[pre-commit.ci] auto fixes from pre-commit.com hooks

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tests/classification/test_average_precision.py

@@ -15,15 +15,15 @@
 
 import numpy as np
 import pytest
-from sklearn.metrics import average_precision_score as sk_average_precision_score
 import torch
+from sklearn.metrics import average_precision_score as sk_average_precision_score
 from torch import tensor
 
 from tests.classification.inputs import _input_binary_prob
 from tests.classification.inputs import _input_multiclass_prob as _input_mcls_prob
 from tests.classification.inputs import _input_multidim_multiclass_prob as _input_mdmc_prob
 from tests.helpers import seed_all
-from tests.helpers.testers import NUM_CLASSES, MetricTester, BATCH_SIZE
+from tests.helpers.testers import BATCH_SIZE, NUM_CLASSES, MetricTester
 from torchmetrics.classification.average_precision import AveragePrecision
 from torchmetrics.functional import average_precision
 
@@ -123,10 +123,10 @@ def test_average_precision(scores, target, expected_score):
 
 @pytest.mark.parametrize(
     "preds, target, sk_metric, num_classes", [
-        (torch.randn(BATCH_SIZE, NUM_CLASSES),
-         torch.randint(0, 2, (BATCH_SIZE, NUM_CLASSES)),
-         _sk_avg_prec_multiclass_prob,
-         NUM_CLASSES),
+        (
+            torch.randn(BATCH_SIZE, NUM_CLASSES), torch.randint(0, 2, (BATCH_SIZE, NUM_CLASSES)),
+            _sk_avg_prec_multiclass_prob, NUM_CLASSES
+        ),
     ]
 )
 def test_average_precision_multilabel(preds, target, sk_metric, num_classes):