status.get()),
      TFE_DeleteTensorHandle);
  ASSERT_TRUE(arrived);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  // Base case: two CPU inputs executes fine.
  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> matmul(
      MatMulOp(context.get(), hcpu.get(), hcpu.get()), TFE_DeleteOp);
  TFE_TensorHandle* retval;
  int num_retvals = 1;

* o cabeçalho `Authorization`
* o cabeçalho encaminhado

* o sistema de injeção de dependências
* a dependência
* o dependable
* o dependant

* limitado por I/O
* limitado por CPU
* concorrência
* paralelismo
* multiprocessamento

* a env var
* a variável de ambiente
* o `PATH`
* a variável `PATH`

* a autenticação
* o provedor de autenticação
* a autorização

* 類別
* 基底類別
* 父類別
* 子類別
* 子類別
* 同級類別
* 類別方法

* 標頭
* 標頭
* 授權標頭
* `Authorization` 標頭
* 轉送標頭

* 相依性注入系統
* 相依項
* 可相依對象
* 相依者

* I/O 受限
* CPU 受限
* 並發
* 平行處理
* 多處理程序

* 環境變數
* 環境變數
* `PATH`
* `PATH` 變數

* 驗證
* 驗證提供者
* 授權
* 授權表單
* 授權提供者
* 使用者進行驗證
* 系統驗證使用者

* CLI
* 命令列介面

* 伺服器

* header
* headers
* authorization header
* `Authorization` header
* forwarded header

* dependency injection system
* dependency
* dependable
* dependant

* I/O bound
* CPU bound
* concurrency
* parallelism
* multiprocessing

* env var
* environment variable
* `PATH`
* `PATH` variable

* authentication
* authentication provider
* authorization

 * Generally speaking, this class reduces object allocation and memory consumption at the price of
 * moderately increased constant factors of CPU. Only use this class when there is a specific reason
 * to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 * @author Jon Noack
 */
@GwtIncompatible // not worth using in GWT for now

The Resource Management Working Group graduated three features to beta in the 1.10 release.  First, [CPU Manager](https://kubernetes.io/docs/tasks/administer-cluster/cpu-management-policies/), which allows users to request exclusive CPU cores.  This helps performance in a variety of use-cases, including network latency sensitive applications, as well as applications that benefit from CPU cache residency.  Next, [Huge Pages](https://kubernetes.io/docs/tasks/manage-hugepages/scheduling-hugepages/),...

  cleanup_makefile()
  setup_python(environ_cp)

  if is_windows():
    environ_cp['TF_NEED_OPENCL'] = '0'
    environ_cp['TF_CUDA_CLANG'] = '0'
    # TODO(ibiryukov): Investigate using clang as a cpu or cuda compiler on
    # Windows.
    environ_cp['TF_DOWNLOAD_CLANG'] = '0'
    environ_cp['TF_NEED_MPI'] = '0'

  if is_ppc64le():
    # Enable MMA Dynamic Dispatch support if 'gcc' and if linker >= 2.35

- Moved the CPU Manager static policy option `strict-cpu-reservation` to the GA version. ([#134388](https://github.com/kubernetes/kubernetes/pull/134388), [@psasnal](https://github.com/psasnal))

- Added a kubelet metrics to report informations about the cpu pools managed by cpumanager when the static policy is in use. ([#127506](https://github.com/kubernetes/kubernetes/pull/127506), [@ffromani](https://github.com/ffromani)) [SIG Node and Testing]

- Added a new option `strict-cpu-reservation` for CPU Manager static policy. When this option is enabled, CPU cores in `reservedSystemCPUs` will be strictly used for system daemons and interrupt processing no longer available for any workload. ([#130290](https://github.com/kubernetes/kubernetes/pull/130290), [@psasnal...