test_arg_utils.py 10.5 KB
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import json
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from argparse import ArgumentError
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from contextlib import nullcontext
from dataclasses import dataclass, field
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from typing import Annotated, Literal
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import pytest

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from vllm.config import CompilationConfig, config
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from vllm.engine.arg_utils import (
    EngineArgs,
    contains_type,
    get_kwargs,
    get_type,
    get_type_hints,
    is_not_builtin,
    is_type,
    literal_to_kwargs,
    optional_type,
    parse_type,
)
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from vllm.utils import FlexibleArgumentParser


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@pytest.mark.parametrize(
    ("type", "value", "expected"),
    [
        (int, "42", 42),
        (float, "3.14", 3.14),
        (str, "Hello World!", "Hello World!"),
        (json.loads, '{"foo":1,"bar":2}', {"foo": 1, "bar": 2}),
    ],
)
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def test_parse_type(type, value, expected):
    parse_type_func = parse_type(type)
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    assert parse_type_func(value) == expected
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def test_optional_type():
    optional_type_func = optional_type(int)
    assert optional_type_func("None") is None
    assert optional_type_func("42") == 42
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@pytest.mark.parametrize(
    ("type_hint", "type", "expected"),
    [
        (int, int, True),
        (int, float, False),
        (list[int], list, True),
        (list[int], tuple, False),
        (Literal[0, 1], Literal, True),
    ],
)
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def test_is_type(type_hint, type, expected):
    assert is_type(type_hint, type) == expected


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@pytest.mark.parametrize(
    ("type_hints", "type", "expected"),
    [
        ({float, int}, int, True),
        ({int, tuple}, int, True),
        ({int, tuple[int]}, int, True),
        ({int, tuple[int, ...]}, int, True),
        ({int, tuple[int]}, float, False),
        ({int, tuple[int, ...]}, float, False),
        ({str, Literal["x", "y"]}, Literal, True),
    ],
)
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def test_contains_type(type_hints, type, expected):
    assert contains_type(type_hints, type) == expected


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@pytest.mark.parametrize(
    ("type_hints", "type", "expected"),
    [
        ({int, float}, int, int),
        ({int, float}, str, None),
        ({str, Literal["x", "y"]}, Literal, Literal["x", "y"]),
    ],
)
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def test_get_type(type_hints, type, expected):
    assert get_type(type_hints, type) == expected


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@pytest.mark.parametrize(
    ("type_hints", "expected"),
    [
        ({Literal[1, 2]}, {"type": int, "choices": [1, 2]}),
        ({str, Literal["x", "y"]}, {"type": str, "metavar": ["x", "y"]}),
        ({Literal[1, "a"]}, Exception),
    ],
)
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def test_literal_to_kwargs(type_hints, expected):
    context = nullcontext()
    if expected is Exception:
        context = pytest.raises(expected)
    with context:
        assert literal_to_kwargs(type_hints) == expected


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@config
@dataclass
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class NestedConfig:
    field: int = 1
    """field"""


@config
@dataclass
class DummyConfig:
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    regular_bool: bool = True
    """Regular bool with default True"""
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    optional_bool: bool | None = None
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    """Optional bool with default None"""
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    optional_literal: Literal["x", "y"] | None = None
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    """Optional literal with default None"""
    tuple_n: tuple[int, ...] = field(default_factory=lambda: (1, 2, 3))
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    """Tuple with variable length"""
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    tuple_2: tuple[int, int] = field(default_factory=lambda: (1, 2))
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    """Tuple with fixed length"""
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    list_n: list[int] = field(default_factory=lambda: [1, 2, 3])
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    """List with variable length"""
    list_literal: list[Literal[1, 2]] = field(default_factory=list)
    """List with literal choices"""
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    list_union: list[str | type[object]] = field(default_factory=list)
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    """List with union type"""
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    literal_literal: Literal[Literal[1], Literal[2]] = 1
    """Literal of literals with default 1"""
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    json_tip: dict = field(default_factory=dict)
    """Dict which will be JSON in CLI"""
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    nested_config: NestedConfig = field(default_factory=NestedConfig)
    """Nested config"""
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@pytest.mark.parametrize(
    ("type_hint", "expected"),
    [
        (int, False),
        (DummyConfig, True),
    ],
)
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def test_is_not_builtin(type_hint, expected):
    assert is_not_builtin(type_hint) == expected


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@pytest.mark.parametrize(
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    ("type_hint", "expected"),
    [
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        (Annotated[int, "annotation"], {int}),
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        (int | None, {int, type(None)}),
        (Annotated[int | None, "annotation"], {int, type(None)}),
        (Annotated[int, "annotation"] | None, {int, type(None)}),
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    ],
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    ids=["Annotated", "or_None", "Annotated_or_None", "or_None_Annotated"],
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)
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def test_get_type_hints(type_hint, expected):
    assert get_type_hints(type_hint) == expected


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def test_get_kwargs():
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    kwargs = get_kwargs(DummyConfig)
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    print(kwargs)

