src/f16-dwconv2d-chw/3x3s2p1-neonfp16arith.c.in - platform/external/XNNPACK - Git at Google

 // Copyright 2020 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 ROW_TILE >= 1
 $assert ACCUMULATORS >= 1
 #include <assert.h>

 #include <arm_neon.h>

 #include <xnnpack/dwconv.h>
 #include <xnnpack/math.h>


 void xnn_f16_dwconv2d_chw_ukernel_3x3s2p1__neonfp16arith_${ROW_TILE}x4${"_acc%d" % ACCUMULATORS if ACCUMULATORS > 1 else ""}(
     size_t input_height,
     size_t input_width,
     const void* input,
     const void* weights,
     const void* zero,
     void* output,
     uint32_t padding_top,
     const union xnn_f16_chw_params params[restrict XNN_MIN_ELEMENTS(1)]) XNN_OOB_READS
 {
   assert(input_height != 0);
   assert(input_width != 0);
   assert(input_width % sizeof(__fp16) == 0);
   assert(padding_top >= 0);
   assert(padding_top <= 1);

   const uint16x4_t vmask_even = vld1_u16(params->neonfp16arith.mask_even);
   const uint16x4_t vmask_odd  = vld1_u16(params->neonfp16arith.mask_odd);
   const float16x4_t vmax = vld1_dup_f16(&params->neonfp16arith.max);
   const float16x4_t vmin = vld1_dup_f16(&params->neonfp16arith.min);

   const __fp16* w0 = (const __fp16*)weights;
   const float16x8_t vw01234567 = vld1q_f16(w0);
   const float16x4_t vw89 = vreinterpret_f16_u32(vld1_lane_u32((const void*)(w0 + 8), vmov_n_u32(0), 0));

   const size_t input_decrement = round_down_po2(input_width, 4 /* SIMD output width */ * 2 /* subsampling */ * sizeof(__fp16));
   $if ROW_TILE > 1:
     const size_t output_width = round_down_po2((input_width + (2 /* padding */ - 3 /* kernel size */ + 2 /* subsampling */) * sizeof(__fp16)) / 2, sizeof(__fp16));

   const __fp16* i0 = (const __fp16*) ((uintptr_t) input - ((-padding_top) & input_width));
   const __fp16* i1 = (const __fp16*) ((uintptr_t) i0 + input_width);
   if XNN_UNPREDICTABLE(padding_top != 0) {
     i0 = zero;
   }
   $for M in range(2, 1 + 2 * ROW_TILE):
     const __fp16* i${M} = (const __fp16*) ((uintptr_t) i${M-1} + input_width);

   __fp16* o0 = output;
   $for M in range(1, ROW_TILE):
     __fp16* o${M} = (__fp16*) ((uintptr_t) o${M-1} + output_width);

   size_t padded_input_height = input_height + padding_top + 1 /* padding bottom */;
   size_t output_height = (padded_input_height - 3 /* kernel size */ + 2 /* subsampling */) / 2;
   do {
     $for M in range(2, 1 + 2 * ROW_TILE):
       if XNN_UNPREDICTABLE(padded_input_height < ${2 + M}) {
         i${M} = zero;
         $if M % 2 == 1:
           o${(M - 1) // 2} = o${(M - 1) // 2 - 1};
       }

     $for M in range(1 + 2 * ROW_TILE):
       float16x4_t vi${M}x1357 = vmov_n_f16(0);

     size_t w = input_width;
     for (; w >= 8 * sizeof(__fp16); w -= 8 * sizeof(__fp16)) {
       $for M in range(ROW_TILE):
         float16x4_t vo${M}p0 = vdup_laneq_f16(vw01234567, 0);

       $for M in range(1 + 2 * ROW_TILE):
         const float16x4x2_t vi${M}x8ACE9BDF = vld2_f16(i${M}); i${M} += 8;

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 1:
           float16x4_t vo${M}p1 = vmul_laneq_f16(vi${2*M}x8ACE9BDF.val[0], vw01234567, 2);
         $else:
           vo${M}p0 = vfma_laneq_f16(vo${M}p0, vi${2*M}x8ACE9BDF.val[0], vw01234567, 2);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 2:
           float16x4_t vo${M}p2 = vmul_laneq_f16(vi${2*M+1}x8ACE9BDF.val[0], vw01234567, 5);
         $else:
           vo${M}p0 = vfma_laneq_f16(vo${M}p0, vi${2*M+1}x8ACE9BDF.val[0], vw01234567, 5);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 3:
           float16x4_t vo${M}p3 = vmul_lane_f16(vi${2*M+2}x8ACE9BDF.val[0], vw89, 0);
         $else:
           vo${M}p${4 % ACCUMULATORS} = vfma_lane_f16(vo${M}p${4 % ACCUMULATORS}, vi${2*M+2}x8ACE9BDF.val[0], vw89, 0);

