Update fig (#272)

2026-04-04 03:09:07 +08:00 · 2022-04-12 11:57:10 +08:00
parent 9c6f64b116
commit 2e97cd7cf6
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--- a/chapter_programming_interface/index.md
+++ b/chapter_programming_interface/index.md
@@ -2,7 +2,7 @@

 现代机器学习框架包含大量的组件。这些组件使得用户得以高效开发机器学习算法，处理数据，部署模型，性能调优和使用硬件加速器。在设计这些组件的编程接口时，一个核心的诉求是：如何平衡框架性能和易用性？为了达到最优的性能，开发者需要利用硬件亲和的编程语言如：C和C++来进行开发。这是因为：C和C++的使用使得机器学习框架可以高效调用硬件的底层API，从而最大限度发挥硬件性能。同时，现代操作系统（如Linux和Windows）提供丰富的基于C和C++的编程接口（如文件系统，网络编程，多线程管理等），通过直接调用操作系统API，可以降低框架运行的开销。

-从易用性的角度分析，机器学习框架的使用者往往具有丰富的行业背景（如数据科学家，生物学家，化学家，物理学家等）。他们的常用的编程语言是高层次脚本语言：Python，Matlab，R和Julia。相比于C和C++，这些语言在提供编程的易用性的同时，丧失了C和C++对底层硬件和操作系统进行深度优化的能力。因此，机器学习框架的核心设计目标是：其要具有易用编程接口来支持用户用高层次语言如Python来实现机器学习算法，同时其也要具备以C和C++为核心的低层次编程接口，使得框架开发者可以用C和C++实现大量高性能组件，从而在硬件上高效执行。在本章中，我们将会讲述如何达到这个设计目标。
+从易用性的角度分析，机器学习框架的使用者往往具有丰富的行业背景（如数据科学家，生物学家，化学家，物理学家等）。他们常用的编程语言是高层次脚本语言：Python，Matlab，R和Julia。相比于C和C++，这些语言在提供编程的易用性的同时，丧失了C和C++对底层硬件和操作系统进行深度优化的能力。因此，机器学习框架的核心设计目标是：其要具有易用编程接口来支持用户用高层次语言如Python来实现机器学习算法，同时其也要具备以C和C++为核心的低层次编程接口，使得框架开发者可以用C和C++实现大量高性能组件，从而在硬件上高效执行。在本章中，我们将会讲述如何达到这个设计目标。

 本章的学习目标包括：

--- a/chapter_programming_interface/ml_workflow.md
+++ b/chapter_programming_interface/ml_workflow.md
@@ -19,7 +19,7 @@
 -   **测试和调试：**
    训练过程中，用户需要测试API来对当前模型的精度进行评估。当精度达到目标后，训练结束。这一过程中，用户往往需要调试API来完成对模型的性能和正确性进行验证。

-![机器学习系统工作流](../img/ch02/workflow.svg)
+![机器学习系统工作流](../img/ch02/img_workflow.svg)
 :width:`800px`
 :label:`img_workflow`

--- a/chapter_programming_interface/summary.md
+++ b/chapter_programming_interface/summary.md
@@ -19,3 +19,8 @@
 - Python和C之间的互操作性一般通过CType等技术实现。

 - 机器学习框架一般具有多种C和C++接口允许用户定义和注册C++实现的算子。这些算子使得用户可以开发高性能模型，数据处理函数，优化器等一系列框架拓展。
+
+## 扩展阅读
+
+- MindSpore编程指南：[MindSpore](https://www.mindspore.cn/docs/programming_guide/zh-CN/r1.6/index.html)
+- Python和C/C++混合编程：[Pybind11](https://pybind11.readthedocs.io/en/latest/basics.html#creating-bindings-for-a-simple-function)
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