65 lines
2.3 KiB
Python
65 lines
2.3 KiB
Python
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# -*- coding: utf-8 -*-
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"""推理后端工厂：按配置选择后端实现（可插拔适配层）。
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PRD 5.6「配置点：资源配额、推理后端选择、灰度发布策略」——
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`backend: gpu|npu` 即推理后端选择；业务代码只调用 `build_backend()`
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返回的接口对象，不感知具体硬件。
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"""
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import os
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from inference_backend.base import InferenceBackend
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from inference_backend.gpu_backend import NvidiaGpuBackend
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from inference_backend.npu_backend import AscendNpuBackend
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#: 可插拔后端注册表：配置名 -> 实现类。新增硬件只需注册新类。
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BACKEND_REGISTRY = {
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"gpu": NvidiaGpuBackend, # NVIDIA 5090（Triton/ONNX）
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"npu": AscendNpuBackend, # 华为昇腾（ACL/CANN）
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}
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def build_backend(config: dict) -> InferenceBackend:
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"""依据配置构建推理后端实例（切换后端仅改配置，业务代码零改动）。
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Args:
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config: 后端配置字典（见 config/backends.template.yaml），
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至少包含 ``backend`` 键（gpu | npu）。
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Returns:
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实现了 :class:`InferenceBackend` 接口的后端实例。
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Raises:
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ValueError: 配置缺失或指定了未注册的后端。
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"""
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if not isinstance(config, dict) or not config.get("backend"):
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raise ValueError("推理后端配置缺失：需要 backend: gpu|npu")
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name = str(config["backend"]).lower()
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if name not in BACKEND_REGISTRY:
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raise ValueError(
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f"未注册的推理后端: {name!r}，可用: {sorted(BACKEND_REGISTRY)}"
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)
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cls = BACKEND_REGISTRY[name]
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inf = config.get("inference", {}) or {}
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return cls(
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endpoint=inf.get("endpoint", ""),
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model=inf.get("model", "iaop-default"),
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timeout_seconds=float(inf.get("timeout_seconds", 10)),
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runtime=inf.get("runtime", ""),
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device=inf.get("device", ""),
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cann_version=inf.get("cann_version", ""),
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)
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def load_backend_config(path: str) -> dict:
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"""从 YAML 配置资产加载后端配置（模板可覆盖资产）。"""
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import yaml
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with open(path, "r", encoding="utf-8") as fh:
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return yaml.safe_load(fh) or {}
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def default_config_path() -> str:
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"""返回本模块模板配置资产的默认路径。"""
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return os.path.join(os.path.dirname(os.path.abspath(__file__)),
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"config", "backends.template.yaml")
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