Update black

src/orion/algo/asha.py

@@ -73,7 +73,7 @@ def compute_budgets(
     for bracket_ressources in ressources:
         bracket_budgets = []
         for i, min_ressources in enumerate(bracket_ressources[::-1]):
-            budget = (reduction_factor ** i, min_ressources)
+            budget = (reduction_factor**i, min_ressources)
             bracket_budgets.append(budget)
             budgets_tab[len(bracket_ressources) - i - 1].append(budget)
         budgets.append(bracket_budgets[::-1])

src/orion/algo/evolution_es.py

@@ -60,8 +60,8 @@ def compute_budgets(
                 num_brackets - bracket_id
             )
             for i in range(0, num_brackets - bracket_id + 1):
-                n_i = int(num_trials / reduction_factor ** i)
-                min_i = int(min_resources * reduction_factor ** i)
+                n_i = int(num_trials / reduction_factor**i)
+                min_i = int(min_resources * reduction_factor**i)
                 bracket_budgets.append((n_i, min_i))
 
                 if budgets_tab.get(i):

src/orion/algo/hyperband.py

@@ -53,8 +53,8 @@ def compute_budgets(max_resources, reduction_factor):
 
         min_resources = max_resources / reduction_factor ** (num_brackets - bracket_id)
         for i in range(0, num_brackets - bracket_id + 1):
-            n_i = int(num_trials / reduction_factor ** i)
-            min_i = int(min_resources * reduction_factor ** i)
+            n_i = int(num_trials / reduction_factor**i)
+            min_i = int(min_resources * reduction_factor**i)
             bracket_budgets.append((n_i, min_i))
 
             if budgets_tab.get(i):

src/orion/analysis/lpi_utils.py

@@ -138,7 +138,7 @@ def lpi(
     results = numpy.zeros((n_runs, len(flattened_space)))
     for i in range(n_runs):
         trained_model = train_regressor(
-            model, data, random_state=rng.randint(2 ** 32 - 1), **kwargs
+            model, data, random_state=rng.randint(2**32 - 1), **kwargs
         )
         results[i] = modes[mode](best_point, flattened_space, trained_model, n_points)
 

src/orion/benchmark/task/base.py

@@ -49,7 +49,7 @@ def __call__(self, *args, **kwargs):
 
     @property
     def max_trials(self) -> int:
-        """Return the max number of trials to run for the task. """
+        """Return the max number of trials to run for the task."""
         return self._max_trials
 
     @abstractmethod

src/orion/benchmark/task/profet/forrester.py

@@ -19,7 +19,7 @@
 
 
 class ProfetForresterTask(ProfetTask):
-    """Simulated Task consisting in training a model on a variant of the Forrester function. """
+    """Simulated Task consisting in training a model on a variant of the Forrester function."""
 
     @dataclass
     class ModelConfig(ProfetTask.ModelConfig):

src/orion/benchmark/task/profet/profet_task.py

@@ -51,10 +51,10 @@ def make_reproducible(seed: int):
     with torch.random.fork_rng():
         # Set the random state, using the given seed.
         random.seed(seed)
-        np_seed = random.randint(0, 2 ** 32 - 1)
+        np_seed = random.randint(0, 2**32 - 1)
         np.random.seed(np_seed)
 
-        torch_seed = random.randint(0, 2 ** 32 - 1)
+        torch_seed = random.randint(0, 2**32 - 1)
         torch.random.manual_seed(torch_seed)
         if torch.cuda.is_available():
             torch.cuda.manual_seed_all(torch_seed)

src/orion/testing/evc.py

@@ -57,7 +57,7 @@ def build_root_experiment(space=None, trials=None):
     if space is None:
         space = {"x": "uniform(0, 100)", "y": "uniform(0, 100)", "z": "uniform(0, 100)"}
     if trials is None:
-        trials = [{"x": i, "y": i * 2, "z": i ** 2} for i in range(4)]
+        trials = [{"x": i, "y": i * 2, "z": i**2} for i in range(4)]
 
