SYMBOL INDEX (142 symbols across 5 files)

FILE: carbs/carbs.py
  class CARBS (line 62) | class CARBS:
    method __init__ (line 75) | def __init__(self, config: CARBSParams, params: List[Param]) -> None:
    method set_search_center (line 145) | def set_search_center(self, input_in_param: ParamDictType) -> None:
    method suggest (line 150) | def suggest(
    method observe (line 218) | def observe(self, new_observation_in_param: ObservationInParam) -> Obs...
    method forget_suggestion (line 240) | def forget_suggestion(self, suggestion_to_forget: ParamDictType) -> None:
    method initialize_from_observations (line 254) | def initialize_from_observations(
    method __getstate__ (line 272) | def __getstate__(self) -> Dict[str, object]:
    method __setstate__ (line 278) | def __setstate__(self, state: Dict[str, object]) -> None:
    method _set_seed (line 282) | def _set_seed(self, seed: int) -> None:
    method _get_mask_for_invalid_points_in_basic (line 287) | def _get_mask_for_invalid_points_in_basic(self, input_in_basic: Tensor...
    method _round_integer_values_in_basic (line 298) | def _round_integer_values_in_basic(self, input_in_basic: Tensor) -> Te...
    method _param_space_real_to_basic_space_real (line 305) | def _param_space_real_to_basic_space_real(
    method _param_space_obs_to_basic_space_obs (line 315) | def _param_space_obs_to_basic_space_obs(
    method _basic_space_to_param_space (line 328) | def _basic_space_to_param_space(self, real_number_input: Tensor) -> Pa...
    method _basic_space_to_unrounded_param_space (line 336) | def _basic_space_to_unrounded_param_space(
    method _remember_suggestion (line 346) | def _remember_suggestion(
    method _add_observation (line 358) | def _add_observation(
    method _search_distribution_in_basic (line 376) | def _search_distribution_in_basic(self) -> Distribution:
    method _sample_around_origins_in_basic (line 379) | def _sample_around_origins_in_basic(
    method _get_probability_in_search_space (line 401) | def _get_probability_in_search_space(
    method _is_random_sampling (line 418) | def _is_random_sampling(self) -> bool:
    method sample_search_space (line 422) | def sample_search_space(self, num_samples: int) -> List[SuggestionInBa...
    method _generate_candidate (line 456) | def _generate_candidate(self) -> Optional[SuggestionInBasic]:
    method get_surrogate_model (line 586) | def get_surrogate_model(self) -> SurrogateModel:
    method _get_random_suggestion (line 596) | def _get_random_suggestion(
    method _observation_group_output_pos_better (line 616) | def _observation_group_output_pos_better(self, group: Sequence[Observa...
    method _crank_oversampling_up (line 619) | def _crank_oversampling_up(self) -> None:
    method _get_pareto_groups (line 624) | def _get_pareto_groups(
    method _get_pareto_set (line 649) | def _get_pareto_set(
    method _get_resample_suggestion (line 657) | def _get_resample_suggestion(self) -> SuggestionInBasic:
    method _init_wandb (line 688) | def _init_wandb(self) -> None:
    method cumulative_cost (line 712) | def cumulative_cost(self) -> float:
    method observation_count (line 717) | def observation_count(self) -> int:
    method _get_observation_log (line 720) | def _get_observation_log(self, observation: ObservationInParam) -> Dic...
    method _get_suggestion_log (line 805) | def _get_suggestion_log(
    method _autosave (line 826) | def _autosave(self) -> None:
    method load_from_file (line 833) | def load_from_file(
    method load_from_string (line 847) | def load_from_string(
    method get_state_dict (line 854) | def get_state_dict(self) -> Dict[str, Any]:
    method load_state_dict (line 871) | def load_state_dict(cls, state: Dict[str, Any]) -> "CARBS":
    method save_to_file (line 879) | def save_to_file(self, filename: str, upload_to_wandb: bool = False) -...
    method serialize (line 888) | def serialize(self) -> str:
    method warm_start_from_wandb (line 894) | def warm_start_from_wandb(
    method warm_start (line 903) | def warm_start(

