}

	var types strings.Builder
	if len(cl.Types) == 0 {
		fmt.Fprintf(&types, "%*sTypes: nil", indent+2, "")
	} else {
		fmt.Fprintf(&types, "%*sTypes:", indent+2, "")
		for i, t := range cl.Types {
			types.WriteByte('\n')
			types.WriteString(t.goString(indent+4, fmt.Sprintf("%d: ", i)))
		}
	}

	var callConstraint string

		terminatingErr          error
		prepareWorker           func(t *testing.T, w *podWorkers, records map[types.UID][]syncPodRecord)
		wantWorker              func(t *testing.T, w *podWorkers, records map[types.UID][]syncPodRecord)
		wantWorkerAfterRetry    func(t *testing.T, w *podWorkers, records map[types.UID][]syncPodRecord)
		wantErr                 bool
		expectMetrics           map[string]string

</p>


<h2 id="Types">Types</h2>

<p>
A type determines a set of values together with operations and methods specific
to those values. A type may be denoted by a <i>type name</i>, if it has one,
or specified using a <i>type literal</i>, which composes a type from existing types.
</p>

<pre class="ebnf">
Type      = TypeName | TypeLit | "(" Type ")" .

// TODO(jpienaar): Expand to all int types.
def TFL_IntTensor : TypeAlias<TFL_I32Tensor, "tensor of any integer type">;

class TFL_0DTensorOf<list<Type> allowedRuntimeTypes,
                     list<Type> allowedOpTypes = [AnyType]> :
  0DTensorOf<allowedOpTypes>, TFL_RuntimeType<TensorOf<allowedRuntimeTypes>>;
class TFL_1DTensorOf<list<Type> allowedRuntimeTypes,
                     list<Type> allowedOpTypes = [AnyType]> :

Attribute ConstFoldBinaryOp(
    Type result_type, ArrayRef<Attribute> operands,
    llvm::function_ref<APFloat(APFloat, APFloat)> float_calculate,
    llvm::function_ref<APInt(APInt, APInt)> int_calculate) {
  // Note: All types are wrapped in tensor types in TFlite. E.g., f32 is
  // represented as tensor<f32>. So we are only handling tensor types here.
  auto type = result_type.dyn_cast<ShapedType>();
  if (!type) return {};

	if expect, actual := []types.UID(nil), kubelet.podWorkers.(*fakePodWorkers).triggeredDeletion; !reflect.DeepEqual(expect, actual) {
		t.Fatalf("expected %v kills, got %v", expect, actual)
	}

	ready = true
	kubelet.HandlePodRemoves(pods)
	time.Sleep(2 * time.Second)

	// Sources are ready. Remove unwanted pods.

func (kl *Kubelet) findContainer(ctx context.Context, podFullName string, podUID types.UID, containerName string) (*kubecontainer.Container, error) {
	pods, err := kl.containerRuntime.GetPods(ctx, false)
	if err != nil {
		return nil, err
	}
	// Resolve and type convert back again.
	// We need the static pod UID but the kubecontainer API works with types.UID.
	podUID = types.UID(kl.podManager.TranslatePodUID(podUID))

						Succeeded: func() []types.UID {
							uids := make([]types.UID, 499)
							for i := range uids {
								uids[i] = types.UID(strconv.Itoa(i))
							}
							return uids
						}(),
						Failed: []types.UID{"b"},
					},
					Failed: 1,
				},
				{
					UncountedTerminatedPods: &batch.UncountedTerminatedPods{
						Failed: []types.UID{"b"},
					},
					Succeeded: 499,

        }
        node->AddAttr("shape", index_it->second->second.shape);
        DataType dtype = index_it->second->second.imported_dtype;
        // Uses the existing output type if it isn't specified by the user.
        if (dtype == DT_INVALID) {
          dtype = node->output_type(0);
        }
        node->AddAttr("dtype", dtype);
      }
    }
    if (!node_added_to_shape_refiner) {

		add chain ip kube-proxy filter-prerouting { type filter hook prerouting priority -110 ; }
		add chain ip kube-proxy filter-forward { type filter hook forward priority -110 ; }
		add chain ip kube-proxy filter-input { type filter hook input priority -110 ; }
		add chain ip kube-proxy filter-output { type filter hook output priority -110 ; }
		add chain ip kube-proxy filter-output-post-dnat { type filter hook output priority -90 ; }