// If not set the client will not keep track of health.
	// Calling this returns true or false if the target
	// is online or offline.
	HealthCheckFn func() bool

	// HealthCheckRetryUnit will be used to calculate the exponential
	// backoff when trying to reconnect to an offline node
	HealthCheckReconnectUnit time.Duration

	// HealthCheckTimeout determines timeout for each call.
	HealthCheckTimeout time.Duration

                                                           int bucket_count) {
  return new TFE_MonitoringBuckets([scale, growth_factor, bucket_count]() {
    return tensorflow::monitoring::Buckets::Exponential(scale, growth_factor,
                                                        bucket_count);
  });
}

void TFE_MonitoringDeleteBuckets(TFE_MonitoringBuckets* buckets) {
  delete buckets;
}

- Fixed an issue where failed pods associated with a job with `parallelism = 1` are recreated by the job controller honoring exponential backoff delay again. However, for jobs with `parallelism > 1`, pods might be created without exponential backoff delay. ([#114516](https://github.com/kubernetes/kubernetes/pull/114516), [@nikhita](https://github.com/nikhita))

- Improved exponential backoff in Reflector, significantly reducing the load on Kubernetes apiserver in case of throttling of requests. ([#118132](https://github.com/kubernetes/kubernetes/pull/118132), [@marseel](https://github.com/marseel)) [SIG API Machinery and Scalability]...

*   Performance improvements for gRPC
*   Improved support for fp16
*   New high-level ops in tf.contrib. {layers,metrics}
*   New features for TensorBoard, such as shape display, exponential smoothing
*   Faster and more stable Google Cloud Storage (GCS) filesystem support
*   Support for zlib compression and decompression for TFRecordReader and
    TFRecordWriter
*   Support for reading (animated) GIFs