55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
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# SPDX-License-Identifier: Apache-2.0
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from __future__ import annotations
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from typing import Any
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from vllm_omni.lora.request import LoRARequest
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from vllm_omni.lora.utils import stable_lora_int_id
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def get_stage_type(stage_cfg: Any) -> str:
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"""Best-effort stage type resolver across dict/omegaconf/object configs."""
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if isinstance(stage_cfg, dict):
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return stage_cfg.get("stage_type", "llm")
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if hasattr(stage_cfg, "get"):
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try:
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return stage_cfg.get("stage_type", "llm")
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except Exception:
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pass
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return getattr(stage_cfg, "stage_type", "llm")
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def parse_lora_request(lora_body: Any) -> tuple[LoRARequest | None, float | None]:
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"""Parse a request-level LoRA object into a LoRARequest and optional scale.
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Raises:
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ValueError: If the object shape is invalid or required fields are missing.
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"""
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if lora_body is None:
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return None, None
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if not isinstance(lora_body, dict):
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raise ValueError("Invalid lora field: expected an object.")
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lora_name = lora_body.get("name") or lora_body.get("lora_name") or lora_body.get("adapter")
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lora_path = (
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lora_body.get("local_path")
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or lora_body.get("path")
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or lora_body.get("lora_path")
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or lora_body.get("lora_local_path")
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)
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lora_scale = lora_body.get("scale")
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if lora_scale is None:
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lora_scale = lora_body.get("lora_scale")
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lora_int_id = lora_body.get("int_id")
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if lora_int_id is None:
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lora_int_id = lora_body.get("lora_int_id")
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if lora_int_id is None and lora_path:
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lora_int_id = stable_lora_int_id(str(lora_path))
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if not lora_name or not lora_path:
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raise ValueError("Invalid lora object: both name and path are required.")
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scale = float(lora_scale) if lora_scale is not None else None
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return LoRARequest(str(lora_name), int(lora_int_id), str(lora_path)), scale
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