Q6K quantization (#495)

* Print the detected arch options.

* Add the q6k quantization.

* Add a currently broken test.

* Bugfix.

* Bugfix.

* Another bugfix.

* Another bugfix + get the test to work.

candle-core/src/quantized/k_quants.rs

@@ -457,6 +457,143 @@ impl GgmlType for BlockQ5K {
     }
 }
 
+fn nearest_int(v: f32) -> i32 {
+    v.round() as i32
+}
+
+unsafe fn make_qx_quants(n: usize, nmax: i32, x: *const f32, ls: *mut i8, rmse_type: i32) -> f32 {
+    let mut max = 0f32;
+    let mut amax = 0f32;
+    for i in 0..n {
+        let x = *x.add(i);
+        let ax = x.abs();
+        if ax > amax {
+            amax = ax;
+            max = x;
+        }
+    }
+    if amax == 0. {
+        // all zero
+        for i in 0..n {
+            *ls.add(i) = 0;
+        }
+        return 0.;
+    }
+    let mut iscale = -(nmax as f32) / max;
+    if rmse_type == 0 {
+        for i in 0..n {
+            let x = *x.add(i);
+            let l = nearest_int(iscale * x);
+            *ls.add(i) = (nmax + l.clamp(-nmax, nmax - 1)) as i8;
+        }
+        return 1.0 / iscale;
+    }
+    let weight_type = rmse_type % 2;
+    let mut sumlx = 0f32;
+    let mut suml2 = 0f32;
+    for i in 0..n {
+        let x = *x.add(i);
+        let l = nearest_int(iscale * x);
+        let l = l.clamp(-nmax, nmax - 1);
+        *ls.add(i) = (l + nmax) as i8;
+        let w = if weight_type == 1 { x * x } else { 1.0 };
+        let l = l as f32;
+        sumlx += w * x * l;
+        suml2 += w * l * l;
+    }
+    let mut scale = sumlx / suml2;
+    let mut best = scale * sumlx;
+    for _itry in 0..3 {
+        let iscale = 1.0 / scale;
+        let mut slx = 0f32;
+        let mut sl2 = 0f32;
+        let mut changed = false;
+        for i in 0..n {
+            let x = *x.add(i);
+            let l = nearest_int(iscale * x);
+            let l = l.clamp(-nmax, nmax - 1);
+            if l + nmax != *ls.add(i) as i32 {
+                changed = true;
+            }
+            let w = if weight_type == 1 { x * x } else { 1f32 };
+            let l = l as f32;
+            slx += w * x * l;
+            sl2 += w * l * l;
+        }
+        if !changed || sl2 == 0.0 || slx * slx <= best * sl2 {
+            break;
+        }
+        for i in 0..n {
+            let x = *x.add(i);
+            let l = nearest_int(iscale * x);
+            *ls.add(i) = (nmax + l.clamp(-nmax, nmax - 1)) as i8;
+        }
+        sumlx = slx;
+        suml2 = sl2;
+        scale = sumlx / suml2;
+        best = scale * sumlx;
+    }
+    for _itry in 0..5 {
+        let mut n_changed = 0;
+        for i in 0..n {
+            let x = *x.add(i);
+            let w = if weight_type == 1 { x * x } else { 1. };
+            let l = *ls.add(i) as i32 - nmax;
+            let mut slx = sumlx - w * x * l as f32;
+            if slx > 0. {
+                let mut sl2 = suml2 - w * l as f32 * l as f32;
+                let new_l = nearest_int(x * sl2 / slx);
+                let new_l = new_l.clamp(-nmax, nmax - 1);
+                if new_l != l {
+                    slx += w * x * new_l as f32;
+                    sl2 += w * new_l as f32 * new_l as f32;
+                    if sl2 > 0. && slx * slx * suml2 > sumlx * sumlx * sl2 {
+                        *ls.add(i) = (nmax + new_l) as i8;
+                        sumlx = slx;
+                        suml2 = sl2;
+                        scale = sumlx / suml2;
+                        best = scale * sumlx;
+                        n_changed += 1;
+                    }
+                }
+            }
+        }
+        if n_changed == 0 {
+            break;
+        }
+    }
+    if rmse_type < 3 {
+        return scale;
+    }
+    for is in -4..4 {
+        if is == 0 {
+            continue;
+        }
+        iscale = -(nmax as f32 + 0.1f32 * is as f32) / max;
+        let mut sumlx = 0.;
+        let mut suml2 = 0.;
+        for i in 0..n {
+            let x = *x.add(i);
+            let l = nearest_int(iscale * x);
+            let l = i32::max(-nmax, i32::min(nmax - 1, l));
+            let w = if weight_type == 1 { x * x } else { 1. };
+            let l = l as f32;
+            sumlx += w * x * l;
+            suml2 += w * l * l;
+        }
+        if suml2 > 0. && sumlx * sumlx > best * suml2 {
+            for i in 0..n {
+                let x = *x.add(i);
+                let l = nearest_int(iscale * x);
+                *ls.add(i) = (nmax + l.clamp(-nmax, nmax - 1)) as i8;
+            }
+            scale = sumlx / suml2;
+            best = scale * sumlx;
+        }
+    }
+    scale
+}
+
 impl GgmlType for BlockQ6K {
     const DTYPE: GgmlDType = GgmlDType::Q6K;
     const BLCK_SIZE: usize = QK_K;
@@ -524,8 +661,76 @@ impl GgmlType for BlockQ6K {
         Ok(sums.iter().sum())
     }
 
