e074a049205829feb52c7d90f2011519327e56f3,examples/reuters_mlp.py,,,#,22

Before Change

acc = np_utils.accuracy(classes, y_test)
print("Test accuracy:", acc)

model.save("testsave.m")

After Change

// import cPickle
// model = cPickle.load(open("testsave.m.pkl"))

for v in range(3):
    for sa in [True, False]:
        for vs in [0, 0.1]:
            print("="*40)
            print("v:%d, sa:%r, vs:%f" % (v, sa, vs))
            print("Training...")
            model.fit(X_train, Y_train, nb_epoch=2, batch_size=batch_size, verbose=v, show_accuracy=sa, validation_split=vs)
            score = model.evaluate(X_test, Y_test, batch_size=batch_size, verbose=v, show_accuracy=sa)
            print("Test score:", score)

            classes = model.predict_classes(X_test, batch_size=batch_size, verbose=v)
            acc = np_utils.accuracy(classes, y_test)
            print("Test accuracy:", acc)

// model.save("testsave.m")

Instances