def test_elemwise_collapse4():

    shape = (4, 5)
    a = cuda_ndarray.CudaNdarray(theano._asarray(numpy.random.rand(*shape),
                                                 dtype='float32'))
    a = theano._asarray(numpy.random.rand(*shape), dtype='float32')
    a2 = tcn.shared_constructor(a, 'a')
    a3 = a2.dimshuffle('x', 0, 1, 'x')
    b = tcn.CudaNdarrayType((False, False, False, False))()
    c = (a3 + b + 2)
    f = pfunc([b], [c], mode=mode_with_gpu)

    v = theano._asarray(numpy.random.rand(5, shape[0], shape[1], 4),
                        dtype='float32')
    v = cuda_ndarray.CudaNdarray(v)
    # let debugmode catch errors
    out = f(v)[0]
    assert numpy.allclose(out, a.reshape(1, shape[0], shape[1], 1) + v + 2)
    # print "Expected collapse to 3 dimensions"
Test when only one inputs have two broadcastable dimension at
dataset/ETHPy150Open rizar/attention-lvcsr/libs/Theano/theano/sandbox/cuda/tests/test_basic_ops.py/test_elemwise_collapse4