chore: bump sglang-kernel version to 0.4.1.post1 (#23733)

Co-authored-by: sglang-bot <sglang-bot@users.noreply.github.com>
Co-authored-by: Kangyan Zhou <zky314343421@gmail.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

test/manual/4-gpu-models/test_qwen35_hicache.py

@@ -1,135 +0,0 @@
-"""
-# TODO: Fails on cu13 venv migration. Ref: https://github.com/sgl-project/sglang/actions/runs/24616960626/job/71980705674?pr=23119
-# Should move back to registered test after it's fixed
-"""
-
-import shutil
-import tempfile
-import unittest
-from types import SimpleNamespace
-
-import requests
-
-from sglang.srt.utils import kill_process_tree
-from sglang.test.ci.ci_register import register_cuda_ci
-
-# This eval harness applies the chat_template, which is critical for qwen3.5
-# to get good accuracy on gsm8k
-from sglang.test.run_eval import run_eval
-from sglang.test.test_utils import (
-    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-    DEFAULT_URL_FOR_TEST,
-    CustomTestCase,
-    popen_launch_server,
-)
-
-register_cuda_ci(est_time=540, suite="stage-c-test-4-gpu-h100")
-
-QWEN35_27B_MODEL = "Qwen/Qwen3.5-27B"
-ACC_THRESHOLDS = {QWEN35_27B_MODEL: {"gsm8k": 0.8}}
-
-
-class TestQwen35WithHiCache(CustomTestCase):
-    @classmethod
-    def setUpClass(cls):
-        cls.model = QWEN35_27B_MODEL
-        cls.base_url = DEFAULT_URL_FOR_TEST
-        cls.storage_dir = tempfile.mkdtemp(prefix="qwen35-hicache-")
-        env = {
-            "SGLANG_HICACHE_FILE_BACKEND_STORAGE_DIR": cls.storage_dir,
-        }
-        cls.process = popen_launch_server(
-            cls.model,
-            cls.base_url,
-            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
-            env=env,
-            other_args=[
-                "--tp-size",
-                "4",
-                "--max-mamba-cache-size",
-                "500",
-                "--max-total-tokens",
-                "120000",
-                "--chunked-prefill-size",
-                "2048",
-                "--mamba-scheduler-strategy",
-                "extra_buffer",
-                "--mamba-track-interval",
-                "128",
-                "--mamba-ssm-dtype",
-                "bfloat16",
-                "--max-running-requests",
-                "128",
-                "--reasoning-parser",
-                "qwen3",
-                "--model-loader-extra-config",
-                '{"enable_multithread_load": true,"num_threads": 64}',
-                "--hicache-mem-layout",
-                "page_first_direct",
-                "--enable-hierarchical-cache",
-                "--hicache-ratio",
-                "2",
-                "--hicache-size",
-                "0",
-                "--hicache-write-policy",
-                "write_through",
-                "--hicache-storage-backend",
-                "file",
-                "--hicache-storage-prefetch-policy",
-                "wait_complete",
-            ],
-        )
-
-    @classmethod
-    def tearDownClass(cls):
-        kill_process_tree(cls.process.pid)
-        shutil.rmtree(cls.storage_dir, ignore_errors=True)
-
-    def _run_gsm8k(self):
-        args = SimpleNamespace(
-            model=self.model,
-            eval_name="gsm8k",
-            num_shots=5,
-            num_examples=100,
-            max_tokens=16000,
-            num_threads=50,
-            repeat=1,
-            temperature=0.6,
-            top_p=0.95,
-            top_k=20,
-            base_url=self.base_url,
-            host="http://127.0.0.1",
-            port=int(self.base_url.split(":")[-1]),
-        )
-        return run_eval(args)
-
-    def test_gsm8k(self):
-        first_metrics = self._run_gsm8k()
-        print(f"first_metrics={first_metrics}")
-        self.assertGreaterEqual(
-            first_metrics["score"], ACC_THRESHOLDS[self.model]["gsm8k"]
-        )
-
-        print(f"flush cache")
-        res = requests.post(
-            f"{self.base_url}/flush_cache",
-            params={"timeout": 30},
-            timeout=40,
-        )
-        res.raise_for_status()
-
-        second_metrics = self._run_gsm8k()
-        print(f"second_metrics={second_metrics}")
-        self.assertGreaterEqual(
-            second_metrics["score"], ACC_THRESHOLDS[self.model]["gsm8k"]
-        )
-        self.assertLessEqual(
-            abs(second_metrics["score"] - first_metrics["score"]),
-            0.05,
-            f"HiCache prefetch accuracy drift too large: "
-            f"first={first_metrics['score']}, second={second_metrics['score']}",
-        )
-
-
-if __name__ == "__main__":
-    unittest.main()