def METHOD_NAME(test_case):
    arg_dict = OrderedDict()
    # set up test functions
    arg_dict["test_fun"] = [
        _test_skip_layer_norm,
    ]
    # set up test parameters
    if is_profiling:
        arg_dict["x_shape"] = [[1, 5120]]
        arg_dict["has_gamma"] = [True]
        arg_dict["has_beta"] = [True]
        arg_dict["has_bias"] = [True]
        arg_dict["has_skip"] = [True]
        arg_dict["eps"] = [1e-6]
        arg_dict["alpha"] = [1e-5]
        arg_dict["dtype"] = [flow.float32]
    else:
        arg_dict["x_shape"] = [[1, 5120]]
        arg_dict["has_gamma"] = [True, False]
        arg_dict["has_beta"] = [True, False]
        arg_dict["has_bias"] = [True, False]
        arg_dict["has_skip"] = [True, False]
        arg_dict["eps"] = [1e-6]
        arg_dict["alpha"] = [1e-5]
        arg_dict["dtype"] = [flow.float32, flow.float16]
    # run test functions
    for arg in GenArgList(arg_dict):
        arg[0](test_case, *arg[1:])