def METHOD_NAME():
    fload = tvm.get_global_func("vm.builtin.ndarray_cache.load")
    fget_params = tvm.get_global_func("vm.builtin.param_array_from_cache")
    param_dict = {
        "x_0": np.array([1, 2, 3], dtype="int32"),
        "x_1": np.random.uniform(size=[10, 20]).astype("float32"),
    }
    temp = utils.tempdir()
    tvmjs.dump_ndarray_cache(param_dict, temp.path, encode_format="f32-to-bf16")
    fload(str(temp.path), tvm.cpu().device_type, 0)
    res = fget_params("x", -1)
    for i, v in enumerate(res):
        v_np = param_dict[f"x_{i}"]
        if v_np.dtype == "float32":
            v_np = tvmjs._convert_bf16_to_f32(tvmjs._convert_f32_to_bf16(v_np))
        np.testing.assert_allclose(v.numpy(), v_np, atol=1e-6, rtol=1e-6)