chore: import upstream snapshot with attribution

2026-07-13 12:38:16 +08:00
commit 94057c3d3e
7152 changed files with 2120455 additions and 0 deletions
@@ -0,0 +1,118 @@
+"""STANDALONE speculative-decoding server fixture.
+
+Variants combine this base with `CustomTestCase` and override class
+attributes (`attention_backend`, plus optional `speculative_eagle_topk` /
+`speculative_num_draft_tokens` / `disable_overlap` /
+`enable_deterministic_inference`) to select a backend, deterministic mode,
+and the V1 / V2 spec engine.
+
+Pure mixin (does NOT inherit `TestCase`), so unittest does not collect
+the base itself.
+"""
+
+from types import SimpleNamespace
+
+import requests
+
+from sglang.srt.environ import envs
+from sglang.srt.utils import kill_process_tree
+from sglang.test.run_eval import run_eval
+from sglang.test.test_utils import (
+    DEFAULT_DRAFT_MODEL_STANDALONE,
+    DEFAULT_TARGET_MODEL_STANDALONE,
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    popen_launch_server,
+)
+
+GSM_DATASET_PATH = None
+
+
+class StandaloneServerBase:
+    model = DEFAULT_TARGET_MODEL_STANDALONE
+    draft_model = DEFAULT_DRAFT_MODEL_STANDALONE
+    base_url = DEFAULT_URL_FOR_TEST
+    accuracy_threshold = 0.69
+    spec_decode_threshold = 3.6
+
+    # Subclasses set these:
+    attention_backend: str = ""
+    # Overlap defaults; synchronous subclasses override to (2, 7, True).
+    speculative_num_steps: int = 4
+    speculative_eagle_topk: int = 1
+    speculative_num_draft_tokens: int = 5
+    disable_overlap: bool = False
+    enable_deterministic_inference: bool = False
+
+    @classmethod
+    def get_server_args(cls):
+        assert cls.attention_backend, f"{cls.__name__} must set `attention_backend`"
+        args = [
+            "--trust-remote-code",
+            "--cuda-graph-max-bs-decode",
+            "8",
+            "--speculative-algorithm",
+            "STANDALONE",
+            "--speculative-draft-model-path",
+            DEFAULT_DRAFT_MODEL_STANDALONE,
+            "--speculative-num-steps",
+            str(cls.speculative_num_steps),
+            "--speculative-eagle-topk",
+            str(cls.speculative_eagle_topk),
+            "--speculative-num-draft-tokens",
+            str(cls.speculative_num_draft_tokens),
+            "--mem-fraction-static",
+            0.7,
+            "--attention-backend",
+            cls.attention_backend,
+        ]
+        if cls.enable_deterministic_inference:
+            args.append("--enable-deterministic-inference")
+        return args
+
+    @classmethod
+    def setUpClass(cls):
+        # disable deep gemm precompile to make launch server faster
+        # please don't do this if you want to make your inference workload faster
+        envs.SGLANG_JIT_DEEPGEMM_PRECOMPILE.set(False)
+        envs.SGLANG_ENABLE_JIT_DEEPGEMM.set(False)
+        other_args = cls.get_server_args()
+        if cls.disable_overlap:
+            other_args = other_args + ["--disable-overlap-schedule"]
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=other_args,
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        kill_process_tree(cls.process.pid)
+
+    def test_gsm8k(self):
+        requests.get(self.base_url + "/flush_cache")
+
+        args = SimpleNamespace(
+            base_url=self.base_url,
+            model=self.model,
+            eval_name="gsm8k",
+            api="completion",
+            max_tokens=512,
+            num_examples=100,
+            num_threads=128,
+            num_shots=4,
+            gsm8k_data_path=GSM_DATASET_PATH,
+        )
+        metrics = run_eval(args)
+        print(f"{metrics=}")
+
+        metric_key = "score"
+        self.assertGreaterEqual(metrics[metric_key], self.accuracy_threshold)
+
+        server_info = requests.get(self.base_url + "/server_info")
+        avg_spec_accept_length = server_info.json()["internal_states"][0][
+            "avg_spec_accept_length"
+        ]
+        print(f"{avg_spec_accept_length=}")
+        self.assertGreater(avg_spec_accept_length, self.spec_decode_threshold)