}
        return sensitivePattern;
    }

    /**
     * Masks sensitive values for logging purposes.
     * Keys matching the pattern defined in 'app.log.sensitive.property.pattern' system property
     * will have their values replaced with "********".
     *
     * @param key The key name to check
     * @param value The value to potentially mask

  private val sinkBuffer: Buffer = sink.buffer
  private var writerClosed = false

  /** Lazily initialized on first use. */
  private var messageDeflater: MessageDeflater? = null

  // Masks are only a concern for client writers.
  private val maskKey: ByteArray? = if (isClient) ByteArray(4) else null
  private val maskCursor: Buffer.UnsafeCursor? = if (isClient) Buffer.UnsafeCursor() else null

  private val controlFrameBuffer = Buffer()
  private val messageFrameBuffer = Buffer()

  /** Lazily initialized on first use. */
  private var messageInflater: MessageInflater? = null

  // Masks are only a concern for server writers.
  private val maskKey: ByteArray? = if (isClient) null else ByteArray(4)
  private val maskCursor: Buffer.UnsafeCursor? = if (isClient) null else Buffer.UnsafeCursor()

                .map(user -> user.hasRoles(roles) || user.hasRoles(ComponentUtil.getFessConfig().getAuthenticationAdminRolesAsArray()))
                .orElse(false);
    }

    /**
     * Masks email addresses in the input string for privacy protection.
     *
     * @param value the string that may contain email addresses
     * @return string with email addresses replaced by masked pattern
     */

			Offset: frameSize,
			// Argsize set below.
		},
	}
	nameAddr.Sym.Func().Text = prog
	prog.To.Val = int32(argSize)
	p.append(prog, "", true)
}

// asmData assembles a DATA pseudo-op.
// DATA masks<>+0x00(SB)/4, $0x00000000
func (p *Parser) asmData(operands [][]lex.Token) {
	if len(operands) != 2 {
		p.errorf("expect two operands for DATA")
		return
	}

	// Operand 0 has the general form foo<>+0x04(SB)/4.

        copyAccessEntry(original, newEntry);
        copyWriteEntry(original, newEntry);
        return newEntry;
      }
    };

    // Masks used to compute indices in the following table.

    static final int ACCESS_MASK = 1;
    static final int WRITE_MASK = 2;
    static final int WEAK_MASK = 4;

    /** Look-up table for factories. */

        copyAccessEntry(original, newEntry);
        copyWriteEntry(original, newEntry);
        return newEntry;
      }
    };

    // Masks used to compute indices in the following table.

    static final int ACCESS_MASK = 1;
    static final int WRITE_MASK = 2;
    static final int WEAK_MASK = 4;

    /** Look-up table for factories. */

        [`tf.keras.layers.MultiHeadAttention`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/MultiHeadAttention).
        *   Implicit masks for `query`, `key` and `value` inputs will
            automatically be used to compute a correct attention mask for the
            layer. These padding masks will be combined with any
            `attention_mask` passed in directly when calling the layer. This can
            be used with

# Tareas en Segundo Plano { #background-tasks }

Puedes definir tareas en segundo plano para que se ejecuten *después* de devolver un response.

Esto es útil para operaciones que necesitan ocurrir después de un request, pero para las que el cliente realmente no necesita esperar a que la operación termine antes de recibir el response.

Esto incluye, por ejemplo:

* Notificaciones por email enviadas después de realizar una acción:

# Background Tasks { #background-tasks }

You can define background tasks to be run *after* returning a response.

This is useful for operations that need to happen after a request, but that the client doesn't really have to be waiting for the operation to complete before receiving the response.

This includes, for example:

* Email notifications sent after performing an action: