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In hard rounding mode, we first round down the tensor (i.e, flooring). Then (self.alpha >= 0).float() is used to determine either rounding up or rounding down. When alpha is less than 0, it is 0, otherwise, it would be 1 and therefore round up the weights.
BRECQ/quant/adaptive_rounding.py
Lines 50 to 51 in 819d440
Would you elaborate how you derived hard-rounding scheme and what's the use of it?
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