text: // Auto-generated file. Do not edit!
  //   Template: src/f32-raddstoreexpminusmax/neon-lut64-p2.c.in
  //   Generator: tools/xngen
  //
  // 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.
  
  #include <assert.h>
  
  #include <arm_neon.h>
  
  #include <xnnpack/common.h>
  #include <xnnpack/raddstoreexpminusmax.h>
  
  
  extern XNN_INTERNAL const float xnn_table_exp2_k_over_64[64];
  
  void xnn_f32_raddstoreexpminusmax_ukernel__neonfma_lut64_p2_x16(
      size_t elements,
      const float* input,
      float* output,
      float* sum,
      float max)
  {
    assert(elements % sizeof(float) == 0);
  
    const float32x4_t vmagic_bias = vmovq_n_f32(0x1.800000p23f);
    // The smallest x for which expf(x) is normalized.
    const float32x4_t vdenorm_cutoff = vmovq_n_f32(-0x1.5D589Ep6f);
    const float32x4_t vlog2e_x64  = vmovq_n_f32(0x1.715476p6f);
    const float32x4_t vminus_ln2_o64_hi = vmovq_n_f32(-0x1.62e43p-7f);
    const float32x4_t vminus_ln2_o64_lo = vmovq_n_f32(0x1.05c61p-35f);
  
    const float32x4_t vc2 = vmovq_n_f32(0x1.FFFF0Ap-2f);
  
    const int32x4_t vindex_mask = vmovq_n_s32(INT32_C(0x3F));
  
    const float32x4_t vi_max = vdupq_n_f32(max);
  
    float32x4_t vacc0 = vmovq_n_f32(0.0f);
    for (; elements >= 16 * sizeof(float); elements -= 16 * sizeof(float)) {
      // Load 16 (4x4) inputs at a time.
      const float32x4_t vi0123 = vld1q_f32(input); input += 4;
      const float32x4_t vi4567 = vld1q_f32(input); input += 4;
      const float32x4_t vi89AB = vld1q_f32(input); input += 4;
      const float32x4_t viCDEF = vld1q_f32(input); input += 4;
  
      // Subtract maximum input x := i - i_max. This implies x <= 0.
      const float32x4_t vx0123 = vsubq_f32(vi0123, vi_max);
      const float32x4_t vx4567 = vsubq_f32(vi4567, vi_max);
      const float32x4_t vx89AB = vsubq_f32(vi89AB, vi_max);
      const float32x4_t vxCDEF = vsubq_f32(viCDEF, vi_max);
  
      // Compute reduced argument n := round(x * 64 / log(2)).
      // We do it by adding a large number (magic bias), which cause rounding of the result to an integer, then subtracing
      // the large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
      // The trick with adding large number is valid only within certain bounds (|x * 64 / log(2)| <= 2**22, i.e.
      // |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs outside of [-87.336540, 0.0]
      // result in denormalized or underflown expf(x). We fixup the result for such inputs at the very end of the
      // algorithm.
      float32x4_t vn0123 = vfmaq_f32(vmagic_bias, vx0123, vlog2e_x64);
      float32x4_t vn4567 = vfmaq_f32(vmagic_bias, vx4567, vlog2e_x64);
      float32x4_t vn89AB = vfmaq_f32(vmagic_bias, vx89AB, vlog2e_x64);
      float32x4_t vnCDEF = vfmaq_f32(vmagic_bias, vxCDEF, vlog2e_x64);
  
      // Create a floating-point number s (scale) such that s := 2**(n / 64) for such inputs that expf(x) is normalized,
      // i.e. -87.33642 <= x <= 0.0. As n has 6 fractional bits, we split s == 2**(n / 64) = 2**e * 2**(n / 64 - e), where
      // e := int(n / 64). We create s in two steps:
      // 1. Fetch 2**(n / 64 - e) = 2**(n % 64) from the table using the 6 low bits of n, as integer. Note that the
      //    fetched values are in the [1.0, 2.0) range, i.e. their floating-point exponent is 0.
      // 2. Adjust fecthed value by addition of e to its floating-point exponent. The result is always a normalized
      //    number, because for -87.33642 <= x <= 0.0 (inputs for which expf(x) is normalized) we have -126 <= e <= 0,
      //    and thus the adjusted exponent is not lower than -126.
      //
      // Extract e from bits 6:14 of n and shift it into bits 23:31 (position of floating-point exponent).
      const int32x4_t ve0123 = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn0123), vmovq_n_s32(INT32_C(0x3F))), 17);
      const int32x4_t ve4567 = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn4567), vmovq_n_s32(INT32_C(0x3F))), 17);
      const int32x4_t ve89AB = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn89AB), vmovq_n_s32(INT32_C(0x3F))), 17);
      const int32x4_t veCDEF = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vnCDEF), vmovq_n_s32(INT32_C(0x3F))), 17);
  
