from ray._private.utils import get_function_args
from ray.tune.suggest.search import SearchAlgorithm
from ray.tune.suggest.basic_variant import BasicVariantGenerator
from ray.tune.suggest.suggestion import Searcher, ConcurrencyLimiter
from ray.tune.suggest.search_generator import SearchGenerator
from ray.tune.suggest.variant_generator import grid_search
from ray.tune.suggest.repeater import Repeater


def create_searcher(
        search_alg,
        **kwargs,
):
    """Instantiate a search algorithm based on the given string.

    This is useful for swapping between different search algorithms.

    Args:
        search_alg (str): The search algorithm to use.
        metric (str): The training result objective value attribute. Stopping
            procedures will use this attribute.
        mode (str): One of {min, max}. Determines whether objective is
            minimizing or maximizing the metric attribute.
        **kwargs: Additional parameters.
            These keyword arguments will be passed to the initialization
            function of the chosen class.
    Returns:
        ray.tune.suggest.Searcher: The search algorithm.
    Example:
        >>> search_alg = tune.create_searcher('ax')
    """

    def _import_variant_generator():
        return BasicVariantGenerator

    def _import_ax_search():
        from ray.tune.suggest.ax import AxSearch
        return AxSearch

    def _import_dragonfly_search():
        from ray.tune.suggest.dragonfly import DragonflySearch
        return DragonflySearch

    def _import_skopt_search():
        from ray.tune.suggest.skopt import SkOptSearch
        return SkOptSearch

    def _import_hyperopt_search():
        from ray.tune.suggest.hyperopt import HyperOptSearch
        return HyperOptSearch

    def _import_bayesopt_search():
        from ray.tune.suggest.bayesopt import BayesOptSearch
        return BayesOptSearch

    def _import_bohb_search():
        from ray.tune.suggest.bohb import TuneBOHB
        return TuneBOHB

    def _import_nevergrad_search():
        from ray.tune.suggest.nevergrad import NevergradSearch
        return NevergradSearch

    def _import_optuna_search():
        from ray.tune.suggest.optuna import OptunaSearch
        return OptunaSearch

    def _import_zoopt_search():
        from ray.tune.suggest.zoopt import ZOOptSearch
        return ZOOptSearch

    def _import_sigopt_search():
        from ray.tune.suggest.sigopt import SigOptSearch
        return SigOptSearch

    SEARCH_ALG_IMPORT = {
        "variant_generator": _import_variant_generator,
        "random": _import_variant_generator,
        "ax": _import_ax_search,
        "dragonfly": _import_dragonfly_search,
        "skopt": _import_skopt_search,
        "hyperopt": _import_hyperopt_search,
        "bayesopt": _import_bayesopt_search,
        "bohb": _import_bohb_search,
        "nevergrad": _import_nevergrad_search,
        "optuna": _import_optuna_search,
        "zoopt": _import_zoopt_search,
        "sigopt": _import_sigopt_search,
    }
    search_alg = search_alg.lower()
    if search_alg not in SEARCH_ALG_IMPORT:
        raise ValueError(
            f"Search alg must be one of {list(SEARCH_ALG_IMPORT)}. "
            f"Got: {search_alg}")

    SearcherClass = SEARCH_ALG_IMPORT[search_alg]()

    search_alg_args = get_function_args(SearcherClass)
    trimmed_kwargs = {k: v for k, v in kwargs.items() if k in search_alg_args}

    return SearcherClass(**trimmed_kwargs)


__all__ = [
    "SearchAlgorithm", "Searcher", "BasicVariantGenerator", "SearchGenerator",
    "grid_search", "Repeater", "ConcurrencyLimiter"
]


def BayesOptSearch(*args, **kwargs):
    raise DeprecationWarning("""This class has been moved. Please import via
        `from ray.tune.suggest.bayesopt import BayesOptSearch`""")


def HyperOptSearch(*args, **kwargs):
    raise DeprecationWarning("""This class has been moved. Please import via
        `from ray.tune.suggest.hyperopt import HyperOptSearch`""")


def NevergradSearch(*args, **kwargs):
    raise DeprecationWarning("""This class has been moved. Please import via
        `from ray.tune.suggest.nevergrad import NevergradSearch`""")


def SkOptSearch(*args, **kwargs):
    raise DeprecationWarning("""This class has been moved. Please import via
        `from ray.tune.suggest.skopt import SkOptSearch`""")


def SigOptSearch(*args, **kwargs):
    raise DeprecationWarning("""This class has been moved. Please import via
        `from ray.tune.suggest.sigopt import SigOptSearch`""")

@@ -2482,24 +2482,135 @@
 gOptSearch%0A%0A
+    def _import_hebo_search():%0A        from ray.tune.suggest.hebo import HEBOSearch%0A        return HEBOSearch%0A%0A
     SEARCH_A
@@ -3134,24 +3134,61 @@
 opt_search,%0A
+        %22hebo%22: _import_hebo_search,%0A
     %7D%0A    se

Add HEBO to search algorithm shim function (#15468)