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 {};

  auto elemType = type.getElementType();

	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.

	}

	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

}

// Get a list of pods that have data directories.
func (kl *Kubelet) listPodsFromDisk() ([]types.UID, error) {
	podInfos, err := os.ReadDir(kl.getPodsDir())
	if err != nil {
		return nil, err
	}
	pods := []types.UID{}
	for i := range podInfos {
		if podInfos[i].IsDir() {
			pods = append(pods, types.UID(podInfos[i].Name()))
		}
	}
	return pods, nil
}

						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,

	enoptrdata := ldr.CreateSymForUpdate("runtime.enoptrdata", 0)
	ldr.SetAttrSpecial(enoptrdata.Sym(), false)

	types := ldr.CreateSymForUpdate("runtime.types", 0)
	types.SetType(sym.STYPE)
	types.SetSize(8)
	ldr.SetAttrSpecial(types.Sym(), false)

	etypes := ldr.CreateSymForUpdate("runtime.etypes", 0)
	etypes.SetType(sym.SFUNCTAB)
	ldr.SetAttrSpecial(etypes.Sym(), false)

  // inputs to the IfRegion op results. This is possible only if the yield
  // types match the result types.
  auto yield = cast<YieldOp>(region.front().getTerminator());
  auto updated_results = llvm::to_vector<4>(yield.getOperands());

  // If the yield types do not match the IfRegion result types, add appropriate
  // casts.
  rewriter.setInsertionPoint(yield);

			Namespace: namespace,
			Labels:    map[string]string{discovery.LabelServiceName: name},
		},
	}
	epsFunc(eps)
	return eps
}

func makeNSN(namespace, name string) types.NamespacedName {
	return types.NamespacedName{Namespace: namespace, Name: name}
}

func makeServicePortName(ns, name, port string, protocol v1.Protocol) proxy.ServicePortName {
	return proxy.ServicePortName{

        "node": ">=12"
      }
    },
    "node_modules/@types/json-schema": {
      "version": "7.0.11",
      "resolved": "https://registry.npmjs.org/@types/json-schema/-/json-schema-7.0.11.tgz",
      "integrity": "sha512-wOuvG1SN4Us4rez+tylwwwCV1psiNVOkJeM3AUWUNWg/jDQY2+HE/444y5gc+jBmRqASOm2Oeh5c1axHobwRKQ==",
      "dev": true
    },
    "node_modules/@types/minimist": {
      "version": "1.2.2",

    stack_traces_ = LoadTracesFromDebugInfo(debug_info_);
  }

  // Returns the inferred function signature of the given function body. Input
  // types are unranked tensor of the respective datatype in the function and
  // result types are inferred by the shape_refiner_. Result types need not be
  // unranked tensors and could be ranked tensors in cases where result type
  // depends on an op with static output shape like tf.Const.