def METHOD_NAME():
    n = 1024
    l = 128
    m = 235
    bias = te.var("bias", dtype="float32")
    A = te.placeholder((l,), name="A")
    B = te.placeholder((m, l), name="B")
    C = nnpack.fully_connected_inference(A, B)
    D = te.compute(C.shape, lambda i: C[i] + bias, name="D")
    s = te.create_schedule(D.op)
    def verify(target="llvm"):
        if not tvm.get_global_func("tvm.contrib.nnpack.fully_connected_inference", True):
            pytest.skip("extern function is not available")
        if not nnpack.is_available():
            pytest.skip("nnpack is not available")
        dev = tvm.cpu(0)
        f = tvm.build(s, [A, B, D, bias], target)
        a = tvm.nd.array(np.random.uniform(size=(l)).astype(A.dtype), dev)
        b = tvm.nd.array(np.random.uniform(size=(m, l)).astype(B.dtype), dev)
        d = tvm.nd.array(np.zeros((m,), dtype=D.dtype), dev)
        bb = 10.0
        f(a, b, d, bb)
        tvm.testing.assert_allclose(d.numpy(), np.dot(a.numpy(), b.numpy().T) + bb, rtol=1e-5)
    verify()