use crate::error::{QuantError, QuantResult};
use crate::traits::QuantKernel;
use crate::types::QuantTensor;
const Q5_K_BLOCK_SIZE: usize = 256;
const Q5_K_BLOCK_BYTES: usize = 176;
pub struct Q5KRef;
fn decode_scales_mins(scales_raw: &[u8]) -> ([u8; 8], [u8; 8]) {
let mut sc = [0u8; 8];
let mut mn = [0u8; 8];
for j in 0..4 {
sc[j] = scales_raw[j] & 0x3F;
mn[j] = scales_raw[j + 4] & 0x3F;
}
for j in 4..8 {
let lo_sc = scales_raw[j + 4] & 0x0F;
let hi_sc = (scales_raw[j - 4] >> 6) & 0x03;
sc[j] = lo_sc | (hi_sc << 4);
let lo_mn = (scales_raw[j + 4] >> 4) & 0x0F;
let hi_mn = (scales_raw[j] >> 6) & 0x03;
mn[j] = lo_mn | (hi_mn << 4);
}
(sc, mn)
}
impl QuantKernel for Q5KRef {
fn dequant_block(&self, block: &[u8], output: &mut [f32]) -> QuantResult<()> {
if block.len() < Q5_K_BLOCK_BYTES {
return Err(QuantError::BufferTooSmall {
needed: Q5_K_BLOCK_BYTES,
available: block.len(),
});
}
if output.len() < Q5_K_BLOCK_SIZE {
return Err(QuantError::BufferTooSmall {
needed: Q5_K_BLOCK_SIZE,
available: output.len(),
});
}
let d = f16_to_f32(u16::from_le_bytes([block[0], block[1]]));
let dmin = f16_to_f32(u16::from_le_bytes([block[2], block[3]]));
let scales_raw = &block[4..16];
let qh = &block[16..48]; let qs = &block[48..176];
let (sc, mn) = decode_scales_mins(scales_raw);
let mut is = 0usize;
let mut qs_offset = 0usize;
let mut out_offset = 0usize;
for group in 0..4 {
let d1 = d * sc[is] as f32;
let m1 = dmin * mn[is] as f32;
let d2 = d * sc[is + 1] as f32;
let m2 = dmin * mn[is + 1] as f32;
for l in 0..32 {
let qh_bit = (qh[l] >> group) & 1;
let q = ((qs[qs_offset + l] & 0x0F) | (qh_bit << 4)) as f32;
output[out_offset + l] = d1 * q - m1;
}
for l in 0..32 {
let qh_bit = (qh[l] >> (group + 4)) & 1;
let q = (((qs[qs_offset + l] >> 4) & 0x0F) | (qh_bit << 4)) as f32;
output[out_offset + 32 + l] = d2 * q - m2;
}
is += 2;
qs_offset += 32;
out_offset += 64;
}
Ok(())
}
fn gemv(
&self,
quant_matrix: &QuantTensor,
input: &[f32],
output: &mut [f32],
) -> QuantResult<()> {
let n_rows = quant_matrix.shape[0];
let n_cols = if quant_matrix.shape.len() > 1 {
quant_matrix.shape[1]
} else {
quant_matrix.n_elements() / n_rows
};
if input.len() < n_cols {
return Err(QuantError::DimensionMismatch {
expected: n_cols,
got: input.len(),
});
}
if output.len() < n_rows {
return Err(QuantError::DimensionMismatch {
expected: n_rows,
got: output.len(),
});
}
let blocks_per_row = n_cols.div_ceil(Q5_K_BLOCK_SIZE);
let row_bytes = blocks_per_row * Q5_K_BLOCK_BYTES;
for (row, out) in output.iter_mut().enumerate().take(n_rows) {
let row_start = row * row_bytes;
let mut sum = 0.0f32;
for blk in 0..blocks_per_row {
let bo = row_start + blk * Q5_K_BLOCK_BYTES;
let data = &quant_matrix.data;
let d = f16_to_f32(u16::from_le_bytes([data[bo], data[bo + 1]]));
let dmin = f16_to_f32(u16::from_le_bytes([data[bo + 2], data[bo + 3]]));
let scales_raw = &data[bo + 4..bo + 16];
let qh = &data[bo + 16..bo + 48];
let qs = &data[bo + 48..bo + 176];
let (sc, mn) = decode_scales_mins(scales_raw);
let inp = &input[blk * Q5_K_BLOCK_SIZE..];
let cols_in_block = (n_cols - blk * Q5_K_BLOCK_SIZE).min(Q5_K_BLOCK_SIZE);
let mut is = 0usize;
let mut qs_offset = 0usize;
let mut in_off = 0usize;
for group in 0..4 {
let d1 = d * sc[is] as f32;
let m1 = dmin * mn[is] as f32;
let d2 = d * sc[is + 1] as f32;
let m2 = dmin * mn[is + 1] as f32;
for l in 0..32 {
let col = in_off + l;
if col >= cols_in_block {
break;
}
let qh_bit = (qh[l] >> group) & 1;
