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[V1][Tests] Adding additional testing for multimodal models to V1 (#13308)

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Signed-off-by: andoorve <37849411+andoorve@users.noreply.github.com>
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Murali Andoorveedu 2025-02-18 09:53:14 -08:00 committed by GitHub
parent 7b203b7694
commit a4d577b379
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1 changed files with 48 additions and 12 deletions
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60
tests/v1/engine/test_async_llm.py
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@ -8,7 +8,9 @@ import pytest
from tests.v1.engine.utils import PLP_APC_UNSUPPORTED_MSG
from vllm import SamplingParams
from vllm.assets.image import ImageAsset
from vllm.engine.arg_utils import AsyncEngineArgs
from vllm.inputs import PromptType
from vllm.platforms import current_platform
from vllm.sampling_params import RequestOutputKind
from vllm.v1.engine.async_llm import AsyncLLM
@ -17,13 +19,32 @@ if not current_platform.is_cuda():
pytest.skip(reason="V1 currently only supported on CUDA.",
allow_module_level=True)
ENGINE_ARGS = AsyncEngineArgs(model="meta-llama/Llama-3.2-1B-Instruct",
enforce_eager=True,
disable_log_requests=True)
TEXT_ENGINE_ARGS = AsyncEngineArgs(model="meta-llama/Llama-3.2-1B-Instruct",
enforce_eager=True,
disable_log_requests=True)
VISION_ENGINE_ARGS = AsyncEngineArgs(model="Qwen/Qwen2-VL-2B-Instruct",
enforce_eager=True,
disable_log_requests=True)
TEXT_PROMPT = "Hello my name is Robert and"
VISION_PROMPT_TEMPLATE = (
"<|im_start|>system\nYou are a helpful assistant.<|im_end|>"
"\n<|im_start|>user\n<|vision_start|><|image_pad|><|vision_end|>"
"What is in the image?<|im_end|>\n"
"<|im_start|>assistant\n")
VISION_PROMPT = {
"prompt": VISION_PROMPT_TEMPLATE,
"multi_modal_data": {
"image": ImageAsset("stop_sign").pil_image
}
}
async def generate(engine: AsyncLLM,
request_id: str,
prompt: PromptType,
output_kind: RequestOutputKind,
max_tokens: int,
prompt_logprobs: Optional[int] = None) -> Tuple[int, str]:
@ -32,11 +53,12 @@ async def generate(engine: AsyncLLM,
count = 0
sampling_params = SamplingParams(max_tokens=max_tokens,
ignore_eos=True,
output_kind=output_kind,
temperature=0,
prompt_logprobs=prompt_logprobs)
async for out in engine.generate(request_id=request_id,
prompt="Hello my name is Robert and",
prompt=prompt,
sampling_params=sampling_params):
num_tokens = len(out.outputs[0].token_ids)
@ -74,6 +96,7 @@ async def test_async_llm_refuses_prompt_logprobs_with_apc(
await asyncio.create_task(
generate(engine,
"request-0",
TEXT_PROMPT,
output_kind,
10,
prompt_logprobs=5))
@ -86,18 +109,24 @@ async def test_async_llm_refuses_prompt_logprobs_with_apc(
@pytest.mark.parametrize(
"output_kind", [RequestOutputKind.DELTA, RequestOutputKind.FINAL_ONLY])
@pytest.mark.parametrize("engine_args_and_prompt",
[(TEXT_ENGINE_ARGS, TEXT_PROMPT),
(VISION_ENGINE_ARGS, VISION_PROMPT)])
@pytest.mark.asyncio
async def test_load(monkeypatch, output_kind: RequestOutputKind):
async def test_load(monkeypatch, output_kind: RequestOutputKind,
engine_args_and_prompt: Tuple[AsyncEngineArgs,
PromptType]):
# TODO(rickyx): Remove monkeypatch once we have a better way to test V1
# so that in the future when we switch, we don't have to change all the
# tests.
with monkeypatch.context() as m, ExitStack() as after:
m.setenv("VLLM_USE_V1", "1")
engine_args, prompt = engine_args_and_prompt
engine = AsyncLLM.from_engine_args(ENGINE_ARGS)
engine = AsyncLLM.from_engine_args(engine_args)
after.callback(engine.shutdown)
NUM_REQUESTS = 10000
NUM_REQUESTS = 100
NUM_EXPECTED_TOKENS = 10
request_ids = [f"request-{i}" for i in range(NUM_REQUESTS)]
@ -107,7 +136,7 @@ async def test_load(monkeypatch, output_kind: RequestOutputKind):
for request_id in request_ids:
tasks.append(
asyncio.create_task(
generate(engine, request_id, output_kind,
generate(engine, request_id, prompt, output_kind,
NUM_EXPECTED_TOKENS)))
# Confirm that we got all the EXPECTED tokens from the requests.
@ -126,13 +155,19 @@ async def test_load(monkeypatch, output_kind: RequestOutputKind):
@pytest.mark.parametrize(
"output_kind", [RequestOutputKind.DELTA, RequestOutputKind.FINAL_ONLY])
@pytest.mark.parametrize("engine_args_and_prompt",
[(TEXT_ENGINE_ARGS, TEXT_PROMPT),
(VISION_ENGINE_ARGS, VISION_PROMPT)])
@pytest.mark.asyncio
async def test_abort(monkeypatch, output_kind: RequestOutputKind):
async def test_abort(monkeypatch, output_kind: RequestOutputKind,
engine_args_and_prompt: Tuple[AsyncEngineArgs,
PromptType]):
with monkeypatch.context() as m, ExitStack() as after:
m.setenv("VLLM_USE_V1", "1")
engine_args, prompt = engine_args_and_prompt
engine = AsyncLLM.from_engine_args(ENGINE_ARGS)
engine = AsyncLLM.from_engine_args(engine_args)
after.callback(engine.shutdown)
NUM_REQUESTS = 100
@ -146,7 +181,7 @@ async def test_abort(monkeypatch, output_kind: RequestOutputKind):
for request_id in request_ids:
tasks.append(
asyncio.create_task(
generate(engine, request_id, output_kind,
generate(engine, request_id, prompt, output_kind,
NUM_EXPECTED_TOKENS)))
# API server cancels requests when they disconnect.
@ -172,7 +207,8 @@ async def test_abort(monkeypatch, output_kind: RequestOutputKind):
# Confirm we can do another generation.
request_id = f"request-{REQUEST_IDS_TO_ABORT[0]}"
task = asyncio.create_task(
generate(engine, request_id, output_kind, NUM_EXPECTED_TOKENS))
generate(engine, request_id, prompt, output_kind,
NUM_EXPECTED_TOKENS))
num_generated_tokens, request_id = await task
assert num_generated_tokens == NUM_EXPECTED_TOKENS
assert not engine.output_processor.has_unfinished_requests()