      // Use bits 0:6 bits of n, as integer, as an index for table lookup of l := 2**(n % 64).
      const uint64x2_t vidx0123 = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn0123), vindex_mask));
      const uint64_t vidx01 = vgetq_lane_u64(vidx0123, 0);
      const uint64_t vidx23 = vgetq_lane_u64(vidx0123, 1);
      const uint64x2_t vidx4567 = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn4567), vindex_mask));
      const uint64_t vidx45 = vgetq_lane_u64(vidx4567, 0);
      const uint64_t vidx67 = vgetq_lane_u64(vidx4567, 1);
      const uint64x2_t vidx89AB = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn89AB), vindex_mask));
      const uint64_t vidx89 = vgetq_lane_u64(vidx89AB, 0);
      const uint64_t vidxAB = vgetq_lane_u64(vidx89AB, 1);
      const uint64x2_t vidxCDEF = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vnCDEF), vindex_mask));
      const uint64_t vidxCD = vgetq_lane_u64(vidxCDEF, 0);
      const uint64_t vidxEF = vgetq_lane_u64(vidxCDEF, 1);
  
      float32x2_t vl01 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx01]);
      float32x2_t vl23 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx23]);
      float32x2_t vl45 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx45]);
      float32x2_t vl67 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx67]);
      float32x2_t vl89 = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx89]);
      float32x2_t vlAB = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidxAB]);
      float32x2_t vlCD = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidxCD]);
      float32x2_t vlEF = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidxEF]);
  
      vl01 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx01 >> 32)], vl01, 1);
      vl23 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx23 >> 32)], vl23, 1);
      const float32x4_t vl0123 = vcombine_f32(vl01, vl23);
      vl45 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx45 >> 32)], vl45, 1);
      vl67 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx67 >> 32)], vl67, 1);
      const float32x4_t vl4567 = vcombine_f32(vl45, vl67);
      vl89 = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx89 >> 32)], vl89, 1);
      vlAB = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidxAB >> 32)], vlAB, 1);
      const float32x4_t vl89AB = vcombine_f32(vl89, vlAB);
      vlCD = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidxCD >> 32)], vlCD, 1);
      vlEF = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidxEF >> 32)], vlEF, 1);
      const float32x4_t vlCDEF = vcombine_f32(vlCD, vlEF);
  
      // Adjust exponent of the value l fetched from the table to get the final s value.
      const float32x4_t vs0123 = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl0123), ve0123));
      const float32x4_t vs4567 = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl4567), ve4567));
      const float32x4_t vs89AB = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl89AB), ve89AB));
      const float32x4_t vsCDEF = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vlCDEF), veCDEF));
  
      // Subtract the large number back to get final n := round(x * 64 / log(2)) as a floating-point number.
      vn0123 = vsubq_f32(vn0123, vmagic_bias);
      vn4567 = vsubq_f32(vn4567, vmagic_bias);
      vn89AB = vsubq_f32(vn89AB, vmagic_bias);
      vnCDEF = vsubq_f32(vnCDEF, vmagic_bias);
  
      // Compute reduced argument t := x - n * log(2) / 64.
      // Use Cody-Waite range reduction method (note the two constants representing log(2) / 64) to improve accuracy.
      float32x4_t vt0123 = vfmaq_f32(vx0123, vn0123, vminus_ln2_o64_hi);
      float32x4_t vt4567 = vfmaq_f32(vx4567, vn4567, vminus_ln2_o64_hi);
      float32x4_t vt89AB = vfmaq_f32(vx89AB, vn89AB, vminus_ln2_o64_hi);
      float32x4_t vtCDEF = vfmaq_f32(vxCDEF, vnCDEF, vminus_ln2_o64_hi);
  
      vt0123 = vfmaq_f32(vt0123, vn0123, vminus_ln2_o64_lo);
      vt4567 = vfmaq_f32(vt4567, vn4567, vminus_ln2_o64_lo);
      vt89AB = vfmaq_f32(vt89AB, vn89AB, vminus_ln2_o64_lo);
      vtCDEF = vfmaq_f32(vtCDEF, vnCDEF, vminus_ln2_o64_lo);
  
