add cls model quant code

deploy/slim/quantization/export_model.py

@@ -51,6 +51,7 @@ from paddleslim.quant import quant_aware, convert
 from paddle.fluid.layer_helper import LayerHelper
 from eval_utils.eval_det_utils import eval_det_run
 from eval_utils.eval_rec_utils import eval_rec_run
+from eval_utils.eval_cls_utils import eval_cls_run
 
 
 def main():
@@ -105,6 +106,8 @@ def main():
 
     if alg_type == 'det':
         final_metrics = eval_det_run(exe, config, quant_info_dict, "eval")
+    elif alg_type == 'cls':
+        final_metrics = eval_cls_run(exe, quant_info_dict)
     else:
         final_metrics = eval_rec_run(exe, config, quant_info_dict, "eval")
     print(final_metrics)

deploy/slim/quantization/quant.py

@@ -178,9 +178,12 @@ def main():
     if train_alg_type == 'det':
         program.train_eval_det_run(
             config, exe, train_info_dict, eval_info_dict, is_slim="quant")
-    else:
+    elif train_alg_type == 'rec':
         program.train_eval_rec_run(
             config, exe, train_info_dict, eval_info_dict, is_slim="quant")
+    else:
+        program.train_eval_cls_run(
+            config, exe, train_info_dict, eval_info_dict, is_slim="quant")
 
 
 if __name__ == '__main__':

ppocr/modeling/architectures/cls_model.py

@@ -65,6 +65,7 @@ class ClsModel(object):
             labels = None
             loader = None
             image = fluid.data(name='image', shape=image_shape, dtype='float32')
+        image.stop_gradient = False
         return image, labels, loader
 
     def __call__(self, mode):