Fix: remove redundant 1- from SSIMLoss docstring examples

Fixes #8822 - The forward() docstring examples used `print(1-SSIMLoss()(x,y))`, but SSIMLoss already computes 1-ssim internally. The `1-` prefix made examples return ssim (not loss), misleading users into training with inverted loss.

Signed-off-by: Zeeshan Modi <92383127+Zeesejo@users.noreply.github.com>

Author: Zeesejo

monai/losses/ssim_loss.py

@@ -111,17 +111,17 @@ def forward(self, input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
                 # 2D data
                 x = torch.ones([1,1,10,10])/2
                 y = torch.ones([1,1,10,10])/2
-                print(1-SSIMLoss(spatial_dims=2)(x,y))
+                print(SSIMLoss(spatial_dims=2)(x,y))
 
                 # pseudo-3D data
                 x = torch.ones([1,5,10,10])/2  # 5 could represent number of slices
                 y = torch.ones([1,5,10,10])/2
-                print(1-SSIMLoss(spatial_dims=2)(x,y))
+                print(SSIMLoss(spatial_dims=2)(x,y))
 
                 # 3D data
                 x = torch.ones([1,1,10,10,10])/2
                 y = torch.ones([1,1,10,10,10])/2
-                print(1-SSIMLoss(spatial_dims=3)(x,y))
+                print(SSIMLoss(spatial_dims=3)(x,y))
         """
         ssim_value = self.ssim_metric._compute_tensor(input, target).view(-1, 1)
         loss: torch.Tensor = 1 - ssim_value