if err != nil {
		return resp, err
	}
	switch any(req).(type) {
	case *MSS, *URLValues:
		ctx = context.WithValue(ctx, TraceParamsKey{}, req)
	case *NoPayload, *Bytes:
		// do not need to trace nopayload and bytes payload
	default:
		ctx = context.WithValue(ctx, TraceParamsKey{}, fmt.Sprintf("type=%T", req))
	}
	if h.callReuseReq {
		defer h.recycleReq(req)
	}
	res, err := c.Request(ctx, h.id, payload)

This property is sometimes referred to as DRF-SC: data-race-free programs
execute in a sequentially consistent manner.
</p>

<p>
While programmers should write Go programs without data races,
there are limitations to what a Go implementation can do in response to a data race.
An implementation may always react to a data race by reporting the race and terminating the program.

package cmd

import (
	"bytes"
	"fmt"

	"github.com/google/uuid"
	"github.com/minio/minio/internal/bucket/lifecycle"
)

const freeVersion = "free-version"

// InitFreeVersion creates a free-version to track the tiered-content of j. If j has
// no tiered content, it returns false.
func (j xlMetaV2Object) InitFreeVersion(fi FileInfo) (xlMetaV2Version, bool) {
	if fi.SkipTierFreeVersion() {
		return xlMetaV2Version{}, false
	}

"Operation" here refers to one of the HTTP "methods".

One of:

* `POST`
* `GET`
* `PUT`
* `DELETE`

...and the more exotic ones:

* `OPTIONS`
* `HEAD`
* `PATCH`
* `TRACE`

In the HTTP protocol, you can communicate to each path using one (or more) of these "methods".

---

When building APIs, you normally use these specific HTTP methods to perform a specific action.

- When you create your backup job, choose the backup repository you created above.

## Test the setup

The next time the backup job runs, you can use the  `mc admin trace myminio` command and verify traffic is flowing to the MinIO nodes. For Veeam Backup and Replication you will need to wait for the backup to complete to the performance tier before it migrates data to the capacity tier (i.e., MinIO).

```

#include "tensorflow/core/platform/intrusive_ptr.h"
#include "tensorflow/core/platform/refcount.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class FunctionRecord;

// A traced function: this hides the complexity of converting the serialized
// representation between various supported formats e.g. FunctionDef and Mlir
// function.
class AbstractFunction : public core::RefCounted {
 protected:

                }
                // one extra acquire to keep this open till the stream is released
                return this.handle.acquire();
            }

        }
        log.trace("Pipe already open");
        return this.handle.acquire();
    }


    /**
     * {@inheritDoc}
     *
     * @see jcifs.SmbPipeHandle#getInput()
     */
    @Override

                                            <la:option value="INFO">INFO</la:option>
                                            <la:option value="DEBUG">DEBUG</la:option>
                                            <la:option value="TRACE">TRACE</la:option>
                                            <la:option value="ALL">ALL</la:option>
                                        </la:select>
                                    </div>

// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,
// inputs and outputs and the gradient function These data structures combined
// allow us to trace the data dependencies between operations and hence compute
// gradients.
//
// `ZerosLike` is not expected to be called and returns a nullptr. The creation

{* ../../docs_src/background_tasks/tutorial001.py hl[6:9] *}

## Ajouter une tâche d'arrière-plan

Dans votre *fonction de chemin*, passez votre fonction de tâche à l'objet de type `BackgroundTasks` (`background_tasks` ici) grâce à la méthode `.add_task()` :


{* ../../docs_src/background_tasks/tutorial001.py hl[14] *}

`.add_task()` reçoit comme arguments :

* Une fonction de tâche à exécuter en arrière-plan (`write_notification`).