Это будет **сильно зависеть** от того, как вы **развёртываете систему**, как запускаете программы, обрабатываете перезапуски и т.д.

Некоторые возможные идеи:

* «Init Container» в Kubernetes, который запускается перед контейнером с приложением
* Bash‑скрипт, который выполняет предварительные шаги, а затем запускает приложение

              <!-- was only a workaround for Plexus Container, hopefully never used by anyone else -->
              <exclude>org.apache.maven.plugin.DefaultBuildPluginManager#setMojoExecutionListeners(java.util.List)</exclude>

        <artifactId>plexus-utils</artifactId>
        <version>${plexusUtilsVersion}</version>
      </dependency>
      <dependency>
        <groupId>org.codehaus.plexus</groupId>
        <artifactId>plexus-container-default</artifactId>
        <version>${plexusVersion}</version>
      </dependency>
      <dependency>
        <groupId>org.codehaus.plexus</groupId>
        <artifactId>plexus-component-annotations</artifactId>

	ttl  time.Duration
	done chan struct{}

	// buckets for expiration
	buckets []bucket[K, V]
	// uint8 because it's number between 0 and numBuckets
	nextCleanupBucket uint8
}

// bucket is a container for holding entries to be expired
type bucket[K comparable, V any] struct {
	entries     map[K]*Entry[K, V]
	newestEntry time.Time
}

// noEvictionTTL - very long ttl to prevent eviction

When a plugin has a complete and valid configuration, the plugin would be looked up in the Plexus container and be ready to perform any operations requested of it.

h3. Execution of the plugin

    development to avoid installing the packages directly on your system (in
    which case remember to change the directory from `/root` to `/tensorflow`
    once you get into the running container so `bazel` can find the `tensorflow`
    workspace).

    you can do this by using the following command. As an example-

    ```bash
    docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10

		// Validate that the client cannot access the bucket after revocation.
		c.mustNotListObjects(ctx, minioClient, bucket)
	}
}

// SetUpLDAP - expects to setup an LDAP test server using the test LDAP
// container and canned data from https://github.com/minio/minio-ldap-testing
func (s *TestSuiteIAM) SetUpLDAP(c *check, serverAddr string) {
	ctx, cancel := context.WithTimeout(context.Background(), testDefaultTimeout)
	defer cancel()

  }

  FunctionDef fdef() {
    tensorflow::FunctionDef fdef;
    EXPECT_TRUE(GetFunctionDef(func_, &fdef));
    return fdef;
  }

  // logging utility
  template <class Container>
  string ToString(const Container& v) {
    std::stringstream ss;
    ss << "{";
    size_t i = 0;
    for (const auto& e : v) {
      if (i != 0) {
        ss << ", ";
      }
      ss << e.ToString();
      ++i;

另外，请记住，根据您的设置，在某些情况下，您在开始应用程序之前**可能甚至不需要任何先前的步骤**。

 在这种情况下，您就不必担心这些。 🤷

///

### 前面步骤策略的示例

这将在**很大程度上取决于您部署系统的方式**，并且可能与您启动程序、处理重启等的方式有关。

以下是一些可能的想法：

* Kubernetes 中的“Init Container”在应用程序容器之前运行
* 一个 bash 脚本，运行前面的步骤，然后启动您的应用程序
     * 您仍然需要一种方法来启动/重新启动 bash 脚本、检测错误等。

/// tip

我将在以后的章节中为您提供使用容器执行此操作的更具体示例：[容器中的 FastAPI - Docker](docker.md){.internal-link target=_blank}。

///

*   Support for reading (animated) GIFs
*   Improved support for SparseTensor
*   Added support for more probability distributions (Dirichlet, Beta,
    Bernoulli, etc.)
*   Added Python interfaces to reset resource containers.
*   Many bugfixes and performance improvements
*   Many documentation fixes

## Thanks to our Contributors

This release contains contributions from many people at Google, as well as: