diff --git a/deploy/slim/quantization/export_model.py b/deploy/slim/quantization/export_model.py
index 90f79dab34a5f20d4556ae4b10ad1d4e1f8b7f0d..fd1c3e5e109667fa74f5ade18b78f634e4d325db 100755
--- a/deploy/slim/quantization/export_model.py
+++ b/deploy/slim/quantization/export_model.py
@@ -17,9 +17,9 @@ import sys
 
 __dir__ = os.path.dirname(os.path.abspath(__file__))
 sys.path.append(__dir__)
-sys.path.append(os.path.abspath(os.path.join(__dir__, '..', '..', '..')))
-sys.path.append(
-    os.path.abspath(os.path.join(__dir__, '..', '..', '..', 'tools')))
+sys.path.insert(0, os.path.abspath(os.path.join(__dir__, '..', '..', '..')))
+sys.path.insert(
+    0, os.path.abspath(os.path.join(__dir__, '..', '..', '..', 'tools')))
 
 import argparse
 
@@ -129,7 +129,6 @@ def main():
     quanter.quantize(model)
 
     load_model(config, model)
-    model.eval()
 
     # build metric
     eval_class = build_metric(config['Metric'])
@@ -142,6 +141,7 @@ def main():
     # start eval
     metric = program.eval(model, valid_dataloader, post_process_class,
                           eval_class, model_type, use_srn)
+    model.eval()
 
     logger.info('metric eval ***************')
     for k, v in metric.items():
@@ -156,7 +156,6 @@ def main():
     if arch_config["algorithm"] in ["Distillation", ]:  # distillation model
         archs = list(arch_config["Models"].values())
         for idx, name in enumerate(model.model_name_list):
-            model.model_list[idx].eval()
             sub_model_save_path = os.path.join(save_path, name, "inference")
             export_single_model(model.model_list[idx], archs[idx],
                                 sub_model_save_path, logger, quanter)
diff --git a/ppocr/modeling/architectures/base_model.py b/ppocr/modeling/architectures/base_model.py
index f5b29f94057d5b1f1fbec27686d5f1d679b15479..c6b50d4886daa9bfd2f863c1d8fd6dbc3d1e42c0 100644
--- a/ppocr/modeling/architectures/base_model.py
+++ b/ppocr/modeling/architectures/base_model.py
@@ -92,6 +92,9 @@ class BaseModel(nn.Layer):
         else:
             y["head_out"] = x
         if self.return_all_feats:
-            return y
+            if self.training:
+                return y
+            else:
+                return {"head_out": y["head_out"]}
         else:
             return x