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## Run benchmark | ||
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### Benchmark sglang | ||
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Run Llama-8b | ||
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```bash | ||
python3 -m sglang.launch_server --model-path meta-llama/Llama-3.1-8B-Instruct --port 30000 | ||
``` | ||
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Benchmark | ||
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```bash | ||
python3 bench_sglang.py | ||
``` |
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import argparse | ||
import json | ||
import time | ||
from typing import List, Tuple | ||
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import jsonschema | ||
from datasets import load_dataset | ||
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import sglang as sgl | ||
from sglang.test.test_utils import ( | ||
add_common_sglang_args_and_parse, | ||
select_sglang_backend, | ||
) | ||
from sglang.utils import dump_state_text | ||
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@sgl.function | ||
def schema_gen(s, message: Tuple[str, str], json_schema: str): | ||
system, user = message | ||
s += sgl.system(system) | ||
s += sgl.user(user) | ||
s += sgl.assistant( | ||
sgl.gen("json_output", temperature=0, max_tokens=256, json_schema=json_schema) | ||
) | ||
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def contains_formats(schema, formats: List[str]): | ||
if isinstance(schema, dict): | ||
if schema.get("format", None) in formats: | ||
return True | ||
for value in schema.values(): | ||
if contains_formats(value, formats): | ||
return True | ||
elif isinstance(schema, list): | ||
for item in schema: | ||
if contains_formats(item, formats): | ||
return True | ||
return False | ||
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def convert_dataset(path: str): | ||
raw_dataset = load_dataset(path) | ||
dataset = [] | ||
for data in raw_dataset["train"]: | ||
messages = data["prompt"] | ||
schema = data["schema"] | ||
obj = json.loads(schema) | ||
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# skip some corrupted examples | ||
if obj.get("type", None) is None: | ||
continue | ||
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# skip schema with format "email" | ||
# which is not supported by outlines for now | ||
if contains_formats(obj, ["email"]): | ||
continue | ||
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system = messages[0] | ||
user = messages[1] | ||
assert system["role"] == "system", "invalid role" | ||
assert user["role"] == "user", "invalid role" | ||
assert len(messages) == 2, "invalid message length" | ||
message = json.dumps(system["content"]), json.dumps(user["content"]) | ||
dataset.append( | ||
{ | ||
"message": message, | ||
"json_schema": schema, | ||
} | ||
) | ||
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return dataset | ||
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def bench_schema(args): | ||
arguments = convert_dataset(args.data_path) | ||
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if args.num_jsons < 0 or args.num_jsons > len(arguments): | ||
args.num_jsons = len(arguments) | ||
arguments = arguments[: args.num_jsons] | ||
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# Select backend | ||
backend = select_sglang_backend(args) | ||
sgl.set_default_backend(backend) | ||
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# Run requests | ||
tic = time.time() | ||
states = schema_gen.run_batch( | ||
arguments, | ||
temperature=0, | ||
num_threads=args.parallel, | ||
progress_bar=True, | ||
) | ||
latency = time.time() - tic | ||
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# Check if the outputs are valid | ||
indexs = [] | ||
for i, state in enumerate(states): | ||
try: | ||
schema = json.loads(arguments[i]["json_schema"]) | ||
obj = json.loads(state["json_output"]) | ||
assert jsonschema.validate(obj, schema) is None | ||
except Exception as e: | ||
print(e) | ||
indexs.append(i) | ||
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assert len(indexs) == 0, f"Invalid json outputs: {indexs}" | ||
return states, latency | ||
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def main(args): | ||
states, latency = bench_schema(args) | ||
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# Compute accuracy | ||
print(f"Latency: {latency:.3f}") | ||
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# Write results | ||
dump_state_text(f"tmp_output_{args.backend}.txt", states) | ||
with open(f"{args.backend}.json", "w") as fout: | ||
for state in states: | ||
fout.write(state["json_output"] + "\n") | ||
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with open(args.result_file, "a") as fout: | ||
value = { | ||
"task": "json_schema", | ||
"backend": args.backend, | ||
"latency": round(latency, 3), | ||
"num_jsons": args.num_jsons, | ||
"parallel": args.parallel, | ||
} | ||
fout.write(json.dumps(value) + "\n") | ||
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if __name__ == "__main__": | ||
parser = argparse.ArgumentParser() | ||
parser.add_argument("--data-path", type=str, default="NousResearch/json-mode-eval") | ||
parser.add_argument("--num-jsons", type=int, default=-1) | ||
args = add_common_sglang_args_and_parse(parser) | ||
main(args) |