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I see you have qconv2d_batchnorm layer which folds the weights of the two layers and then quantizes.
We're bringing support for that to hls4ml, and it should help us save some resources & latency.
I'm wondering, do you plan to add the equivalent combined QDense + BatchNormalization layer to QKeras?
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