// Mask returns the type as mask.
func (e Event) Mask() uint64 {
	return e.EventName.Mask()
}

// Log represents event information for some event targets.
type Log struct {
	EventName Name
	Key       string
	Records   []Event

	// Inter-node JWT token expiry is 100 years approx.
	defaultInterNodeJWTExpiry = 100 * 365 * 24 * time.Hour
)

var (
	errInvalidAccessKeyID = errors.New("The access key ID you provided does not exist in our records")
	errAccessKeyDisabled  = errors.New("The access key you provided is disabled")
	errAuthentication     = errors.New("Authentication failed, check your access credentials")
	errNoAuthToken        = errors.New("JWT token missing")

```
mc cp myphoto.jpg myminio/images
```

You should receive the following event notification via RabbitMQ once the upload completes.

```py
python rabbit.py

	if err != nil {
		return err
	}
	key := eventData.S3.Bucket.Name + "/" + objectName

	data, err := json.Marshal(event.Log{EventName: eventData.EventName, Key: key, Records: []event.Event{eventData}})
	if err != nil {
		return err
	}

	req, err := http.NewRequest(http.MethodPost, target.args.Endpoint.String(), bytes.NewReader(data))
	if err != nil {
		return err
	}

		if eventData.EventName == event.ObjectRemovedDelete {
			_, err = target.deleteStmt.Exec(key)
		} else {
			var data []byte
			if data, err = json.Marshal(struct{ Records []event.Event }{[]event.Event{eventData}}); err != nil {
				return err
			}

			_, err = target.updateStmt.Exec(key, data)
		}

		return err
	}

	if target.args.Format == event.AccessFormat {

	buf.WriteByte(7)
	buf.Write([]byte{0, 24})
	buf.WriteString("application/octet-stream")

	buf.WriteByte(11)
	buf.WriteString(":event-type")
	buf.WriteByte(7)
	buf.Write([]byte{0, 7})
	buf.WriteString("Records")

	fmt.Println(buf.Bytes())
}

// Continuation Message
// ====================
// Header specification
// --------------------
// Continuation messages contain two headers, as follows:

				}
			} else {
				var outputRecord sql.Record
				// We will attempt to reuse the records in the table.
				// The type of these should not change.
				// The queue should always have at least one entry left for this to work.
				outputQueue = outputQueue[:len(outputQueue)+1]
				if t := outputQueue[len(outputQueue)-1]; t != nil {
					// If the output record is already set, we reuse it.
					outputRecord = t

  // This is a no-op if the tensor is already being watched either from an
  // earlier call to `GradientTape::Watch` or being an output of an op with
  // watched inputs.
  void Watch(const AbstractTensorHandle*);
  // Records an operation with given inputs and outputs
  // on the tape and marks all its outputs as watched if at
  // least one input of the op is watched and has a trainable dtype.
  // op_name is optional and is used for debugging only.

	err = decoder.Decode(multipartResponse)
	if err != nil {
		t.Fatalf("Error decoding the recorded response Body")
	}
	uploadID := multipartResponse.UploadID

	a := 0
	b := globalMinPartSize
	var parts []CompletePart
	for partNumber := 1; partNumber <= 2; partNumber++ {
		// initialize HTTP NewRecorder, this records any mutations to response writer inside the handler.
		rec := httptest.NewRecorder()

  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each
  // value records whether the graph has been mutated since the corresponding
  // session has been run (this is detected in RecordMutation function). If the
  // string is empty, no mutation has occurred. Otherwise the string is a