diff --git a/doc/user_guide.rst b/doc/user_guide.rst
index 3b15d2b6f63b37249fe009a41e46ade5f55abc39..b9b8db420059ef0adb86705e2a36bbb698cfccea 100644
--- a/doc/user_guide.rst
+++ b/doc/user_guide.rst
@@ -56,10 +56,10 @@ The example consists in training a very simple **CNN** with `MNIST` dataset in 4
     >>>
     >>> loss = BaseLoss(tf.nn.sparse_softmax_cross_entropy_with_logits, tf.reduce_mean)
     >>>
-    >>> optimizer = tf.train.GradientDescentOptimizer(0.001)
-    >>>
     >>> learning_rate = constant(base_learning_rate=0.001)
     >>>
+    >>> optimizer = tf.train.GradientDescentOptimizer(learning_rate)
+    >>>
     >>> trainer = Trainer
 
 Now that you have defined your data, architecture, loss and training algorithm you can save this in a python file,