def make_sequential_keras_model(initializer='ones'):
    model = keras.models.Sequential()
    model.add(keras.layers.Dense(64, kernel_initializer=initializer, bias_initializer='zeros', input_shape=(10,)))
    model.add(keras.layers.Dense(128, kernel_initializer=initializer, bias_initializer='zeros'))
    model.add(keras.layers.Dense(256, kernel_initializer=initializer, bias_initializer='zeros'))
    model.add(keras.layers.Dense(256, kernel_initializer=initializer, bias_initializer='zeros'))
    model.add(keras.layers.Dense(10, kernel_initializer=initializer, bias_initializer='zeros'))
    return model
def make_sequential_keras_model(initializer='ones'):
    model = keras.models.Sequential()
    model.add(keras.layers.Dense(64, kernel_initializer=initializer, bias_initializer='zeros', input_shape=(10,)))
    model.add(keras.layers.Dense(128, kernel_initializer=initializer, bias_initializer='zeros'))
    model.add(keras.layers.Dense(256, kernel_initializer=initializer, bias_initializer='zeros'))
    model.add(keras.layers.Dense(256, kernel_initializer=initializer, bias_initializer='zeros'))
    model.add(keras.layers.Dense(10, kernel_initializer=initializer, bias_initializer='zeros'))
    return model