testClusterDNSDomain := "TEST"

	configurer := NewConfigurer(recorder, nodeRef, nil, nil, testClusterDNSDomain, "")

	pod := &v1.Pod{
		ObjectMeta: metav1.ObjectMeta{
			UID:         "",
			Name:        "test_pod",
			Namespace:   "testNS",
			Annotations: map[string]string{},
		},
	}

	testCases := []struct {
		desc         string
		hostNames    []string
		resultSearch []string
		events       []string

		// is not recommended because it usually relies on
		// routing stuff for finding out an appropriate
		// nexthop containing both network and link layer
		// adjacencies.
		if ifi == nil || !*testIPv4 {
			continue
		}
		for _, tt := range ipv4MulticastListenerTests {
			var err error
			cs := make([]*UDPConn, 2)
			if cs[0], err = ListenMulticastUDP(tt.net, ifi, tt.gaddr); err != nil {
				t.Fatal(err)

    assert response.json() == {
        "name": "Baz",
        "description": None,
        "price": 50.2,
        "tax": 10.5,
        "tags": [],
    }


def test_put(client: TestClient):
    response = client.put(
        "/items/bar", json={"name": "Barz", "price": 3, "description": None}
    )
    assert response.json() == {
        "name": "Barz",
        "description": None,

    assert response.json() == {
        "name": "Baz",
        "description": None,
        "price": 50.2,
        "tax": 10.5,
        "tags": [],
    }


@needs_py310
def test_put(client: TestClient):
    response = client.put(
        "/items/bar", json={"name": "Barz", "price": 3, "description": None}
    )
    assert response.json() == {
        "name": "Barz",
        "description": None,

  Status s = tensorflow::GetValue(t, &result_t);
  ASSERT_TRUE(s.ok()) << s.message();
  auto value = static_cast<T*>(TF_TensorData(result_t));
  EXPECT_EQ(*value, expected);
  TF_DeleteTensor(result_t);
}

TEST_P(VariableTest, CreateAssignReadDestroy) {
  // Create uninitialized variable.
  tensorflow::AbstractTensorHandlePtr var;
  {
    AbstractTensorHandle* var_ptr = nullptr;
    PartialTensorShape scalar_shape;

    assert response.json() == "a"


def test_b():
    response = client.get("/b")
    assert response.status_code == 200, response.text
    assert response.json() == "b"


def test_c():
    response = client.get("/c")
    assert response.status_code == 200, response.text
    assert response.json() == "c"


def test_d():
    response = client.get("/d")

	log.Println("Test HTTP RPC server listening on", httpServerAddr)
}

func TestRPC(t *testing.T) {
	once.Do(startServer)
	testRPC(t, serverAddr)
	newOnce.Do(startNewServer)
	testRPC(t, newServerAddr)
	testNewServerRPC(t, newServerAddr)
}

func testRPC(t *testing.T, addr string) {
	client, err := Dial("tcp", addr)
	if err != nil {
		t.Fatal("dialing", err)
	}

 private:
  std::unique_ptr<StaticDeviceMgr> device_mgr_;
  EagerContextPtr ctx_;
};

// Basic sanity check that roundtripping a Tensor->Tensorproto->Constant
// preserves values.
TEST_P(ConstantTest, CreateConstantSuccessful) {
  // Get test parameters
  auto& test_params = GetParam();
  DataType dtype = std::get<0>(test_params);
  TensorShape shape(std::get<1>(test_params));

  GradientRegistry registry_;
  Status status_;

 public:
  bool UseMlir() const { return strcmp(std::get<0>(GetParam()), "mlir") == 0; }
  bool UseFunction() const { return std::get<2>(GetParam()); }
};

TEST_P(CppGradients, TestIdentityNGrad) {
  // This test is interesting because the current implementation of GradientTape
  // would return [0, 1] whereas we use build_default_zeros_grads=false here
  // so we get back [nullptr, 1].

                                          /*output_gradients=*/{},
                                          /*result=*/outputs));
  exp_output->Unref();
  return absl::OkStatus();
}

TEST_P(CustomGradientTest, ExpWithPassThroughGrad) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  AbstractContextPtr ctx;
  {
    AbstractContext* ctx_raw = nullptr;