use crate::filter_weights::FilterBounds;
use crate::mlaf::mlaf;
use crate::neon::utils::prefer_vfmaq_f32;
use std::arch::aarch64::*;
pub(crate) fn convolve_column_u16(
_: usize,
bounds: &FilterBounds,
src: &[u16],
dst: &mut [u16],
src_stride: usize,
weight: &[f32],
bit_depth: u32,
) {
unsafe {
let max_colors = (1u32 << bit_depth) - 1;
let mut cx = 0usize;
let bounds_size = bounds.size;
let zeros = vdupq_n_f32(0.);
let v_max_colors = vdupq_n_u16(max_colors as u16);
let v_px = cx;
let iter16 = dst.chunks_exact_mut(16);
for (x, dst) in iter16.enumerate() {
let mut store0 = zeros;
let mut store1 = zeros;
let mut store2 = zeros;
let mut store3 = zeros;
let v_dx = v_px + x * 16;
for (j, &k_weight) in weight.iter().take(bounds_size).enumerate() {
let py = bounds.start + j;
let src_ptr = src.get_unchecked((src_stride * py + v_dx)..);
let v_weight = vdupq_n_f32(k_weight);
let item_row0 = vld1q_u16(src_ptr.as_ptr());
let item_row1 = vld1q_u16(src_ptr.as_ptr().add(8));
let lo0 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(item_row0)));
let hi0 = vcvtq_f32_u32(vmovl_high_u16(item_row0));
let lo1 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(item_row1)));
let hi1 = vcvtq_f32_u32(vmovl_high_u16(item_row1));
store0 = prefer_vfmaq_f32(store0, lo0, v_weight);
store1 = prefer_vfmaq_f32(store1, hi0, v_weight);
store2 = prefer_vfmaq_f32(store2, lo1, v_weight);
store3 = prefer_vfmaq_f32(store3, hi1, v_weight);
}
let u_store0 = vcvtaq_u32_f32(store0);
let u_store1 = vcvtaq_u32_f32(store1);
let u_store2 = vcvtaq_u32_f32(store2);
let u_store3 = vcvtaq_u32_f32(store3);
let item0 = vminq_u16(
vcombine_u16(vqmovn_u32(u_store0), vqmovn_u32(u_store1)),
v_max_colors,
);
vst1q_u16(dst.as_mut_ptr(), item0);
let item1 = vminq_u16(
vcombine_u16(vqmovn_u32(u_store2), vqmovn_u32(u_store3)),
v_max_colors,
);
vst1q_u16(dst.as_mut_ptr().add(8), item1);
cx += 16;
}
let tail16 = dst.chunks_exact_mut(16).into_remainder();
let iter8 = tail16.chunks_exact_mut(8);
let v_px = cx;
for (x, dst) in iter8.enumerate() {
let mut store0 = zeros;
let mut store1 = zeros;
let v_dx = v_px + x * 8;
for (j, &k_weight) in weight.iter().take(bounds_size).enumerate() {
let py = bounds.start + j;
let src_ptr = src.get_unchecked((src_stride * py + v_dx)..);
let v_weight = vdupq_n_f32(k_weight);
let item_row = vld1q_u16(src_ptr.as_ptr());
let lo = vcvtq_f32_u32(vmovl_u16(vget_low_u16(item_row)));
let hi = vcvtq_f32_u32(vmovl_high_u16(item_row));
store0 = prefer_vfmaq_f32(store0, lo, v_weight);
store1 = prefer_vfmaq_f32(store1, hi, v_weight);
}
let u_store0 = vcvtaq_u32_f32(store0);
let u_store1 = vcvtaq_u32_f32(store1);
let item = vminq_u16(
vcombine_u16(vqmovn_u32(u_store0), vqmovn_u32(u_store1)),
v_max_colors,
);
vst1q_u16(dst.as_mut_ptr(), item);
cx += 8;
}
let tail8 = tail16.chunks_exact_mut(8).into_remainder();
let iter4 = tail8.chunks_exact_mut(4);
let v_cx = cx;
for (x, dst) in iter4.enumerate() {
let mut store0 = zeros;
let v_dx = v_cx + x * 4;
for (j, &k_weight) in weight.iter().take(bounds_size).enumerate() {
let py = bounds.start + j;
let src_ptr = src.get_unchecked((src_stride * py + v_dx)..);
let v_weight = vdupq_n_f32(k_weight);
let item_row = vld1_u16(src_ptr.as_ptr());
let lo = vcvtq_f32_u32(vmovl_u16(item_row));
store0 = prefer_vfmaq_f32(store0, lo, v_weight);
}
let u_store0 = vcvtaq_u32_f32(store0);
vst1_u16(
dst.as_mut_ptr(),
vmin_u16(vqmovn_u32(u_store0), vget_low_u16(v_max_colors)),
);
cx += 4;
}
let tail4 = tail8.chunks_exact_mut(4).into_remainder();
let a_px = cx;
for (x, dst) in tail4.iter_mut().enumerate() {
let mut store0 = 0.;
for (j, &k_weight) in weight.iter().take(bounds_size).enumerate() {
let py = bounds.start + j;
let offset = src_stride * py + a_px + x;
let src_ptr = *src.get_unchecked(offset);
store0 = mlaf(store0, src_ptr as f32, k_weight);
}
*dst = store0.round().max(0.).min(max_colors as f32) as u16;
}
}
}