Description:          m.Description,
		Value:                m.Value,
		HistogramBucketLabel: m.HistogramBucketLabel,
		StaticLabels:         make(map[string]string, len(m.StaticLabels)),
		VariableLabels:       make(map[string]string, len(m.VariableLabels)),
		Histogram:            make(map[string]uint64, len(m.Histogram)),
	}
	for k, v := range m.StaticLabels {
		metric.StaticLabels[k] = v
	}

			BitrotChecksumAlgo: HighwayHash,
			ErasureDist:        make([]uint8, len(fi.Erasure.Distribution)),
			PartNumbers:        make([]int, len(fi.Parts)),
			PartETags:          nil,
			PartSizes:          make([]int64, len(fi.Parts)),
			PartActualSizes:    make([]int64, len(fi.Parts)),
			MetaSys:            make(map[string][]byte),
			MetaUser:           make(map[string]string, len(fi.Metadata)),
		}

func newBatchJobPool(ctx context.Context, o ObjectLayer, workers int) *BatchJobPool {
	jpool := &BatchJobPool{
		ctx:          ctx,
		objLayer:     o,
		jobCh:        make(chan *BatchJobRequest, 10000),
		workerKillCh: make(chan struct{}, workers),
		jobCancelers: make(map[string]context.CancelFunc),
	}
	jpool.ResizeWorkers(workers)

	randomWait := func() time.Duration {

//       .Attr("N: int >= 2")
//       .Attr("T: type");
// that defines two inputs, "concat_dim" and "values" (in that order).
// You must use TF_AddInput() for the first input (since it takes a
// single tensor), and TF_AddInputList() for the second input (since
// it takes a list, even if you were to pass a list with a single
// tensor), as in:
//   TF_OperationDescription* desc = TF_NewOperation(graph, "Concat", "c");

eData":"2015-12-21T00:00:00","IssueTime":"1251","RPState":"CA","PlateExpiry":"200304","Make":"HOND","BodyStyle":"PA","Color":"GY","Location":"13147 WELBY WAY","Route":"01521","Agency":1,"ViolationCode":"4000A1","ViolationDescr":"NO EVIDENCE OF REG","Fine":50,"Latitude":99999,"Longitude":99999} {"Ticket":1103700150,"IssueData":"2015-12-21T00:00:00","IssueTime":"1435","RPState":"CA","PlateExpiry":"201512","Make":"GMC","BodyStyle":"VN","Color":"WH","Location":"525 S MAIN ST","Route":"1C51","Agency"...

# installed into a virtual environment, and then that venv is used to run all
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which
# drops all the bazel dependencies for each py_test; this makes all the tests
# use the wheel's TensorFlow installation instead of the one made available
# through bazel. This must be done in a different root directory, //bazel_pip/...,

				host, _, err := net.SplitHostPort(getHost(r))
				if err != nil {
					host = r.Host
				}
				// Make sure to skip matching minio.<domain>` this is
				// specifically meant for operator/k8s deployment
				// The reason we need to skip this is for a special
				// usecase where we need to make sure that
				// minio.<namespace>.svc.<cluster_domain> is ignored
				// by the bucketDNS style to ensure that path style

func listIAMConfigItems(ctx context.Context, objAPI ObjectLayer, pathPrefix string) <-chan itemOrErr[string] {
	ch := make(chan itemOrErr[string])

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

		// Allocate new results channel to receive ObjectInfo.
		objInfoCh := make(chan itemOrErr[ObjectInfo])

		if err := objAPI.Walk(ctx, minioMetaBucket, pathPrefix, objInfoCh, WalkOptions{}); err != nil {
			select {

### Create your feature branch

Before making code changes, make sure you create a separate branch for these changes

```
git checkout -b my-new-feature
```

### Test MinIO server changes

After your code changes, make sure

- To add test cases for the new code. If you have questions about how to do it, please ask on our [Slack](https://slack.min.io) channel.
- To run `make verifiers`

> NOTE: Server side replication is supported for idempotent versions on directory objects.

### Idempotent versions on delete markers