FILE: carbs/model.py
  class SurrogateObservationOutputs (line 24) | class SurrogateObservationOutputs:
  class SurrogateModel (line 35) | class SurrogateModel:
    method __init__ (line 36) | def __init__(
    method _get_kernel (line 52) | def _get_kernel(self) -> Kernel:
    method _get_model (line 60) | def _get_model(self, inputs: Tensor, outputs: Tensor, kernel: Optional...
    method fit_observations (line 80) | def fit_observations(self, success_observations: List[ObservationInBas...
    method _fit_target_transformers (line 90) | def _fit_target_transformers(self, success_observations: List[Observat...
    method _target_to_surrogate (line 106) | def _target_to_surrogate(self, x: Tensor) -> Tensor:
    method _surrogate_to_target (line 116) | def _surrogate_to_target(self, x: Tensor) -> Tensor:
    method _cost_to_logcost (line 128) | def _cost_to_logcost(self, x: Tensor) -> Tensor:
    method _logcost_to_cost (line 136) | def _logcost_to_cost(self, x: Tensor) -> Tensor:
    method fit_suggestions (line 145) | def fit_suggestions(self, outstanding_suggestions: List[SuggestionInBa...
    method fit_pareto_set (line 175) | def fit_pareto_set(self, pareto_observations: List[ObservationInBasic]...
    method get_pareto_surrogate_for_cost (line 185) | def get_pareto_surrogate_for_cost(self, cost: float) -> float:
    method fit_failures (line 194) | def fit_failures(
    method _get_success_prob (line 209) | def _get_success_prob(self, samples_in_natural: Tensor):
    method observe_surrogate (line 219) | def observe_surrogate(self, samples_in_basic: Tensor) -> SurrogateObse...

FILE: carbs/serialization.py
  class Serializable (line 33) | class Serializable:
    method __attrs_post_init__ (line 35) | def __attrs_post_init__(self) -> None:
    method __setattr__ (line 38) | def __setattr__(self, item: str, value: Any):
    method mutable_clone (line 44) | def mutable_clone(self: TC) -> ContextManager[TC]:
    method to_dict (line 76) | def to_dict(self) -> dict:
    method from_dict (line 85) | def from_dict(cls: Type[TC], dump: dict, is_upgrade_allowed: bool = Fa...
  function _to_dict (line 120) | def _to_dict(v: Any) -> Any:
  function _from_value (line 144) | def _from_value(v: Dict[str, Any], is_upgrade_allowed: bool) -> Any:
  class ParamTypeError (line 183) | class ParamTypeError(TypeError):
  function _get_all_subclasses (line 187) | def _get_all_subclasses(cls):
  function _compute_unserializable (line 195) | def _compute_unserializable(qualnames: List[str]) -> None:
  function _dedupe_subclasses_by_qualname (line 206) | def _dedupe_subclasses_by_qualname(subclasses: List[type]) -> List[type]:
  function _dedupe_subclasses_by_id (line 211) | def _dedupe_subclasses_by_id(subclasses: List[type]) -> List[type]:
  function get_all_serializable_classes (line 216) | def get_all_serializable_classes() -> List[type]:
  function get_serializable_type_from_qualname (line 224) | def get_serializable_type_from_qualname(qualname: str) -> Type[Serializa...
  function get_qualname_from_serializable_type (line 239) | def get_qualname_from_serializable_type(serializable_type: type) -> str:
  function flatten_dict (line 260) | def flatten_dict(d: DictNest, prefix: str = "") -> DictFlat:
  function inflate_dict (line 270) | def inflate_dict(d: DictFlat) -> DictNest:

FILE: carbs/test_carbs.py
  function carbs_config (line 23) | def carbs_config() -> CARBSParams:
  function params (line 28) | def params() -> List[Param]:
  function carbs_instance (line 37) | def carbs_instance(carbs_config: CARBSParams, params: List[Param]) -> CA...
  function test_suggest_one (line 41) | def test_suggest_one(carbs_instance: CARBS) -> None:
  function test_suggest_observe_ten (line 51) | def test_suggest_observe_ten(carbs_instance: CARBS) -> None:
  function test_observe (line 63) | def test_observe(carbs_instance: CARBS) -> None:
  function test_forget (line 76) | def test_forget(carbs_instance: CARBS) -> None:

