// 1: Pending replication
			name: "existing object replication on object in Pending replication status",
			info: ObjectInfo{
				Size:                      100,
				ReplicationStatusInternal: "arn1:PENDING;",
				ReplicationStatus:         replication.Pending,
				VersionID:                 "a3348c34-c352-4498-82f0-1098e8b34df9",
			},

2. Running the CI scripts locally, as explained below
3. **Google employees only**: Google employees can use an internal-only tool
called "MLCI" that makes testing more convenient: it can execute any full CI job
against a pending change. Search for "MLCI" internally to find it.

You may invoke a CI script of your choice by following these instructions:

```bash
cd tensorflow-git-dir

//go:generate msgp -file=$GOFILE

// StatusType of Replication for x-amz-replication-status header
type StatusType string

// Type - replication type enum
type Type int

const (
	// Pending - replication is pending.
	Pending StatusType = "PENDING"

	// Completed - replication completed ok.
	Completed StatusType = "COMPLETED"

	// CompletedLegacy was called "COMPLETE" incorrectly.
	CompletedLegacy StatusType = "COMPLETE"

// - replicated size for all objects sent to this target
// - replica size for all objects received from this target
// - replication pending size for all objects pending replication to this target
// - replication failed size for all objects failed replication to this target
// - replica pending count
// - replica failed count
type BucketTargetUsageInfo struct {
	ReplicationPendingSize  uint64 `json:"objectsPendingReplicationTotalSize"`

     * Last fragment flag - indicates last fragment of a multi-fragment message
     */
    int DCERPC_LAST_FRAG = 0x02; /* Last fragment */
    /**
     * Pending cancel flag - indicates cancel was pending at sender
     */
    int DCERPC_PENDING_CANCEL = 0x04; /* Cancel was pending at sender */
    /**
     * Reserved flag for future use
     */
    int DCERPC_RESERVED_1 = 0x08;
    /**
     * Supports concurrent multiplexing flag

)

var (
	ilmExpiryPendingTasksMD             = NewGaugeMD(expiryPendingTasks, "Number of pending ILM expiry tasks in the queue")
	ilmTransitionActiveTasksMD          = NewGaugeMD(transitionActiveTasks, "Number of active ILM transition tasks")
	ilmTransitionPendingTasksMD         = NewGaugeMD(transitionPendingTasks, "Number of pending ILM transition tasks in the queue")

     * Last fragment flag - indicates last fragment of a multi-fragment message
     */
    int DCERPC_LAST_FRAG = 0x02; /* Last fragment */
    /**
     * Pending cancel flag - indicates cancel was pending at sender
     */
    int DCERPC_PENDING_CANCEL = 0x04; /* Cancel was pending at sender */
    /**
     * Reserved flag for future use
     */
    int DCERPC_RESERVED_1 = 0x08;
    /**
     * Supports concurrent multiplexing flag.

mouth enough for it to speak with.

  Alice waited till the eyes appeared, and then nodded.  `It's no
use speaking to it,' she thought, `till its ears have come, or at
least one of them.'  In another minute the whole head appeared,
and then Alice put down her flamingo, and began an account of the
game, feeling very glad she had someone to listen to her.  The
Cat seemed to think that there was enough of it now in sight, and

class Settings(BaseSettings):
    github_repository: str
    github_token: SecretStr
    deploy_url: str | None = None
    commit_sha: str
    run_id: int
    state: Literal["pending", "success", "error"] = "pending"


class LinkData(BaseModel):
    previous_link: str
    preview_link: str
    en_link: str | None = None


def main() -> None:
    logging.basicConfig(level=logging.INFO)

### Replication of object version and metadata