história que estava contando (terminar o trabalho atual ⏯ / tarefa sendo processada 🤓), sorri gentilmente e diz que você está indo buscar os hambúrgueres ⏸.

Então você vai ao balcão 🔀, para a tarefa inicial que agora está finalizada ⏯, pega os hambúrgueres, agradece, e leva-os para a mesa. Isso finaliza esse passo / tarefa da interação com o balcão ⏹. Isso, por sua vez, cria uma nova tarefa, a de "comer hambúrgueres" 🔀 ⏯, mas a tarefa anterior de "pegar os hambúrgueres" já está finalizada...

                });
                threads[i].start();
            }

            // Wait for all threads to complete
            for (Thread thread : threads) {
                thread.join();
            }
        }

        // Then
        for (int i = 0; i < threadCount; i++) {
            assertTrue(results[i], "Thread " + i + " should have completed successfully");
        }
    }

                } catch (Exception e) {
                    logger.error("Thread {} failed", index, e);
                    results[index] = false;
                }
            });
            threads[i].start();
        }

        // Wait for all threads to complete
        for (Thread thread : threads) {
            thread.join();
        }

        // Then

        Thread[] threads = new Thread[10];

        // Act
        for (int i = 0; i < threads.length; i++) {
            final int index = i;
            threads[i] = new Thread(() -> {
                results[index] = transPeekNamedPipe.toString();
            });
            threads[i].start();
        }

        for (Thread thread : threads) {
            thread.join();
        }

            // Create multiple threads to call size()
            Thread[] threads = new Thread[10];
            for (int i = 0; i < threads.length; i++) {
                threads[i] = new Thread(() -> {
                    for (int j = 0; j < 1000; j++) {
                        assertEquals(expectedSize, buffer.size());
                    }
                });
                threads[i].start();
            }

      return;
    }
    TimedWaiterThread thread = new TimedWaiterThread(new AbstractFuture<Object>() {}, 2, SECONDS);
    thread.start();
    thread.awaitWaiting();
    Thread.class.getMethod("suspend").invoke(thread);
    // Sleep for enough time to add 1500 milliseconds of overwait to the get() call.
    long toWaitMillis = 3500 - NANOSECONDS.toMillis(System.nanoTime() - thread.startTime);
    Thread.sleep(toWaitMillis);

                    success[index] = false;
                }
            });
            threads[i].start();
        }

        // Wait for all threads to complete
        for (Thread thread : threads) {
            thread.join();
        }

        // All threads should complete successfully
        for (boolean s : success) {
            assertTrue(s);
        }
    }

                    success[index] = false;
                }
            });
            threads[i].start();
        }

        // Wait for all threads to complete
        for (Thread thread : threads) {
            thread.join();
        }

        // All threads should complete successfully
        for (boolean s : success) {
            assertTrue(s);
        }
    }

### Migration and Enforcement

* **New code**: All new contributions must use American English
* **Existing code**: British English spellings in existing code should be updated opportunistically when those areas are modified, unless constrained by backward compatibility
* **Documentation**: Documentation should be updated to use American English, prioritizing user-facing documentation

`SavedModel`) and executes them in parallel on available executors. Running
TensorFlow in a multitenant design mixes the risks described above with the
inherent ones from multitenant configurations. The primary areas of concern are
tenant isolation, resource allocation, model sharing and hardware attacks.

### Tenant isolation

Since any tenants or users providing models, graphs or checkpoints can execute