Skip to content

handle corner case for factors during quantization #9

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jun 12, 2025
Merged

handle corner case for factors during quantization #9

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 12 additions & 1 deletion rabitqlib/quantization/rabitq_impl.hpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -100,6 +100,11 @@ inline void one_bit_code_with_factor(
// dot product between centroid and xu_cb
T ip_cent_xucb = dot_product<T>(centroid, xu_cb.data(), dim);

// corner case
if (ip_resi_xucb == 0) {
ip_resi_xucb = std::numeric_limits<T>::infinity();
}

// We use unnormalized vector to get error factor. To be more specific,
// sqrt((1 - <o, o_bar>^2) / <o, o_bar>^2) / sqrt(dim - 1) = 3rd item in following
// expression
Expand Down Expand Up @@ -465,6 +470,11 @@ inline void ex_bits_code_with_factor(
T ip_resi_xucb = dot_product<T>(residual_arr.data(), xu_cb.data(), dim);
T ip_cent_xucb = dot_product<T>(centroid, xu_cb.data(), dim);

// corner case
if (ip_resi_xucb == 0) {
ip_resi_xucb = std::numeric_limits<T>::infinity();
}

T tmp_error =
l2_norm * kConstEpsilon *
std::sqrt(
Expand Down Expand Up @@ -556,7 +566,8 @@ static inline void rabitq_scalar_impl(

float norm_data = std::sqrt(l2norm_sqr(residual_arr.data(), dim));
float norm_quan = std::sqrt(l2norm_sqr(u_cb.data(), dim));
float cos_similarity = dot_product<T>(residual_arr.data(), u_cb.data(), dim) / (norm_data * norm_quan);
float cos_similarity =
dot_product<T>(residual_arr.data(), u_cb.data(), dim) / (norm_data * norm_quan);

if (scalar_quantizer_type == ScalarQuantizerType::RECONSTRUCTION) {
delta = norm_data / norm_quan * cos_similarity;
Expand Down