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Predicting zero-valued activations with lightweight convolutional neural networks
Thanks for the cool tool!
Could you please give me some detail descriptions of the code?
And something user should pay special attention to?
Very interesting paper.
I see the point in predicting zero activations which reduces the MAC. And central to this argument is the widespread usage of ReLU.
Will ZAP be beneficial if my CNN is using Leaky Relu and thus i expect not many activations will be zero?
Thankyou
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