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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

301 lines
10 KiB
Python

# Copyright 2023-2024 SGLang Team
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Utilities for auto-deriving argparse CLI arguments from dataclass fields.
Usage::
from sglang.srt.arg_groups.arg_utils import A, Arg, add_cli_args_from_dataclass
@dataclasses.dataclass
class ServerArgs:
# Simple fields — bare string is the help text:
host: A[str, "The host of the HTTP server."] = "127.0.0.1"
port: A[int, "The port of the HTTP server."] = 30000
trust_remote_code: A[bool, "Whether to allow custom models."] = False
tokenizer_path: A[Optional[str], "The path of the tokenizer."] = None
# Fields with extra metadata — use Arg(...):
model_path: A[str, Arg(help="Path to model weights.", aliases=["--model"])]
load_format: A[str, Arg(help="Format.", choices=CHOICES)] = "auto"
@staticmethod
def add_cli_args(parser):
add_cli_args_from_dataclass(parser, ServerArgs)
``A`` is a short alias for ``typing.Annotated``. A bare ``str`` inside the
annotation is equivalent to ``Arg(help=that_string)``.
"""
from __future__ import annotations
import dataclasses
import functools
import types
from typing import (
Annotated,
Any,
Callable,
List,
Literal,
Optional,
Union,
get_args,
get_origin,
get_type_hints,
)
A = Annotated
@dataclasses.dataclass(frozen=True)
class Arg:
"""CLI argument metadata attached to a dataclass field via ``Annotated``."""
help: str = ""
choices: Optional[list] = None
aliases: Optional[List[str]] = None
cli_name: Optional[str] = None
type_parser: Optional[Callable] = None
nargs: Optional[str] = None
required: Optional[bool] = None
action: Optional[Any] = None
action_kwargs: Optional[dict] = None
const: Optional[Any] = None
# When True, this field is skipped by add_cli_args_from_dataclass.
# Use for fields that have no CLI surface (e.g. injected via Python only).
no_cli: bool = False
# When True, this field may be written by config resolution (model
# overrides and post-process passes): it is part of the whitelist accepted
# by the declaration stash, and its resolved value materializes onto the
# field at the end of __post_init__.
resolvable: bool = False
@functools.lru_cache(maxsize=None)
def resolvable_fields(cls) -> frozenset:
"""Names of ``cls`` dataclass fields whose ``Arg`` metadata declares
``resolvable=True`` — the whitelist for config resolution.
Non-dataclass types (e.g. mock config objects in tests) have no Arg
metadata and yield an empty whitelist."""
if not dataclasses.is_dataclass(cls):
return frozenset()
hints = get_type_hints(cls, include_extras=True)
names = set()
for field in dataclasses.fields(cls):
_, arg = _unwrap_annotated(hints.get(field.name, field.type))
if arg is not None and arg.resolvable:
names.add(field.name)
return frozenset(names)
# ---------------------------------------------------------------------------
# Internal helpers
# ---------------------------------------------------------------------------
_MISSING = dataclasses.MISSING
def _unwrap_annotated(tp):
"""Return (inner_type, Arg | None) from ``Annotated[T, Arg(...)]``.
Also accepts a bare string as shorthand: ``Annotated[T, "help text"]``
is equivalent to ``Annotated[T, Arg(help="help text")]``.
"""
origin = get_origin(tp)
if origin is Annotated:
args = get_args(tp)
inner = args[0]
for a in args[1:]:
if isinstance(a, Arg):
return inner, a
if isinstance(a, str):
return inner, Arg(help=a)
return inner, None
return tp, None
def _unwrap_optional(tp):
"""If tp is Optional[X] (i.e. Union[X, None]), return (X, True). Else (tp, False)."""
origin = get_origin(tp)
is_union = origin is Union or (
hasattr(types, "UnionType") and origin is types.UnionType
)
if is_union:
args = get_args(tp)
non_none = [a for a in args if a is not type(None)]
if len(non_none) == 1:
return non_none[0], True
return tp, False
def _unwrap_literal(tp):
"""If tp is Literal[...], return list of values. Else None."""
origin = get_origin(tp)
if origin is Literal:
return list(get_args(tp))
return None
def _infer_type_func(tp):
"""Map a Python type annotation to an argparse ``type=`` callable."""
if tp is str:
return str
if tp is int:
return int
if tp is float:
return float
return str
def _field_default(field):
"""Return the default value for a dataclass field, or _MISSING."""
if field.default is not _MISSING:
return field.default
if field.default_factory is not _MISSING:
return field.default_factory()
return _MISSING
def _field_to_cli_name(name: str) -> str:
"""Convert a field name like ``model_path`` to ``--model-path``."""
return "--" + name.replace("_", "-")
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
def add_cli_args_from_dataclass(parser, cls, *, fields: Optional[List[str]] = None):
"""Add argparse arguments for every ``A[T, "help"]`` or ``A[T, Arg(...)]`` field.
