I have a question about Show, Attend and Tell: Neural Image CaptionGeneration with Visual Attention paper by Xu. The basic mechanism of stochastic hard attention is that each pixel of the input image has a corresponding parameter $\alpha_i$, which describes the probability that this pixel will be chosen for further processing.

But I don't see an explanation of how to train or define this parameter in the paper. Can someone explain how to train this $\alpha_i$ for each pixel?


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