Hier werden wir die Datei `requirements.txt` generieren.

3. Installiere Poetry in dieser Docker-Phase.

4. Kopiere die Dateien `pyproject.toml` und `poetry.lock` in das Verzeichnis `/tmp`.

    Da es `./poetry.lock*` verwendet (endet mit einem `*`), stürzt es nicht ab, wenn diese Datei noch nicht verfügbar ist.

5. Generiere die Datei `requirements.txt`.

				if _, ok := err.(BucketExists); !ok {
					t.Logf("unexpected error: %T: %v", err, err)
					return
				}
				mu.Lock()
				errs++
				mu.Unlock()
				return
			}
			mu.Lock()
			ok++
			mu.Unlock()
		}()
	}
	close(start)
	wg.Wait()
	if ok != 1 {
		t.Fatalf("want 1 ok, got %d", ok)
	}
	if errs != n-1 {

// Allows a single op at a time to be launched without blocking.
//
// DeviceThread itself is thread-safe, in that StartExecute will block if there
// is a pending execution. Since StartExecute is equivalent to grabbing a lock,
// multiple DeviceThreads should always be accessed in the same order to avoid
// deadlocks.
class DeviceThread {
 public:
  // Starts a background thread waiting for `StartExecute`.

	}

	setDisks := func(newDisks ...StorageAPI) {
		objLayer.(*erasureServerPools).serverPools[0].erasureDisksMu.Lock()
		copy(disks, newDisks)
		objLayer.(*erasureServerPools).serverPools[0].erasureDisksMu.Unlock()
	}
	getDisk := func(n int) StorageAPI {
		objLayer.(*erasureServerPools).serverPools[0].erasureDisksMu.Lock()
		disk := disks[n]
		objLayer.(*erasureServerPools).serverPools[0].erasureDisksMu.Unlock()
		return disk
	}

	return p.ext
}

// Returns current profile data, returns error if there is no active
// profiling in progress. Stops an active profile.
func getProfileData() (map[string][]byte, error) {
	globalProfilerMu.Lock()
	defer globalProfilerMu.Unlock()

	if len(globalProfiler) == 0 {
		return nil, errors.New("profiler not enabled")
	}

	dst := make(map[string][]byte, len(globalProfiler))

```

1. 这是第一阶段，称为`requirements-stage`。

2. 将 `/tmp` 设置为当前工作目录。

     这是我们生成文件`requirements.txt`的地方

3. 在此阶段安装Poetry。

4. 将`pyproject.toml`和`poetry.lock`文件复制到`/tmp`目录。

     因为它使用 `./poetry.lock*` （以 `*` 结尾），所以如果该文件尚不可用，它不会崩溃。

5. 生成`requirements.txt`文件。

6. 这是最后阶段，这里的任何内容都将保留在最终的容器镜像中。

7. 将当前工作目录设置为`/code`。

8. 将 `requirements.txt` 文件复制到 `/code` 目录。

  static std::unordered_map<std::string, void*>* loaded_libs =
      new std::unordered_map<std::string, void*>();
  tensorflow::Env* env = tensorflow::Env::Default();
  {
    tensorflow::mutex_lock lock(mu);
    auto it = loaded_libs->find(library_filename);
    if (it != loaded_libs->end()) {
      lib_handle->lib_handle = it->second;
    } else {
      status->status =

   * value, you should always choose it explicitly.
   *
   * <p>The current implementation uses the concurrency level to create a fixed number of hashtable
   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and
   * once after loading completes). Much internal cache management is performed at the segment

			newAcc := &AccElem{}
			old := e.cached.Swap(newAcc)
			var a AccElem
			a.Size = atomic.LoadInt64(&old.Size)
			a.Total = atomic.LoadInt64(&old.Total)
			a.N = atomic.LoadInt64(&old.N)
			e.mu.Lock()
			e.lastMinuteLatency.addAll(t-1, a)
			e.mu.Unlock()
			acc = newAcc
		} else {
			// We may be able to grab the new accumulator by yielding.
			runtime.Gosched()
			acc = e.cached.Load()
		}
	}

// a goroutine that will attempt to reconnect if HealthCheckFn is set.
// returns true if the node changed state from online to offline
func (c *Client) MarkOffline(err error) bool {
	c.Lock()
	c.lastErr = err
	c.lastErrTime = time.Now()
	atomic.StoreInt64(&c.lastConn, time.Now().UnixNano())
	c.Unlock()

	return c.runHealthCheck()