      // Compute degree-2 polynomial approxiatmion for exp(t) on [-log(2)/128, log(2)/128].
      float32x4_t vp0123 = vmulq_f32(vt0123, vc2);
      float32x4_t vp4567 = vmulq_f32(vt4567, vc2);
      float32x4_t vp89AB = vmulq_f32(vt89AB, vc2);
      float32x4_t vpCDEF = vmulq_f32(vtCDEF, vc2);
  
      vp0123 = vfmaq_f32(vt0123, vt0123, vp0123);
      vp4567 = vfmaq_f32(vt4567, vt4567, vp4567);
      vp89AB = vfmaq_f32(vt89AB, vt89AB, vp89AB);
      vpCDEF = vfmaq_f32(vtCDEF, vtCDEF, vpCDEF);
  
      // Reconstruct the final f value:
      //   f = s * (1 + t * (1 + t * c2))
      //     = s * (1 + t + t * (t * c2))
      //     = s + s * (t + t * (t * c2))
      //     = s + s * p
      float32x4_t vf0123 = vfmaq_f32(vs0123, vs0123, vp0123);
      float32x4_t vf4567 = vfmaq_f32(vs4567, vs4567, vp4567);
      float32x4_t vf89AB = vfmaq_f32(vs89AB, vs89AB, vp89AB);
      float32x4_t vfCDEF = vfmaq_f32(vsCDEF, vsCDEF, vpCDEF);
  
      // For inputs below denormal cutoff, replace output with +0.0f.
      // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
      vf0123 = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf0123), vcltq_f32(vx0123, vdenorm_cutoff)));
      vf4567 = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf4567), vcltq_f32(vx4567, vdenorm_cutoff)));
      vf89AB = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf89AB), vcltq_f32(vx89AB, vdenorm_cutoff)));
      vfCDEF = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vfCDEF), vcltq_f32(vxCDEF, vdenorm_cutoff)));
  
      // Store 16 (4x4) outputs at a time.
      vst1q_f32(output, vf0123); output += 4;
      vst1q_f32(output, vf4567); output += 4;
      vst1q_f32(output, vf89AB); output += 4;
      vst1q_f32(output, vfCDEF); output += 4;
  
      // Accumulate computed exponents.
      vacc0 = vaddq_f32(vacc0, vf0123);
      vacc0 = vaddq_f32(vacc0, vf4567);
      vacc0 = vaddq_f32(vacc0, vf89AB);
      vacc0 = vaddq_f32(vacc0, vfCDEF);
    }
  
    float32x4_t vacc = vacc0;
    for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) {
      // Load 4 inputs at a time.
      const float32x4_t vi = vld1q_f32(input); input += 4;
  
      // Subtract maximum input x := i - i_max. This implies x <= 0.
      const float32x4_t vx = vsubq_f32(vi, vi_max);
  
      // Compute reduced argument n := round(x * 64 / log(2)).
      // We do it by adding a large number (magic bias), which cause rounding of the result to an integer, then subtracing
      // the large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
      // The trick with adding large number is valid only within certain bounds (|x * 64 / log(2)| <= 2**22, i.e.
      // |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs outside of [-87.336540, 0.0]
      // result in denormalized or underflown expf(x). We fixup the result for such inputs at the very end of the
      // algorithm.
      float32x4_t vn = vfmaq_f32(vmagic_bias, vx, vlog2e_x64);
  
      // Create a floating-point number s (scale) such that s := 2**(n / 64) for such inputs that expf(x) is normalized,
      // i.e. -87.33642 <= x <= 0.0. As n has 6 fractional bits, we split s == 2**(n / 64) = 2**e * 2**(n / 64 - e), where
      // e := int(n / 64). We create s in two steps:
      // 1. Fetch 2**(n / 64 - e) = 2**(n % 64) from the table using the 6 low bits of n, as integer. Note that the
      //    fetched values are in the [1.0, 2.0) range, i.e. their floating-point exponent is 0.
      // 2. Adjust fecthed value by addition of e to its floating-point exponent. The result is always a normalized
      //    number, because for -87.33642 <= x <= 0.0 (inputs for which expf(x) is normalized) we have -126 <= e <= 0,
      //    and thus the adjusted exponent is not lower than -126.
      //
      // Extract e from bits 6:14 of n and shift it into bits 23:31 (position of floating-point exponent).
      const int32x4_t ve = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn), vmovq_n_s32(INT32_C(0x3F))), 17);
  
