def METHOD_NAME(self, draw):
    N = draw(st.integers(min_value=1, max_value=4))
    C = draw(st.integers(min_value=1, max_value=128))
    H = draw(st.integers(min_value=1, max_value=128))
    W = draw(st.integers(min_value=1, max_value=128))
    in_shape = draw(st.sampled_from([[N, C, H, W]]))
    in_shape = draw(
        st.lists(
            st.integers(
                min_value=3, max_value=5), min_size=1, max_size=4))
    in_shape = draw(st.sampled_from([in_shape, []]))
    in_dtype = draw(st.sampled_from([np.float32]))
    def generate_X_data():
        return np.random.normal(0.0, 5.0, in_shape).astype(in_dtype)
    k_data = draw(st.integers(min_value=1, max_value=2))
    axis_data = draw(st.integers(min_value=0, max_value=1))
    choose_k = draw(st.sampled_from(["k", "K"]))
    inputs = {"X": ["X_data"]}
    if in_shape == []:
        axis_data = draw(st.sampled_from([-1, 0]))
        k_data = 1
    else:
        assume(k_data <= in_shape[-1])
        assume(axis_data < len(in_shape))
    def generate_K_data():
        if (choose_k == "K"):
            inputs["K"] = ["K_data"]
            a = np.array([k_data]).astype(np.int32)
            return a
        else:
            return np.random.randint(1, 5, []).astype(np.int32)
    # Lite does not have these two attributes
    largest_data = draw(st.booleans())
    sorted_data = draw(st.booleans())
    top_k_v2_op = OpConfig(
        type="top_k_v2",
        inputs=inputs,
        outputs={"Out": ["Out_data"],
                 "Indices": ["Indices_data"]},
        attrs={
            "k": k_data,
            "axis": axis_data,
            #"largest": largest_data,
            #"sorted": sorted_data
        })
    top_k_v2_op.outputs_dtype = {"Out_data": in_dtype}
    program_config = ProgramConfig(
        ops=[top_k_v2_op],
        weights={},
        inputs={
            "X_data": TensorConfig(data_gen=partial(generate_X_data)),
            "K_data": TensorConfig(data_gen=partial(generate_K_data))
        },
        outputs=["Out_data", "Indices_data"])
    return program_config