def METHOD_NAME(self, draw):
    in_shape = draw(
        st.lists(
            st.integers(
                min_value=2, max_value=64), min_size=4, max_size=4))
    epsilon_data = draw(st.floats(min_value=0.0, max_value=0.001))
    act_type = draw(st.sampled_from(
        ['relu']))  #opencl instance_norm kernel only support relu
    instance_norm_op = OpConfig(
        type="instance_norm",
        inputs={
            "X": ["input_data"],
            "Scale": ["scale_data"],
            "Bias": ["bisa_data"]
        },
        outputs={
            "Y": ["y_output_data"],
            "SavedMean": ["SavedMean_data"],
            "SavedVariance": ["SavedVariance_data"]
        },
        attrs={"epsilon": epsilon_data})
    active_op = OpConfig(
        type=act_type,
        inputs={"X": ["y_output_data"]},
        outputs={"Out": ["output_data"]},
        attrs={})
    ops = [instance_norm_op, active_op]
    program_config = ProgramConfig(
        ops=ops,
        weights={},
        inputs={
            "input_data": TensorConfig(shape=in_shape),
            "scale_data": TensorConfig(shape=[in_shape[1]]),
            "bisa_data": TensorConfig(shape=[in_shape[1]])
        },
        outputs=["output_data"])
    return program_config