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d91766b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | from __future__ import annotations
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional
import yaml
@dataclass
class EndpointConfig:
base_url: str
model: str
engine_name: str = "sglang"
api_key: str = "EMPTY"
tokenizer_path: Optional[str] = None
trust_remote_code: bool = True
apply_chat_template: bool = False
chat_completions: bool = False
timeout: float = 600.0
verify: bool = True
@dataclass
class EvalConfig:
dataset_name: str = "gsm8k_diffulex"
dataset_limit: Optional[int] = 10
include_path: Optional[str] = None
dataset_data_files: Optional[str] = None
temperature: float = 0.0
max_tokens: int = 256
ignore_eos: bool = False
add_bos_token: Optional[bool] = None
output_dir: str = "benchmark_results/oai_lm_eval"
use_run_subdirectory: bool = True
save_results: bool = True
@classmethod
def from_dict(cls, data: Dict) -> "EvalConfig":
valid = set(cls.__dataclass_fields__)
return cls(**{k: v for k, v in data.items() if k in valid})
@dataclass
class BenchmarkConfig:
endpoint: EndpointConfig
eval: EvalConfig
@classmethod
def from_yaml(cls, path: str) -> "BenchmarkConfig":
raw = yaml.safe_load(Path(path).read_text(encoding="utf-8"))
return cls(
endpoint=EndpointConfig(**raw.get("endpoint", {})),
eval=EvalConfig.from_dict(raw.get("eval", {})),
)
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