    def _check_empty_profile_dir(self):
+        if os.path.isdir(OUTPUT_DIR):
+            self.assertEqual(
+                len(os.listdir(OUTPUT_DIR)), 0, "Output directory is non-empty!"
+            )
+
+
+if __name__ == "__main__":
+    os.environ["SGLANG_TORCH_PROFILER_DIR"] = OUTPUT_DIR
+    unittest.main()