diff --git a/ppocr/data/rec/img_tools.py b/ppocr/data/rec/img_tools.py
index d41abd9ba5c867853984b4b3b4c9eda41ebeff7c..0835603b5896a4f7ab946c4a694dcbec3f853a54 100755
--- a/ppocr/data/rec/img_tools.py
+++ b/ppocr/data/rec/img_tools.py
@@ -360,7 +360,7 @@ def process_image(img,
         text = char_ops.encode(label)
         if len(text) == 0 or len(text) > max_text_length:
             logger.info(
-                "Warning in ppocr/data/rec/img_tools.py:line362: Wrong data type."
+                "Warning in ppocr/data/rec/img_tools.py: Wrong data type."
                 "Excepted string with length between 1 and {}, but "
                 "got '{}'. Label is '{}'".format(max_text_length,
                                                  len(text), label))
diff --git a/ppocr/optimizer.py b/ppocr/optimizer.py
index f5f4958351239a413fa2cb19dec4a068f1bb44f4..eb1037c2053de30dacb82c889a02f023683d25d3 100755
--- a/ppocr/optimizer.py
+++ b/ppocr/optimizer.py
@@ -36,17 +36,28 @@ def AdamDecay(params, parameter_list=None):
     l2_decay = params.get("l2_decay", 0.0)
 
     if 'decay' in params:
+        supported_decay_mode = ["cosine_decay", "piecewise_decay"]
         params = params['decay']
         decay_mode = params['function']
-        step_each_epoch = params['step_each_epoch']
-        total_epoch = params['total_epoch']
+        assert decay_mode in supported_decay_mode, "Supported decay mode is {}, but got {}".format(
+            supported_decay_mode, decay_mode)
+
         if decay_mode == "cosine_decay":
+            step_each_epoch = params['step_each_epoch']
+            total_epoch = params['total_epoch']
             base_lr = fluid.layers.cosine_decay(
                 learning_rate=base_lr,
                 step_each_epoch=step_each_epoch,
                 epochs=total_epoch)
-        else:
-            logger.info("Only support Cosine decay currently")
+        elif decay_mode == "piecewise_decay":
+            boundaries = params["boundaries"]
+            decay_rate = params["decay_rate"]
+            values = [
+                base_lr * decay_rate**idx
+                for idx in range(len(boundaries) + 1)
+            ]
+            base_lr = fluid.layers.piecewise_decay(boundaries, values)
+
     optimizer = fluid.optimizer.Adam(
         learning_rate=base_lr,
         beta1=beta1,