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clean up

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This commit is contained in:
Anonymous-submission-repo 2022-10-15 03:53:08 +00:00
parent 44883f7463
commit 2daaa4c637
8 changed files with 99 additions and 60 deletions
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1
flaml/automl.py
View File

@ -3690,4 +3690,3 @@ class AutoML(BaseEstimator):
q += inv[i] / s
if p < q:
return estimator_list[i]

48
flaml/tune/searcher/flow2.py
View File

@ -111,12 +111,18 @@ class FLOW2(Searcher):
self.lexico_objectives = lexico_objectives
if self.lexico_objectives is not None:
if "modes" not in self.lexico_objectives.keys():
self.lexico_objectives["modes"] = ["min"]*len(self.lexico_objectives["metrics"])
for t_metric, t_mode in zip(self.lexico_objectives["metrics"], self.lexico_objectives["modes"]):
self.lexico_objectives["modes"] = ["min"] * len(
self.lexico_objectives["metrics"]
)
for t_metric, t_mode in zip(
self.lexico_objectives["metrics"], self.lexico_objectives["modes"]
):
if t_metric not in self.lexico_objectives["tolerances"].keys():
self.lexico_objectives["tolerances"][t_metric] = 0
if t_metric not in self.lexico_objectives["targets"].keys():
self.lexico_objectives["targets"][t_metric] = -float("inf") if t_mode == "min" else float("inf")
self.lexico_objectives["targets"][t_metric] = (
-float("inf") if t_mode == "min" else float("inf")
)
self.resource_multiple_factor = (
resource_multiple_factor or SAMPLE_MULTIPLY_FACTOR
)
@ -299,7 +305,7 @@ class FLOW2(Searcher):
flow2.best_obj = {}
for k, v in obj.items():
flow2.best_obj[k] = (
v * -1
-v
if self.lexico_objectives["modes"][
self.lexico_objectives["metrics"].index(k)
]
@ -345,7 +351,9 @@ class FLOW2(Searcher):
self._init_search()
return True
def update_fbest(self,):
def update_fbest(
self,
):
obj_initial = self.lexico_objectives["metrics"][0]
feasible_index = [*range(len(self._histories[obj_initial]))]
for k_metric in self.lexico_objectives["metrics"]:
@ -376,10 +384,32 @@ class FLOW2(Searcher):
for k in self.lexico_objectives["metrics"]:
self._histories[k].append(result[k])
self.update_fbest()
for k_metric, k_mode in zip(self.lexico_objectives["metrics"],self.lexico_objectives["modes"]):
k_target = self.lexico_objectives["targets"][k_metric] if k_mode == "min" else -1*self.lexico_objectives["targets"][k_metric]
if (result[k_metric] < max([self._f_best[k_metric] + self.lexico_objectives["tolerances"][k_metric], k_target])) and (
self.best_obj[k_metric] < max([self._f_best[k_metric] + self.lexico_objectives["tolerances"][k_metric], k_target])
for k_metric, k_mode in zip(
self.lexico_objectives["metrics"], self.lexico_objectives["modes"]
):
k_target = (
self.lexico_objectives["targets"][k_metric]
if k_mode == "min"
else -self.lexico_objectives["targets"][k_metric]
)
if (
result[k_metric]
< max(
[
self._f_best[k_metric]
+ self.lexico_objectives["tolerances"][k_metric],
k_target,
]
)
) and (
self.best_obj[k_metric]
< max(
[
self._f_best[k_metric]
+ self.lexico_objectives["tolerances"][k_metric],
k_target,
]
)
):
continue
elif result[k_metric] < self.best_obj[k_metric]:

4
flaml/tune/searcher/search_thread.py
View File

@ -150,9 +150,7 @@ class SearchThread:
self.obj_best1 = obj
self.cost_best = self.cost_last
self.best_result = result
if (
getattr(self._search_alg, "lexico_objectives", None) is None
):
if getattr(self._search_alg, "lexico_objectives", None) is None:
# TODO: Improve this behavior. When lexico_objectives is provided to CFO,
# related variables are not callable.
self._update_speed()

24
flaml/tune/tune.py
View File

@ -74,13 +74,19 @@ class ExperimentAnalysis(EA):
histories[objective].append(
results[keys[time_index]][objective]
if mode == "min"
else trials[keys[time_index]][objective] * -1
else -trials[keys[time_index]][objective]
)
obj_initial = self.lexico_objectives["metrics"][0]
feasible_index = [*range(len(histories[obj_initial]))]
for k_metric, k_mode in zip(self.lexico_objectives["metrics"],self.lexico_objectives["modes"]):
for k_metric, k_mode in zip(
self.lexico_objectives["metrics"], self.lexico_objectives["modes"]
):
k_values = np.array(histories[k_metric])
k_target = self.lexico_objectives["targets"][k_metric] * -1 if k_mode == "max" else self.lexico_objectives["targets"][k_metric]
k_target = (
-self.lexico_objectives["targets"][k_metric]
if k_mode == "max"
else self.lexico_objectives["targets"][k_metric]
)
f_best[k_metric] = np.min(k_values.take(feasible_index))
feasible_index_prior = np.where(
k_values
@ -449,8 +455,11 @@ def run(
logger.setLevel(logging.CRITICAL)
from .searcher.blendsearch import BlendSearch, CFO
if lexico_objectives != None:
logger.warning("If lexico_objectives is not None, search_alg is forced to be CFO")
if lexico_objectives is not None:
logger.warning(
"If lexico_objectives is not None, search_alg is forced to be CFO"
)
search_alg = None
if search_alg is None:
flaml_scheduler_resource_attr = (
@ -469,9 +478,12 @@ def run(
if lexico_objectives is None:
try:
import optuna as _
SearchAlgorithm = BlendSearch
logger.info(
"Using search algorithm {}.".format(SearchAlgorithm.__class__.__name__)
"Using search algorithm {}.".format(
SearchAlgorithm.__class__.__name__
)
)
except ImportError:
SearchAlgorithm = CFO