def METHOD_NAME(self):
    inputs = keras.Input(shape=(5, 10))
    layer = keras.layers.Dropout(0.5, noise_shape=(None, 1, None))
    outputs = layer(inputs)
    model = keras.Model(inputs, outputs)
    out = model(np.ones((20, 5, 10)), training=True)
    out_np = keras.backend.get_value(out)
    # Test that dropout mask is shared across second dim.
    self.assertAllClose(out_np[:, 0, :], out_np[:, 1, :])