def test_neibs_wrap_centered_step_manual(self):

        expected1 = [[24, 20, 21,  4,  0,  1,  9,  5,  6],
                     [21, 22, 23,  1,  2,  3,  6,  7,  8],
                     [23, 24, 20,  3,  4,  0,  8,  9,  5],
                     [ 9,  5,  6, 14, 10, 11, 19, 15, 16],
                     [ 6,  7,  8, 11, 12, 13, 16, 17, 18],
                     [ 8,  9,  5, 13, 14, 10, 18, 19, 15],
                     [19, 15, 16, 24, 20, 21,  4,  0,  1],
                     [16, 17, 18, 21, 22, 23,  1,  2,  3],
                     [18, 19, 15, 23, 24, 20,  3,  4,  0]]
        expected2 = [[ 24,  20,  21,   4,   0,   1,   9,   5,   6],
                     [ 22,  23,  24,   2,   3,   4,   7,   8,   9],
                     [ 14,  10,  11,  19,  15,  16,  24,  20,  21],
                     [ 12,  13,  14,  17,  18,  19,  22,  23,  24]]
        expected3 = [[19, 15, 16, 24, 20, 21,  4,  0,  1,  9,  5,  6, 14, 10, 11],
                     [17, 18, 19, 22, 23, 24,  2,  3,  4,  7,  8,  9, 12, 13, 14],
                     [ 9,  5,  6, 14, 10, 11, 19, 15, 16, 24, 20, 21,  4,  0,  1],
                     [ 7,  8,  9, 12, 13, 14, 17, 18, 19, 22, 23, 24,  2,  3,  4]]
        expected4 = [[23, 24, 20, 21, 22,  3,  4,  0,  1,  2,  8,  9,  5,  6,  7],
                     [21, 22, 23, 24, 20,  1,  2,  3,  4,  0,  6,  7,  8,  9,  5],
                     [13, 14, 10, 11, 12, 18, 19, 15, 16, 17, 23, 24, 20, 21, 22],
                     [11, 12, 13, 14, 10, 16, 17, 18, 19, 15, 21, 22, 23, 24, 20]]
        expected5 = [[24, 20, 21,  4,  0,  1,  9,  5,  6],
                     [22, 23, 24,  2,  3,  4,  7,  8,  9],
                     [ 9,  5,  6, 14, 10, 11, 19, 15, 16],
                     [ 7,  8,  9, 12, 13, 14, 17, 18, 19],
                     [19, 15, 16, 24, 20, 21,  4,  0,  1],
                     [17, 18, 19, 22, 23, 24,  2,  3,  4]]
        expected6 = [[24, 20, 21,  4,  0,  1,  9,  5,  6],
                     [21, 22, 23,  1,  2,  3,  6,  7,  8],
                     [23, 24, 20,  3,  4,  0,  8,  9,  5],
                     [14, 10, 11, 19, 15, 16, 24, 20, 21],
                     [11, 12, 13, 16, 17, 18, 21, 22, 23],
                     [13, 14, 10, 18, 19, 15, 23, 24, 20]]

        # TODO test discontinous image

        for shp_idx, (shape, neib_shape, neib_step, expected) in enumerate([
            [(7, 8, 5, 5), (3, 3), (2, 2), expected1],
            [(7, 8, 5, 5), (3, 3), (3, 3), expected2],
            [(7, 8, 5, 5), (5, 3), (3, 3), expected3],
            [(7, 8, 5, 5), (3, 5), (3, 3), expected4],
            [(80, 90, 5, 5), (3, 3), (2, 3), expected5],
            [(1025, 9, 5, 5), (3, 3), (3, 2), expected6],
            [(1, 1, 5, 1035), (3, 3), (3, 3), None],
            [(1, 1, 1045, 5), (3, 3), (3, 3), None],
            ]):

            for dtype in self.dtypes:

                images = shared(numpy.asarray(numpy.arange(numpy.prod(
                                shape)).reshape(shape), dtype=dtype))
                neib_shape = T.as_tensor_variable(neib_shape)
                neib_step = T.as_tensor_variable(neib_step)
                expected = numpy.asarray(expected)

                f = function([], images2neibs(images, neib_shape, neib_step,
                                              mode="wrap_centered"),
                             mode=self.mode)
                neibs = f()

                if 1 > expected.size:
                    for i in range(shape[0] * shape[1]):
                        assert numpy.allclose(
                                neibs[i * expected.shape[0]:
                                      (i + 1) * expected.shape[0], :],
                                expected + 25 * i), "wrap_centered"

                assert self.op in [type(node.op)
                                   for node in f.maker.fgraph.toposort()]

                #g = function([], neibs2images(neibs, neib_shape, images.shape), mode=self.mode)
                # TODO: why this is commented?
                #assert numpy.allclose(images.get_value(borrow=True), g())
dataset/ETHPy150Open rizar/attention-lvcsr/libs/Theano/theano/tensor/nnet/tests/test_neighbours.py/T_Images2Neibs.test_neibs_wrap_centered_step_manual/swapped operands of `>`