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Align terminology in pooling.md #1395

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2 changes: 1 addition & 1 deletion chapter_convolutional-neural-networks/pooling.md
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与卷积层类似，汇聚层运算符由一个固定形状的窗口组成，该窗口根据其步幅大小在输入的所有区域上滑动，为固定形状窗口（有时称为*汇聚窗口*）遍历的每个位置计算一个输出。
然而，不同于卷积层中的输入与卷积核之间的互相关计算，汇聚层不包含参数。
相反，池运算是确定性的，我们通常计算汇聚窗口中所有元素的最大值或平均值。这些操作分别称为*最大汇聚层*（maximum pooling）和*平均汇聚层*（average pooling）。
相反，汇聚运算是确定性的，我们通常计算汇聚窗口中所有元素的最大值或平均值。这些操作分别称为*最大汇聚层*（maximum pooling）和*平均汇聚层*（average pooling）。

在这两种情况下，与互相关运算符一样，汇聚窗口从输入张量的左上角开始，从左往右、从上往下的在输入张量内滑动。在汇聚窗口到达的每个位置，它计算该窗口中输入子张量的最大值或平均值。计算最大值或平均值是取决于使用了最大汇聚层还是平均汇聚层。

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