mirror of
https://git.datalinker.icu/vllm-project/vllm.git
synced 2025-12-24 03:45:31 +08:00
518 lines
17 KiB
Python
518 lines
17 KiB
Python
# SPDX-License-Identifier: Apache-2.0
|
|
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
|
|
|
import json
|
|
from argparse import ArgumentError
|
|
from contextlib import nullcontext
|
|
from dataclasses import dataclass, field
|
|
from typing import Annotated, Literal
|
|
|
|
import pytest
|
|
|
|
from vllm.config import AttentionConfig, CompilationConfig, config
|
|
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,
|
|
)
|
|
from vllm.utils.argparse_utils import FlexibleArgumentParser
|
|
|
|
|
|
@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}),
|
|
],
|
|
)
|
|
def test_parse_type(type, value, expected):
|
|
parse_type_func = parse_type(type)
|
|
assert parse_type_func(value) == expected
|
|
|
|
|
|
def test_optional_type():
|
|
optional_type_func = optional_type(int)
|
|
assert optional_type_func("None") is None
|
|
assert optional_type_func("42") == 42
|
|
|
|
|
|
@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),
|
|
],
|
|
)
|
|
def test_is_type(type_hint, type, expected):
|
|
assert is_type(type_hint, type) == expected
|
|
|
|
|
|
@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),
|
|
],
|
|
)
|
|
def test_contains_type(type_hints, type, expected):
|
|
assert contains_type(type_hints, type) == expected
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
("type_hints", "type", "expected"),
|
|
[
|
|
({int, float}, int, int),
|
|
({int, float}, str, None),
|
|
({str, Literal["x", "y"]}, Literal, Literal["x", "y"]),
|
|
],
|
|
)
|
|
def test_get_type(type_hints, type, expected):
|
|
assert get_type(type_hints, type) == expected
|
|
|
|
|
|
@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),
|
|
],
|
|
)
|
|
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
|
|
|
|
|
|
@config
|
|
@dataclass
|
|
class NestedConfig:
|
|
field: int = 1
|
|
"""field"""
|
|
|
|
|
|
@config
|
|
@dataclass
|
|
class DummyConfig:
|
|
regular_bool: bool = True
|
|
"""Regular bool with default True"""
|
|
optional_bool: bool | None = None
|
|
"""Optional bool with default None"""
|
|
optional_literal: Literal["x", "y"] | None = None
|
|
"""Optional literal with default None"""
|
|
tuple_n: tuple[int, ...] = field(default_factory=lambda: (1, 2, 3))
|
|
"""Tuple with variable length"""
|
|
tuple_2: tuple[int, int] = field(default_factory=lambda: (1, 2))
|
|
"""Tuple with fixed length"""
|
|
list_n: list[int] = field(default_factory=lambda: [1, 2, 3])
|
|
"""List with variable length"""
|
|
list_literal: list[Literal[1, 2]] = field(default_factory=list)
|
|
"""List with literal choices"""
|
|
list_union: list[str | type[object]] = field(default_factory=list)
|
|
"""List with union type"""
|
|
set_n: set[int] = field(default_factory=lambda: {1, 2, 3})
|
|
"""Set with variable length"""
|
|
literal_literal: Literal[Literal[1], Literal[2]] = 1
|
|
"""Literal of literals with default 1"""
|
|
json_tip: dict = field(default_factory=dict)
|
|
"""Dict which will be JSON in CLI"""
|
|
nested_config: NestedConfig = field(default_factory=NestedConfig)
|
|
"""Nested config"""
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
("type_hint", "expected"),
|
|
[
|
|
(int, False),
|
|
(DummyConfig, True),
|
|
],
|
|
)
|
|
def test_is_not_builtin(type_hint, expected):
|
|
assert is_not_builtin(type_hint) == expected
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
("type_hint", "expected"),
|
|
[
|
|
(Annotated[int, "annotation"], {int}),
|
|
(int | None, {int, type(None)}),
|
|
(Annotated[int | None, "annotation"], {int, type(None)}),
|
|
