Fix saliency: enable_grad + debug logging

app.py

@@ -248,14 +248,17 @@ def _compute_saliency(bw_t, adj_t, models):
     maps = []
     for _, task in sample:
         try:
-            adj = adj_t.clone().requires_grad_(True)
-            logits = task.model(bw_t, adj)
-            if isinstance(logits, tuple):
-                logits = logits[0]
-            torch.softmax(logits, -1)[0, 1].backward()
+            adj = adj_t.clone().detach().requires_grad_(True)
+            bw  = bw_t.clone().detach()
+            with torch.enable_grad():
+                out = task.model(bw, adj)
+                logits = out[0] if isinstance(out, tuple) else out
+                prob = torch.softmax(logits, -1)[0, 1]
+                prob.backward()
             if adj.grad is not None:
-                maps.append(adj.grad[0].abs().detach().numpy())
-        except Exception:
+                maps.append(adj.grad[0].abs().detach().cpu().numpy())
+        except Exception as e:
+            print(f"[saliency model] {e}")
             continue
     if not maps:
         n = adj_t.shape[-1]
@@ -522,7 +525,9 @@ def run_gcn(file_path):
             net_bounds=net_bounds,
             net_colors=atlas_cfg["net_colors"],
         )
-    except Exception:
+    except Exception as _sal_err:
+        print(f"[saliency] failed: {_sal_err}")
+        import traceback; traceback.print_exc()
         sal_img = None
 
     # ── Verdict ──