let q = ((qs[qs_offset + l] & 0x0F) | (qh_bit << 4)) as f32;
sum += (d1 * q - m1) * inp[col];
}
for l in 0..32 {
let col = in_off + 32 + l;
if col >= cols_in_block {
break;
}
let qh_bit = (qh[l] >> (group + 4)) & 1;
let q = (((qs[qs_offset + l] >> 4) & 0x0F) | (qh_bit << 4)) as f32;
sum += (d2 * q - m2) * inp[col];
}
is += 2;
qs_offset += 32;
in_off += 64;
}
}
*out = sum;
}
Ok(())
}
fn gemm(
&self,
quant_matrix: &QuantTensor,
input: &[f32],
output: &mut [f32],
m: usize,
n: usize,
k: usize,
) -> QuantResult<()> {
for row in 0..m {
let input_row = &input[row * k..(row + 1) * k];
let output_row = &mut output[row * n..(row + 1) * n];
self.gemv(quant_matrix, input_row, output_row)?;
}
Ok(())
}
fn block_size(&self) -> usize {
Q5_K_BLOCK_SIZE
}
fn block_bytes(&self) -> usize {
Q5_K_BLOCK_BYTES
}
fn name(&self) -> &'static str {
"Q5_K"
}
}
fn f16_to_f32(bits: u16) -> f32 {
half::f16::from_bits(bits).to_f32()
}
#[cfg(test)]
mod tests {
use super::*;
fn make_q5_k_block(
d: f32,
dmin: f32,
scales: &[u8; 12],
qh: &[u8; 32],
qs: &[u8; 128],
) -> Vec<u8> {
let mut block = Vec::with_capacity(Q5_K_BLOCK_BYTES);
block.extend_from_slice(&half::f16::from_f32(d).to_bits().to_le_bytes());
block.extend_from_slice(&half::f16::from_f32(dmin).to_bits().to_le_bytes());
block.extend_from_slice(scales);
block.extend_from_slice(qh);
block.extend_from_slice(qs);
block
}
#[test]
fn test_dequant_zero_scale() {
let block = make_q5_k_block(0.0, 0.0, &[0; 12], &[0; 32], &[0; 128]);
let kernel = Q5KRef;
let mut output = vec![0.0f32; 256];
kernel.dequant_block(&block, &mut output).unwrap();
for &v in &output {
assert!((v).abs() < 1e-5, "expected 0, got {v}");
}
}
#[test]
fn test_dequant_uniform() {
let mut scales = [0u8; 12];
scales[..4].fill(1); scales[8..12].fill(1);
let qh = [0x00u8; 32]; let qs = [0x88u8; 128];
let block = make_q5_k_block(1.0, 0.0, &scales, &qh, &qs);
let kernel = Q5KRef;
let mut output = vec![0.0f32; 256];
kernel.dequant_block(&block, &mut output).unwrap();
for (i, &v) in output.iter().enumerate() {
assert!((v - 8.0).abs() < 0.01, "weight[{i}] = {v}, expected 8.0");
}
}
#[test]
fn test_dequant_with_high_bit() {
let mut scales = [0u8; 12];
scales[..4].fill(1);
scales[8..12].fill(1);
let qh = [0xFFu8; 32]; let qs = [0x00u8; 128];
let block = make_q5_k_block(1.0, 0.0, &scales, &qh, &qs);
let kernel = Q5KRef;
let mut output = vec![0.0f32; 256];
kernel.dequant_block(&block, &mut output).unwrap();
for (i, &v) in output.iter().enumerate() {
assert!((v - 16.0).abs() < 0.01, "weight[{i}] = {v}, expected 16.0");
}
}
#[test]
fn test_gemv_q5_k() {
let mut scales = [0u8; 12];
for (i, s) in scales.iter_mut().enumerate() {
*s = ((i * 17 + 3) & 0xFF) as u8;
}
let mut qh = [0u8; 32];
for (i, h) in qh.iter_mut().enumerate() {
*h = ((i * 13 + 7) & 0xFF) as u8;
}
let mut qs = [0u8; 128];
for (i, q) in qs.iter_mut().enumerate() {
*q = ((i * 5 + 11) & 0xFF) as u8;
}
let block = make_q5_k_block(0.5, 0.25, &scales, &qh, &qs);
let kernel = Q5KRef;
let mut dequant = vec![0.0f32; 256];
kernel.dequant_block(&block, &mut dequant).unwrap();
let input: Vec<f32> = (0..256).map(|i| (i as f32 * 0.01) - 1.28).collect();
let expected: f32 = dequant.iter().zip(input.iter()).map(|(w, x)| w * x).sum();
let tensor = QuantTensor::new(block, vec![1, 256], oxillama_gguf::GgufTensorType::Q5K);
let mut output = vec![0.0f32; 1];
kernel.gemv(&tensor, &input, &mut output).unwrap();
assert!(
(output[0] - expected).abs() < 0.1,
"gemv={}, expected={}",
output[0],
expected
);
}
}