      // Use bits 0:6 bits of n, as integer, as an index for table lookup of l := 2**(n % 64).
      const uint64x2_t vidx = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn), vindex_mask));
      const uint64_t vidx_lo = vgetq_lane_u64(vidx, 0);
      const uint64_t vidx_hi = vgetq_lane_u64(vidx, 1);
      float32x2_t vl_lo = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx_lo]);
      float32x2_t vl_hi = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx_hi]);
      vl_lo = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx_lo >> 32)], vl_lo, 1);
      vl_hi = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx_hi >> 32)], vl_hi, 1);
      const float32x4_t vl = vcombine_f32(vl_lo, vl_hi);
      // Adjust exponent of the value l fetched from the table to get the final s value.
      const float32x4_t vs = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl), ve));
  
      // Subtract the large number back to get final n := round(x * 64 / log(2)) as a floating-point number.
      vn = vsubq_f32(vn, vmagic_bias);
  
      // Compute reduced argument t := x - n * log(2) / 64.
      // Use Cody-Waite range reduction method (note the two constants representing log(2) / 64) to improve accuracy.
      float32x4_t vt = vfmaq_f32(vx, vn, vminus_ln2_o64_hi);
      vt = vfmaq_f32(vt, vn, vminus_ln2_o64_lo);
  
      // Compute degree-2 polynomial approxiatmion for exp(t) on [-log(2)/128, log(2)/128].
      float32x4_t vp = vmulq_f32(vt, vc2);
      vp = vfmaq_f32(vt, vt, vp);
  
      // Reconstruct the final f value:
      //   f = s * (1 + t * (1 + t * c2))
      //     = s * (1 + t + t * (t * c2))
      //     = s + s * (t + t * (t * c2))
      //     = s + s * p
      float32x4_t vf = vfmaq_f32(vs, vs, vp);
  
      // For inputs below denormal cutoff, replace output with +0.0f.
      // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
      vf = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf), vcltq_f32(vx, vdenorm_cutoff)));
  
      // Store 4 outputs at a time.
      vst1q_f32(output, vf); output += 4;
  
      // Accumulate computed exponents.
      vacc = vaddq_f32(vacc, vf);
    }
  #if XNN_ARCH_ARM64
    float vacc_lo = vaddvq_f32(vacc);
  #else
    float32x2_t vacc_lo = vadd_f32(vget_high_f32(vacc), vget_low_f32(vacc));
  #endif
    if (elements != 0) {
      assert(elements >= 1 * sizeof(float));
      assert(elements <= 3 * sizeof(float));
      // Load 4 inputs at a time.
      const float32x4_t vi = vld1q_f32(input); input += 4;
  
      // Subtract maximum input x := i - i_max. This implies x <= 0.
      const float32x4_t vx = vsubq_f32(vi, vi_max);
  
      // Compute reduced argument n := round(x * 64 / log(2)).
      // We do it by adding a large number (magic bias), which cause rounding of the result to an integer, then subtracing
      // the large number back. The first addition is combined with multiplication by log2e into a single FMA instruction.
      // The trick with adding large number is valid only within certain bounds (|x * 64 / log(2)| <= 2**22, i.e.
      // |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs outside of [-87.336540, 0.0]
      // result in denormalized or underflown expf(x). We fixup the result for such inputs at the very end of the
      // algorithm.
      float32x4_t vn = vfmaq_f32(vmagic_bias, vx, vlog2e_x64);
  
