ecfb7febc19941314261a644ec37787ffbf6d4ad,snntoolbox/models/cifar_cnn_deeper_max.py,,,#,17

Before Change

model.add(Activation("softmax"))

// let"s train the model using SGD + momentum (how original).
sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss="categorical_crossentropy", optimizer=sgd,
              metrics=["accuracy"])

if not data_augmentation:

After Change

model.compile(loss="categorical_crossentropy", optimizer="adadelta",
              metrics=["accuracy"])
early_stopping = EarlyStopping(monitor="val_loss", patience=3)
history = model.fit(X_train, Y_train, batch_size=batch_size, nb_epoch=nb_epoch,
                    verbose=1, validation_data=(X_test, Y_test))
//                    callbacks=[early_stopping])
score = model.evaluate(X_test, Y_test, verbose=0)

Instances