# CUDA WHEEL
test:linux_cuda_wheel_test_filters --test_tag_filters=gpu,requires-gpu,-no_gpu,-no_oss,-tf_tosa,-oss_excluded,-oss_serial,-benchmark-test,-no_cuda11,-no_oss_py38,-no_oss_py39,-no_oss_py310,-no_oss_py313
test:linux_cuda_wheel_test_filters --build_tag_filters=gpu,requires-gpu,-no_gpu,-no_oss,-tf_tosa,-oss_excluded,-oss_serial,-benchmark-test,-no_cuda11,-no_oss_py38,-no_oss_py39,-no_oss_py310,-no_oss_py313

        with:
          api-level: ${{ matrix.api-level }}
          arch: ${{ matrix.api-level == '34' && 'x86_64' || 'x86' }}
          force-avd-creation: false
          emulator-options: -no-window -gpu swiftshader_indirect -noaudio -no-boot-anim -camera-back none
          disable-animations: false
          script: echo "Generated AVD snapshot for caching."

      - name: Run Tests

А затем сразу после `yield` мы выгружаем модель. Этот код будет выполнен после того, как приложение закончит обрабатывать запросы, непосредственно перед shutdown. Это может, например, освободить ресурсы, такие как память или GPU.

/// tip | Совет

`shutdown` произойдёт, когда вы останавливаете приложение.

Возможно, вам нужно запустить новую версию, или вы просто устали от него. 🤷

///

### Функция lifespan { #lifespan-function }

And then, right after the `yield`, we unload the model. This code will be executed **after** the application **finishes handling requests**, right before the *shutdown*. This could, for example, release resources like memory or a GPU.

/// tip

The `shutdown` would happen when you are **stopping** the application.

Maybe you need to start a new version, or you just got tired of running it. 🤷

///

E então, logo após o `yield`, descarregamos o modelo. Esse código será executado **depois** de a aplicação **terminar de lidar com as requisições**, pouco antes do *encerramento*. Isso poderia, por exemplo, liberar recursos como memória ou uma GPU.

/// tip | Dica

O `shutdown` aconteceria quando você estivesse **encerrando** a aplicação.

Talvez você precise iniciar uma nova versão, ou apenas cansou de executá-la. 🤷

///

/// tip | Consejo

El `shutdown` ocurriría cuando estás **deteniendo** la aplicación.

Quizás necesites iniciar una nueva versión, o simplemente te cansaste de ejecutarla. 🤷

///

TEST(CAPI, Session_Min_GPU) {
  const string gpu_device = GPUDeviceName();
  // Skip this test if no GPU is available.
  if (gpu_device.empty()) return;

  RunMinTest(gpu_device, /*use_XLA=*/false);
}

TEST(CAPI, Session_Min_XLA_GPU) {
  const string gpu_device = GPUDeviceName();
  // Skip this test if no GPU is available.
  if (gpu_device.empty()) return;

  RunMinTest(gpu_device, /*use_XLA=*/true);
}

/// tip | Tipp

Das `shutdown` würde erfolgen, wenn Sie die Anwendung **stoppen**.

Möglicherweise müssen Sie eine neue Version starten, oder Sie haben es einfach satt, sie auszuführen. 🤷

///

)

config_setting(
    name = "with_xla_support",
    define_values = {"with_xla_support": "true"},
    visibility = ["//visibility:public"],
)

# By default, XLA GPU is compiled into tensorflow when building with
# --config=cuda even when `with_xla_support` is false. The config setting
# here allows us to override the behavior if needed.
config_setting(
    name = "no_xla_deps_in_cuda",

    for (auto input : inputs) {
      TF_AddInput(desc, input);
    }
    // Set device to CPU because some ops inside the function might not be
    // available on GPU.
    TF_SetDevice(desc, "/cpu:0");
    *op = TF_FinishOperation(desc, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
    ASSERT_NE(*op, nullptr);
  }

  FunctionDef fdef() {