(Annotated[int, "annotation"] | None, {int, type(None)}),
|
|
],
|
|
ids=["Annotated", "or_None", "Annotated_or_None", "or_None_Annotated"],
|
|
)
|
|
def test_get_type_hints(type_hint, expected):
|
|
assert get_type_hints(type_hint) == expected
|
|
|
|
|
|
def test_get_kwargs():
|
|
kwargs = get_kwargs(DummyConfig)
|
|
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"] == "+"
|
|
# 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]
|
|
# 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
|
|
# sets should work like lists
|
|
assert kwargs["set_n"]["type"] is int
|
|
assert kwargs["set_n"]["nargs"] == "+"
|
|
# literals of literals should have merged choices
|
|
assert kwargs["literal_literal"]["choices"] == [1, 2]
|
|
# dict should have json tip in help
|
|
json_tip = "Should either be a valid JSON string or JSON keys"
|
|
assert json_tip in kwargs["json_tip"]["help"]
|
|
# nested config should construct the nested config
|
|
assert kwargs["nested_config"]["type"]('{"field": 2}') == NestedConfig(2)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
("arg", "expected"),
|
|
[
|
|
(None, dict()),
|
|
('{"video": {"num_frames": 123} }', {"video": {"num_frames": 123}}),
|
|
(
|
|
'{"video": {"num_frames": 123, "fps": 1.0, "foo": "bar"}, "image": {"foo": "bar"} }', # noqa
|
|
{
|
|
"video": {"num_frames": 123, "fps": 1.0, "foo": "bar"},
|
|
"image": {"foo": "bar"},
|
|
},
|
|
),
|
|
],
|
|
)
|
|
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
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
("args", "expected"),
|
|
[
|
|
(["-O", "1"], "1"),
|
|
(["-O", "2"], "2"),
|
|
(["-O", "3"], "3"),
|
|
(["-O0"], "0"),
|
|
(["-O1"], "1"),
|
|
(["-O2"], "2"),
|
|
(["-O3"], "3"),
|
|
],
|
|
)
|
|
def test_optimization_level(args, expected):
|
|
"""
|
|
Test space-separated optimization levels (-O 1, -O 2, -O 3) map to
|
|
optimization_level.
|
|
"""
|
|
parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
|
|
parsed_args = parser.parse_args(args)
|
|
assert parsed_args.optimization_level == expected
|
|
assert parsed_args.compilation_config.mode is None
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
("args", "expected"),
|
|
[
|
|
(["-cc.mode=0"], 0),
|
|
(["-cc.mode=1"], 1),
|
|
(["-cc.mode=2"], 2),
|
|
(["-cc.mode=3"], 3),
|
|
],
|
|
)
|
|
def test_mode_parser(args, expected):
|
|
"""
|
|
Test compilation config modes (-cc.mode=int) map to compilation_config.
|
|
"""
|
|
parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
|
|
parsed_args = parser.parse_args(args)
|
|
assert parsed_args.compilation_config.mode == expected
|
|
|
|
|
|
def test_compilation_config():
|
|
parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
|
|
|
|
# default value
|
|
args = parser.parse_args([])
|
|
assert args.compilation_config == CompilationConfig()
|
|
|
|
# set to string form of a dict
|
|
args = parser.parse_args(
|
|
[
|
|
"-cc",
|
|
'{"mode": 3, "cudagraph_capture_sizes": [1, 2, 4, 8], "backend": "eager"}',
|
|
]
|
|
)
|
|
assert (
|
|
args.compilation_config.mode == 3
|
|
and args.compilation_config.cudagraph_capture_sizes == [1, 2, 4, 8]
|
|
and args.compilation_config.backend == "eager"
|
|
)
|
|
|
|
# set to string form of a dict
|
|
args = parser.parse_args(
|
|
[
|
|
"--compilation-config="
|
|
'{"mode": 3, "cudagraph_capture_sizes": [1, 2, 4, 8], '
|
|
'"backend": "inductor"}',
|
|
]
|
|
)
|
|
assert (
|
|
args.compilation_config.mode == 3
|
|
and args.compilation_config.cudagraph_capture_sizes == [1, 2, 4, 8]
|
|
and args.compilation_config.backend == "inductor"
|
|
)
|
|
|
|
|
|
def test_attention_config():
|
|
from vllm.attention.backends.registry import AttentionBackendEnum
