threestudio/models/guidance/stable_zero123_guidance.py [21:71]:
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def get_obj_from_str(string, reload=False):
    module, cls = string.rsplit(".", 1)
    if reload:
        module_imp = importlib.import_module(module)
        importlib.reload(module_imp)
    return getattr(importlib.import_module(module, package=None), cls)


def instantiate_from_config(config):
    if not "target" in config:
        if config == "__is_first_stage__":
            return None
        elif config == "__is_unconditional__":
            return None
        raise KeyError("Expected key `target` to instantiate.")
    return get_obj_from_str(config["target"])(**config.get("params", dict()))


# load model
def load_model_from_config(config, ckpt, device, vram_O=True, verbose=False):
    pl_sd = torch.load(ckpt, map_location="cpu")

    if "global_step" in pl_sd and verbose:
        print(f'[INFO] Global Step: {pl_sd["global_step"]}')

    sd = pl_sd["state_dict"]

    model = instantiate_from_config(config.model)
    m, u = model.load_state_dict(sd, strict=False)

    if len(m) > 0 and verbose:
        print("[INFO] missing keys: \n", m)
    if len(u) > 0 and verbose:
        print("[INFO] unexpected keys: \n", u)

    # manually load ema and delete it to save GPU memory
    if model.use_ema:
        if verbose:
            print("[INFO] loading EMA...")
        model.model_ema.copy_to(model.model)
        del model.model_ema

    if vram_O:
        # we don't need decoder
        del model.first_stage_model.decoder

    torch.cuda.empty_cache()

    model.eval().to(device)

    return model
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threestudio/models/guidance/zero123_guidance.py [21:71]:
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def get_obj_from_str(string, reload=False):
    module, cls = string.rsplit(".", 1)
    if reload:
        module_imp = importlib.import_module(module)
        importlib.reload(module_imp)
    return getattr(importlib.import_module(module, package=None), cls)


def instantiate_from_config(config):
    if not "target" in config:
        if config == "__is_first_stage__":
            return None
        elif config == "__is_unconditional__":
            return None
        raise KeyError("Expected key `target` to instantiate.")
    return get_obj_from_str(config["target"])(**config.get("params", dict()))


# load model
def load_model_from_config(config, ckpt, device, vram_O=True, verbose=False):
    pl_sd = torch.load(ckpt, map_location="cpu")

    if "global_step" in pl_sd and verbose:
        print(f'[INFO] Global Step: {pl_sd["global_step"]}')

    sd = pl_sd["state_dict"]

    model = instantiate_from_config(config.model)
    m, u = model.load_state_dict(sd, strict=False)

    if len(m) > 0 and verbose:
        print("[INFO] missing keys: \n", m)
    if len(u) > 0 and verbose:
        print("[INFO] unexpected keys: \n", u)

    # manually load ema and delete it to save GPU memory
    if model.use_ema:
        if verbose:
            print("[INFO] loading EMA...")
        model.model_ema.copy_to(model.model)
        del model.model_ema

    if vram_O:
        # we don't need decoder
        del model.first_stage_model.decoder

    torch.cuda.empty_cache()

    model.eval().to(device)

    return model
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