diff --git a/patches/hypernetworks.py b/patches/hypernetworks.py
index 928692f..2308d63 100644
--- a/patches/hypernetworks.py
+++ b/patches/hypernetworks.py
@@ -222,12 +222,12 @@ class SingularForward(Forward):
     def __call__(self, context_k, context_v=None, layer=None):
         if self.processor in available_opts:
             context_layers = available_opts[self.processor].layers.get(context_k.shape[2], None)
-            if context_layers is None:
-                return context_k, context_k
             if context_v is None:
                 context_v = context_k
+            if context_layers is None:
+                return context_k, context_v
             if layer is not None and hasattr(layer, 'hyper_k') and hasattr(layer, 'hyper_v'):
-                layer.hyper_v = context_layers[0], layer.hyper_k = context_layers[1]
+                layer.hyper_k = context_layers[0], layer.hyper_v = context_layers[1]
             return context_layers[0](context_k, multiplier=self.strength), context_layers[1](context_v,
                                                                                              multiplier=self.strength)  # define forward_strength, which invokes HNModule with specified strength.
         # Note : we share same HN if it is called multiple time, which means you might not be able to train it via this structure.