blob: 4441225ca188fc26bddd4e78e42adf9abc404668 [file] [log] [blame] [edit]
// Copyright 2022 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
$assert CHANNEL_TILE % 8 == 0
$assert CHANNEL_TILE >= 8
$assert PIXEL_TILE == 1
$ABC = "456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
#include <assert.h>
#include <arm_neon.h>
#include <xnnpack/common.h>
#include <xnnpack/ibilinear.h>
void xnn_f16_ibilinear_ukernel__neonfp16arith_c${CHANNEL_TILE}${"" if PIXEL_TILE == 1 else "x%d" % PIXEL_TILE}(
size_t output_pixels,
size_t channels,
const void**restrict input,
size_t input_offset,
const void*restrict weights,
void*restrict output,
size_t output_increment) XNN_OOB_READS
{
assert(output_pixels != 0);
assert(channels != 0);
assert(channels % sizeof(__fp16) == 0);
__fp16* o = (__fp16*) output;
do {
const __fp16* i0 = (const __fp16*) ((uintptr_t) input[0] + input_offset);
const __fp16* i1 = (const __fp16*) ((uintptr_t) input[1] + input_offset);
const __fp16* i2 = (const __fp16*) ((uintptr_t) input[2] + input_offset);
const __fp16* i3 = (const __fp16*) ((uintptr_t) input[3] + input_offset);
input += 4;
const float16x8_t valphah = vld1q_dup_f16(weights); weights = (const __fp16*) weights + 1;
const float16x8_t valphav = vld1q_dup_f16(weights); weights = (const __fp16*) weights + 1;
size_t c = channels;
$if CHANNEL_TILE > 8:
for (; c >= ${CHANNEL_TILE} * sizeof(__fp16); c -= ${CHANNEL_TILE} * sizeof(__fp16)) {
$for C in range(0, CHANNEL_TILE, 8):
const float16x8_t vtl${ABC[C:C+8]} = vld1q_f16(i0); i0 += 8;
const float16x8_t vtr${ABC[C:C+8]} = vld1q_f16(i1); i1 += 8;
const float16x8_t vbl${ABC[C:C+8]} = vld1q_f16(i2); i2 += 8;
const float16x8_t vbr${ABC[C:C+8]} = vld1q_f16(i3); i3 += 8;
$for C in range(0, CHANNEL_TILE, 8):
const float16x8_t vtd${ABC[C:C+8]} = vsubq_f16(vtr${ABC[C:C+8]}, vtl${ABC[C:C+8]});
const float16x8_t vbd${ABC[C:C+8]} = vsubq_f16(vbr${ABC[C:C+8]}, vbl${ABC[C:C+8]});
$for C in range(0, CHANNEL_TILE, 8):
const float16x8_t vt${ABC[C:C+8]} = vfmaq_f16(vtl${ABC[C:C+8]}, vtd${ABC[C:C+8]}, valphah);
const float16x8_t vb${ABC[C:C+8]} = vfmaq_f16(vbl${ABC[C:C+8]}, vbd${ABC[C:C+8]}, valphah);
$for C in range(0, CHANNEL_TILE, 8):
const float16x8_t vd${ABC[C:C+8]} = vsubq_f16(vb${ABC[C:C+8]}, vt${ABC[C:C+8]});
$for C in range(0, CHANNEL_TILE, 8):
const float16x8_t vo${ABC[C:C+8]} = vfmaq_f16(vt${ABC[C:C+8]}, vd${ABC[C:C+8]}, valphav);
$for C in range(0, CHANNEL_TILE, 8):
vst1q_f16(o, vo${ABC[C:C+8]}); o += 8;
}
for (; c >= 8 * sizeof(__fp16); c -= 8 * sizeof(__fp16)) {
const float16x8_t vtl = vld1q_f16(i0); i0 += 8;
const float16x8_t vtr = vld1q_f16(i1); i1 += 8;
const float16x8_t vbl = vld1q_f16(i2); i2 += 8;
const float16x8_t vbr = vld1q_f16(i3); i3 += 8;
const float16x8_t vtd = vsubq_f16(vtr, vtl);
const float16x8_t vbd = vsubq_f16(vbr, vbl);
const float16x8_t vt = vfmaq_f16(vtl, vtd, valphah);
const float16x8_t vb = vfmaq_f16(vbl, vbd, valphah);
const float16x8_t vd = vsubq_f16(vb, vt);
const float16x8_t vo = vfmaq_f16(vt, vd, valphav);
vst1q_f16(o, vo); o += 8;
}
if XNN_UNLIKELY(c != 0) {
const float16x8_t vtl = vld1q_f16(i0);
const float16x8_t vtr = vld1q_f16(i1);
const float16x8_t vbl = vld1q_f16(i2);
const float16x8_t vbr = vld1q_f16(i3);
const float16x8_t vtd = vsubq_f16(vtr, vtl);
const float16x8_t vbd = vsubq_f16(vbr, vbl);
const float16x8_t vt = vfmaq_f16(vtl, vtd, valphah);
const float16x8_t vb = vfmaq_f16(vbl, vbd, valphah);
const float16x8_t vd = vsubq_f16(vb, vt);
float16x8_t vo = vfmaq_f16(vt, vd, valphav);
float16x4_t vo_lo = vget_low_f16(vo);
if (c & (4 * sizeof(__fp16))) {
vst1_f16(o, vo_lo); o += 4;
vo_lo = vget_high_f16(vo);
}
if (c & (2 * sizeof(__fp16))) {
vst1_lane_u32((void*) o, vreinterpret_u32_f16(vo_lo), 0); o += 2;
vo_lo = vext_f16(vo_lo, vo_lo, 2);
}
if (c & (1 * sizeof(__fp16))) {
vst1_lane_f16(o, vo_lo, 0); o += 1;
}
}
o = (__fp16*) ((uintptr_t) o + output_increment);
} while (--output_pixels != 0);
}