diff --git a/yolort/v5/utils/autoanchor.py b/yolort/v5/utils/autoanchor.py
index 82d12440..530ff388 100644
--- a/yolort/v5/utils/autoanchor.py
+++ b/yolort/v5/utils/autoanchor.py
@@ -147,9 +147,9 @@ def print_results(k):
     print(f"{prefix}Running kmeans for {n} anchors on {len(wh)} points...")
     s = wh.std(0)  # sigmas for whitening
     k, dist = kmeans(wh / s, n, iter=30)  # points, mean distance
-    assert len(k) == n, (
-        f"{prefix}ERROR: scipy.cluster.vq.kmeans requested {n} points but returned only {len(k)}"
-    )
+    assert (
+        len(k) == n
+    ), f"{prefix}ERROR: scipy.cluster.vq.kmeans requested {n} points but returned only {len(k)}"
     k *= s
     wh = torch.tensor(wh, dtype=torch.float32)  # filtered
     wh0 = torch.tensor(wh0, dtype=torch.float32)  # unfiltered
diff --git a/yolort/v5/utils/datasets.py b/yolort/v5/utils/datasets.py
index 3a24898a..1a84c8d6 100644
--- a/yolort/v5/utils/datasets.py
+++ b/yolort/v5/utils/datasets.py
@@ -362,9 +362,9 @@ def __init__(
             tqdm(None, desc=prefix + d, total=n, initial=n)  # display cache results
             if cache["msgs"]:
                 logging.info("\n".join(cache["msgs"]))  # display warnings
-        assert nf > 0 or not augment, (
-            f"{prefix}No labels in {cache_path}. Can not train without labels. See {HELP_URL}"
-        )
+        assert (
+            nf > 0 or not augment
+        ), f"{prefix}No labels in {cache_path}. Can not train without labels. See {HELP_URL}"
 
         # Read cache
         [cache.pop(k) for k in ("hash", "version", "msgs")]  # remove items
diff --git a/yolort/v5/utils/general.py b/yolort/v5/utils/general.py
index 7cbbf77d..cc44b97e 100644
--- a/yolort/v5/utils/general.py
+++ b/yolort/v5/utils/general.py
@@ -515,9 +515,9 @@ def non_max_suppression(
     xc = prediction[..., 4] > conf_thres  # candidates
 
     # Checks
-    assert 0 <= conf_thres <= 1, (
-        f"Invalid Confidence threshold {conf_thres}, valid values are between 0.0 and 1.0"
-    )
+    assert (
+        0 <= conf_thres <= 1
+    ), f"Invalid Confidence threshold {conf_thres}, valid values are between 0.0 and 1.0"
     assert 0 <= iou_thres <= 1, f"Invalid IoU {iou_thres}, valid values are between 0.0 and 1.0"
 
     # Settings
diff --git a/yolort/v5/utils/torch_utils.py b/yolort/v5/utils/torch_utils.py
index 566e43c4..54f4a8d0 100644
--- a/yolort/v5/utils/torch_utils.py
+++ b/yolort/v5/utils/torch_utils.py
@@ -308,9 +308,7 @@ def model_info(model, verbose=False, img_size=640):
     except (ImportError, Exception):
         fs = ""
 
-    LOGGER.info(
-        f"Model Summary: {len(list(model.modules()))} layers, {n_p} parameters, {n_g} gradients{fs}"
-    )
+    LOGGER.info(f"Model Summary: {len(list(model.modules()))} layers, {n_p} parameters, {n_g} gradients{fs}")
 
 
 def load_classifier(name="resnet101", n=2):