diff --git a/model_zoo/official/cv/crnn_seq2seq_ocr/src/seq2seq.py b/model_zoo/official/cv/crnn_seq2seq_ocr/src/seq2seq.py
index 480672216f5..9643c7c46fc 100755
--- a/model_zoo/official/cv/crnn_seq2seq_ocr/src/seq2seq.py
+++ b/model_zoo/official/cv/crnn_seq2seq_ocr/src/seq2seq.py
@@ -75,8 +75,8 @@ class AttnDecoderRNN(nn.Cell):
         self.dropout = nn.Dropout(keep_prob=1.0 - self.dropout_p)
         self.gru = nn.GRU(input_size=hidden_size, hidden_size=hidden_size,
                           num_layers=1, has_bias=True,
-                          batch_first=False, dropout=0,
-                          bidirectional=False).to_float(mstype.float16)
+                          batch_first=False, dropout=0.0,
+                          bidirectional=False)
         self.out = nn.Dense(in_channels=self.hidden_size, out_channels=self.output_size).to_float(mstype.float16)
         self.transpose = P.Transpose()
         self.concat = P.Concat(axis=2)
@@ -95,6 +95,7 @@ class AttnDecoderRNN(nn.Cell):
         embedded = self.transpose(embedded, (1, 0, 2))
         embedded = self.dropout(embedded)
         embedded = self.cast(embedded, mstype.float16)
+        hidden = self.cast(hidden, mstype.float16)
 
         embedded_concat = self.concat((embedded, hidden))
         embedded_concat = self.squeeze1(embedded_concat)
@@ -110,6 +111,8 @@ class AttnDecoderRNN(nn.Cell):
         output = self.unsqueeze(output, 0)
         output = self.relu(output)
 
+        output = self.cast(output, mstype.float32)
+        hidden = self.cast(hidden, mstype.float32)
         output, hidden = self.gru(output, hidden)
         output = self.squeeze1(output)
         output = self.log_softmax(self.out(output))