"msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "ctx": {"limit_value": 0},
                    "loc": ["body", "item", "price"],

	{err: nil, errCode: ErrNone},
	{err: errors.New("Custom error"), errCode: ErrInternalError}, // Case where err type is unknown.
}

func TestAPIErrCode(t *testing.T) {
	ctx := context.Background()
	for i, testCase := range toAPIErrorTests {
		errCode := toAPIErrorCode(ctx, testCase.err)
		if errCode != testCase.errCode {
			t.Errorf("Test %d: Expected error code %d, got %d", i+1, testCase.errCode, errCode)
		}
	}
}

                    "msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "ctx": {"limit_value": 0},
                    "loc": ["body", "item", "price"],

  }
  return wrap(handle);
}

TFE_Context* TF_ExecutionContextGetTFEContext(TF_ExecutionContext* ctx,
                                              TF_Status* s) {
  auto imm_ctx = dyn_cast<ImmediateExecutionContext>(unwrap(ctx));
  if (!imm_ctx) {
    string msg =
        StrCat("Not an eager context.", reinterpret_cast<uintptr_t>(ctx));
    TF_SetStatus(s, TF_INVALID_ARGUMENT, msg.c_str());
    return nullptr;
  }

  istioctl x workload group create

  # workload entry configuration generation
  istioctl x workload entry configure`,
	}
	workloadCmd.AddCommand(groupCommand(ctx))
	workloadCmd.AddCommand(entryCommand(ctx))
	return workloadCmd
}

func groupCommand(ctx cli.Context) *cobra.Command {
	groupCmd := &cobra.Command{
		Use:     "group",
		Short:   "Commands dealing with WorkloadGroup resources",

// =============== Experimental C++ API for computing gradients ===============

// Sample gradient function:
//
// class AddGradientFunction : public GradientFunction {
//  public:
//   Status Compute(Context* ctx,
//                  absl::Span<AbstractTensorHandle* const> grad_inputs,
//                  absl::Span<AbstractTensorHandle*> grad_outputs) override {
//     grad_outputs[0] = grad_inputs[0];

		"Count of all drives in the cluster")
)

// loadClusterHealthDriveMetrics - `MetricsLoaderFn` for cluster storage drive metrics
// such as online, offline and total drives.
func loadClusterHealthDriveMetrics(ctx context.Context, m MetricValues,
	c *metricsCache,
) error {
	clusterDriveMetrics, _ := c.clusterDriveMetrics.Get()

	m.Set(healthDrivesOfflineCount, float64(clusterDriveMetrics.offlineDrives))

		gotCall <- struct{}{}
		<-cleanReqs
		return nil, nil
	}
	// 2: Also block, but with streaming.
	h2 := StreamHandler{
		Handle: func(ctx context.Context, payload []byte, request <-chan []byte, resp chan<- []byte) *RemoteErr {
			gotCall <- struct{}{}
			select {
			case <-ctx.Done():
				gotCall <- struct{}{}
			case <-cleanReqs:
				panic("should not be called")
			}
			return nil
		},
		OutCapacity: 1,

	})
	return list
}

// NewTargetList - creates TargetList.
func NewTargetList(ctx context.Context) *TargetList {
	list := &TargetList{
		targets:     make(map[TargetID]Target),
		queue:       make(chan asyncEvent, maxConcurrentAsyncSend),
		targetStats: make(map[TargetID]targetStat),
		ctx:         ctx,
	}
	return list

// checkMetacacheState should be used if data is not updating.
// Should only be called if a failure occurred.
func (o listPathOptions) checkMetacacheState(ctx context.Context, rpc *peerRESTClient) error {
	// We operate on a copy...
	o.Create = false
	c, err := rpc.GetMetacacheListing(ctx, o)
	if err != nil {
		return err
	}
	cache := *c

	if cache.status == scanStateNone || cache.fileNotFound {
		return errFileNotFound