fi
  export project_name="$TFCI_INSTALLER_WHL_PROJECT_NAME"
fi

# Mac builds have some specific setup needs. See setup_macos.sh for details
if [[ "${OSTYPE}" =~ darwin* ]]; then
  source ./ci/official/utilities/setup_macos.sh
fi

# Create and expand to the full path of TFCI_OUTPUT_DIR
export TFCI_OUTPUT_DIR=$(realpath "$TFCI_OUTPUT_DIR")
mkdir -p "$TFCI_OUTPUT_DIR"

  // Number of dimensions. -1 indicates unknown rank.
  int num_dims;
  // Array of dimensions. -1 indicates unknown dim.
  int64_t* dims;
  // The data type. May be 0 to denote unknown type.
  TF_DataType dtype;
};

typedef struct TF_ShapeAndType TF_ShapeAndType;

// A list of TF_ShapeAndType elements..
struct TF_ShapeAndTypeList {
  int num_items;
  TF_ShapeAndType* items;
};

func (r *BatchJobKeyRotateV1) Start(ctx context.Context, api ObjectLayer, job BatchJobRequest) error {
	ri := &batchJobInfo{
		JobID:     job.ID,
		JobType:   string(job.Type()),
		StartTime: job.Started,
	}
	if err := ri.loadOrInit(ctx, api, job); err != nil {
		return err
	}
	if ri.Complete {
		return nil
	}

type replicatedTargetInfo struct {
	Arn                   string
	Size                  int64
	Duration              time.Duration
	ReplicationAction     replicationAction // full or metadata only
	OpType                replication.Type  // whether incoming replication, existing object, healing etc..
	ReplicationStatus     replication.StatusType
	PrevReplicationStatus replication.StatusType

// there are more than one), or "" otherwise.
string GPUDeviceName(TF_Session* session) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  TF_Status* s = status.get();
  std::unique_ptr<TF_DeviceList, decltype(&TF_DeleteDeviceList)> list(
      TF_SessionListDevices(session, s), TF_DeleteDeviceList);
  TF_DeviceList* device_list = list.get();

	ReplicationStatusInternal  string
	VersionPurgeStatusInternal string
	VersionPurgeStatus         VersionPurgeStatusType
	ReplicationState           ReplicationState
	DeleteMarker               bool

	OpType               replication.Type
	EventType            string
	RetryCount           uint32
	ResetID              string
	Dsc                  ReplicateDecision
	ExistingObjResync    ResyncDecision

		// reject removal of remote target if replication configuration is present
		rcfg, err := getReplicationConfig(ctx, bucket)
		if err == nil && rcfg != nil {
			for _, tgtArn := range rcfg.FilterTargetArns(replication.ObjectOpts{OpType: replication.AllReplicationType}) {
				if err == nil && (tgtArn == arnStr || rcfg.RoleArn == arnStr) {
					sys.RLock()
					_, ok := sys.arnRemotesMap[arnStr]
					sys.RUnlock()
					if ok {

// Start the batch expiration job, resumes if there was a pending job via "job.ID"
func (r *BatchJobExpire) Start(ctx context.Context, api ObjectLayer, job BatchJobRequest) error {
	ri := &batchJobInfo{
		JobID:     job.ID,
		JobType:   string(job.Type()),
		StartTime: job.Started,
	}
	if err := ri.loadOrInit(ctx, api, job); err != nil {
		return err
	}

	globalBatchJobsMetrics.save(job.ID, ri)
	lastObject := ri.Object

	}

	if !hasExistingObjEnabled {
		writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrReplicationNoExistingObjects), r.URL)
		return
	}

	tgtArns := config.FilterTargetArns(
		replication.ObjectOpts{
			OpType:    replication.ResyncReplicationType,
			TargetArn: arn,
		})

	if len(tgtArns) == 0 {
		writeErrorResponseJSON(ctx, w, errorCodes.ToAPIErrWithErr(ErrBadRequest, InvalidArgument{
			Bucket: bucket,

        the layer's dtype. If you had a model that used `float64`, it will
        probably silently use `float32` in TensorFlow2, and a warning will be
        issued that starts with Layer "layer-name" is casting an input tensor
        from dtype float64 to the layer's dtype of float32. To fix, either set
        the default dtype to float64 with