       $for M in range(1 + 2 * ROW_TILE):
         const float16x4_t vi${M}x7BDF = vext_f16(vi${M}x1357, vi${M}x8ACE9BDF.val[1], 3);
         vi${M}x1357 = vi${M}x8ACE9BDF.val[1];

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 4:
           float16x4_t vo${M}p4 = vmul_laneq_f16(vi${2*M}x7BDF, vw01234567, 1);
         $else:
           vo${M}p${5 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${5 % ACCUMULATORS}, vi${2*M}x7BDF, vw01234567, 1);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 5:
           float16x4_t vo${M}p5 = vmul_laneq_f16(vi${2*M+1}x7BDF, vw01234567, 4);
         $else:
           vo${M}p${6 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${6 % ACCUMULATORS}, vi${2*M+1}x7BDF, vw01234567, 4);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 6:
           float16x4_t vo${M}p6 = vmul_laneq_f16(vi${2*M+2}x7BDF, vw01234567, 5);
         $else:
           vo${M}p${7 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${7 % ACCUMULATORS}, vi${2*M+2}x7BDF, vw01234567, 7);

       $for M in range(ROW_TILE):
         vo${M}p${8 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${8 % ACCUMULATORS}, vi${2*M}x8ACE9BDF.val[1], vw01234567, 3);

       $for M in range(ROW_TILE):
         vo${M}p${9 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${9 % ACCUMULATORS}, vi${2*M+1}x8ACE9BDF.val[1], vw01234567, 6);

       $for M in range(ROW_TILE):
         vo${M}p${10 % ACCUMULATORS} = vfma_lane_f16(vo${M}p${10 % ACCUMULATORS}, vi${2*M+2}x8ACE9BDF.val[1], vw89, 1);

       $if ACCUMULATORS > 1:
         $ACC_SLICE = 1
         $while ACC_SLICE < ACCUMULATORS:
           $for A in range(0, ACCUMULATORS, ACC_SLICE * 2):
             $if A + ACC_SLICE < ACCUMULATORS:
               $for M in range(ROW_TILE):
                 vo${M}p${A} = vadd_f16(vo${M}p${A}, vo${M}p${A + ACC_SLICE});
           $ACC_SLICE *= 2

       $for M in range(ROW_TILE):
         float16x4_t vo${M} = vmax_f16(vo${M}p0, vmin);

       $for M in range(ROW_TILE):
         vo${M} = vmin_f16(vo${M}, vmax);

       $for M in reversed(range(ROW_TILE)):
         vst1_f16(o${M}, vo${M}); o${M} += 4;
     }
     // Last block has 0-7 pixels to process.
     assert(w < 8 * sizeof(__fp16));
     if XNN_LIKELY(w != 0) {
       $for M in range(ROW_TILE):
         float16x4_t vo${M}p0 = vdup_laneq_f16(vw01234567, 0);

       $for M in range(1 + 2 * ROW_TILE):
         const float16x4x2_t vi${M}x8ACE9BDF = vld2_f16(i${M});

       $for M in range(1 + 2 * ROW_TILE):
         const float16x4_t vi${M}x8ACE = vreinterpret_f16_u16(vand_u16(vmask_even, vreinterpret_u16_f16(vi${M}x8ACE9BDF.val[0])));
         const float16x4_t vi${M}x9BDF = vreinterpret_f16_u16(vand_u16(vmask_odd,  vreinterpret_u16_f16(vi${M}x8ACE9BDF.val[1])));

