diff --git a/ppocr/modeling/heads/rec_satrn_head.py b/ppocr/modeling/heads/rec_satrn_head.py
index b969c89693..263c3b1bb3 100644
--- a/ppocr/modeling/heads/rec_satrn_head.py
+++ b/ppocr/modeling/heads/rec_satrn_head.py
@@ -283,13 +283,15 @@ def forward(self, feat, valid_ratios=None):
             Tensor: A tensor of shape :math:`(N, T, D_m)`.
         """
         if valid_ratios is None:
-            valid_ratios = [1.0 for _ in range(feat.shape[0])]
+            bs = paddle.shape(feat)[0]
+            valid_ratios = paddle.full((bs, 1), 1., dtype=paddle.float32)
+
         feat = self.position_enc(feat)
         n, c, h, w = feat.shape
 
         mask = paddle.zeros((n, h, w))
         for i, valid_ratio in enumerate(valid_ratios):
-            valid_width = min(w, math.ceil(w * valid_ratio))
+            valid_width = int(min(w, paddle.ceil(w * valid_ratio)))
             mask[i, :, :valid_width] = 1
 
         mask = mask.reshape([n, h * w])
@@ -347,7 +349,6 @@ def _get_sinusoid_encoding_table(self, n_position, d_hid):
         return sinusoid_table.unsqueeze(0)
 
     def forward(self, x):
-
         x = x + self.position_table[:, :x.shape[1]].clone().detach()
         return self.dropout(x)
 
@@ -514,7 +515,6 @@ def forward_train(self, feat, out_enc, targets, valid_ratio):
         return outputs
 
     def forward_test(self, feat, out_enc, valid_ratio):
-
         src_mask = self._get_mask(out_enc, valid_ratio)
         N = out_enc.shape[0]
         init_target_seq = paddle.full(
@@ -556,13 +556,11 @@ def __init__(self, enc_cfg, dec_cfg, **kwargs):
         self.decoder = SATRNDecoder(**dec_cfg)
 
     def forward(self, feat, targets=None):
-
         if targets is not None:
             targets, valid_ratio = targets
         else:
             targets, valid_ratio = None, None
         holistic_feat = self.encoder(feat, valid_ratio)  # bsz c
-
         final_out = self.decoder(feat, holistic_feat, targets, valid_ratio)
 
         return final_out