def test_flattener_layer_state_separation_for_softmax():
    soft1 = Softmax(5, 'sf1', .1)
    soft2 = Softmax(5, 'sf2', .1)
    mlp = MLP(layers=[FlattenerLayer(CompositeLayer('comp',
                                                    [soft1, soft2]))],
              nvis=2)

    X = np.random.rand(20, 2).astype(theano.config.floatX)
    y = np.random.rand(20, 10).astype(theano.config.floatX)
    dataset = DenseDesignMatrix(X=X, y=y)

    train = Train(dataset, mlp, SGD(0.1,
                                    batch_size=5,
                                    monitoring_dataset=dataset))
    train.algorithm.termination_criterion = EpochCounter(1)
    train.main_loop()
Creates a CompositeLayer wrapping two Softmax layers
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/models/tests/test_mlp.py/test_flattener_layer_state_separation_for_softmax