Merge pull request #1868 from HydrogenSulfate/fix_optimizer_init

fix bug for static graph

ppcls/engine/engine.py

@@ -224,7 +224,7 @@ class Engine(object):
         # build optimizer
         if self.mode == 'train':
             self.optimizer, self.lr_sch = build_optimizer(
-                self.config, self.config["Global"]["epochs"],
+                self.config["Optimizer"], self.config["Global"]["epochs"],
                 len(self.train_dataloader),
                 [self.model, self.train_loss_func])
 

ppcls/optimizer/__init__.py

@@ -44,8 +44,7 @@ def build_lr_scheduler(lr_config, epochs, step_each_epoch):
 
 # model_list is None in static graph
 def build_optimizer(config, epochs, step_each_epoch, model_list=None):
-    config = copy.deepcopy(config)
-    optim_config = config["Optimizer"]
+    optim_config = copy.deepcopy(config)
     if isinstance(optim_config, dict):
         # convert {'name': xxx, **optim_cfg} to [{name: {scope: xxx, **optim_cfg}}]
         optim_name = optim_config.pop("name")
@@ -93,6 +92,15 @@ def build_optimizer(config, epochs, step_each_epoch, model_list=None):
         else:
             grad_clip = None
         optim_model = []
+
+        # for static graph
+        if model_list is None:
+            optim = getattr(optimizer, optim_name)(
+                learning_rate=lr, grad_clip=grad_clip,
+                **optim_cfg)(model_list=optim_model)
+            return optim, lr
+
+        # for dynamic graph
         for i in range(len(model_list)):
             if len(model_list[i].parameters()) == 0:
                 continue
@@ -103,7 +111,7 @@ def build_optimizer(config, epochs, step_each_epoch, model_list=None):
                 if optim_scope.endswith("Loss"):
                     # optimizer for loss
                     for m in model_list[i].sublayers(True):
-                        if m.__class_name == optim_scope:
+                        if m.__class__.__name__ == optim_scope:
                             optim_model.append(m)
                 else:
                     # opmizer for module in model, such as backbone, neck, head...