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 1:
           float16x4_t vo${M}p1 = vmul_laneq_f16(vi${2*M}x8ACE, vw01234567, 2);
         $else:
           vo${M}p0 = vfma_laneq_f16(vo${M}p0, vi${2*M}x8ACE, vw01234567, 2);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 2:
           float16x4_t vo${M}p2 = vmul_laneq_f16(vi${2*M+1}x8ACE, vw01234567, 5);
         $else:
           vo${M}p0 = vfma_laneq_f16(vo${M}p0, vi${2*M+1}x8ACE, vw01234567, 5);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 3:
           float16x4_t vo${M}p3 = vmul_lane_f16(vi${2*M+2}x8ACE, vw89, 0);
         $else:
           vo${M}p${4 % ACCUMULATORS} = vfma_lane_f16(vo${M}p${4 % ACCUMULATORS}, vi${2*M+2}x8ACE, vw89, 0);

       $for M in range(1 + 2 * ROW_TILE):
         const float16x4_t vi${M}x7BDF = vext_f16(vi${M}x1357, vi${M}x9BDF, 3);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 4:
           float16x4_t vo${M}p4 = vmul_laneq_f16(vi${2*M}x7BDF, vw01234567, 1);
         $else:
           vo${M}p${5 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${5 % ACCUMULATORS}, vi${2*M}x7BDF, vw01234567, 1);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 5:
           float16x4_t vo${M}p5 = vmul_laneq_f16(vi${2*M+1}x7BDF, vw01234567, 4);
         $else:
           vo${M}p${6 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${6 % ACCUMULATORS}, vi${2*M+1}x7BDF, vw01234567, 4);

       $for M in range(ROW_TILE):
         $if ACCUMULATORS > 6:
           float16x4_t vo${M}p6 = vmul_laneq_f16(vi${2*M+2}x7BDF, vw01234567, 5);
         $else:
           vo${M}p${7 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${7 % ACCUMULATORS}, vi${2*M+2}x7BDF, vw01234567, 7);

       $for M in range(ROW_TILE):
         vo${M}p${8 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${8 % ACCUMULATORS}, vi${2*M}x9BDF, vw01234567, 3);

       $for M in range(ROW_TILE):
         vo${M}p${9 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${9 % ACCUMULATORS}, vi${2*M+1}x9BDF, vw01234567, 6);

       $for M in range(ROW_TILE):
         vo${M}p${10 % ACCUMULATORS} = vfma_lane_f16(vo${M}p${10 % ACCUMULATORS}, vi${2*M+2}x9BDF, vw89, 1);

       $if ACCUMULATORS > 1:
         $ACC_SLICE = 1
         $while ACC_SLICE < ACCUMULATORS:
           $for A in range(0, ACCUMULATORS, ACC_SLICE * 2):
             $if A + ACC_SLICE < ACCUMULATORS:
               $for M in range(ROW_TILE):
                 vo${M}p${A} = vadd_f16(vo${M}p${A}, vo${M}p${A + ACC_SLICE});
           $ACC_SLICE *= 2

       $for M in range(ROW_TILE):
         float16x4_t vo${M} = vmax_f16(vo${M}p0, vmin);

       $for M in range(ROW_TILE):
         vo${M} = vmin_f16(vo${M}, vmax);

       w += 1 * sizeof(__fp16);

       if XNN_LIKELY(w == 8 * sizeof(__fp16)) {
         $for M in reversed(range(ROW_TILE)):
           vst1_f16(o${M}, vo${M}); o${M} += 4;
       } else {
         if (w & (4 * sizeof(__fp16))) {
           $for M in reversed(range(ROW_TILE)):
             vst1_lane_u32((void*) o${M}, vreinterpret_u32_f16(vo${M}), 0); o${M} += 2;

           $for M in range(ROW_TILE):
             vo${M} = vext_f16(vo${M}, vo${M}, 2);
         }
         if (w & (2 * sizeof(__fp16))) {
           $for M in reversed(range(ROW_TILE)):
             vst1_lane_f16(o${M}, vo${M}, 0); o${M} += 1;
         }
       }

     }

     i0 = (const __fp16*) ((uintptr_t) i${2 * ROW_TILE} - input_decrement);
     $for M in range(1, 1 + 2 * ROW_TILE):
       i${M} = (const __fp16*) ((uintptr_t) i${M-1} + input_width);

     $if ROW_TILE > 1:
       o0 = o${ROW_TILE - 1};
       $for M in range(1, ROW_TILE):
         o${M} = (__fp16*) ((uintptr_t) o${M-1} + output_width);

     $if ROW_TILE > 1:
       output_height = doz(output_height, ${ROW_TILE});
       padded_input_height = doz(padded_input_height, ${ROW_TILE * 2});
     $else:
       output_height -= 1;
       padded_input_height -= 2;
   } while (output_height != 0);
 }
	// Copyright 2020 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 ROW_TILE >= 1
	$assert ACCUMULATORS >= 1
	#include <assert.h>

