tinymind-native-colab-handoff/bundle/train/lora_patterns.py

from __future__ import annotations


def parse_lora_pattern(value: str | None) -> dict[str, int]:
    if not value:
        return {}
    pattern: dict[str, int] = {}
    for part in value.split(","):
        item = part.strip()
        if not item:
            continue
        if ":" not in item:
            raise ValueError(f"invalid LoRA pattern entry {item!r}; expected module:int")
        key, raw = item.split(":", 1)
        key = key.strip()
        if not key:
            raise ValueError(f"invalid LoRA pattern entry {item!r}; empty module")
        rank = int(raw.strip())
        if rank <= 0:
            raise ValueError(f"invalid LoRA pattern entry {item!r}; value must be positive")
        pattern[key] = rank
    return pattern