FILE: carbs/utils.py
  class ParamSpace (line 35) | class ParamSpace(Serializable):
    method basic_from_param (line 36) | def basic_from_param(self, value: ParamType) -> Any:
    method param_from_basic (line 39) | def param_from_basic(self, value: Any) -> ParamType:
    method drop_type (line 42) | def drop_type(self) -> Any:
  class Param (line 47) | class Param:
  class RealNumberSpace (line 54) | class RealNumberSpace(ParamSpace):
    method basic_from_param (line 61) | def basic_from_param(self, value: ParamType) -> float:
    method param_from_basic (line 64) | def param_from_basic(self, value: float, is_rounded: bool = True) -> P...
    method round_tensor_in_basic (line 67) | def round_tensor_in_basic(self, value: Tensor) -> Tensor:
    method min_bound (line 73) | def min_bound(self):
    method max_bound (line 80) | def max_bound(self):
    method plot_scale (line 87) | def plot_scale(self) -> str:
  class LinearSpace (line 92) | class LinearSpace(RealNumberSpace):
    method __attrs_post_init__ (line 96) | def __attrs_post_init__(self) -> None:
    method basic_from_param (line 102) | def basic_from_param(self, value: ParamType) -> float:
    method param_from_basic (line 106) | def param_from_basic(self, value: float, is_rounded: bool = True) -> f...
    method round_tensor_in_basic (line 112) | def round_tensor_in_basic(self, value: Tensor) -> Tensor:
    method plot_scale (line 123) | def plot_scale(self) -> str:
  class LogSpace (line 128) | class LogSpace(RealNumberSpace):
    method basic_from_param (line 133) | def basic_from_param(self, value: ParamType) -> float:
    method param_from_basic (line 139) | def param_from_basic(self, value: float, is_rounded: bool = True) -> f...
    method round_tensor_in_basic (line 145) | def round_tensor_in_basic(self, value: Tensor) -> Tensor:
    method plot_scale (line 159) | def plot_scale(self) -> str:
  class LogitSpace (line 164) | class LogitSpace(RealNumberSpace):
    method basic_from_param (line 168) | def basic_from_param(self, value: ParamType) -> float:
    method param_from_basic (line 176) | def param_from_basic(self, value: float, is_rounded: bool = True) -> f...
    method plot_scale (line 181) | def plot_scale(self) -> str:
  function log_norm_cdf (line 189) | def log_norm_cdf(z: Tensor):
  function expected_improvement (line 204) | def expected_improvement(
  function probability_of_improvement (line 222) | def probability_of_improvement(
  function aggregate_logical_and_across_dim (line 236) | def aggregate_logical_and_across_dim(x: Tensor, dim: int = -1) -> Tensor:
  function add_dict_key_prefix (line 243) | def add_dict_key_prefix(input_dict: Dict[str, Any], prefix: str):
  class ObservationInParam (line 248) | class ObservationInParam(Serializable):
  class ObservationInBasic (line 256) | class ObservationInBasic(Serializable):
  class SuggestionInBasic (line 264) | class SuggestionInBasic(Serializable):
  class OutstandingSuggestionEstimatorEnum (line 269) | class OutstandingSuggestionEstimatorEnum(Enum):
  class SuggestionRedistributionMethodEnum (line 275) | class SuggestionRedistributionMethodEnum(Enum):
  class WandbLoggingParams (line 281) | class WandbLoggingParams(Serializable):
  class CARBSParams (line 293) | class CARBSParams(Serializable):
  class SurrogateModelParams (line 344) | class SurrogateModelParams(Serializable):
  class SuggestOutput (line 356) | class SuggestOutput:
  class ObserveOutput (line 362) | class ObserveOutput:
  function load_observations_from_wandb_run (line 366) | def load_observations_from_wandb_run(
  function get_checkpoint_obs_count (line 398) | def get_checkpoint_obs_count(checkpoint_name: str) -> int:
  function load_latest_checkpoint_from_wandb_run (line 406) | def load_latest_checkpoint_from_wandb_run(
  function load_checkpoint_from_wandb_run (line 424) | def load_checkpoint_from_wandb_run(
  function assert_empty (line 438) | def assert_empty(x: Sized, message: str = "unexpected elements") -> None:
  function ordered_dict_index (line 442) | def ordered_dict_index(od: OrderedDict, value: Any) -> int:
  function group_observations (line 453) | def group_observations(
  function observation_group_cost (line 475) | def observation_group_cost(group: Sequence[ObservationInBasic]) -> float:
  function observation_group_output (line 479) | def observation_group_output(group: Sequence[ObservationInBasic]) -> float:
  function pareto_area_from_groups (line 483) | def pareto_area_from_groups(obs_groups: Tuple[ObservationGroup, ...]) ->...
  function get_pareto_groups (line 498) | def get_pareto_groups(
  function get_pareto_groups_conservative (line 538) | def get_pareto_groups_conservative(
  function get_pareto_curve_plot (line 611) | def get_pareto_curve_plot(