diff --git a/TensorFlow/built-in/cv/detection/CRNN_Kernel_ID0055_for_TensorFlow/crnn_model/crnn_net.py b/TensorFlow/built-in/cv/detection/CRNN_Kernel_ID0055_for_TensorFlow/crnn_model/crnn_net.py
index 648867ce1520ac380f4004032a34c63efc688ae9..0e3b31a4c7db23d351ee16ef8ede4b9343409c45 100644
--- a/TensorFlow/built-in/cv/detection/CRNN_Kernel_ID0055_for_TensorFlow/crnn_model/crnn_net.py
+++ b/TensorFlow/built-in/cv/detection/CRNN_Kernel_ID0055_for_TensorFlow/crnn_model/crnn_net.py
@@ -188,15 +188,15 @@ class ShadowNet(cnn_basenet.CNNBaseModel):
             
             inputdata = tf.transpose(inputdata, [1, 0, 2], name='transpose_inputdata')
             # for RNN cell instances and self._layers_nums=2
-            fw_cell = DynamicRNN(self._hidden_nums, dtypes.float32, time_major=True, forget_bias=1.0)
-            bw_cell = DynamicRNN(self._hidden_nums, dtypes.float32, time_major=True, forget_bias=1.0)
+            fw_cell = DynamicRNN(self._hidden_nums, dtypes.float16, time_major=True, forget_bias=1.0)
+            bw_cell = DynamicRNN(self._hidden_nums, dtypes.float16, time_major=True, forget_bias=1.0)
 
             fw_y1, output_h, output_c, i, j, f, o, tanh = fw_cell(inputdata)
             bw_y1, output_h, output_c, i, j, f, o, tanh = bw_cell(tf.reverse(inputdata, axis=[0]))
             output_rnn1 = tf.concat((fw_y1, tf.reverse(bw_y1, axis=[0])), axis=2)
 
-            fw_cell2 = DynamicRNN(self._hidden_nums, dtypes.float32, time_major=True, forget_bias=1.0)
-            bw_cell2 = DynamicRNN(self._hidden_nums, dtypes.float32, time_major=True, forget_bias=1.0)
+            fw_cell2 = DynamicRNN(self._hidden_nums, dtypes.float16, time_major=True, forget_bias=1.0)
+            bw_cell2 = DynamicRNN(self._hidden_nums, dtypes.float16, time_major=True, forget_bias=1.0)
 
             fw_y2, output_h, output_c, i, j, f, o, tanh = fw_cell2(output_rnn1)
             bw_y2, output_h, output_c, i, j, f, o, tanh = bw_cell2(tf.reverse(output_rnn1, axis=[0]))