code

def basic_cnn():
    model = Sequential()
    model.add(Conv2D(4, kernel_size=(5, 5), strides=(1, 1), activation='relu'))
    model.add(MaxPooling2D(pool_size=(2, 2), strides=(2, 2)))
    model.add(Conv2D(8, kernel_size=(5, 5), activation='relu'))
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Flatten())
    model.add(Dense(NUM_CLASSES, activation='softmax'))
    # sgd = SGD(lr=0.000001) # unused
    model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
    return model