[Simulator] Add high-fidelity CPU-based inference simulator (#33824)

Co-authored-by: zhouhaizhu.zhz <zhouhaizhu.zhz@alibaba-inc.com>
Co-authored-by: LinSiyuan814 <linsiyuan.lsy@alibaba-inc.com>
Co-authored-by: hzh0425 <hzh0425@apache.org>

tools/sglang-simulator/examples/build_example_assets.py

@@ -0,0 +1,55 @@
+#!/usr/bin/env python3
+"""Rebuild the small ML and tokenizer assets used by examples and tests."""
+
+from pathlib import Path
+
+import joblib
+import numpy as np
+from sglang_simulator.time_predictor.ml import MLTimePredictor
+from sklearn.dummy import DummyRegressor
+from tokenizers import Tokenizer
+from tokenizers.models import WordLevel
+from tokenizers.pre_tokenizers import Whitespace
+from transformers import PreTrainedTokenizerFast
+
+ASSETS = Path(__file__).parent / "assets"
+
+
+def build_ml_model() -> None:
+    model = DummyRegressor(strategy="constant", constant=0.001)
+    model.fit(np.zeros((1, len(MLTimePredictor.FEATURE_NAMES))), [0.001])
+    joblib.dump(
+        {"model": model, "features": MLTimePredictor.FEATURE_NAMES},
+        ASSETS / "model.pkl",
+    )
+
+
+def build_tokenizer() -> None:
+    tokenizer = Tokenizer(
+        WordLevel(
+            {
+                "[UNK]": 0,
+                "prefix": 1,
+                "caching": 2,
+                "latency": 3,
+                "decode": 4,
+                "token": 5,
+            },
+            unk_token="[UNK]",
+        )
+    )
+    tokenizer.pre_tokenizer = Whitespace()
+    PreTrainedTokenizerFast(
+        tokenizer_object=tokenizer,
+        unk_token="[UNK]",
+    ).save_pretrained(ASSETS / "tokenizer")
+
+
+def main() -> None:
+    ASSETS.mkdir(parents=True, exist_ok=True)
+    build_ml_model()
+    build_tokenizer()
+
+
+if __name__ == "__main__":
+    main()