def METHOD_NAME(target):
    dev = tvm.device(target, 0)
    if not tvm.testing.device_enabled(target):
        print("Skip because %s is not enabled" % target)
        return
    if not nvcc.have_tensorcore(dev.compute_version):
        print("skip because gpu does not support Tensor Cores")
        return
    print("Running on target: %s" % target)
    with tvm.target.Target(target):
        fcompute, fschedule = topi.testing.dispatch(target, _conv2d_hwnc_tensorcore_implement)
        C = fcompute(A, W, stride, padding, dilation, dtype, "int32")
        s = fschedule([C])
    a = tvm.nd.array(a_np.transpose((1, 2, 0, 3)), dev)
    w = tvm.nd.array(w_np, dev)
    c = tvm.nd.array(np.zeros(get_const_tuple(C.shape), dtype=C.dtype), dev)
    func = tvm.build(
        s,
        [A, W, C],
        target,
        name="relu_%d_%d_%d_%d_%d_%d_%d_%d"
        % (batch, in_channel, in_size, num_filter, kernel, stride, padding_sum, dilation),
    )
    func(a, w, c)
    rtol = 1e-3
    tvm.testing.assert_allclose(c.numpy().transpose((2, 0, 1, 3)), c_np, rtol=rtol)