     root = build_experiment(name="root", max_trials=len(trials), space=space)
 

tests/functional/algos/test_algos.py

@@ -74,7 +74,7 @@ def rosenbrock(x, noise=None):
         z *= random.gauss(0, noise)
 
     return [
-        {"name": "objective", "type": "objective", "value": 4 * z ** 2 + 23.4},
+        {"name": "objective", "type": "objective", "value": 4 * z**2 + 23.4},
         {"name": "gradient", "type": "gradient", "value": [8 * z]},
     ]
 

tests/functional/backward_compatibility/black_box.py

@@ -10,7 +10,7 @@
 def function(x, noise):
     """Evaluate partial information of a quadratic."""
     z = (x - 34.56789) * random.gauss(0, noise)
-    return 4 * z ** 2 + 23.4, 8 * z
+    return 4 * z**2 + 23.4, 8 * z
 
 
 def execute():

tests/functional/backward_compatibility/test_versions.py

@@ -27,7 +27,7 @@
 def function(x):
     """Evaluate partial information of a quadratic."""
     z = x - 34.56789
-    return [dict(name="example_objective", type="objective", value=4 * z ** 2 + 23.4)]
+    return [dict(name="example_objective", type="objective", value=4 * z**2 + 23.4)]
 
 
 def get_branch_argument(version):

tests/functional/benchmark/test_benchmark_flow.py

@@ -38,7 +38,7 @@ def __init__(self, max_trials=20):
 
     def call(self, x):
 
-        y = (2 * x ** 4 + x ** 2 + 2) / (x ** 4 + 1)
+        y = (2 * x**4 + x**2 + 2) / (x**4 + 1)
 
         return [dict(name="birdlike", type="objective", value=y)]
 

tests/functional/branching/black_box.py

@@ -10,7 +10,7 @@
 def function(x):
     """Evaluate partial information of a quadratic."""
     y = x - 34.56789
-    return 4 * y ** 2 + 23.4, 8 * y
+    return 4 * y**2 + 23.4, 8 * y
 
 
 def execute():

tests/functional/branching/black_box_new.py

@@ -10,7 +10,7 @@
 def function(x):
     """Evaluate partial information of a quadratic."""
     y = x - 34.56789
-    return 4 * y ** 2 + 23.4, 8 * y
+    return 4 * y**2 + 23.4, 8 * y
 
 
 def execute():

tests/functional/branching/black_box_with_y.py

@@ -9,7 +9,7 @@
 def function(x, y):
     """Evaluate partial information of a quadratic."""
     y = x + y - 34.56789
-    return 4 * y ** 2 + 23.4, 8 * y
+    return 4 * y**2 + 23.4, 8 * y
 
 
 def execute():

tests/functional/branching/black_box_with_z.py

@@ -10,7 +10,7 @@
 def function(x, z):
     """Evaluate partial information of a quadratic."""
     y = x + z - 34.56789
-    return 4 * y ** 2 + 23.4, 8 * y
+    return 4 * y**2 + 23.4, 8 * y
 
 
 def execute():

tests/functional/commands/black_box.py

@@ -9,7 +9,7 @@
 def function(x):
     """Evaluate partial information of a quadratic."""
     z = x - 34.56789
-    return 4 * z ** 2 + 23.4, 8 * z
+    return 4 * z**2 + 23.4, 8 * z
 
 
 def execute():

tests/functional/demo/black_box.py

@@ -10,7 +10,7 @@
 def function(x):
     """Evaluate partial information of a quadratic."""
     z = x - 34.56789
-    return 4 * z ** 2 + 23.4, 8 * z
+    return 4 * z**2 + 23.4, 8 * z
 
 
 def execute():

tests/functional/demo/black_box_w_config.py

@@ -11,7 +11,7 @@
 def function(x):
     """Evaluate partial information of a quadratic."""
     z = x - 34.56789
-    return 4 * z ** 2 + 23.4, 8 * z
+    return 4 * z**2 + 23.4, 8 * z
 
 
 def execute():

