Re-enabled training

lenet5.py

@@ -164,10 +164,6 @@ def main():
     test['features'], test['labels'] = read_mnist('t10k-images-idx3-ubyte.gz',
                                                   't10k-labels-idx1-ubyte.gz')
 
-    print(type(train))
-    print(type(train['features']))
-    print(type(train['labels']))
-
     # Step 3:
     # Explore the dataset
     print('Number of training images:', train['features'].shape[0])
@@ -208,9 +204,9 @@ def main():
     model = create_lenet5()
 
     # Step 8:
-    # Train and save the LeNet-5 model
-    # train_lenet5(model)
-    # model.save('lenet5.h5')
+    # Train, save and load the LeNet-5 model
+    train_lenet5(model)
+    model.save('lenet5.h5')
     model = load_model('lenet5.h5')
 
     # Step 9: