use crate::error::{QuantError, QuantResult};
use crate::traits::QuantKernel;
use crate::types::QuantTensor;
const Q2_K_BLOCK_SIZE: usize = 256;
const Q2_K_BLOCK_BYTES: usize = 84;
pub struct Q2KRef;
impl QuantKernel for Q2KRef {
fn dequant_block(&self, block: &[u8], output: &mut [f32]) -> QuantResult<()> {
if block.len() < Q2_K_BLOCK_BYTES {
return Err(QuantError::BufferTooSmall {
needed: Q2_K_BLOCK_BYTES,
available: block.len(),
});
}
if output.len() < Q2_K_BLOCK_SIZE {
return Err(QuantError::BufferTooSmall {
needed: Q2_K_BLOCK_SIZE,
available: output.len(),
});
}
let scales = &block[0..16];
let qs = &block[16..80];
let d = f16_to_f32(u16::from_le_bytes([block[80], block[81]]));
let dmin = f16_to_f32(u16::from_le_bytes([block[82], block[83]]));
let mut is = 0usize; let mut qs_off = 0usize;
let mut out_off = 0usize;
for _n in 0..2 {
for shift in (0..8).step_by(2) {
let sc_byte = scales[is];
let dl = d * (sc_byte & 0x0F) as f32;
let ml = dmin * (sc_byte >> 4) as f32;
is += 1;
for l in 0..16 {
let q = (qs[qs_off + l] >> shift) & 3;
output[out_off + l] = dl * q as f32 - ml;
}
out_off += 16;
let sc_byte = scales[is];
let dl = d * (sc_byte & 0x0F) as f32;
let ml = dmin * (sc_byte >> 4) as f32;
is += 1;
for l in 0..16 {
let q = (qs[qs_off + 16 + l] >> shift) & 3;
output[out_off + l] = dl * q as f32 - ml;
}
out_off += 16;
}
qs_off += 32;
}
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(Q2_K_BLOCK_SIZE);
let row_bytes = blocks_per_row * Q2_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 * Q2_K_BLOCK_BYTES;
let data = &quant_matrix.data;
let scales = &data[bo..bo + 16];
let qs = &data[bo + 16..bo + 80];
let d = f16_to_f32(u16::from_le_bytes([data[bo + 80], data[bo + 81]]));
let dmin = f16_to_f32(u16::from_le_bytes([data[bo + 82], data[bo + 83]]));
let inp = &input[blk * Q2_K_BLOCK_SIZE..];
let cols_in_block = (n_cols - blk * Q2_K_BLOCK_SIZE).min(Q2_K_BLOCK_SIZE);
let mut is = 0usize;
let mut qs_off = 0usize;
let mut in_off = 0usize;
for _n in 0..2 {
for shift in (0..8).step_by(2) {
let sc_byte = scales[is];
let dl = d * (sc_byte & 0x0F) as f32;
let ml = dmin * (sc_byte >> 4) as f32;
is += 1;
for l in 0..16 {
if in_off + l < cols_in_block {
let q = (qs[qs_off + l] >> shift) & 3;
sum += (dl * q as f32 - ml) * inp[in_off + l];
}
}
in_off += 16;
let sc_byte = scales[is];
let dl = d * (sc_byte & 0x0F) as f32;
let ml = dmin * (sc_byte >> 4) as f32;
is += 1;
for l in 0..16 {
if in_off + l < cols_in_block {
let q = (qs[qs_off + 16 + l] >> shift) & 3;
sum += (dl * q as f32 - ml) * inp[in_off + l];
}
}
in_off += 16;
}
qs_off += 32;
}
}
*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 {
Q2_K_BLOCK_SIZE
}
fn block_bytes(&self) -> usize {
Q2_K_BLOCK_BYTES
}
fn name(&self) -> &'static str {
"Q2_K"
}
}
fn f16_to_f32(bits: u16) -> f32 {
half::f16::from_bits(bits).to_f32()
}
#[cfg(test)]
mod tests {
use super::*;
fn make_q2_k_block(d: f32, dmin: f32, scales: &[u8; 16], qs: &[u8; 64]) -> Vec<u8> {
let mut block = Vec::with_capacity(Q2_K_BLOCK_BYTES);
block.extend_from_slice(scales);
block.extend_from_slice(qs);
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
}
#[test]
fn test_dequant_zeros() {
let block = make_q2_k_block(0.0, 0.0, &[0; 16], &[0; 64]);
let kernel = Q2KRef;
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 scales = [0x01u8; 16]; let qs = [0xFFu8; 64];
let block = make_q2_k_block(1.0, 0.0, &scales, &qs);
let kernel = Q2KRef;
let mut output = vec![0.0f32; 256];
kernel.dequant_block(&block, &mut output).unwrap();
for (i, &v) in output.iter().enumerate() {
assert!((v - 3.0).abs() < 0.01, "weight[{i}] = {v}, expected 3.0");
}
}
#[test]
fn test_dequant_with_min() {
let scales = [0x11u8; 16]; let qs = [0x00u8; 64];
let block = make_q2_k_block(2.0, 1.0, &scales, &qs);
let kernel = Q2KRef;
let mut output = vec![0.0f32; 256];
kernel.dequant_block(&block, &mut output).unwrap();
for (i, &v) in output.iter().enumerate() {
assert!(
(v - (-1.0)).abs() < 0.01,
"weight[{i}] = {v}, expected -1.0"
);
}
}
#[test]
fn test_gemv_q2_k() {
let mut scales = [0u8; 16];
let mut qs = [0u8; 64];
for (i, s) in scales.iter_mut().enumerate() {
*s = 0x21 + i as u8; }
for (i, q) in qs.iter_mut().enumerate() {
*q = ((i * 3 + 7) & 0xFF) as u8;
}
let block = make_q2_k_block(0.5, 0.25, &scales, &qs);
let kernel = Q2KRef;
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::Q2K);
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
);
}
}