diff --git a/ppcls/arch/gears/metabnneck.py b/ppcls/arch/gears/metabnneck.py
index 7dd78cd8294758d0576f00cf33a1530317504281..d2f743da6f832f03fb51eee8b59bc9c759f509af 100644
--- a/ppcls/arch/gears/metabnneck.py
+++ b/ppcls/arch/gears/metabnneck.py
@@ -22,7 +22,7 @@ import paddle.nn.functional as F
 from ..utils import get_param_attr_dict
 
 
-class MetaBN1D(nn.BatchNorm2D):
+class MetaBN1D(nn.BatchNorm1D):
     def forward(self, inputs, opt={}):
         mode = opt.get("bn_mode", "general") if self.training else "eval"
         if mode == "general":  # update, but not apply running_mean/var
diff --git a/ppcls/engine/train/train_metabin.py b/ppcls/engine/train/train_metabin.py
index 21a4a7863f186e06bbbd2ab34ff91de0c5dffc5a..b4994b699b55b182178684601b04de7c43d966d8 100644
--- a/ppcls/engine/train/train_metabin.py
+++ b/ppcls/engine/train/train_metabin.py
@@ -141,15 +141,15 @@ def setup_opt(engine, stage):
         opt["bn_mode"] = "hold"
         opt["enable_inside_update"] = True
         opt["lr_gate"] = norm_lr * cyclic_lr
-    for name, layer in engine.model.backbone.named_sublayers():
-        if "bn" == name.split('.')[-1]:
+    for layer in engine.model.backbone.sublayers():
+        if type_name(layer) == "MetaBIN":
             layer.setup_opt(opt)
     engine.model.neck.setup_opt(opt)
 
 
 def reset_opt(model):
-    for name, layer in model.backbone.named_sublayers():
-        if "bn" == name.split('.')[-1]:
+    for layer in model.backbone.sublayers():
+        if type_name(layer) == "MetaBIN":
             layer.reset_opt()
     model.neck.reset_opt()