"""TD-MPC2 baseline model definition."""

import torch

from experiments.shared.src.models.image_world_models import TDMPC2ImageWorldModel
from experiments.tdmpc2.src.config import default_config

def build_model(config):
    return TDMPC2ImageWorldModel(config)


def load_model(checkpoint_path, config=None):
    cfg = default_config() if config is None else config
    model = build_model(cfg)
    model.load_state_dict(torch.load(checkpoint_path, map_location="cpu"))
    return model