tests/functional/demo/black_box_w_config_other.py

@@ -11,7 +11,7 @@
 def function(x):
     """Evaluate partial information of a quadratic."""
     z = x - 34.56789
-    return 4 * z ** 2 + 23.4, 8 * z
+    return 4 * z**2 + 23.4, 8 * z
 
 
 def execute():

tests/functional/demo/dir_per_trial.py

@@ -12,7 +12,7 @@
 def function(x):
     """Evaluate partial information of a quadratic."""
     z = x - 34.56789168765984988448213179176
-    return 4 * z ** 2 + 23.4, 8 * z
+    return 4 * z**2 + 23.4, 8 * z
 
 
 def execute():

tests/functional/storage/test_io.py

@@ -38,7 +38,7 @@ def foo(x, sleep_time):
 keys = ["net_in", "net_out"]
 MongoStat = namedtuple("MongoStat", keys)
 
-order_values = dict(b=1 / 1000.0, k=1, m=1000, g=1000 ** 2)
+order_values = dict(b=1 / 1000.0, k=1, m=1000, g=1000**2)
 
 
 def _convert_str_size(size):

tests/unittests/algo/pbt/test_pbt.py

@@ -23,7 +23,7 @@ def test_base_1(self):
         assert compute_fidelities(10, 10, 20, 1) == list(map(float, range(10, 21)))
 
     def test_other_bases(self):
-        assert compute_fidelities(9, 2, 2 ** 10, 2) == [2 ** i for i in range(1, 11)]
+        assert compute_fidelities(9, 2, 2**10, 2) == [2**i for i in range(1, 11)]
 
 
 class TestPBTObserve:

tests/unittests/algo/test_space.py

@@ -354,13 +354,13 @@ def test_basic_cardinality(self):
             ("reciprocal", 1e-4, 1e-2, 2, 90 * 2 + 1),
             ("reciprocal", 1e-5, 1e-2, 2, 90 + 90 * 2 + 1),
             ("reciprocal", 5.234e-3, 1.5908e-2, 2, (90 - 52) + 15 + 1),
-            ("reciprocal", 5.234e-3, 1.5908e-2, 4, (9 * 10 ** 3 - 5234) + 1590 + 1),
+            ("reciprocal", 5.234e-3, 1.5908e-2, 4, (9 * 10**3 - 5234) + 1590 + 1),
             (
                 "reciprocal",
                 5.234e-5,
                 1.5908e-2,
                 4,
-                (9 * 10 ** 3 * 3 - 5234) + 1590 + 1,
+                (9 * 10**3 * 3 - 5234) + 1590 + 1,
             ),
             ("uniform", 1e-5, 1e-2, 2, np.inf),
             ("uniform", -3, 4, 3, np.inf),
@@ -885,11 +885,11 @@ def test_cardinality(self):
         dim = Fidelity("epoch", 1, 9, 3)
         space.register(dim)
 
-        assert space.cardinality == (4 ** 2) * (6 + 1) * 1
+        assert space.cardinality == (4**2) * (6 + 1) * 1
 
         dim = Integer("yolo3", "uniform", -3, 2, shape=(3, 2))
         space.register(dim)
-        assert space.cardinality == (4 ** 2) * (6 + 1) * 1 * ((2 + 1) ** (3 * 2))
+        assert space.cardinality == (4**2) * (6 + 1) * 1 * ((2 + 1) ** (3 * 2))
 
         dim = Real("yolo4", "norm", 0.9)
         space.register(dim)

tests/unittests/core/evc/test_experiment_tree.py

@@ -53,10 +53,10 @@
 }
 
 
-CHILD_TRIALS_DUPLICATES = [{"x": i, "y": i * 2, "z": i ** 2} for i in range(2, 8)]
+CHILD_TRIALS_DUPLICATES = [{"x": i, "y": i * 2, "z": i**2} for i in range(2, 8)]
 
 GRAND_CHILD_TRIALS_DUPLICATES = [
-    {"x": i, "y": i * 2, "z": i ** 2} for i in list(range(1, 4)) + list(range(8, 10))
+    {"x": i, "y": i * 2, "z": i**2} for i in list(range(1, 4)) + list(range(8, 10))
 ]
 
