from functools import partial from ray.rllib.utils.annotations import override, PublicAPI, DeveloperAPI from ray.rllib.utils.framework import try_import_tf, try_import_tfp, \ try_import_torch, check_framework from ray.rllib.utils.deprecation import deprecation_warning, renamed_agent, \ renamed_class, renamed_function from ray.rllib.utils.filter_manager import FilterManager from ray.rllib.utils.filter import Filter from ray.rllib.utils.numpy import sigmoid, softmax, relu, one_hot, fc, lstm, \ SMALL_NUMBER, LARGE_INTEGER from ray.rllib.utils.policy_client import PolicyClient from ray.rllib.utils.policy_server import PolicyServer from ray.rllib.utils.schedules import LinearSchedule, PiecewiseSchedule, \ PolynomialSchedule, ExponentialSchedule, ConstantSchedule from ray.rllib.utils.test_utils import check from ray.tune.utils import merge_dicts, deep_update def add_mixins(base, mixins): """Returns a new class with mixins applied in priority order.""" mixins = list(mixins or []) while mixins: class new_base(mixins.pop(), base): pass base = new_base return base def force_list(elements=None, to_tuple=False): """ Makes sure `elements` is returned as a list, whether `elements` is a single item, already a list, or a tuple. Args: elements (Optional[any]): The inputs as single item, list, or tuple to be converted into a list/tuple. If None, returns empty list/tuple. to_tuple (bool): Whether to use tuple (instead of list). Returns: Union[list,tuple]: All given elements in a list/tuple depending on `to_tuple`'s value. If elements is None, returns an empty list/tuple. """ ctor = list if to_tuple is True: ctor = tuple return ctor() if elements is None else ctor(elements) \ if type(elements) in [list, tuple] else ctor([elements]) force_tuple = partial(force_list, to_tuple=True) __all__ = [ "add_mixins", "check", "check_framework", "deprecation_warning", "fc", "force_list", "force_tuple", "lstm", "one_hot", "relu", "sigmoid", "softmax", "deep_update", "merge_dicts", "override", "renamed_function", "renamed_agent", "renamed_class", "try_import_tf", "try_import_tfp", "try_import_torch", "ConstantSchedule", "DeveloperAPI", "ExponentialSchedule", "Filter", "FilterManager", "LARGE_INTEGER", "LinearSchedule", "PiecewiseSchedule", "PolicyClient", "PolicyServer", "PolynomialSchedule", "PublicAPI", "SMALL_NUMBER", ]