diff --git a/modules/dml/hijack/torch.py b/modules/dml/hijack/torch.py
index f70479d0da0..ff5ee4df8e5 100644
--- a/modules/dml/hijack/torch.py
+++ b/modules/dml/hijack/torch.py
@@ -3,10 +3,10 @@
 from modules.sd_hijack_utils import CondFunc
 
 CondFunc('torchsde._brownian.brownian_interval._randn', lambda _, size, dtype, device, seed: torch.randn(size, dtype=dtype, device=torch.device("cpu"), generator=torch.Generator(torch.device("cpu")).manual_seed(int(seed))).to(device), lambda _, size, dtype, device, seed: device.type == 'privateuseone')
-
 # https://github.com/microsoft/DirectML/issues/400
 CondFunc('torch.Tensor.new', lambda orig, self, *args, **kwargs: orig(self.cpu(), *args, **kwargs).to(self.device), lambda orig, self, *args, **kwargs: torch.dml.is_directml_device(self.device))
 
+
 _lerp = torch.lerp
 def lerp(*args, **kwargs) -> torch.Tensor:
     rep = None
@@ -41,10 +41,11 @@ def lerp(*args, **kwargs) -> torch.Tensor:
     return _lerp(*args, **kwargs)
 torch.lerp = lerp
 
+
 # https://github.com/lshqqytiger/stable-diffusion-webui-directml/issues/436
 _pow_ = torch.Tensor.pow_
 def pow_(self: torch.Tensor, *args, **kwargs):
     if self.dtype == torch.float64:
         return _pow_(self.cpu(), *args, **kwargs).to(self.device)
     return _pow_(self, *args, **kwargs)
-torch.Tensor.pow_ = _pow_
+torch.Tensor.pow_ = pow_