Introducing a model for pruning the TX size search
Use a neural-network-based binary classifier to predict the first split decision on the highest level of the TX size RD search tree. Depending on how confident we are in the prediction we either keep full unmodified TX size search or use the largest possible TX size and stop any further search. Average speed-up: 3-4% Quality loss (lowres): 0.062% Quality loss (midres): 0.018% Change-Id: I64c0317db74cbeddfbdf772147c43e99e275891f
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