perf: run LTXVDilateVideoMask pooling on GPU for massive speedup

vanish_nodes.py

@@ -59,19 +59,23 @@ def execute(
     ) -> io.NodeOutput:
         if mask is None and image_as_mask is None:
             raise ValueError("Either 'mask' or 'image_as_mask' must be provided.")
-
+        
         if mask is None:
             mask = image_as_mask.mean(dim=-1)
-
+            
         if mask.ndim == 4:
             mask = mask[:, :, :, 0]
 
+        from comfy import model_management
+        device = model_management.get_torch_device()
+        mask = mask.to(device)
+
         s_kernel = spatial_radius * 2 + 1
         t_kernel = temporal_radius * 2 + 1
 
         # Separable dilation: 2D spatial + 1D temporal (much faster than 3D pooling)
         if s_kernel > 1:
-            mask = mask.unsqueeze(1)  # (B, 1, H, W)
+            mask = mask.unsqueeze(1) # (B, 1, H, W)
             mask = F.max_pool2d(
                 mask, kernel_size=s_kernel, stride=1, padding=spatial_radius
             )
@@ -86,6 +90,7 @@ def execute(
             mask = mask.reshape(H, W, B).permute(2, 0, 1)
 
         mask = (mask > 0.5).float()
+        mask = mask.cpu()
         return io.NodeOutput(mask)