def METHOD_NAME(W_b_input):
    model = chain(get_model(W_b_input), Dropout(1.0))
    nr_batch, nr_out, nr_in = get_shape(W_b_input)
    W, b, input_ = W_b_input
    for node in model.walk():
        if node.name == "dropout":
            node.attrs["dropout_rate"] = 1.0
    fwd_dropped, finish_update = model.begin_update(input_)
    grad_BO = numpy.ones((nr_batch, nr_out), dtype="f")
    grad_BI = finish_update(grad_BO)
    assert all(val == 0.0 for val in grad_BI.flatten())