diff --git a/comfy/controlnet.py b/comfy/controlnet.py
index 5921e6b1..6d37aa74 100644
--- a/comfy/controlnet.py
+++ b/comfy/controlnet.py
@@ -208,7 +208,7 @@ class ControlLoraOps:
 
         def forward(self, input):
             if self.up is not None:
-                return torch.nn.functional.linear(input, self.weight.to(input.device) + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), self.bias)
+                return torch.nn.functional.linear(input, self.weight.to(input.dtype).to(input.device) + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), self.bias)
             else:
                 return torch.nn.functional.linear(input, self.weight.to(input.device), self.bias)
 
@@ -247,7 +247,7 @@ class ControlLoraOps:
 
         def forward(self, input):
             if self.up is not None:
-                return torch.nn.functional.conv2d(input, self.weight.to(input.device) + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), self.bias, self.stride, self.padding, self.dilation, self.groups)
+                return torch.nn.functional.conv2d(input, self.weight.to(input.dtype).to(input.device) + (torch.mm(self.up.flatten(start_dim=1), self.down.flatten(start_dim=1))).reshape(self.weight.shape).type(input.dtype), self.bias, self.stride, self.padding, self.dilation, self.groups)
             else:
                 return torch.nn.functional.conv2d(input, self.weight.to(input.device), self.bias, self.stride, self.padding, self.dilation, self.groups)