	#include <arm_neon.h>

	#include <xnnpack/dwconv.h>
	#include <xnnpack/math.h>


	void xnn_f16_dwconv2d_chw_ukernel_3x3s2p1__neonfp16arith_${ROW_TILE}x4${"_acc%d" % ACCUMULATORS if ACCUMULATORS > 1 else ""}(
	size_t input_height,
	size_t input_width,
	const void* input,
	const void* weights,
	const void* zero,
	void* output,
	uint32_t padding_top,
	const union xnn_f16_chw_params params[restrict XNN_MIN_ELEMENTS(1)]) XNN_OOB_READS
	{
	assert(input_height != 0);
	assert(input_width != 0);
	assert(input_width % sizeof(__fp16) == 0);
	assert(padding_top >= 0);
	assert(padding_top <= 1);

	const uint16x4_t vmask_even = vld1_u16(params->neonfp16arith.mask_even);
	const uint16x4_t vmask_odd = vld1_u16(params->neonfp16arith.mask_odd);
	const float16x4_t vmax = vld1_dup_f16(&params->neonfp16arith.max);
	const float16x4_t vmin = vld1_dup_f16(&params->neonfp16arith.min);

	const __fp16* w0 = (const __fp16*)weights;
	const float16x8_t vw01234567 = vld1q_f16(w0);
	const float16x4_t vw89 = vreinterpret_f16_u32(vld1_lane_u32((const void*)(w0 + 8), vmov_n_u32(0), 0));

	const size_t input_decrement = round_down_po2(input_width, 4 /* SIMD output width / 2 /* subsampling / sizeof(__fp16));
	$if ROW_TILE > 1:
	const size_t output_width = round_down_po2((input_width + (2 /* padding / - 3 / kernel size / + 2 / subsampling /) sizeof(__fp16)) / 2, sizeof(__fp16));

	const __fp16* i0 = (const __fp16*) ((uintptr_t) input - ((-padding_top) & input_width));
	const __fp16* i1 = (const __fp16*) ((uintptr_t) i0 + input_width);
	if XNN_UNPREDICTABLE(padding_top != 0) {
	i0 = zero;
	}
	$for M in range(2, 1 + 2 * ROW_TILE):
	const __fp16* i${M} = (const __fp16*) ((uintptr_t) i${M-1} + input_width);

	__fp16* o0 = output;
	$for M in range(1, ROW_TILE):
	__fp16* o${M} = (__fp16*) ((uintptr_t) o${M-1} + output_width);

	size_t padded_input_height = input_height + padding_top + 1 /* padding bottom */;
	size_t output_height = (padded_input_height - 3 /* kernel size / + 2 / subsampling */) / 2;
	do {
	$for M in range(2, 1 + 2 * ROW_TILE):
	if XNN_UNPREDICTABLE(padded_input_height < ${2 + M}) {
	i${M} = zero;
	$if M % 2 == 1:
	o${(M - 1) // 2} = o${(M - 1) // 2 - 1};
	}

	$for M in range(1 + 2 * ROW_TILE):
	float16x4_t vi${M}x1357 = vmov_n_f16(0);

	size_t w = input_width;
	for (; w >= 8 * sizeof(__fp16); w -= 8 * sizeof(__fp16)) {
	$for M in range(ROW_TILE):
	float16x4_t vo${M}p0 = vdup_laneq_f16(vw01234567, 0);

	$for M in range(1 + 2 * ROW_TILE):
	const float16x4x2_t vi${M}x8ACE9BDF = vld2_f16(i${M}); i${M} += 8;

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 1:
	float16x4_t vo${M}p1 = vmul_laneq_f16(vi${2*M}x8ACE9BDF.val[0], vw01234567, 2);
	$else:
	vo${M}p0 = vfma_laneq_f16(vo${M}p0, vi${2*M}x8ACE9BDF.val[0], vw01234567, 2);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 2:
	float16x4_t vo${M}p2 = vmul_laneq_f16(vi${2*M+1}x8ACE9BDF.val[0], vw01234567, 5);
	$else:
	vo${M}p0 = vfma_laneq_f16(vo${M}p0, vi${2*M+1}x8ACE9BDF.val[0], vw01234567, 5);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 3:
	float16x4_t vo${M}p3 = vmul_lane_f16(vi${2*M+2}x8ACE9BDF.val[0], vw89, 0);
	$else:
	vo${M}p${4 % ACCUMULATORS} = vfma_lane_f16(vo${M}p${4 % ACCUMULATORS}, vi${2*M+2}x8ACE9BDF.val[0], vw89, 0);

