def load_hparams_from_yaml(config_yaml: _PATH, use_omegaconf: bool = True) -> dict[str, Any]:
    """Load hparams from a file.

        Args:
            config_yaml: Path to config yaml file
            use_omegaconf: If omegaconf is available and ``use_omegaconf=True``,
                the hparams will be converted to ``DictConfig`` if possible.

    >>> hparams = Namespace(batch_size=32, learning_rate=0.001, data_root='./any/path/here')
    >>> path_yaml = './testing-hparams.yaml'
    >>> save_hparams_to_yaml(path_yaml, hparams)
    >>> hparams_new = load_hparams_from_yaml(path_yaml)
    >>> vars(hparams) == hparams_new
    True
    >>> os.remove(path_yaml)

    """
    fs = get_filesystem(config_yaml)
    if not fs.exists(config_yaml):
        rank_zero_warn(f"Missing Tags: {config_yaml}.", category=RuntimeWarning)
        return {}

    with fs.open(config_yaml, "r") as fp:
        hparams = yaml.full_load(fp)

    if _OMEGACONF_AVAILABLE and use_omegaconf:
        from omegaconf import OmegaConf
        from omegaconf.errors import UnsupportedValueType, ValidationError

        with contextlib.suppress(UnsupportedValueType, ValidationError):
            return OmegaConf.create(hparams)
    return hparams
Load hparams from a file.

        Args:
            config_yaml: Path to config yaml file
            use_omegaconf: If omegaconf is available and ``use_omegaconf=True``,
                the hparams will be converted to ``DictConfig`` if possible.

    >>> hparams = Namespace(batch_size=32, learning_rate=0.001, data_root='./any/path/here')
    >>> path_yaml = './testing-hparams.yaml'
    >>> save_hparams_to_yaml(path_yaml, hparams)
    >>> hparams_new = load_hparams_from_yaml(path_yaml)
    >>> vars(hparams) == hparams_new
    True
    >>> os.remove(path_yaml)

    
src/lightning/pytorch/core/saving.py