Fields without an ``Arg`` or bare-string annotation are silently skipped —
they must still be registered manually (this allows incremental migration).
Parameters
----------
parser : argparse.ArgumentParser
cls : dataclass type
fields : optional list of field names to include. If None, all fields with
``Arg`` annotations are included.
"""
hints = get_type_hints(cls, include_extras=True)
for field in dataclasses.fields(cls):
if fields is not None and field.name not in fields:
continue
hint = hints.get(field.name)
if hint is None:
continue
raw_type, arg_meta = _unwrap_annotated(hint)
if arg_meta is None:
continue
if arg_meta.no_cli:
continue
cli_name = arg_meta.cli_name or _field_to_cli_name(field.name)
names = [cli_name] + (arg_meta.aliases or [])
default = _field_default(field)
# Anchor dest to the field name so argparse stores the value
# under the dataclass attribute directly, even when cli_name
# differs (e.g. --tensor-parallel-size → tp_size).
auto_dest = cli_name.lstrip("-").replace("-", "_")
dest_kwarg = {"dest": field.name} if field.name != auto_dest else {}
# Handle custom action
if arg_meta.action is not None:
kwargs = {
"action": arg_meta.action,
"help": arg_meta.help,
**dest_kwarg,
}
if default is not _MISSING:
kwargs["default"] = default
if arg_meta.action_kwargs:
kwargs.update(arg_meta.action_kwargs)
parser.add_argument(*names, **kwargs)
continue
# Unwrap Optional
inner_type, is_optional = _unwrap_optional(raw_type)
# Check for Literal — auto-derive choices
literal_vals = _unwrap_literal(inner_type)
if literal_vals is not None:
choices = arg_meta.choices or literal_vals
# Infer type from first literal value
val_type = type(literal_vals[0]) if literal_vals else str
type_func = arg_meta.type_parser or _infer_type_func(val_type)
kwargs = dict(
type=type_func, choices=choices, help=arg_meta.help, **dest_kwarg
)
if default is not _MISSING:
kwargs["default"] = default
if arg_meta.const is not None:
kwargs["const"] = arg_meta.const
parser.add_argument(*names, **kwargs)
continue
# Check for List[X] — but skip if type_parser is set (the parser
# handles the whole value as a single string, e.g. json_list_type).
origin = get_origin(inner_type)
if (origin is list or origin is List) and arg_meta.type_parser is None:
elem_args = get_args(inner_type)
elem_type = elem_args[0] if elem_args else str
type_func = _infer_type_func(elem_type)
nargs = arg_meta.nargs or "+"
kwargs = dict(
type=type_func,
nargs=nargs,
help=arg_meta.help,
**dest_kwarg,
)
if arg_meta.choices:
kwargs["choices"] = arg_meta.choices
if default is not _MISSING:
kwargs["default"] = default
if arg_meta.const is not None:
kwargs["const"] = arg_meta.const
parser.add_argument(*names, **kwargs)
continue
# Bool → store_true
if inner_type is bool:
kwargs = dict(action="store_true", help=arg_meta.help, **dest_kwarg)
if default is not _MISSING:
kwargs["default"] = default
parser.add_argument(*names, **kwargs)
continue
# Scalar types (str, int, float, etc.)
type_func = arg_meta.type_parser or _infer_type_func(inner_type)
kwargs = dict(type=type_func, help=arg_meta.help, **dest_kwarg)
if arg_meta.choices:
kwargs["choices"] = arg_meta.choices
if arg_meta.nargs:
kwargs["nargs"] = arg_meta.nargs
if default is not _MISSING:
kwargs["default"] = default
if arg_meta.const is not None:
kwargs["const"] = arg_meta.const
if (
arg_meta.required is True
or (arg_meta.required is None and default is _MISSING)
) and any(name.startswith("-") for name in names):
kwargs["required"] = True
parser.add_argument(*names, **kwargs)