	$for M in range(1 + 2 * ROW_TILE):
	const float16x4_t vi${M}x7BDF = vext_f16(vi${M}x1357, vi${M}x8ACE9BDF.val[1], 3);
	vi${M}x1357 = vi${M}x8ACE9BDF.val[1];

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 4:
	float16x4_t vo${M}p4 = vmul_laneq_f16(vi${2*M}x7BDF, vw01234567, 1);
	$else:
	vo${M}p${5 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${5 % ACCUMULATORS}, vi${2*M}x7BDF, vw01234567, 1);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 5:
	float16x4_t vo${M}p5 = vmul_laneq_f16(vi${2*M+1}x7BDF, vw01234567, 4);
	$else:
	vo${M}p${6 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${6 % ACCUMULATORS}, vi${2*M+1}x7BDF, vw01234567, 4);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 6:
	float16x4_t vo${M}p6 = vmul_laneq_f16(vi${2*M+2}x7BDF, vw01234567, 5);
	$else:
	vo${M}p${7 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${7 % ACCUMULATORS}, vi${2*M+2}x7BDF, vw01234567, 7);

	$for M in range(ROW_TILE):
	vo${M}p${8 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${8 % ACCUMULATORS}, vi${2*M}x8ACE9BDF.val[1], vw01234567, 3);

	$for M in range(ROW_TILE):
	vo${M}p${9 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${9 % ACCUMULATORS}, vi${2*M+1}x8ACE9BDF.val[1], vw01234567, 6);

	$for M in range(ROW_TILE):
	vo${M}p${10 % ACCUMULATORS} = vfma_lane_f16(vo${M}p${10 % ACCUMULATORS}, vi${2*M+2}x8ACE9BDF.val[1], vw89, 1);

	$if ACCUMULATORS > 1:
	$ACC_SLICE = 1
	$while ACC_SLICE < ACCUMULATORS:
	$for A in range(0, ACCUMULATORS, ACC_SLICE * 2):
	$if A + ACC_SLICE < ACCUMULATORS:
	$for M in range(ROW_TILE):
	vo${M}p${A} = vadd_f16(vo${M}p${A}, vo${M}p${A + ACC_SLICE});
	$ACC_SLICE *= 2

	$for M in range(ROW_TILE):
	float16x4_t vo${M} = vmax_f16(vo${M}p0, vmin);

	$for M in range(ROW_TILE):
	vo${M} = vmin_f16(vo${M}, vmax);

	$for M in reversed(range(ROW_TILE)):
	vst1_f16(o${M}, vo${M}); o${M} += 4;
	}
	// Last block has 0-7 pixels to process.
	assert(w < 8 * sizeof(__fp16));
	if XNN_LIKELY(w != 0) {
	$for M in range(ROW_TILE):
	float16x4_t vo${M}p0 = vdup_laneq_f16(vw01234567, 0);

	$for M in range(1 + 2 * ROW_TILE):
	const float16x4x2_t vi${M}x8ACE9BDF = vld2_f16(i${M});

	$for M in range(1 + 2 * ROW_TILE):
	const float16x4_t vi${M}x8ACE = vreinterpret_f16_u16(vand_u16(vmask_even, vreinterpret_u16_f16(vi${M}x8ACE9BDF.val[0])));
	const float16x4_t vi${M}x9BDF = vreinterpret_f16_u16(vand_u16(vmask_odd, vreinterpret_u16_f16(vi${M}x8ACE9BDF.val[1])));

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 1:
	float16x4_t vo${M}p1 = vmul_laneq_f16(vi${2*M}x8ACE, vw01234567, 2);
	$else:
	vo${M}p0 = vfma_laneq_f16(vo${M}p0, vi${2*M}x8ACE, vw01234567, 2);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 2:
	float16x4_t vo${M}p2 = vmul_laneq_f16(vi${2*M+1}x8ACE, vw01234567, 5);
	$else:
	vo${M}p0 = vfma_laneq_f16(vo${M}p0, vi${2*M+1}x8ACE, vw01234567, 5);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 3:
	float16x4_t vo${M}p3 = vmul_lane_f16(vi${2*M+2}x8ACE, vw89, 0);
	$else:
	vo${M}p${4 % ACCUMULATORS} = vfma_lane_f16(vo${M}p${4 % ACCUMULATORS}, vi${2*M+2}x8ACE, vw89, 0);

