use crate::error::{QuantError, QuantResult};
use crate::traits::QuantKernel;
use crate::types::QuantTensor;
const Q5_0_BLOCK_SIZE: usize = 32;
const Q5_0_BLOCK_BYTES: usize = 22;
pub struct Q5_0Ref;
impl QuantKernel for Q5_0Ref {
fn dequant_block(&self, block: &[u8], output: &mut [f32]) -> QuantResult<()> {
if block.len() < Q5_0_BLOCK_BYTES {
return Err(QuantError::BufferTooSmall {
needed: Q5_0_BLOCK_BYTES,
available: block.len(),
});
}
if output.len() < Q5_0_BLOCK_SIZE {
return Err(QuantError::BufferTooSmall {
needed: Q5_0_BLOCK_SIZE,
available: output.len(),
});
}
let d = f16_to_f32(u16::from_le_bytes([block[0], block[1]]));
let qh = u32::from_le_bytes([block[2], block[3], block[4], block[5]]);
let qs = &block[6..22];
for i in 0..16 {
let lo_nibble = qs[i] & 0x0F;
let hi_nibble = (qs[i] >> 4) & 0x0F;
let hi_bit_0 = ((qh >> i) & 1) as u8;
let hi_bit_1 = ((qh >> (i + 16)) & 1) as u8;
let q0 = (lo_nibble | (hi_bit_0 << 4)) as i32 - 16;
let q1 = (hi_nibble | (hi_bit_1 << 4)) as i32 - 16;
output[i] = d * q0 as f32;
output[i + 16] = d * q1 as f32;
}
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_0_BLOCK_SIZE);
let row_bytes = blocks_per_row * Q5_0_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_0_BLOCK_BYTES;
let data = &quant_matrix.data;
let d = f16_to_f32(u16::from_le_bytes([data[bo], data[bo + 1]]));
let qh =
u32::from_le_bytes([data[bo + 2], data[bo + 3], data[bo + 4], data[bo + 5]]);
let qs = &data[bo + 6..bo + 22];
let inp = &input[blk * Q5_0_BLOCK_SIZE..];
for i in 0..16 {
let lo_nibble = qs[i] & 0x0F;
let hi_nibble = qs[i] >> 4;
let hi_bit_0 = ((qh >> i) & 1) as u8;
let hi_bit_1 = ((qh >> (i + 16)) & 1) as u8;
let q0 = (lo_nibble | (hi_bit_0 << 4)) as i32 - 16;
let q1 = (hi_nibble | (hi_bit_1 << 4)) as i32 - 16;
sum += d * q0 as f32 * inp[i];
sum += d * q1 as f32 * inp[i + 16];
}
}
*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_0_BLOCK_SIZE
}
fn block_bytes(&self) -> usize {
Q5_0_BLOCK_BYTES
}
fn name(&self) -> &'static str {
"Q5_0"
}
}
fn f16_to_f32(bits: u16) -> f32 {
half::f16::from_bits(bits).to_f32()
}
#[cfg(test)]
mod tests {
use super::*;
fn make_q5_0_block(d: f32, qh: u32, qs: &[u8; 16]) -> Vec<u8> {
let mut block = Vec::with_capacity(Q5_0_BLOCK_BYTES);
block.extend_from_slice(&half::f16::from_f32(d).to_bits().to_le_bytes());
block.extend_from_slice(&qh.to_le_bytes());
block.extend_from_slice(qs);
block
}
#[test]
fn test_dequant_zeros() {
let block = make_q5_0_block(0.0, 0, &[0; 16]);
let kernel = Q5_0Ref;
let mut output = vec![0.0f32; 32];
kernel.dequant_block(&block, &mut output).unwrap();
for &v in &output {
assert!((v).abs() < 1e-5, "expected 0, got {v}");
}
}
#[test]
fn test_dequant_center() {
let block = make_q5_0_block(1.0, 0xFFFFFFFF, &[0; 16]);
let kernel = Q5_0Ref;
let mut output = vec![99.0f32; 32];
kernel.dequant_block(&block, &mut output).unwrap();
for (i, &v) in output.iter().enumerate() {
assert!((v).abs() < 0.01, "weight[{i}] = {v}, expected 0.0");
}
}
#[test]
fn test_dequant_max_positive() {
let block = make_q5_0_block(1.0, 0xFFFFFFFF, &[0xFF; 16]);
let kernel = Q5_0Ref;
let mut output = vec![0.0f32; 32];
kernel.dequant_block(&block, &mut output).unwrap();
for (i, &v) in output.iter().enumerate() {
assert!((v - 15.0).abs() < 0.01, "weight[{i}] = {v}, expected 15.0");
}
}
#[test]
fn test_dequant_max_negative() {
let block = make_q5_0_block(2.0, 0, &[0; 16]);
let kernel = Q5_0Ref;
let mut output = vec![0.0f32; 32];
kernel.dequant_block(&block, &mut output).unwrap();
for (i, &v) in output.iter().enumerate() {
assert!(
(v - (-32.0)).abs() < 0.01,
"weight[{i}] = {v}, expected -32.0"
);
}
}
#[test]
fn test_gemv_q5_0() {
let qh: u32 = 0xA5A5A5A5; let mut qs = [0u8; 16];
for (i, q) in qs.iter_mut().enumerate() {
*q = ((i * 11 + 5) & 0xFF) as u8;
}
let block = make_q5_0_block(0.5, qh, &qs);
let kernel = Q5_0Ref;
let mut dequant = vec![0.0f32; 32];
kernel.dequant_block(&block, &mut dequant).unwrap();
let input: Vec<f32> = (0..32).map(|i| (i as f32 * 0.1) - 1.6).collect();
let expected: f32 = dequant.iter().zip(input.iter()).map(|(w, x)| w * x).sum();
let tensor = QuantTensor::new(block, vec![1, 32], oxillama_gguf::GgufTensorType::Q5_0);
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
);
}
}