|
|
|
|
parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
|
|
|
|
# default value
|
|
args = parser.parse_args([])
|
|
assert args is not None
|
|
engine_args = EngineArgs.from_cli_args(args)
|
|
assert engine_args.attention_config == AttentionConfig()
|
|
|
|
# set backend via dot notation
|
|
args = parser.parse_args(["--attention-config.backend", "FLASH_ATTN"])
|
|
assert args is not None
|
|
engine_args = EngineArgs.from_cli_args(args)
|
|
assert engine_args.attention_config.backend is not None
|
|
assert engine_args.attention_config.backend.name == "FLASH_ATTN"
|
|
|
|
# set backend via --attention-backend shorthand
|
|
args = parser.parse_args(["--attention-backend", "FLASHINFER"])
|
|
assert args is not None
|
|
engine_args = EngineArgs.from_cli_args(args)
|
|
assert engine_args.attention_backend is not None
|
|
assert engine_args.attention_backend == "FLASHINFER"
|
|
|
|
# set all fields via dot notation
|
|
args = parser.parse_args(
|
|
[
|
|
"--attention-config.backend",
|
|
"FLASH_ATTN",
|
|
"--attention-config.flash_attn_version",
|
|
"3",
|
|
"--attention-config.use_prefill_decode_attention",
|
|
"true",
|
|
"--attention-config.flash_attn_max_num_splits_for_cuda_graph",
|
|
"16",
|
|
"--attention-config.use_cudnn_prefill",
|
|
"true",
|
|
"--attention-config.use_trtllm_ragged_deepseek_prefill",
|
|
"true",
|
|
"--attention-config.use_trtllm_attention",
|
|
"true",
|
|
"--attention-config.disable_flashinfer_prefill",
|
|
"true",
|
|
"--attention-config.disable_flashinfer_q_quantization",
|
|
"true",
|
|
]
|
|
)
|
|
assert args is not None
|
|
engine_args = EngineArgs.from_cli_args(args)
|
|
assert engine_args.attention_config.backend is not None
|
|
assert engine_args.attention_config.backend.name == "FLASH_ATTN"
|
|
assert engine_args.attention_config.flash_attn_version == 3
|
|
assert engine_args.attention_config.use_prefill_decode_attention is True
|
|
assert engine_args.attention_config.flash_attn_max_num_splits_for_cuda_graph == 16
|
|
assert engine_args.attention_config.use_cudnn_prefill is True
|
|
assert engine_args.attention_config.use_trtllm_ragged_deepseek_prefill is True
|
|
assert engine_args.attention_config.use_trtllm_attention is True
|
|
assert engine_args.attention_config.disable_flashinfer_prefill is True
|
|
assert engine_args.attention_config.disable_flashinfer_q_quantization is True
|
|
|
|
# set to string form of a dict with all fields
|
|
args = parser.parse_args(
|
|
[
|
|
"--attention-config="
|
|
'{"backend": "FLASHINFER", "flash_attn_version": 2, '
|
|
'"use_prefill_decode_attention": false, '
|
|
'"flash_attn_max_num_splits_for_cuda_graph": 8, '
|
|
'"use_cudnn_prefill": false, '
|
|
'"use_trtllm_ragged_deepseek_prefill": false, '
|
|
'"use_trtllm_attention": false, '
|
|
'"disable_flashinfer_prefill": false, '
|
|
'"disable_flashinfer_q_quantization": false}',
|
|
]
|
|
)
|
|
assert args is not None
|
|
engine_args = EngineArgs.from_cli_args(args)
|
|
assert engine_args.attention_config.backend is not None
|
|
assert engine_args.attention_config.backend.name == "FLASHINFER"
|
|
assert engine_args.attention_config.flash_attn_version == 2
|
|
assert engine_args.attention_config.use_prefill_decode_attention is False
|
|
assert engine_args.attention_config.flash_attn_max_num_splits_for_cuda_graph == 8
|
|
assert engine_args.attention_config.use_cudnn_prefill is False
|
|
assert engine_args.attention_config.use_trtllm_ragged_deepseek_prefill is False
|
|
assert engine_args.attention_config.use_trtllm_attention is False
|
|
assert engine_args.attention_config.disable_flashinfer_prefill is False
|
|
assert engine_args.attention_config.disable_flashinfer_q_quantization is False