	$for M in range(1 + 2 * ROW_TILE):
	const float16x4_t vi${M}x7BDF = vext_f16(vi${M}x1357, vi${M}x9BDF, 3);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 4:
	float16x4_t vo${M}p4 = vmul_laneq_f16(vi${2*M}x7BDF, vw01234567, 1);
	$else:
	vo${M}p${5 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${5 % ACCUMULATORS}, vi${2*M}x7BDF, vw01234567, 1);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 5:
	float16x4_t vo${M}p5 = vmul_laneq_f16(vi${2*M+1}x7BDF, vw01234567, 4);
	$else:
	vo${M}p${6 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${6 % ACCUMULATORS}, vi${2*M+1}x7BDF, vw01234567, 4);

	$for M in range(ROW_TILE):
	$if ACCUMULATORS > 6:
	float16x4_t vo${M}p6 = vmul_laneq_f16(vi${2*M+2}x7BDF, vw01234567, 5);
	$else:
	vo${M}p${7 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${7 % ACCUMULATORS}, vi${2*M+2}x7BDF, vw01234567, 7);

	$for M in range(ROW_TILE):
	vo${M}p${8 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${8 % ACCUMULATORS}, vi${2*M}x9BDF, vw01234567, 3);

	$for M in range(ROW_TILE):
	vo${M}p${9 % ACCUMULATORS} = vfma_laneq_f16(vo${M}p${9 % ACCUMULATORS}, vi${2*M+1}x9BDF, vw01234567, 6);

	$for M in range(ROW_TILE):
	vo${M}p${10 % ACCUMULATORS} = vfma_lane_f16(vo${M}p${10 % ACCUMULATORS}, vi${2*M+2}x9BDF, vw89, 1);

	$if ACCUMULATORS > 1:
	$ACC_SLICE = 1
	$while ACC_SLICE < ACCUMULATORS:
	$for A in range(0, ACCUMULATORS, ACC_SLICE * 2):
	$if A + ACC_SLICE < ACCUMULATORS:
	$for M in range(ROW_TILE):
	vo${M}p${A} = vadd_f16(vo${M}p${A}, vo${M}p${A + ACC_SLICE});
	$ACC_SLICE *= 2

	$for M in range(ROW_TILE):
	float16x4_t vo${M} = vmax_f16(vo${M}p0, vmin);

	$for M in range(ROW_TILE):
	vo${M} = vmin_f16(vo${M}, vmax);

	w += 1 * sizeof(__fp16);

	if XNN_LIKELY(w == 8 * sizeof(__fp16)) {
	$for M in reversed(range(ROW_TILE)):
	vst1_f16(o${M}, vo${M}); o${M} += 4;
	} else {
	if (w & (4 * sizeof(__fp16))) {
	$for M in reversed(range(ROW_TILE)):
	vst1_lane_u32((void*) o${M}, vreinterpret_u32_f16(vo${M}), 0); o${M} += 2;

	$for M in range(ROW_TILE):
	vo${M} = vext_f16(vo${M}, vo${M}, 2);
	}
	if (w & (2 * sizeof(__fp16))) {
	$for M in reversed(range(ROW_TILE)):
	vst1_lane_f16(o${M}, vo${M}, 0); o${M} += 1;
	}
	}

	}

	i0 = (const __fp16) ((uintptr_t) i${2 ROW_TILE} - input_decrement);
	$for M in range(1, 1 + 2 * ROW_TILE):
	i${M} = (const __fp16*) ((uintptr_t) i${M-1} + input_width);

	$if ROW_TILE > 1:
	o0 = o${ROW_TILE - 1};
	$for M in range(1, ROW_TILE):
	o${M} = (__fp16*) ((uintptr_t) o${M-1} + output_width);

	$if ROW_TILE > 1:
	output_height = doz(output_height, ${ROW_TILE});
	padded_input_height = doz(padded_input_height, ${ROW_TILE * 2});
	$else:
	output_height -= 1;
	padded_input_height -= 2;
	} while (output_height != 0);
	}