Replace tryhw0.py

tryhw0.py

@@ -9,8 +9,15 @@ def softmax_model():
         make_activation_layer(SOFTMAX)]
     return make_net(l)
 
+# The CIFAR model got 51% test accuracy while MNIST got over 97%
+# so the model structure is far better suited for the MNIST data set.
+# Improving MNIST's accuracy by adding layers also improved CIFAR's accuracy as well.
 def neural_net():
-    l = [   make_connected_layer(inputs, 32),
+    l = [   make_connected_layer(inputs, 1024),
+            make_activation_layer(RELU),
+            make_connected_layer(1024, 256),
+            make_activation_layer(RELU),
+            make_connected_layer(256, 32),
             make_activation_layer(RELU),
             make_connected_layer(32, 10),
             make_activation_layer(SOFTMAX)]
@@ -33,7 +40,7 @@ rate = .01
 momentum = .9
 decay = .0
 
-m = softmax_model()
+m = neural_net()
 print("training...")
 train_image_classifier(m, train, batch, iters, rate, momentum, decay)
 print("done")