from __future__ import annotations

from pathlib import Path

import torch

from . import __version__
from .models import SSLModel


def save_checkpoint(path, model, method, config, epoch, metrics):
    payload = {
        "version": __version__, "method": method, "epoch": epoch,
        "config": config, "metrics": metrics, "encoder": model.encoder.state_dict(),
        "projector": model.projector.state_dict() if model.projector else None,
        "rotation_head": model.rotation_head.state_dict() if model.rotation_head else None,
        "decoder": model.decoder.state_dict() if model.decoder else None,
    }
    Path(path).parent.mkdir(parents=True, exist_ok=True)
    torch.save(payload, path)


def load_checkpoint(path, device="cpu"):
    payload = torch.load(path, map_location=device, weights_only=True)
    model = SSLModel(payload["method"], pretrained=False)
    model.encoder.load_state_dict(payload["encoder"])
    for name in ("projector", "rotation_head", "decoder"):
        module, state = getattr(model, name), payload.get(name)
        if module is not None and state is not None:
            module.load_state_dict(state)
    return model.to(device), payload