      // Create a floating-point number s (scale) such that s := 2**(n / 64) for such inputs that expf(x) is normalized,
      // i.e. -87.33642 <= x <= 0.0. As n has 6 fractional bits, we split s == 2**(n / 64) = 2**e * 2**(n / 64 - e), where
      // e := int(n / 64). We create s in two steps:
      // 1. Fetch 2**(n / 64 - e) = 2**(n % 64) from the table using the 6 low bits of n, as integer. Note that the
      //    fetched values are in the [1.0, 2.0) range, i.e. their floating-point exponent is 0.
      // 2. Adjust fecthed value by addition of e to its floating-point exponent. The result is always a normalized
      //    number, because for -87.33642 <= x <= 0.0 (inputs for which expf(x) is normalized) we have -126 <= e <= 0,
      //    and thus the adjusted exponent is not lower than -126.
      //
      // Extract e from bits 6:14 of n and shift it into bits 23:31 (position of floating-point exponent).
      const int32x4_t ve = vshlq_n_s32(vbicq_s32(vreinterpretq_s32_f32(vn), vmovq_n_s32(INT32_C(0x3F))), 17);
  
      // Use bits 0:6 bits of n, as integer, as an index for table lookup of l := 2**(n % 64).
      const uint64x2_t vidx = vreinterpretq_u64_s32(vandq_s32(vreinterpretq_s32_f32(vn), vindex_mask));
      const uint64_t vidx_lo = vgetq_lane_u64(vidx, 0);
      const uint64_t vidx_hi = vgetq_lane_u64(vidx, 1);
      float32x2_t vl_lo = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx_lo]);
      float32x2_t vl_hi = vld1_dup_f32(&xnn_table_exp2_k_over_64[(uint32_t) vidx_hi]);
      vl_lo = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx_lo >> 32)], vl_lo, 1);
      vl_hi = vld1_lane_f32(&xnn_table_exp2_k_over_64[(uint32_t) (vidx_hi >> 32)], vl_hi, 1);
      const float32x4_t vl = vcombine_f32(vl_lo, vl_hi);
      // Adjust exponent of the value l fetched from the table to get the final s value.
      const float32x4_t vs = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl), ve));
  
      // Subtract the large number back to get final n := round(x * 64 / log(2)) as a floating-point number.
      vn = vsubq_f32(vn, vmagic_bias);
  
      // Compute reduced argument t := x - n * log(2) / 64.
      // Use Cody-Waite range reduction method (note the two constants representing log(2) / 64) to improve accuracy.
      float32x4_t vt = vfmaq_f32(vx, vn, vminus_ln2_o64_hi);
      vt = vfmaq_f32(vt, vn, vminus_ln2_o64_lo);
  
      // Compute degree-2 polynomial approxiatmion for exp(t) on [-log(2)/128, log(2)/128].
      float32x4_t vp = vmulq_f32(vt, vc2);
      vp = vfmaq_f32(vt, vt, vp);
  
      // Reconstruct the final f value:
      //   f = s * (1 + t * (1 + t * c2))
      //     = s * (1 + t + t * (t * c2))
      //     = s + s * (t + t * (t * c2))
      //     = s + s * p
      float32x4_t vf = vfmaq_f32(vs, vs, vp);
  
      // For inputs below denormal cutoff, replace output with +0.0f.
      // Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
      vf = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf), vcltq_f32(vx, vdenorm_cutoff)));
  
      float32x2_t vf_lo = vget_low_f32(vf);
      if (elements & (2 * sizeof(float))) {
        // Store 2 outputs at a time.
        vst1_f32(output, vf_lo); output += 2;
  
        // Accumulate 2 computed exponents.
        #if XNN_ARCH_ARM64
          vacc_lo += vaddv_f32(vf_lo);
        #else
          vacc_lo = vadd_f32(vacc_lo, vf_lo);
        #endif
  
        vf_lo = vget_high_f32(vf);
      }
      if (elements & (1 * sizeof(float))) {
        // Store 1 output at a time.
        vst1_lane_f32(output, vf_lo, 0);
  
        // Accumulate 1 computed exponent.
        #if XNN_ARCH_ARM64
          vacc_lo += vget_lane_f32(vf_lo, 0);
        #else
          vacc_lo = vadd_f32(vacc_lo, vreinterpret_f32_u64(vshl_n_u64(vreinterpret_u64_f32(vf_lo), 32)));
        #endif
      }
    }
    // Reduce 4 elements in the SIMD register
  #if XNN_ARCH_ARM64
    *sum = vacc_lo;
  #else
    vst1_lane_f32(sum, vpadd_f32(vacc_lo, vacc_lo), 0);
  #endif
  }
  