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Hi, 感谢作者分享文章的代码。最近在尝试在mobilnet v1做相关的试验,然后可以看到加载mobilnet模型的函数中,Depthwise Conv是根据接在自己后面的ReLU的输出的秩来选取保留的通道,而普通的Conv则是利用前一个卷积(即Depthwise Conv)的Index来选取输入中的需要保留的通道,而根据接在自己后面的ReLU的输出的秩来选取需保留的输出通道。想问下如此设计的原因是什么?因为我们看到其他的剪枝算法是反过来的,就是Depthwise Conv是根据普通Conv的Index来选取保留的通道。期待您的回答
The text was updated successfully, but these errors were encountered:
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Hi, 感谢作者分享文章的代码。最近在尝试在mobilnet v1做相关的试验,然后可以看到加载mobilnet模型的函数中,Depthwise Conv是根据接在自己后面的ReLU的输出的秩来选取保留的通道,而普通的Conv则是利用前一个卷积(即Depthwise Conv)的Index来选取输入中的需要保留的通道,而根据接在自己后面的ReLU的输出的秩来选取需保留的输出通道。想问下如此设计的原因是什么?因为我们看到其他的剪枝算法是反过来的,就是Depthwise Conv是根据普通Conv的Index来选取保留的通道。期待您的回答
The text was updated successfully, but these errors were encountered: