CI_DOCKER_BUILD_EXTRA_PARAMS="--build-arg py_major_minor_version=${{ matrix.pyver }} --build-arg is_nightly=${is_nightly} --build-arg tf_project_name=${tf_project_name}" \

 * java.util.LinkedHashMap}. 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
 */
@J2ktIncompatible // no support for access-order mode in LinkedHashMap delegate
@GwtIncompatible // not worth using in GWT for now

---

Typische Beispiele für CPU-lastige Vorgänge sind Dinge, die komplexe mathematische Berechnungen erfordern.

Zum Beispiel:

* **Audio-** oder **Bildbearbeitung**.

 * java.util.LinkedHashMap}. 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
 */
@J2ktIncompatible // no support for access-order mode in LinkedHashMap delegate
@GwtIncompatible // not worth using in GWT for now

          CI_DOCKER_BUILD_EXTRA_PARAMS="--build-arg py_major_minor_version=${{ matrix.pyver }} --build-arg is_nightly=${is_nightly} --build-arg tf_project_name=${tf_project_name}" \
          ./tensorflow/tools/ci_build/ci_build.sh cpu.arm64 bash tensorflow/tools/ci_build/rel/ubuntu/cpu_arm64_test_build.sh
      - name: Upload pip wheel to PyPI

---

Exemplos comuns de operações limitadas por CPU são coisas que exigem processamento matemático complexo.

Por exemplo:

* **Processamento de áudio** ou **imagem**

			// callhome running on a different node.
			// sleep for some time and try again.
			duration := max(time.Duration(r.Float64()*float64(globalCallhomeConfig.FrequencyDur())),
				// Make sure to sleep at least a second to avoid high CPU ticks.
				time.Second)
			time.Sleep(duration)
		}
	}()
}

func runCallhome(ctx context.Context, objAPI ObjectLayer) bool {
	// Make sure only 1 callhome is running on the cluster.

	}
	return formattedName
}

var (
	// https://github.com/golang/lint/blob/master/lint.go#L770
	commonInitialisms         = []string{"API", "ASCII", "CPU", "CSS", "DNS", "EOF", "GUID", "HTML", "HTTP", "HTTPS", "ID", "IP", "JSON", "LHS", "QPS", "RAM", "RHS", "RPC", "SLA", "SMTP", "SSH", "TLS", "TTL", "UID", "UI", "UUID", "URI", "URL", "UTF8", "VM", "XML", "XSRF", "XSS"}

And as most of the execution time is taken by actual work (instead of waiting), and the work in a computer is done by a <abbr title="Central Processing Unit">CPU</abbr>, they call these problems "CPU bound".

---

Common examples of CPU bound operations are things that require complex math processing.

For example:

* **Audio** or **image processing**.

///

### 官方 Docker 镜像上的进程数

此镜像上的**进程数**是根据可用的 CPU **核心**自动计算的。

这意味着它将尝试尽可能多地**榨取**CPU 的**性能**。

你还可以使用 **环境变量** 等配置来调整它。

但这也意味着，由于进程数量取决于容器运行的 CPU，因此**消耗的内存量**也将取决于该数量。

因此，如果你的应用程序消耗大量内存（例如机器学习模型），并且你的服务器有很多 CPU 核心**但内存很少**，那么你的容器最终可能会尝试使用比实际情况更多的内存 可用，并且性能会下降很多（甚至崩溃）。 🚨

### 创建一个`Dockerfile`

以下是如何根据此镜像创建`Dockerfile`：