update

tune_sklearn/objective.py

@@ -1,21 +1,21 @@
 import os
-import cloudpickle
-from tune.api.factory import TUNE_OBJECT_FACTORY
 from typing import Any, Optional, Tuple
 from uuid import uuid4
 
+import cloudpickle
 import numpy as np
 import pandas as pd
 from sklearn.metrics import get_scorer
 from sklearn.model_selection import cross_val_score
 from triad import FileSystem
+
 from tune import NonIterativeObjectiveFunc, Trial, TrialReport
+from tune.api.factory import TUNE_OBJECT_FACTORY
 from tune.constants import (
     SPACE_MODEL_NAME,
     TUNE_DATASET_DF_DEFAULT_NAME,
     TUNE_DATASET_VALIDATION_DF_DEFAULT_NAME,
 )
-
 from tune_sklearn.utils import to_sk_model, to_sk_model_expr
 
 

tune_tensorflow/utils.py

@@ -1,11 +1,11 @@
-from typing import Any, Type, Dict
+from typing import Any, Dict, Type
 
 from triad.utils.convert import get_full_type_path, to_type
-from tune.concepts.space.parameters import TuningParametersTemplate
 
-from tune_tensorflow.spec import KerasTrainingSpec
 from tune import Space
+from tune.concepts.space.parameters import TuningParametersTemplate
 from tune.constants import SPACE_MODEL_NAME
+from tune_tensorflow.spec import KerasTrainingSpec
 
 _TYPE_DICT: Dict[str, Type[KerasTrainingSpec]] = {}
 

tune_test/local_optmizer.py

@@ -45,7 +45,7 @@ def test_rand(self):
             # common case
             values = self._generate_values(Rand(-2.0, 3.0), lambda x: x**2)
             assert len(values) > 0
-            assert all(x >= -2.0 and x <= 3.0 for x in values)
+            assert all(-2.0 <= x <= 3.0 for x in values)
 
             # with q, and range%q == 0
             values = self._generate_values(Rand(-2.0, 3.0, q=2.5), lambda x: x**2)
@@ -65,7 +65,7 @@ def test_rand(self):
 
             # with log
             values = self._generate_values(Rand(0.1, 3.0, log=True), lambda x: x**2)
-            assert all(x >= 0.1 and x <= 3.0 for x in values)
+            assert all(0.1 <= x <= 3.0 for x in values)
 
             # with log and q, and range%q == 0
             values = self._generate_values(