diff --git a/codes/models/ExtensibleTrainer.py b/codes/models/ExtensibleTrainer.py
index 8f4e2e9e..32b627d3 100644
--- a/codes/models/ExtensibleTrainer.py
+++ b/codes/models/ExtensibleTrainer.py
@@ -230,25 +230,30 @@ class ExtensibleTrainer(BaseModel):
             [e.after_optimize(state) for e in self.experiments]
 
         # Record visual outputs for usage in debugging and testing.
-        if 'visuals' in self.opt['logger'].keys() and self.rank <= 0:
+        if 'visuals' in self.opt['logger'].keys() and self.rank <= 0 and step % self.opt['logger']['visual_debug_rate'] == 0:
             sample_save_path = os.path.join(self.opt['path']['models'], "..", "visual_dbg")
             for v in self.opt['logger']['visuals']:
                 if v not in state.keys():
                     continue   # This can happen for several reasons (ex: 'after' defs), just ignore it.
-                if step % self.opt['logger']['visual_debug_rate'] == 0:
-                    for i, dbgv in enumerate(state[v]):
-                        if 'recurrent_visual_indices' in self.opt['logger'].keys():
-                            for rvi in self.opt['logger']['recurrent_visual_indices']:
-                                rdbgv = dbgv[:, rvi]
-                                if rdbgv.shape[1] > 3:
-                                    rdbgv = rdbgv[:, :3, :, :]
-                                os.makedirs(os.path.join(sample_save_path, v), exist_ok=True)
-                                utils.save_image(rdbgv, os.path.join(sample_save_path, v, "%05i_%02i_%02i.png" % (step, rvi, i)))
-                        else:
-                            if dbgv.shape[1] > 3:
-                                dbgv = dbgv[:,:3,:,:]
+                for i, dbgv in enumerate(state[v]):
+                    if 'recurrent_visual_indices' in self.opt['logger'].keys():
+                        for rvi in self.opt['logger']['recurrent_visual_indices']:
+                            rdbgv = dbgv[:, rvi]
+                            if rdbgv.shape[1] > 3:
+                                rdbgv = rdbgv[:, :3, :, :]
                             os.makedirs(os.path.join(sample_save_path, v), exist_ok=True)
-                            utils.save_image(dbgv, os.path.join(sample_save_path, v, "%05i_%02i.png" % (step, i)))
+                            utils.save_image(rdbgv, os.path.join(sample_save_path, v, "%05i_%02i_%02i.png" % (step, rvi, i)))
+                    else:
+                        if dbgv.shape[1] > 3:
+                            dbgv = dbgv[:,:3,:,:]
+                        os.makedirs(os.path.join(sample_save_path, v), exist_ok=True)
+                        utils.save_image(dbgv, os.path.join(sample_save_path, v, "%05i_%02i.png" % (step, i)))
+            # Some models have their own specific visual debug routines.
+            for net_name, net in self.networks.items():
+                if hasattr(net.module, "visual_dbg"):
+                    model_vdbg_dir = os.path.join(sample_save_path, net_name)
+                    os.makedirs(model_vdbg_dir, exist_ok=True)
+                    net.module.visual_dbg(step, model_vdbg_dir)
 
     def compute_fea_loss(self, real, fake):
         with torch.no_grad():