lastCheckpoint = st.Object
	}
	workers := make([]chan ReplicateObjectInfo, resyncParallelRoutines)
	resultCh := make(chan TargetReplicationResyncStatus, 1)
	defer xioutil.SafeClose(resultCh)
	go func() {
		for r := range resultCh {
			s.incStats(r, opts)
			globalSiteResyncMetrics.updateMetric(r, opts.resyncID)
		}
	}()

	var wg sync.WaitGroup

	// is critical for debugging, in contrary to getting cluster info
	ctx, cancel := context.WithTimeout(ctx, 10*time.Second)
	defer cancel()

	resultCh := make(chan madmin.ClusterRegistrationInfo)

	go func() {
		defer xioutil.SafeClose(resultCh)

		ci := madmin.ClusterRegistrationInfo{}
		ci.Info.NoOfServerPools = len(globalEndpoints)
		ci.Info.NoOfServers = totalNodeCount()

http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf
S. Hochreiter and J. Schmidhuber. 'Long Short-Term Memory'. Neural Computation,
9(8):1735-1780, 1997.
The peephole implementation is based on:
https://research.google.com/pubs/archive/43905.pdf
Hasim Sak, Andrew Senior, and Francoise Beaufays. 'Long short-term memory
recurrent neural network architectures for large scale acoustic modeling.'
INTERSPEECH, 2014.