adapt to sglang v0.5.2rc1 on dcu

2025-09-04 15:56:33 +08:00
commit 909abb58f5
2320 changed files with 489411 additions and 0 deletions
--- a/test/srt/test_two_batch_overlap.py
+++ b/test/srt/test_two_batch_overlap.py
@@ -0,0 +1,152 @@
+import os
+import unittest
+from types import SimpleNamespace
+
+import requests
+
+from sglang.srt.model_executor.forward_batch_info import ForwardMode
+from sglang.srt.two_batch_overlap import (
+    compute_split_seq_index,
+    compute_split_token_index,
+)
+from sglang.srt.utils import kill_process_tree
+from sglang.test.run_eval import run_eval
+from sglang.test.test_utils import (
+    DEFAULT_ENABLE_THINKING_MODEL_NAME_FOR_TEST,
+    DEFAULT_MLA_MODEL_NAME_FOR_TEST,
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    popen_launch_server,
+)
+
+
+class TestTwoBatchOverlap(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=[
+                "--trust-remote-code",
+                "--tp",
+                "2",
+                "--dp",
+                "2",
+                "--enable-dp-attention",
+                "--moe-a2a-backend",
+                "deepep",
+                "--deepep-mode",
+                "normal",
+                "--disable-cuda-graph",  # DeepEP normal does not support CUDA Graph
+                "--enable-two-batch-overlap",
+            ],
+            env={"SGL_ENABLE_JIT_DEEPGEMM": "0", **os.environ},
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_generate_single_prompt(self):
+        response = requests.post(
+            self.base_url + "/generate",
+            # we use an uncommon start to minimise the chance that the cache is hit by chance
+            json={
+                "text": "_ 1+1=2, 1+2=3, 1+3=4, 1+4=",
+                "sampling_params": {"temperature": 0, "max_new_tokens": 8},
+            },
+        )
+        print(f"{response.json()=}")
+        self.assertEqual(response.json()["text"], "5, 1+5=6")
+
+    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.assertGreater(metrics["score"], 0.5)
+
+
+class TestTwoBatchOverlapUnitTest(unittest.TestCase):
+    def test_compute_split_seq_and_token_index(self):
+        for num_tokens, expect in [
+            (0, 0),
+            (100, 50),
+            (99, 49),
+        ]:
+            actual = compute_split_seq_index(
+                forward_mode=ForwardMode.DECODE,
+                num_tokens=num_tokens,
+                extend_lens=None,
+                token_num_per_seq=1,
+            )
+            self.assertEqual(actual, expect)
+
+        for extend_lens, expect in [
+            ([], (0, 0)),
+            ([42], (0, 21)),
+            ([42, 999], (1, 520)),
+            ([999, 42], (0, 520)),
+            ([498, 502], (1, 498)),
+            ([4096, 4096, 4096, 4096], (2, 8192)),
+            ([4095, 4096, 4096, 4096, 1], (2, 8191)),
+            ([1, 4095, 4096, 4096, 4096], (3, 8192)),
+            ([4097, 4096, 4096, 4095, 1], (2, 8193)),
+            ([1, 1, 1, 1, 99999], (4, 50001)),
+            ([99999, 1, 1, 1, 1], (0, 50001)),
+        ]:
+            actual_seq_idx = compute_split_seq_index(
+                forward_mode=ForwardMode.EXTEND,
+                num_tokens=None,
+                extend_lens=extend_lens,
+                token_num_per_seq=None,
+            )
+            actual_token_idx = compute_split_token_index(
+                split_seq_index=actual_seq_idx,
+                forward_mode=ForwardMode.EXTEND,
+                extend_seq_lens=extend_lens,
+                token_num_per_seq=None,
+            )
+            actual = (actual_seq_idx, actual_token_idx)
+            print(f"{extend_lens=} {expect=} {actual=}")
+            self.assertEqual(actual, expect)
+
+
+class TestQwen3TwoBatchOverlap(TestTwoBatchOverlap):
+    @classmethod
+    def setUpClass(cls):
+        cls.model = DEFAULT_ENABLE_THINKING_MODEL_NAME_FOR_TEST
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.api_key = "sk-1234"
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=[
+                "--trust-remote-code",
+                "--tp",
+                "2",
+                "--dp",
+                "2",
+                "--enable-dp-attention",
+                "--moe-a2a-backend",
+                "deepep",
+                "--deepep-mode",
+                "normal",
+                "--disable-cuda-graph",  # DeepEP normal does not support CUDA Graph
+                "--enable-two-batch-overlap",
+            ],
+            env={"SGL_ENABLE_JIT_DEEPGEMM": "0", **os.environ},
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()