HealID string

	ItemsSkipped uint64
	BytesSkipped uint64

	RetryAttempts uint64

	Finished bool // finished healing, whether with errors or not

	// Add future tracking capabilities
	// Be sure that they are included in toHealingDisk
}

// loadHealingTracker will load the healing tracker from the supplied disk.
// The disk ID will be validated against the loaded one.

 * the life cycle methods.
 *
 * <h3>Usage Example</h3>
 *
 * <p>Here is a sketch of a service which crawls a website and uses the scheduling capabilities to
 * rate limit itself.
 *
 * <pre>{@code
 * class CrawlingService extends AbstractScheduledService {
 *   private Set<Uri> visited;
 *   private Queue<Uri> toCrawl;

build:cuda_clang --config=cuda
build:cuda_clang --@local_config_cuda//:cuda_compiler=clang
build:cuda_clang --copt=-Qunused-arguments
# Select supported compute capabilities (supported graphics cards).
# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX

  validate any input config file. Use the `--config` flag to pass a config file
  to it. See the command `--help` screen for more information. As a result of adding
  this new command, enhance the validation capabilities of the existing "kubeadm
  config migrate" command. For both commands unknown APIs or fields will throw errors. ([#118013](https://github.com/kubernetes/kubernetes/pull/118013), [@neolit123](https://github.com/neolit123))

*   Added warmup capabilities to `tf.keras.optimizers.schedules.CosineDecay` learning rate scheduler. You can now specify an initial and target learning rate, and our scheduler will perform a linear interpolation between the two after which it will begin a decay phase.