diff --git a/doc/src/NeuralNet/NeuralNet.do.txt b/doc/src/NeuralNet/NeuralNet.do.txt
index d4cb94a02..e090937ab 100644
--- a/doc/src/NeuralNet/NeuralNet.do.txt
+++ b/doc/src/NeuralNet/NeuralNet.do.txt
@@ -1576,17 +1576,16 @@ being realizations of this object with different hyperparameters. An implementat
 !bc pycod
 class NeuralNetwork:
     def __init__(
-        self,
-        X_data,
-        Y_data,
-        n_hidden_neurons=50,
-        n_categories=10,
-        epochs=10,
-        batch_size=100,
-        eta=0.1,
-        lmbd=0.0,
+            self,
+            X_data,
+            Y_data,
+            n_hidden_neurons=50,
+            n_categories=10,
+            epochs=10,
+            batch_size=100,
+            eta=0.1,
+            lmbd=0.0):
 
-    ):
         self.X_data_full = X_data
         self.Y_data_full = Y_data
 
@@ -1968,19 +1967,18 @@ import tensorflow as tf
 
 class NeuralNetworkTensorflow:
     def __init__(
-        self,
-        X_train,
-        Y_train,
-        X_test,
-        Y_test,
-        n_neurons_layer1=100,
-        n_neurons_layer2=50,
-        n_categories=2,
-        epochs=10,
-        batch_size=100,
-        eta=0.1,
-        lmbd=0.0,
-    ):
+            self,
+            X_train,
+            Y_train,
+            X_test,
+            Y_test,
+            n_neurons_layer1=100,
+            n_neurons_layer2=50,
+            n_categories=2,
+            epochs=10,
+            batch_size=100,
+            eta=0.1,
+            lmbd=0.0):
         
         # keep track of number of steps
         self.global_step = tf.Variable(0, dtype=tf.int32, trainable=False, name='global_step')
@@ -2740,22 +2738,21 @@ import tensorflow as tf
 
 class ConvolutionalNeuralNetworkTensorflow:
     def __init__(
-        self,
-        X_train,
-        Y_train,
-        X_test,
-        Y_test,
-        n_filters=10,
-        n_neurons_connected=50,
-        n_categories=10,
-        receptive_field=3,
-        stride=1,
-        padding=1,
-        epochs=10,
-        batch_size=100,
-        eta=0.1,
-        lmbd=0.0,
-    ):
+            self,
+            X_train,
+            Y_train,
+            X_test,
+            Y_test,
+            n_filters=10,
+            n_neurons_connected=50,
+            n_categories=10,
+            receptive_field=3,
+            stride=1,
+            padding=1,
+            epochs=10,
+            batch_size=100,
+            eta=0.1,
+            lmbd=0.0):
         
         self.global_step = tf.Variable(0, dtype=tf.int32, trainable=False, name='global_step')