如果你的应用很**简单**，这可能**不成问题**，你也许不需要设置严格的内存上限。但如果你**使用大量内存**（例如使用**机器学习**模型），你应该检查自己的内存消耗，并调整**每台机器**上运行的**容器数量**（也许还需要为集群增加机器）。

如果你**每个容器运行多个进程**，你需要确保启动的进程数量不会**消耗超过可用的内存**。

## 启动前的前置步骤与容器 { #previous-steps-before-starting-and-containers }

如果你在使用容器（如 Docker、Kubernetes），你可以采用两种主要方式。

### 多个容器 { #multiple-containers }

    write_action_env_to_bazelrc('HIP_PLATFORM', environ_cp.get('HIP_PLATFORM'))

  if is_windows():
    print('\nWARNING: Cannot build with CUDA support on Windows.\n'
          'Starting in TF 2.11, CUDA build is not supported for Windows. '
          'For using TensorFlow GPU on Windows, you will need to build/install '
          'TensorFlow in WSL2.\n')
    environ_cp['TF_NEED_CUDA'] = '0'
  else:

## Pasos Previos Antes de Comenzar y Contenedores { #previous-steps-before-starting-and-containers }

Si estás usando contenedores (por ejemplo, Docker, Kubernetes), entonces hay dos enfoques principales que puedes usar.

### Múltiples Contenedores { #multiple-containers }

## Schritte vor dem Start und Container { #previous-steps-before-starting-and-containers }

Wenn Sie Container (z. B. Docker, Kubernetes) verwenden, können Sie hauptsächlich zwei Ansätze verwenden.

### Mehrere Container { #multiple-containers }

      // `entries`. The `oldNext` loop is going to traverse that linked list.
      // We need to rewrite the `next` link of each of the elements so that it is in the appropriate
      // linked list starting from `newTable`. In general, each element from the old linked list
      // belongs to a different linked list from `newTable`. We insert each element in turn at the
      // head of its appropriate `newTable` linked list.

Se você executar **múltiplos processos por contêiner**, deve garantir que o número de processos iniciados não **consuma mais memória** do que o disponível.

## Passos anteriores antes de iniciar e contêineres { #previous-steps-before-starting-and-containers }

Se você estiver usando contêineres (por exemplo, Docker, Kubernetes), existem duas abordagens principais que você pode usar.

### Contêineres Múltiplos { #multiple-containers }

Якщо ви запускаєте кілька процесів на контейнер, вам потрібно переконатися, що кількість запущених процесів не споживає більше пам’яті, ніж доступно.

## Попередні кроки перед запуском і контейнери { #previous-steps-before-starting-and-containers }

Якщо ви використовуєте контейнери (наприклад, Docker, Kubernetes), то є два основні підходи.

### Кілька контейнерів { #multiple-containers }

- DRA: Starting Kubernetes 1.33, only users with access to an admin namespace with the `kubernetes.io/dra-admin-access` label are authorized to create ResourceClaim or ResourceClaimTemplate objects with the `adminAccess` field in this admin namespace if they want...

please discuss your idea first on the GitHub issue. If there is no GitHub issue
for your idea, please open one. It may be that somebody is already working on
it, or that there are particular complexities that you should know about before
starting the implementation. There are often a number of ways to fix a problem
and it is important to find the right approach before spending time on a PR
that cannot be merged.

<INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>

# Release 2.21.0

## TensorFlow

### Breaking Changes

* Support for Python 3.9 has been removed starting with TF 2.21.
* The TensorBoard (TB) dependency has been removed starting with TF 2.21.

### Major Features and Improvements

* `tf.lite`
    * Adds int8 and int16x8 support for SQRT operator.
    * Adds int16x8 support for EQUAL and NOT_EQUAL operators.