def METHOD_NAME(targeta):
    if not tvm.testing.device_enabled(targeta):
        print("Skip because %s is not enabled" % targeta)
        return
    if dtype == "float16" and targeta == "cuda" and not have_fp16(tvm.cuda(0).compute_version):
        print("Skip because gpu does not have fp16 support")
        return
    with tvm.target.Target(targeta):
        dev = tvm.device(targeta, 0)
        A = te.placeholder((n, m), name="A", dtype=dtype)
        B = te.compute((n, m), lambda i, j: A[i, j] + tvm.tir.const(1, A.dtype), name="B")
        S = tvm.topi.testing.get_elemwise_schedule(targeta)(B)
        fun = tvm.build(S, [A, B], targeta)
        np_A = tvm.nd.empty((n, m), A.dtype, dev).copyfrom(np.random.uniform(size=(n, m)))
        np_B = tvm.nd.empty((n, m), B.dtype, dev)
        fun(np_A, np_B)
        tvm.testing.assert_allclose(np_B.numpy(), np_A.numpy() + 1, rtol=1e-5)