vllm/benchmarks/backend_request_func.py

390 lines
14 KiB
Python

import json
import os
import sys
import time
import traceback
from dataclasses import dataclass, field
from typing import List, Optional
import aiohttp
from tqdm.asyncio import tqdm
AIOHTTP_TIMEOUT = aiohttp.ClientTimeout(total=6 * 60 * 60)
@dataclass
class RequestFuncInput:
prompt: str
api_url: str
prompt_len: int
output_len: int
model: str
best_of: int = 1
use_beam_search: bool = False
@dataclass
class RequestFuncOutput:
generated_text: str = ""
success: bool = False
latency: float = 0.0
ttft: float = 0.0 # Time to first token
itl: List[float] = field(
default_factory=list) # List of inter-token latencies
prompt_len: int = 0
error: str = ""
async def async_request_tgi(
request_func_input: RequestFuncInput,
pbar: Optional[tqdm] = None,
) -> RequestFuncOutput:
api_url = request_func_input.api_url
assert api_url.endswith("generate_stream")
async with aiohttp.ClientSession(timeout=AIOHTTP_TIMEOUT) as session:
assert not request_func_input.use_beam_search
params = {
"best_of": request_func_input.best_of,
"max_new_tokens": request_func_input.output_len,
"do_sample": True,
"temperature": 0.01, # TGI does not accept 0.0 temperature.
"top_p": 0.99, # TGI does not accept 1.0 top_p.
}
payload = {
"inputs": request_func_input.prompt,
"parameters": params,
}
output = RequestFuncOutput()
output.prompt_len = request_func_input.prompt_len
ttft = 0.0
st = time.perf_counter()
most_recent_timestamp = st
try:
async with session.post(url=api_url, json=payload) as response:
if response.status == 200:
async for chunk_bytes in response.content:
chunk_bytes = chunk_bytes.strip()
if not chunk_bytes:
continue
chunk = remove_prefix(chunk_bytes.decode("utf-8"),
"data:")
data = json.loads(chunk)
timestamp = time.perf_counter()
# First token
if ttft == 0.0:
ttft = time.perf_counter() - st
output.ttft = ttft
# Decoding phase
else:
output.itl.append(timestamp -
most_recent_timestamp)
most_recent_timestamp = timestamp
output.latency = most_recent_timestamp - st
output.success = True
output.generated_text = data["generated_text"]
except Exception:
output.success = False
exc_info = sys.exc_info()
output.error = "".join(traceback.format_exception(*exc_info))
if pbar:
pbar.update(1)
return output
async def async_request_trt_llm(
request_func_input: RequestFuncInput,
pbar: Optional[tqdm] = None,
) -> RequestFuncOutput:
api_url = request_func_input.api_url
assert api_url.endswith("generate_stream")
async with aiohttp.ClientSession(timeout=AIOHTTP_TIMEOUT) as session:
assert not request_func_input.use_beam_search
assert request_func_input.best_of == 1
payload = {
"accumulate_tokens": True,
"text_input": request_func_input.prompt,
"temperature": 0.0,
"top_p": 1.0,
"max_tokens": request_func_input.output_len,
"stream": True,
}
output = RequestFuncOutput()
output.prompt_len = request_func_input.prompt_len
ttft = 0.0
st = time.perf_counter()
most_recent_timestamp = st
try:
async with session.post(url=api_url, json=payload) as response:
if response.status == 200:
async for chunk_bytes in response.content:
chunk_bytes = chunk_bytes.strip()
if not chunk_bytes:
continue
chunk = remove_prefix(chunk_bytes.decode("utf-8"),
"data:")
data = json.loads(chunk)
output.generated_text += data["text_output"]
timestamp = time.perf_counter()
# First token
if ttft == 0.0:
ttft = time.perf_counter() - st
output.ttft = ttft
# Decoding phase
else:
output.itl.append(timestamp -
most_recent_timestamp)
most_recent_timestamp = timestamp
output.latency = most_recent_timestamp - st
output.success = True
else:
output.error = response.reason or ""
output.success = False
except Exception:
output.success = False
exc_info = sys.exc_info()
output.error = "".join(traceback.format_exception(*exc_info))
if pbar:
pbar.update(1)
return output
async def async_request_deepspeed_mii(
request_func_input: RequestFuncInput,
pbar: Optional[tqdm] = None,
) -> RequestFuncOutput:
async with aiohttp.ClientSession(timeout=AIOHTTP_TIMEOUT) as session:
assert request_func_input.best_of == 1
assert not request_func_input.use_beam_search
payload = {
"prompt": request_func_input.prompt,
"max_tokens": request_func_input.output_len,
"temperature": 0.01, # deepspeed-mii does not accept 0.0 temp.
