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refactor: 移除 Python 后端源码，全面迁移至 Rust gateway 架构
- 删除全部 Python 源码 (src/) 及 Alembic 迁移脚本，归档至 _deprecated_py_src/ - 重构 Rust gateway ai_pipeline: 拆分 planner/finalize 模块，新增 contracts/adaptation 层 - 重组 handlers 模块为 admin/public/proxy/internal/shared 子模块结构 - 新增 executor 模块，引入 Rust 原生数据库迁移 (aether-data/migrations) - 简化 CI/Docker 构建流程，移除 base image 二级构建，统一为单一 app image - 移除 Python 相关基础设施文件 (entrypoint.sh, gunicorn_conf.py, Dockerfile.base)
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fawney19
265
_deprecated_py_src/services/provider/pool/dimensions/registry.py
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265
_deprecated_py_src/services/provider/pool/dimensions/registry.py
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"""Preset dimension registry for pool multi-score scheduling."""
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from __future__ import annotations
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from abc import ABC, abstractmethod
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from dataclasses import dataclass
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from threading import RLock
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from typing import Any
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@dataclass(frozen=True, slots=True)
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class PresetDimensionMeta:
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"""Serializable metadata for one preset dimension."""
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name: str
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label: str
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description: str
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providers: tuple[str, ...]
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modes: tuple[str, ...] | None
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default_mode: str | None
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mutex_group: str | None
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evidence_hint: str | None
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class PresetDimensionBase(ABC):
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"""Base class of one pool scheduling preset dimension."""
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@property
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@abstractmethod
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def name(self) -> str:
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"""Stable preset key, e.g. ``free_team_first``."""
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@property
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@abstractmethod
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def label(self) -> str:
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"""User-facing label."""
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@property
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@abstractmethod
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def description(self) -> str:
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"""User-facing description."""
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@property
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def providers(self) -> tuple[str, ...]:
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"""Supported provider types.
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Empty tuple means the dimension is universal and applies to all providers.
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"""
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return ()
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@property
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def modes(self) -> tuple[str, ...] | None:
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"""Optional sub-modes for this dimension."""
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return None
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@property
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def default_mode(self) -> str | None:
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"""Default mode when mode is omitted."""
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return None
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@property
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def mutex_group(self) -> str | None:
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"""Optional mutual-exclusion group key.
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Presets in the same group are expected to be mutually exclusive in UI.
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"""
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return None
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@property
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def evidence_hint(self) -> str | None:
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"""Human-readable hint about which data this preset uses."""
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return None
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@property
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def hidden(self) -> bool:
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"""If True, this dimension is excluded from API metadata listings.
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The dimension remains functional for backward compatibility but
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will not appear in the scheduling dialog.
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"""
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return False
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@abstractmethod
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def compute_metric(
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self,
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*,
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key_id: str,
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all_key_ids: list[str],
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keys_by_id: dict[str, Any],
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lru_scores: dict[str, Any],
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context: dict[str, Any],
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mode: str | None,
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) -> float:
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"""Compute normalized metric in [0, 1], lower is better."""
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def is_applicable(self, provider_type: str) -> bool:
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"""Return whether this dimension applies to the given provider type."""
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if not self.providers:
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return True
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normalized = _normalize_name(provider_type)
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return normalized in self.providers
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def _normalize_name(value: Any) -> str:
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if not isinstance(value, str):
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return ""
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return value.strip().lower()
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def _normalize_names(values: tuple[str, ...] | list[str]) -> tuple[str, ...]:
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normalized = [_normalize_name(item) for item in values]
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return tuple(item for item in normalized if item)
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_registry_lock = RLock()
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_registry: dict[str, PresetDimensionBase] = {}
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def register_preset_dimension(dim: PresetDimensionBase) -> None:
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"""Register or replace one preset dimension by name."""
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name = _normalize_name(dim.name)
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if not name:
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raise ValueError("preset dimension name must be a non-empty string")
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providers = _normalize_names(dim.providers)
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modes = _normalize_names(dim.modes or ())
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default_mode = _normalize_name(dim.default_mode)
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if modes and default_mode and default_mode not in modes:
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raise ValueError(f"default_mode must be one of modes for preset '{name}'")
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class _NormalizedDimension(PresetDimensionBase):
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# Lightweight wrapper to keep normalized metadata while preserving compute logic.
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def __init__(self, wrapped: PresetDimensionBase) -> None:
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self._wrapped = wrapped
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@property
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def name(self) -> str:
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return name
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@property
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def label(self) -> str:
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return self._wrapped.label
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@property
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def description(self) -> str:
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return self._wrapped.description
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@property
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def providers(self) -> tuple[str, ...]:
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return providers
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@property
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def modes(self) -> tuple[str, ...] | None:
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return modes or None
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@property
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def default_mode(self) -> str | None:
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if not modes:
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return None
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if default_mode:
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return default_mode
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return modes[0]
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@property
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def mutex_group(self) -> str | None:
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raw = _normalize_name(self._wrapped.mutex_group)
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return raw or None
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@property
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def evidence_hint(self) -> str | None:
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raw = str(self._wrapped.evidence_hint or "").strip()
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return raw or None
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@property
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def hidden(self) -> bool:
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return self._wrapped.hidden
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def compute_metric(
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self,
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*,
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key_id: str,
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all_key_ids: list[str],
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keys_by_id: dict[str, Any],
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lru_scores: dict[str, Any],
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context: dict[str, Any],
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mode: str | None,
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) -> float:
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return self._wrapped.compute_metric(
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key_id=key_id,
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all_key_ids=all_key_ids,
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keys_by_id=keys_by_id,
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lru_scores=lru_scores,
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context=context,
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mode=mode,
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)
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normalized = _NormalizedDimension(dim)
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with _registry_lock:
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_registry[name] = normalized
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def get_preset_dimension(name: str) -> PresetDimensionBase | None:
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"""Get one registered preset dimension by name."""
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key = _normalize_name(name)
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if not key:
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return None
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with _registry_lock:
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return _registry.get(key)
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def get_all_preset_dimensions() -> list[PresetDimensionBase]:
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"""Get all registered preset dimensions in registration order."""
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with _registry_lock:
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return list(_registry.values())
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def get_preset_names() -> set[str]:
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"""Get all registered preset names."""
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with _registry_lock:
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return set(_registry.keys())
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def get_preset_dimension_metas() -> list[PresetDimensionMeta]:
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"""Get serializable metadata for all preset dimensions."""
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metas: list[PresetDimensionMeta] = []
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for dim in get_all_preset_dimensions():
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if dim.hidden:
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continue
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metas.append(
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PresetDimensionMeta(
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name=dim.name,
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label=dim.label,
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description=dim.description,
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providers=dim.providers,
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modes=dim.modes,
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default_mode=dim.default_mode,
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mutex_group=dim.mutex_group,
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evidence_hint=dim.evidence_hint,
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)
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)
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return metas
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__all__ = [
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"PresetDimensionBase",
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"PresetDimensionMeta",
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"get_all_preset_dimensions",
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"get_preset_dimension",
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"get_preset_dimension_metas",
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"get_preset_names",
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"register_preset_dimension",
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]
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