|
|
|
|
# test --attention-backend flows into VllmConfig.attention_config
|
|
args = parser.parse_args(
|
|
[
|
|
"--model",
|
|
"facebook/opt-125m",
|
|
"--attention-backend",
|
|
"FLASH_ATTN",
|
|
]
|
|
)
|
|
assert args is not None
|
|
engine_args = EngineArgs.from_cli_args(args)
|
|
vllm_config = engine_args.create_engine_config()
|
|
assert vllm_config.attention_config.backend == AttentionBackendEnum.FLASH_ATTN
|
|
|
|
# test --attention-config.backend flows into VllmConfig.attention_config
|
|
args = parser.parse_args(
|
|
[
|
|
"--model",
|
|
"facebook/opt-125m",
|
|
"--attention-config.backend",
|
|
"FLASHINFER",
|
|
]
|
|
)
|
|
assert args is not None
|
|
engine_args = EngineArgs.from_cli_args(args)
|
|
vllm_config = engine_args.create_engine_config()
|
|
assert vllm_config.attention_config.backend == AttentionBackendEnum.FLASHINFER
|
|
|
|
# test --attention-backend and --attention-config.backend are mutually exclusive
|
|
args = parser.parse_args(
|
|
[
|
|
"--model",
|
|
"facebook/opt-125m",
|
|
"--attention-backend",
|
|
"FLASH_ATTN",
|
|
"--attention-config.backend",
|
|
"FLASHINFER",
|
|
]
|
|
)
|
|
assert args is not None
|
|
engine_args = EngineArgs.from_cli_args(args)
|
|
with pytest.raises(ValueError, match="mutually exclusive"):
|
|
engine_args.create_engine_config()
|
|
|
|
|
|
def test_prefix_cache_default():
|
|
parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
|
|
args = parser.parse_args([])
|
|
|
|
# should be None by default (depends on model).
|
|
engine_args = EngineArgs.from_cli_args(args=args)
|
|
assert engine_args.enable_prefix_caching is None
|
|
|
|
# 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
|
|
|
|
|
|
@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"),
|
|
],
|
|
)
|
|
def test_composite_arg_parser(arg, expected, option):
|
|
parser = EngineArgs.add_cli_args(FlexibleArgumentParser())
|
|
if arg is None:
|
|
args = parser.parse_args([])
|
|
else:
|
|
args = parser.parse_args([f"--{option}", arg])
|
|
assert getattr(args, option.replace("-", "_")) == expected
|
|
|
|
|
|
def test_human_readable_model_len():
|
|
# `exit_on_error` disabled to test invalid values below
|
|
parser = EngineArgs.add_cli_args(FlexibleArgumentParser(exit_on_error=False))
|
|
|
|
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
|
|
args = parser.parse_args(["--max-model-len", "2g"])
|
|
assert args.max_model_len == 2_000_000_000
|
|
args = parser.parse_args(["--max-model-len", "2t"])
|
|
assert args.max_model_len == 2_000_000_000_000
|
|
|
|
# Capital
|
|
args = parser.parse_args(["--max-model-len", "3K"])
|
|
assert args.max_model_len == 2**10 * 3
|
|
args = parser.parse_args(["--max-model-len", "10M"])
|
|
assert args.max_model_len == 2**20 * 10
|
|
args = parser.parse_args(["--max-model-len", "4G"])
|
|
assert args.max_model_len == 2**30 * 4
|
|
args = parser.parse_args(["--max-model-len", "4T"])
|
|
assert args.max_model_len == 2**40 * 4
|
|
|
|
# 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", "10.2123451234567k"])
|
|
assert args.max_model_len == 10212
|
|
args = parser.parse_args(["--max-model-len", "10.2123451234567m"])
|
|
assert args.max_model_len == 10212345
|
|
args = parser.parse_args(["--max-model-len", "10.2123451234567g"])
|
|
assert args.max_model_len == 10212345123
|
|
args = parser.parse_args(["--max-model-len", "10.2123451234567t"])
|
|
assert args.max_model_len == 10212345123456
|
|
|
|
# Invalid (do not allow decimals with binary multipliers)
|
|
for invalid in ["1a", "pwd", "10.24", "1.23M", "1.22T"]:
|
|
with pytest.raises(ArgumentError):
|
|
parser.parse_args(["--max-model-len", invalid])
|