Store pre-cached norm weights on self to prevent GC during graph replay — root cause of all-zeros replay bug

single_shot_inference.py

@@ -283,6 +283,11 @@ class CUDAGraphDecoder:
             if kvn is not None:
                 kv_norm_dev[li] = kvn.to(dev, torch.float32) if kvn.device != torch.device(dev) or kvn.dtype != torch.float32 else kvn
         
+        self.attn_norm_dev = attn_norm_dev
+        self.ffn_norm_dev = ffn_norm_dev
+        self.q_norm_dev = q_norm_dev
+        self.kv_norm_dev = kv_norm_dev
+        
         # Verify all MoE/SE buffers are allocated (swizzled buffers must exist before capture)
         for li in range(self.n_layers):
             moe = moe_runners.get(li)