INNER CODE UNIT · Python

indices

lucidrains/vector-quantize-pytorch · vector_quantize_pytorch/binary_mapper.py:157

        indices = (self.power_two * sampled_bits).sum(dim = -1)

        one_hot = F.one_hot(indices, self.num_codes).float()

        # maybe calculate aux loss

        aux_kl_loss = self.zero

        if calc_aux_loss:
            aux_kl_loss = self.calc_aux_loss(orig_logits, reduce_aux_kl_loss = reduce_aux_kl_loss)

        # maybe straight through

        if straight_through:
            # get the soft G for the gradients and do a straight through

            soft_G = (
                einsum(F.logsigmoid(logits), self.codes.float(), '... bits, codes bits -> ... codes') +

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