diff --git a/ppocr/modeling/heads/rec_ctc_head.py b/ppocr/modeling/heads/rec_ctc_head.py
index 5cc4f9d8a4cf8da71e114d70890d6951345658ed..6c1cf0659607186d54dfee6983b135f34d542446 100755
--- a/ppocr/modeling/heads/rec_ctc_head.py
+++ b/ppocr/modeling/heads/rec_ctc_head.py
@@ -80,9 +80,7 @@ class CTCHead(nn.Layer):
             result = (x, predicts)
         else:
             result = predicts
-        print("self.training: ", self.training)
         if not self.training:
-            print("self.training, ", self.training)
             predicts = F.softmax(predicts, axis=2)
             result = predicts
 
diff --git a/ppocr/postprocess/rec_postprocess.py b/ppocr/postprocess/rec_postprocess.py
index de771acca86a8956b06b366b840aac7e21f835a4..0ffe917b0eb519cb0dc15efd69ccb40962a308b8 100644
--- a/ppocr/postprocess/rec_postprocess.py
+++ b/ppocr/postprocess/rec_postprocess.py
@@ -89,10 +89,11 @@ class CTCLabelDecode(BaseRecLabelDecode):
                                              use_space_char)
 
     def __call__(self, preds, label=None, *args, **kwargs):
-        if isinstance(preds, tuple):
+        if isinstance(preds, tuple) or isinstance(preds, list):
             preds = preds[-1]
         if isinstance(preds, paddle.Tensor):
             preds = preds.numpy()
+        print(preds.shape)
         preds_idx = preds.argmax(axis=2)
         preds_prob = preds.max(axis=2)
         text = self.decode(preds_idx, preds_prob, is_remove_duplicate=True)
diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt
index cfe0947fe010f1545288e3e55922f980e89980d2..98c125229d7f968cd3f650c3885ba4edb0de754c 100644
--- a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt
+++ b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt
@@ -1,7 +1,7 @@
 ===========================train_params===========================
 model_name:ch_PPOCRv2_rec_PACT
 python:python3.7
-gpu_list:6
+gpu_list:0|0,1
 Global.use_gpu:True|True
 Global.auto_cast:fp32
 Global.epoch_num:lite_train_lite_infer=6|whole_train_whole_infer=300