diff --git a/09_Recurrent_Neural_Networks/02_Implementing_RNN_for_Spam_Prediction/02_implementing_rnn.py b/09_Recurrent_Neural_Networks/02_Implementing_RNN_for_Spam_Prediction/02_implementing_rnn.py
index 54c06958f..fd31212f0 100644
--- a/09_Recurrent_Neural_Networks/02_Implementing_RNN_for_Spam_Prediction/02_implementing_rnn.py
+++ b/09_Recurrent_Neural_Networks/02_Implementing_RNN_for_Spam_Prediction/02_implementing_rnn.py
@@ -111,8 +111,9 @@ def clean_text(text_string):
 output = tf.nn.dropout(output, dropout_keep_prob)
 
 # Get output of RNN sequence
-output = tf.transpose(output, [1, 0, 2])
-last = tf.gather(output, int(output.get_shape()[0]) - 1)
+# output = tf.transpose(output, [1, 0, 2])
+# last = tf.gather(output, int(output.get_shape()[0]) - 1)
+last = output[:,-1,:]
 
 weight = tf.Variable(tf.truncated_normal([rnn_size, 2], stddev=0.1))
 bias = tf.Variable(tf.constant(0.1, shape=[2]))
@@ -183,4 +184,4 @@ def clean_text(text_string):
 plt.xlabel('Epochs')
 plt.ylabel('Accuracy')
 plt.legend(loc='upper left')
-plt.show()
\ No newline at end of file
+plt.show()