 

tests/unittests/core/io/test_orion_cmdline_parser.py

@@ -51,7 +51,7 @@ class WeirdArgument(NamedTuple):
     ]
 )
 def prior_and_prior_type_and_value(request):
-    """ Fixture that gives a prior str, the prior type, and a value. """
+    """Fixture that gives a prior str, the prior type, and a value."""
     prior_str, prior_type, value = request.param
     return prior_str, prior_type, value
 
@@ -67,7 +67,7 @@ def prior_and_prior_type_and_value(request):
     ]
 )
 def weird_argument(request, prior_and_prior_type_and_value: Tuple[str, str, str]):
-    """ Fixture that provides a weird name, along with a prior and value. """
+    """Fixture that provides a weird name, along with a prior and value."""
     weird_param_name = request.param
     prior_str, prior_type, value = prior_and_prior_type_and_value
     return WeirdArgument(

tests/unittests/core/test_transformer.py

@@ -1322,22 +1322,22 @@ def test_capacity(self, space_each_type):
         dim = Integer("yolo2", "uniform", -3, 6)
         space.register(dim)
         tspace = build_required_space(space, type_requirement="integer")
-        assert tspace.cardinality == (4 ** 2) * (6 + 1)
+        assert tspace.cardinality == (4**2) * (6 + 1)
 
         dim = Integer("yolo3", "uniform", -3, 6, shape=(2, 1))
         space.register(dim)
         tspace = build_required_space(space, type_requirement="integer")
-        assert tspace.cardinality == (4 ** 2) * (6 + 1) * ((6 + 1) ** (2 * 1))
+        assert tspace.cardinality == (4**2) * (6 + 1) * ((6 + 1) ** (2 * 1))
 
         tspace = build_required_space(
             space, type_requirement="integer", shape_requirement="flattened"
         )
-        assert tspace.cardinality == (4 ** 2) * (6 + 1) * ((6 + 1) ** (2 * 1))
+        assert tspace.cardinality == (4**2) * (6 + 1) * ((6 + 1) ** (2 * 1))
 
         tspace = build_required_space(
             space, type_requirement="integer", dist_requirement="linear"
         )
-        assert tspace.cardinality == (4 ** 2) * (6 + 1) * ((6 + 1) ** (2 * 1))
+        assert tspace.cardinality == (4**2) * (6 + 1) * ((6 + 1) ** (2 * 1))
 
 
 def test_quantization_does_not_violate_bounds():

tests/unittests/plotting/test_plotly_backend.py

@@ -270,7 +270,7 @@ def test_multidim(self, monkeypatch):
     def test_fidelity(self, monkeypatch):
         """Tests that fidelity is supported"""
         config = mock_space(y="fidelity(1, 200, base=3)")
-        mock_experiment(monkeypatch, y=[1, 3 ** 2, 1, 3 ** 4])
+        mock_experiment(monkeypatch, y=[1, 3**2, 1, 3**4])
         with create_experiment(config, trial_config) as (_, _, experiment):
             plot = lpi(experiment, model_kwargs=dict(random_state=1))
 
@@ -485,7 +485,7 @@ def test_fidelity(self, monkeypatch):
         """Tests that fidelity is supported"""
         mock_train_regressor(monkeypatch)
         config = mock_space(y="fidelity(1, 200, base=3)")
-        mock_experiment(monkeypatch, y=[1, 3 ** 2, 1, 3 ** 4])
+        mock_experiment(monkeypatch, y=[1, 3**2, 1, 3**4])
         with create_experiment(config, trial_config) as (_, _, experiment):
             plot = partial_dependencies(
                 experiment, n_grid_points=5, model_kwargs=dict(random_state=1)

tox.ini

@@ -121,7 +121,7 @@ description = Verify code style with black
 basepython = python3
 skip_install = true
 deps =
-    black == 20.8b1
+    black == 22.3.0
 commands =
     black --check src/orion/ tests/