    # bools should not have their type set
    assert kwargs["regular_bool"].get("type") is None
    assert kwargs["optional_bool"].get("type") is None
    # optional literals should have None as a choice
    assert kwargs["optional_literal"]["choices"] == ["x", "y", "None"]
    # tuples should have the correct nargs
    assert kwargs["tuple_n"]["nargs"] == "+"
    assert kwargs["tuple_2"]["nargs"] == 2
    # lists should work
    assert kwargs["list_n"]["type"] is int
    assert kwargs["list_n"]["nargs"] == "+"
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    # lists with literals should have the correct choices
    assert kwargs["list_literal"]["type"] is int
    assert kwargs["list_literal"]["nargs"] == "+"
    assert kwargs["list_literal"]["choices"] == [1, 2]
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    # lists with unions should become str type.
    # If not, we cannot know which type to use for parsing
    assert kwargs["list_union"]["type"] is str
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    # literals of literals should have merged choices
    assert kwargs["literal_literal"]["choices"] == [1, 2]
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    # dict should have json tip in help
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    json_tip = "Should either be a valid JSON string or JSON keys"
    assert json_tip in kwargs["json_tip"]["help"]
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    # nested config should construct the nested config
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    assert kwargs["nested_config"]["type"]('{"field": 2}') == NestedConfig(2)
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@pytest.mark.parametrize(
    ("arg", "expected"),
    [
        (None, dict()),
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        ('{"video": {"num_frames": 123} }', {"video": {"num_frames": 123}}),
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        (
            '{"video": {"num_frames": 123, "fps": 1.0, "foo": "bar"}, "image": {"foo": "bar"} }',  # noqa
            {
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                "video": {"num_frames": 123, "fps": 1.0, "foo": "bar"},
                "image": {"foo": "bar"},
            },
        ),
    ],
)
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def test_media_io_kwargs_parser(arg, expected):
    parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
    if arg is None:
        args = parser.parse_args([])
    else:
        args = parser.parse_args(["--media-io-kwargs", arg])

    assert args.media_io_kwargs == expected


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def test_compilation_config():
    parser = EngineArgs.add_cli_args(FlexibleArgumentParser())

    # default value
    args = parser.parse_args([])
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    assert args.compilation_config == CompilationConfig()
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    # set to O3
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    args = parser.parse_args(["-O0"])
    assert args.compilation_config.level == 0
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    # set to O 3 (space)
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    args = parser.parse_args(["-O", "1"])
    assert args.compilation_config.level == 1
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    # set to O 3 (equals)
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    args = parser.parse_args(["-O=2"])
    assert args.compilation_config.level == 2

    # set to O.level 3
    args = parser.parse_args(["-O.level", "3"])
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    assert args.compilation_config.level == 3

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    # set to string form of a dict
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    args = parser.parse_args(
        [
            "-O",
            '{"level": 3, "cudagraph_capture_sizes": [1, 2, 4, 8], '
            '"use_inductor": false}',
        ]
    )
    assert (
        args.compilation_config.level == 3
        and args.compilation_config.cudagraph_capture_sizes == [1, 2, 4, 8]
        and not args.compilation_config.use_inductor
    )
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    # set to string form of a dict
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    args = parser.parse_args(
        [
            "--compilation-config="
            '{"level": 3, "cudagraph_capture_sizes": [1, 2, 4, 8], '
            '"use_inductor": true}',
        ]
    )
    assert (
        args.compilation_config.level == 3
        and args.compilation_config.cudagraph_capture_sizes == [1, 2, 4, 8]
        and args.compilation_config.use_inductor
    )
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def test_prefix_cache_default():
    parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
    args = parser.parse_args([])

    engine_args = EngineArgs.from_cli_args(args=args)
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    assert not engine_args.enable_prefix_caching, "prefix caching defaults to off."
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    # with flag to turn it on.
    args = parser.parse_args(["--enable-prefix-caching"])
    engine_args = EngineArgs.from_cli_args(args=args)
    assert engine_args.enable_prefix_caching

    # with disable flag to turn it off.
    args = parser.parse_args(["--no-enable-prefix-caching"])
    engine_args = EngineArgs.from_cli_args(args=args)
    assert not engine_args.enable_prefix_caching


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@pytest.mark.parametrize(
    ("arg", "expected", "option"),
    [
        (None, None, "mm-processor-kwargs"),
        ("{}", {}, "mm-processor-kwargs"),
        ('{"num_crops": 4}', {"num_crops": 4}, "mm-processor-kwargs"),
        ('{"foo": {"bar": "baz"}}', {"foo": {"bar": "baz"}}, "mm-processor-kwargs"),
    ],
)
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def test_composite_arg_parser(arg, expected, option):
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    parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
    if arg is None:
        args = parser.parse_args([])
    else:
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        args = parser.parse_args([f"--{option}", arg])
    assert getattr(args, option.replace("-", "_")) == expected
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def test_human_readable_model_len():
    # `exit_on_error` disabled to test invalid values below
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    parser = EngineArgs.add_cli_args(FlexibleArgumentParser(exit_on_error=False))
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    args = parser.parse_args([])
    assert args.max_model_len is None

    args = parser.parse_args(["--max-model-len", "1024"])
    assert args.max_model_len == 1024

    # Lower
    args = parser.parse_args(["--max-model-len", "1m"])
    assert args.max_model_len == 1_000_000
    args = parser.parse_args(["--max-model-len", "10k"])
    assert args.max_model_len == 10_000

    # Capital
    args = parser.parse_args(["--max-model-len", "3K"])
    assert args.max_model_len == 1024 * 3
    args = parser.parse_args(["--max-model-len", "10M"])
    assert args.max_model_len == 2**20 * 10

    # Decimal values
    args = parser.parse_args(["--max-model-len", "10.2k"])
    assert args.max_model_len == 10200
    # ..truncated to the nearest int
    args = parser.parse_args(["--max-model-len", "10.212345k"])
    assert args.max_model_len == 10212

    # Invalid (do not allow decimals with binary multipliers)
    for invalid in ["1a", "pwd", "10.24", "1.23M"]:
        with pytest.raises(ArgumentError):
            args = parser.parse_args(["--max-model-len", invalid])