func (s *NetServer) buildZtunnelSnapshot(ambientPodUIDs map[types.UID]*corev1.Pod) error {
	// first add all the pods as empty:
	for uid := range ambientPodUIDs {
		s.currentPodSnapshot.Ensure(string(uid))
	}

	// populate full pod snapshot from cgroups
	return s.scanProcForPodsAndCache(ambientPodUIDs)
}

func (s *NetServer) scanProcForPodsAndCache(pods map[types.UID]*corev1.Pod) error {

	if err != nil {
		return result, toObjectErr(err, bucket, object, uploadID)
	}

	uploadIDPath := er.getUploadIDDir(bucket, object, uploadID)

	// Populate the result stub.
	result.Bucket = bucket
	result.Object = object
	result.UploadID = uploadID
	result.MaxParts = maxParts
	result.PartNumberMarker = partNumberMarker
	result.UserDefined = cloneMSS(fi.Metadata)

			return err
		}
	}

	// Do the same for inline data
	dirs, err := xl.data.list()
	if err != nil {
		return err
	}

	// Clear and repopulate
	for k := range foundDirs {
		delete(foundDirs, k)
	}

	// Populate into map
	for _, k := range dirs {
		foundDirs[k] = struct{}{}
	}

	// Delete all directories we expect to be there.
	for _, dir := range wantDirs {

      switch (size) {
        case 0:
          return of();
        case 1:
          /*
           * requireNonNull is safe because we ensure that the first `size` elements have been
           * populated.
           */
          return (ImmutableSet<E>) of(requireNonNull(contents[0]));
        default:
          ImmutableSet<E> result;
          if (hashTable != null && chooseTableSize(size) == hashTable.length) {

	iamOS, ok := store.IAMStorageAPI.(*IAMObjectStore)
	if !ok {
		// No purging is done for non-object storage.
		return nil
	}
	return iamOS.PurgeExpiredSTS(ctx)
}

// LoadIAMCache reads all IAM items and populates a new iamCache object and
// replaces the in-memory cache object.
func (store *IAMStoreSys) LoadIAMCache(ctx context.Context, firstTime bool) error {
	bootstrapTraceMsg := func(s string) {
		if firstTime {

        Cloud TPUs.
    *   Support for `.fit`, `.evaluate`, `.predict` on TPU using numpy data, in
        addition to `tf.data.Dataset`.
    *   Keras reference implementations for many popular models are available in
        the TensorFlow
        [Model Garden](https://github.com/tensorflow/models/tree/master/official).
*   `tf.data`
    *   Changes rebatching for `tf.data datasets` + DistributionStrategy for