"top_p": 1.0,
}
output = RequestFuncOutput()
output.prompt_len = request_func_input.prompt_len
# NOTE: DeepSpeed-MII doesn't support streaming as of Jan 28 2024,
# will use 0 as placeholder.
# See https://github.com/microsoft/DeepSpeed-MII/pull/311
output.ttft = 0
st = time.perf_counter()
try:
async with session.post(url=request_func_input.api_url,
json=payload) as response:
if response.status == 200:
parsed_resp = await response.json()
output.latency = time.perf_counter() - st
output.generated_text = parsed_resp["text"][0]
output.success = True
else:
output.error = response.reason or ""
output.success = False
except Exception:
output.success = False
exc_info = sys.exc_info()
output.error = "".join(traceback.format_exception(*exc_info))
if pbar:
pbar.update(1)
return output
async def async_request_openai_completions(
request_func_input: RequestFuncInput,
pbar: Optional[tqdm] = None,
) -> RequestFuncOutput:
api_url = request_func_input.api_url
assert api_url.endswith(
"v1/completions"
), "OpenAI Completions API URL must end with 'v1/completions'."
async with aiohttp.ClientSession(timeout=AIOHTTP_TIMEOUT) as session:
assert not request_func_input.use_beam_search
payload = {
"model": request_func_input.model,
"prompt": request_func_input.prompt,
"temperature": 0.0,
"best_of": request_func_input.best_of,
"max_tokens": request_func_input.output_len,
"stream": True,
}
headers = {
"Authorization": f"Bearer {os.environ.get('OPENAI_API_KEY')}"
}
output = RequestFuncOutput()
output.prompt_len = request_func_input.prompt_len
generated_text = ""
ttft = 0.0
st = time.perf_counter()
most_recent_timestamp = st
try:
async with session.post(url=api_url, json=payload,
headers=headers) as response:
if response.status == 200:
async for chunk_bytes in response.content:
chunk_bytes = chunk_bytes.strip()
if not chunk_bytes:
continue
chunk = remove_prefix(chunk_bytes.decode("utf-8"),
"data: ")
if chunk == "[DONE]":
latency = time.perf_counter() - st
else:
data = json.loads(chunk)
if data["choices"][0]["text"]:
timestamp = time.perf_counter()
# First token
if ttft == 0.0:
ttft = time.perf_counter() - st
output.ttft = ttft
# Decoding phase
# NOTE: Some completion API might have a last
# usage summary response without a token so we
# do not want to include as inter-token-latency
elif data.get("usage", None) is None:
output.itl.append(timestamp -
most_recent_timestamp)
most_recent_timestamp = timestamp
generated_text += data["choices"][0]["text"]
output.generated_text = generated_text
output.success = True
output.latency = latency
except Exception:
output.success = False
exc_info = sys.exc_info()
output.error = "".join(traceback.format_exception(*exc_info))
if pbar:
pbar.update(1)
return output
async def async_request_openai_chat_completions(
request_func_input: RequestFuncInput,
pbar: Optional[tqdm] = None,
) -> RequestFuncOutput:
api_url = request_func_input.api_url
assert api_url.endswith(
"v1/chat/completions"
), "OpenAI Chat Completions API URL must end with 'v1/chat/completions'."
async with aiohttp.ClientSession(timeout=AIOHTTP_TIMEOUT) as session:
assert not request_func_input.use_beam_search
payload = {
"model": request_func_input.model,
"messages": [
{
"role": "user",
"content": request_func_input.prompt,
},
],
"temperature": 0.0,
"max_tokens": request_func_input.output_len,
"stream": True,
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {os.environ.get('OPENAI_API_KEY')}",
}
output = RequestFuncOutput()
output.prompt_len = request_func_input.prompt_len
generated_text = ""
ttft = 0.0
st = time.perf_counter()
most_recent_timestamp = st
try:
async with session.post(url=api_url, json=payload,
headers=headers) as response:
if response.status == 200:
async for chunk_bytes in response.content:
chunk_bytes = chunk_bytes.strip()
if not chunk_bytes:
continue
chunk = remove_prefix(chunk_bytes.decode("utf-8"),
"data: ")
if chunk == "[DONE]":
latency = time.perf_counter() - st
else:
timestamp = time.perf_counter()
data = json.loads(chunk)
delta = data["choices"][0]["delta"]
if delta.get("content", None):
# First token
if ttft == 0.0:
ttft = time.perf_counter() - st
output.ttft = ttft
# Decoding phase
else:
output.itl.append(timestamp -
most_recent_timestamp)
generated_text += delta["content"]
most_recent_timestamp = timestamp
output.generated_text = generated_text
output.success = True
output.latency = latency
else:
output.error = response.reason or ""
output.success = False
except Exception:
output.success = False
exc_info = sys.exc_info()
output.error = "".join(traceback.format_exception(*exc_info))
if pbar:
pbar.update(1)
return output
# Since vllm must support Python 3.8, we can't use str.removeprefix(prefix)
# introduced in Python 3.9
def remove_prefix(text: str, prefix: str) -> str:
if text.startswith(prefix):
return text[len(prefix):]
return text
ASYNC_REQUEST_FUNCS = {
"tgi": async_request_tgi,
"vllm": async_request_openai_completions,
"lmdeploy": async_request_openai_completions,
"deepspeed-mii": async_request_deepspeed_mii,
"openai": async_request_openai_completions,
"openai-chat": async_request_openai_chat_completions,
"tensorrt-llm": async_request_trt_llm,
}