test_async_llm.py 5.11 KB
Newer Older
1
2
# SPDX-License-Identifier: Apache-2.0

3
import asyncio
4
from contextlib import ExitStack
5
from typing import List, Tuple
6

zhuwenwen's avatar
zhuwenwen committed
7
import os
8
9
10
11
12
import pytest

from vllm import SamplingParams
from vllm.engine.arg_utils import AsyncEngineArgs
from vllm.platforms import current_platform
13
from vllm.sampling_params import RequestOutputKind
14
from vllm.v1.engine.async_llm import AsyncLLM
zhuwenwen's avatar
zhuwenwen committed
15
from ...utils import models_path_prefix
16
17
18
19
20

if not current_platform.is_cuda():
    pytest.skip(reason="V1 currently only supported on CUDA.",
                allow_module_level=True)

zhuwenwen's avatar
zhuwenwen committed
21
ENGINE_ARGS = AsyncEngineArgs(model=os.path.join(models_path_prefix, "meta-llama/Llama-3.2-1B"),
22
                              enforce_eager=True,
23
24
25
26
                              disable_log_requests=True)


async def generate(engine: AsyncLLM, request_id: str,
27
                   output_kind: RequestOutputKind,
28
29
                   max_tokens: int) -> Tuple[int, str]:
    count = 0
30
31
32
33
34
35
36
37
38
39
40
41
    sampling_params = SamplingParams(max_tokens=max_tokens,
                                     output_kind=output_kind,
                                     temperature=0)
    async for out in engine.generate(request_id=request_id,
                                     prompt="Hello my name is Robert and",
                                     sampling_params=sampling_params):

        num_tokens = len(out.outputs[0].token_ids)
        if output_kind == RequestOutputKind.DELTA:
            count += num_tokens
        else:
            count = num_tokens
42
43
44
45
46
47

        await asyncio.sleep(0.)

    return count, request_id


48
49
@pytest.mark.parametrize(
    "output_kind", [RequestOutputKind.DELTA, RequestOutputKind.FINAL_ONLY])
50
@pytest.mark.asyncio
51
async def test_load(monkeypatch, output_kind: RequestOutputKind):
52
53
54
    # 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.
55
    with monkeypatch.context() as m, ExitStack() as after:
56
57
58
        m.setenv("VLLM_USE_V1", "1")

        engine = AsyncLLM.from_engine_args(ENGINE_ARGS)
59
        after.callback(engine.shutdown)
60
61
62
63
64
65
66
67
68
69
70

        NUM_REQUESTS = 10000
        NUM_EXPECTED_TOKENS = 10

        request_ids = [f"request-{i}" for i in range(NUM_REQUESTS)]

        # Create concurrent requests.
        tasks = []
        for request_id in request_ids:
            tasks.append(
                asyncio.create_task(
71
72
                    generate(engine, request_id, output_kind,
                             NUM_EXPECTED_TOKENS)))
73
74

        # Confirm that we got all the EXPECTED tokens from the requests.
75
76
77
78
79
        done, pending = await asyncio.wait(tasks,
                                           return_when=asyncio.FIRST_EXCEPTION)
        for task in pending:
            task.cancel()
        for task in done:
80
            num_generated_tokens, request_id = await task
81
82
83
            assert num_generated_tokens == NUM_EXPECTED_TOKENS, (
                f"{request_id} generated {num_generated_tokens} but "
                f"expected {NUM_EXPECTED_TOKENS}")
84

85
        assert not engine.output_processor.has_unfinished_requests()
86

87

88
89
@pytest.mark.parametrize(
    "output_kind", [RequestOutputKind.DELTA, RequestOutputKind.FINAL_ONLY])
90
@pytest.mark.asyncio
91
async def test_abort(monkeypatch, output_kind: RequestOutputKind):
92

93
    with monkeypatch.context() as m, ExitStack() as after:
94
95
96
        m.setenv("VLLM_USE_V1", "1")

        engine = AsyncLLM.from_engine_args(ENGINE_ARGS)
97
        after.callback(engine.shutdown)
98
99
100
101
102
103
104
105
106
107
108
109

        NUM_REQUESTS = 100
        NUM_EXPECTED_TOKENS = 100
        REQUEST_IDS_TO_ABORT = range(1, 100, 10)

        request_ids = [f"request-{i}" for i in range(NUM_REQUESTS)]

        # Create concurrent requests.
        tasks: List[asyncio.Task] = []
        for request_id in request_ids:
            tasks.append(
                asyncio.create_task(
110
111
                    generate(engine, request_id, output_kind,
                             NUM_EXPECTED_TOKENS)))
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135

        # API server cancels requests when they disconnect.
        for idx in REQUEST_IDS_TO_ABORT:
            tasks[idx].cancel()
            await asyncio.sleep(0.1)

        # Confirm the other requests are okay.
        for idx, task in enumerate(tasks):
            # Confirm that it was actually canceled.
            if idx in REQUEST_IDS_TO_ABORT:
                with pytest.raises(asyncio.CancelledError):
                    await task
            else:
                # Otherwise, make sure the request was not impacted.
                num_generated_tokens, request_id = await task
                assert num_generated_tokens == NUM_EXPECTED_TOKENS, (
                    f"{request_id} generated {num_generated_tokens} but "
                    f"expected {NUM_EXPECTED_TOKENS}")

        assert not engine.output_processor.has_unfinished_requests()

        # Confirm we can do another generation.
        request_id = f"request-{REQUEST_IDS_TO_ABORT[0]}"
        task = asyncio.create_task(
136
            generate(engine, request_id, output_kind, NUM_EXPECTED_TOKENS))
137
138
139
        num_generated_tokens, request_id = await task
        assert num_generated_tokens == NUM_EXPECTED_TOKENS
        assert not engine.output_processor.has_unfinished_requests()