1aff940e60d7d62bd82ddf7469e666197832e212,src/classifiers/cnn_unittest.py,TestCNNModel,test_mnist,#TestCNNModel#,55

Before Change

        X_train, Y_train, X_test, Y_test = X_train[:NB_TRAIN], Y_train[:NB_TRAIN], X_test[:NB_TEST], Y_test[:NB_TEST]

        // convert class vectors to binary class matrices
        Y_train = np_utils.to_categorical(Y_train,NB_CLASSES)
        Y_test = np_utils.to_categorical(Y_test,NB_CLASSES)

        im_shape = X_train[0].shape

After Change

        model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])

        // Fit the model
        model.fit(X_train,Y_train,epochs=1,batch_size=BATCH_SIZE)

        scores = model.evaluate(X_test,Y_test)

        print("\naccuracy: %.2f%%" % (scores[1] * 100))

Instances