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Fix typo in 4.3 #464

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Fix typo in 4.3 #464

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6 changes: 3 additions & 3 deletions chapter_computational_graph/generation_of_computational_graph.md
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Original file line number Diff line number Diff line change
Expand Up @@ -75,7 +75,7 @@ with tf.Session() as sess:
静态图和动态图除了在前端语言表达上略有差异，本质的区别在于编译执行过程。使用前端语言构建完成模型表达后，动态生成并不采用机器学习框架编译器生成完整的静态计算图，而是采用前端语言的解释器Python API调用机器学习框架，框架利用自身的算子分发功能，将Python调用的算子在相应的硬件如CPU、GPU、NPU等上进行加速计算，然后再将计算结果返回给前端。该过程并不产生静态的计算图，而是按照前端语言描述模型结构，按照计算依赖关系进行调度执行，动态生成临时的图拓扑结构。


如:numref:`dynamicgen`中所示动态生成流程。
如 :numref:`dynamicgen`中所示动态生成流程。

![动态生成](../img/ch03/eager-gen.png)
:width:`700px`
Expand All @@ -93,7 +93,7 @@ with tf.Session() as sess:

### 动态和静态生成的比较

静态生成和动态生成的过程各有利弊。为了方便读者对比，将静态图和动态图特性总结见 :numref:`cmp_dynamic_static`。
静态生成和动态生成的过程各有利弊。为了方便读者对比，将静态图和动态图特性总结见 :numref:`cmp_dynamic_static`。

:静态图和动态图对比

Expand All @@ -104,7 +104,7 @@ with tf.Session() as sess:
| 控制流实现方式 | 特定的语法 | 前端语言语法 |
| 性能 | 优化策略多，性能更佳 | 图优化受限，性能较差 |
| 内存占用 | 内存占用少 | 内存占用相对较多 |
| 内存占用 | 可直接部署 | 不可直接部署 |
| 是否可直接部署 | 可直接部署 | 不可直接部署 |
:label:`cmp_dynamic_static`


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