def gen_data(dtype, keepdims, reduce_axis, shape):
    input1 = random_gaussian(shape, miu=1, sigma=0.1)
    input1 = input1.astype(dtype)
    input1_abs = np.abs(input1)
    expect = np.sum(input1_abs, axis=reduce_axis, keepdims=keepdims)
    out_shape = get_reduce_out_shape(shape, axis=reduce_axis, keepdims=keepdims)
    output = np.full(out_shape, np.nan, dtype)
    return (expect, input1, output)
def gen_data(dtype, keepdims, reduce_axis, shape):
    input1 = random_gaussian(shape, miu=1, sigma=0.1)
    input1 = input1.astype(dtype)
    input1_abs = np.abs(input1)
    expect = np.sum(input1_abs, axis=reduce_axis, keepdims=keepdims)
    out_shape = get_reduce_out_shape(shape, axis=reduce_axis, keepdims=keepdims)
    output = np.full(out_shape, np.nan, dtype)
    return (expect, input1, output)