def test_softmax_weight_init():
    nvis = 5
    num_classes = 10
    MLP(layers=[Softmax(num_classes, 's', irange=0.1)], nvis=nvis)
    MLP(layers=[Softmax(num_classes, 's', istdev=0.1)], nvis=nvis)
    MLP(layers=[Softmax(num_classes, 's', sparse_init=2)], nvis=nvis)
Constructs softmax layers with different weight initialization
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/models/tests/test_mlp.py/test_softmax_weight_init