diff --git a/tests/helpers/testers.py b/tests/helpers/testers.py
index daed5c69501..7b1abdd7e32 100644
--- a/tests/helpers/testers.py
+++ b/tests/helpers/testers.py
@@ -16,11 +16,11 @@
 import sys
 from functools import partial
 from typing import Any, Callable, Dict, Optional, Sequence
-import yaml
 
 import numpy as np
 import pytest
 import torch
+import yaml
 from torch import Tensor, tensor
 from torch.multiprocessing import Pool, set_start_method
 
diff --git a/torchmetrics/metric.py b/torchmetrics/metric.py
index 05c113d04c3..698ae799cef 100644
--- a/torchmetrics/metric.py
+++ b/torchmetrics/metric.py
@@ -418,11 +418,12 @@ def device(self) -> "torch.device":
         return self._device
 
     def to(self, *args: Any, **kwargs: Any) -> "Metric":
-        """Moves the parameters and buffers. Normal dtype casting is not supported by this method
-        instead use the `set_dtype` method instead.
+        """Moves the parameters and buffers.
+
+        Normal dtype casting is not supported by this method instead use the `set_dtype` method instead.
         """
         out = torch._C._nn._parse_to(*args, **kwargs)
-        if len(out)==4:  # pytorch 1.5 and higher
+        if len(out) == 4:  # pytorch 1.5 and higher
             device, dtype, non_blocking, convert_to_format = out
         else:  # pytorch 1.4 and lower
             device, dtype, non_blocking = out
@@ -431,8 +432,12 @@ def to(self, *args: Any, **kwargs: Any) -> "Metric":
 
         def convert(t: Tensor) -> Tensor:
             if convert_to_format is not None and t.dim() in (4, 5):
-                return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None,
-                            non_blocking, memory_format=convert_to_format)
+                return t.to(
+                    device,
+                    dtype if t.is_floating_point() or t.is_complex() else None,
+                    non_blocking,
+                    memory_format=convert_to_format,
+                )
             return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
 
         self._device = device