[bench] Added vllm vs nano-vllm bench.
This commit is contained in:
63
bench_vllm.py
Normal file
63
bench_vllm.py
Normal file
@@ -0,0 +1,63 @@
|
||||
import os
|
||||
os.environ["VLLM_USE_V1"] = "1"
|
||||
import time
|
||||
from random import randint, seed
|
||||
from vllm import LLM, SamplingParams
|
||||
|
||||
|
||||
def bench_decode(llm, num_seqs, max_input_len, max_output_len):
|
||||
"""Benchmark decode performance (original test)"""
|
||||
seed(0)
|
||||
prompt_token_ids = [[randint(0, 10000) for _ in range(randint(100, max_input_len))] for _ in range(num_seqs)]
|
||||
sampling_params = [SamplingParams(temperature=0.6, ignore_eos=True, max_tokens=randint(100, max_output_len)) for _ in range(num_seqs)]
|
||||
prompt_token_ids = [dict(prompt_token_ids=p) for p in prompt_token_ids]
|
||||
|
||||
t = time.time()
|
||||
llm.generate(prompt_token_ids, sampling_params, use_tqdm=False)
|
||||
t = time.time() - t
|
||||
total_output_tokens = sum(sp.max_tokens for sp in sampling_params)
|
||||
throughput = total_output_tokens / t
|
||||
print(f"[Decode] Output: {total_output_tokens}tok, Time: {t:.2f}s, Throughput: {throughput:.2f}tok/s")
|
||||
|
||||
|
||||
def bench_prefill(llm, num_seqs, input_len):
|
||||
"""Benchmark prefill performance"""
|
||||
seed(0)
|
||||
# Fixed length input, minimal output to focus on prefill
|
||||
prompt_token_ids = [[randint(0, 10000) for _ in range(input_len)] for _ in range(num_seqs)]
|
||||
sampling_params = SamplingParams(temperature=0.6, ignore_eos=True, max_tokens=1)
|
||||
prompt_token_ids = [dict(prompt_token_ids=p) for p in prompt_token_ids]
|
||||
|
||||
t = time.time()
|
||||
llm.generate(prompt_token_ids, sampling_params, use_tqdm=False)
|
||||
t = time.time() - t
|
||||
total_input_tokens = num_seqs * input_len
|
||||
throughput = total_input_tokens / t
|
||||
print(f"[Prefill] Input: {total_input_tokens}tok ({num_seqs}x{input_len}), Time: {t:.2f}s, Throughput: {throughput:.2f}tok/s")
|
||||
|
||||
|
||||
def main():
|
||||
path = os.path.expanduser("~/models/Qwen3-4B-Instruct-2507/")
|
||||
llm = LLM(path, enforce_eager=False, max_model_len=4096, max_num_seqs=128, gpu_memory_utilization=0.9)
|
||||
|
||||
# Warmup
|
||||
llm.generate([dict(prompt_token_ids=[0])], SamplingParams())
|
||||
|
||||
print("=" * 60)
|
||||
print("Prefill Benchmark")
|
||||
print("=" * 60)
|
||||
bench_prefill(llm, num_seqs=1, input_len=1024)
|
||||
bench_prefill(llm, num_seqs=1, input_len=2048)
|
||||
bench_prefill(llm, num_seqs=1, input_len=4095)
|
||||
bench_prefill(llm, num_seqs=16, input_len=1024)
|
||||
bench_prefill(llm, num_seqs=64, input_len=1024)
|
||||
|
||||
print("=" * 60)
|
||||
print("Decode Benchmark")
|
||||
print("=" * 60)
|
||||
bench_decode(llm, num_seqs=1, max_input_len=1024, max_output_len=1024)
|
||||
bench_decode(llm, num_seqs=256, max_input_len=1024, max_output_len=1024)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user