update doc

diffsynth/diffusion/base_pipeline.py

@@ -178,15 +178,26 @@ class BasePipeline(torch.nn.Module):
     def get_vram(self):
         return torch.cuda.mem_get_info(self.device)[1] / (1024 ** 3)
     
+    def get_module(self, model, name):
+        if "." in name:
+            name, suffix = name[:name.index(".")], name[name.index(".") + 1:]
+            if name.isdigit():
+                return self.get_module(model[int(name)], suffix)
+            else:
+                return self.get_module(getattr(model, name), suffix)
+        else:
+            return getattr(model, name)
     
     def freeze_except(self, model_names):
-        for name, model in self.named_children():
-            if name in model_names:
-                model.train()
-                model.requires_grad_(True)
-            else:
-                model.eval()
-                model.requires_grad_(False)
+        self.eval()
+        self.requires_grad_(False)
+        for name in model_names:
+            module = self.get_module(self, name)
+            if module is None:
+                print(f"No {name} models in the pipeline. We cannot enable training on the model. If this occurs during the data processing stage, it is normal.")
+                continue
+            module.train()
+            module.requires_grad_(True)
                 
     
     def blend_with_mask(self, base, addition, mask):