-    fn from_float(_xs: &[f32], _ys: &mut [Self]) -> Result<()> {
+    fn from_float(xs: &[f32], ys: &mut [Self]) -> Result<()> {
-        todo!()
+        if xs.len() != ys.len() * Self::BLCK_SIZE {
+            crate::bail!(
+                "quantize_row_q6k: size mismatch {} {} {}",
+                xs.len(),
+                ys.len(),
+                Self::BLCK_SIZE
+            )
+        }
+        let mut l = [0i8; QK_K];
+        let mut scales = [0f32; QK_K / 16];
+        let mut x = xs.as_ptr();
+        let l = l.as_mut_ptr();
+        unsafe {
+            for y in ys.iter_mut() {
+                let mut max_scale = 0f32;
+                let mut max_abs_scale = 0f32;
+                for (ib, scale_) in scales.iter_mut().enumerate() {
+                    let scale = make_qx_quants(16, 32, x.add(16 * ib), l.add(16 * ib), 1);
+                    *scale_ = scale;
+                    let abs_scale = scale.abs();
+                    if abs_scale > max_abs_scale {
+                        max_abs_scale = abs_scale;
+                        max_scale = scale
+                    }
+                }
+
+                let iscale = -128f32 / max_scale;
+                y.d = f16::from_f32(1.0 / iscale);
+
+                for (y_scale, scale) in y.scales.iter_mut().zip(scales.iter()) {
+                    *y_scale = nearest_int(iscale * scale).min(127) as i8
+                }
+
+                for (j, &y_scale) in y.scales.iter().enumerate() {
+                    let d = y.d.to_f32() * y_scale as f32;
+                    if d == 0. {
+                        continue;
+                    }
+                    for ii in 0..16 {
+                        let ll = nearest_int(*x.add(16 * j + ii) / d).clamp(-32, 31);
+                        *l.add(16 * j + ii) = (ll + 32) as i8
+                    }
+                }
+
+                let mut ql = y.ql.as_mut_ptr();
+                let mut qh = y.qh.as_mut_ptr();
+
+                for j in (0..QK_K).step_by(128) {
+                    for l_idx in 0..32 {
+                        let q1 = *l.add(j + l_idx) & 0xF;
+                        let q2 = *l.add(j + l_idx + 32) & 0xF;
+                        let q3 = *l.add(j + l_idx + 64) & 0xF;
+                        let q4 = *l.add(j + l_idx + 96) & 0xF;
+                        *ql.add(l_idx) = (q1 | (q3 << 4)) as u8;
+                        *ql.add(l_idx + 32) = (q2 | (q4 << 4)) as u8;
+                        *qh.add(l_idx) = ((*l.add(j + l_idx) >> 4)
+                            | ((*l.add(j + l_idx + 32) >> 4) << 2)
+                            | ((*l.add(j + l_idx + 64) >> 4) << 4)
+                            | ((*l.add(j + l_idx + 96) >> 4) << 6))
+                            as u8;
+                    }
+                    ql = ql.add(64);
+                    qh = qh.add(32);
+                }
+
+                x = x.add(QK_K)
+            }
+        }
+        Ok(())
     }
 
     // https://github.com/ggerganov/llama.cpp/blob/8183159cf3def112f6d1fe94815fce70e1bffa12/k_quants.c#L1067

candle-core/src/utils.rs

@@ -22,3 +22,19 @@ pub fn has_mkl() -> bool {
 pub fn cuda_is_available() -> bool {
     cfg!(feature = "cuda")
 }
+
+pub fn with_avx() -> bool {
+    cfg!(target_feature = "avx")
+}
+
+pub fn with_neon() -> bool {
+    cfg!(target_feature = "neon")
+}
+
+pub fn with_simd128() -> bool {
+    cfg!(target_feature = "simd128")
+}
+
+pub fn with_f16c() -> bool {
+    cfg!(target_feature = "f16c")
+}

candle-core/tests/quantized_tests.rs

@@ -145,3 +145,29 @@ fn quantize_q8k() -> Result<()> {
     );
     Ok(())
 }
+
+#[test]
+fn quantize_q6k() -> Result<()> {
+    use k_quants::BlockQ6K;
+
+    let src = (0..256 * 4)
+        .map(|v| (v as f32 - 512.) / 1024.)
+        .collect::<Vec<_>>();
+    let mut dst = vec![0f32; 256 * 4];
+    let mut quant = vec![BlockQ6K::zeros(); 4];
+    BlockQ6K::from_float(&src, &mut quant)?;
+    BlockQ6K::to_float(&quant, dst.as_mut_slice())?;
+    assert_eq!(
+        [src[0], src[128], src[256], src[512], src[800], src[1023]],
+        [-0.5, -0.375, -0.25, 0.0, 0.28125, 0.49902344]
+    );
+    let dst = dst
+        .iter()
+        .map(|x| (1000. * x).round() / 1000.)
+        .collect::<Vec<_>>();
+    assert_eq!(
+        [dst[0], dst[128], dst[256], dst[512], dst[800], dst[1023]],
+        [-0.497, -0.372, -0.25, -0.0, 0.284, 0.5]
+    );
+    Ok(())
+}

candle-examples/examples/quantized/main.rs

@@ -348,6 +348,14 @@ fn main() -> anyhow::Result<()> {
         None
     };
 
+    println!(
+        "avx: {}, neon: {}, simd128: {}, f16c: {}",
+        candle::utils::with_avx(),
+        candle::utils::with_neon(),
+        candle::utils::with_simd128(),
+        candle::utils::with_f16c()
+    );
+
     let mut file = std::fs::File::open(&args.model()?)?;
     let start = std::time::Instant::now();
     let model = Content::read(&mut file)?;