xref: /aosp_15_r20/external/XNNPACK/src/f16-gavgpool-cw/neonfp16arith-x4.c (revision 4bdc94577ba0e567308109d787f7fec7b531ce36)
1 // Copyright 2019 Google LLC
2 //
3 // This source code is licensed under the BSD-style license found in the
4 // LICENSE file in the root directory of this source tree.
5 
6 #include <assert.h>
7 
8 #include <arm_neon.h>
9 
10 #include <xnnpack/gavgpool.h>
11 #include <xnnpack/math.h>
12 
13 
xnn_f16_gavgpool_cw_ukernel__neonfp16arith_x4(size_t elements,size_t channels,const void * input,void * output,const union xnn_f16_gavgpool_params params[restrict XNN_MIN_ELEMENTS (1)])14 void xnn_f16_gavgpool_cw_ukernel__neonfp16arith_x4(
15     size_t elements,
16     size_t channels,
17     const void* input,
18     void* output,
19     const union xnn_f16_gavgpool_params params[restrict XNN_MIN_ELEMENTS(1)]) XNN_OOB_READS
20 {
21   assert(elements != 0);
22   assert(elements % sizeof(__fp16) == 0);
23   assert(channels != 0);
24 
25   __fp16* o = (__fp16*) output;
26   const __fp16* i0 = input;
27   const __fp16* i1 = (const __fp16*) ((uintptr_t) i0 + elements);
28   const __fp16* i2 = (const __fp16*) ((uintptr_t) i1 + elements);
29   const __fp16* i3 = (const __fp16*) ((uintptr_t) i2 + elements);
30 
31   const uint16x4_t vmask = vld1_u16(params->neonfp16arith.mask);
32   const float16x4_t vmultiplier = vreinterpret_f16_u16(vld1_dup_u16(&params->neonfp16arith.multiplier));
33   const float16x4_t voutput_min = vreinterpret_f16_u16(vld1_dup_u16(&params->neonfp16arith.output_min));
34   const float16x4_t voutput_max = vreinterpret_f16_u16(vld1_dup_u16(&params->neonfp16arith.output_max));
35 
36   while (channels >= 4) {
37     float16x4_t vsum0 = vmov_n_f16(0);
38     float16x4_t vsum1 = vmov_n_f16(0);
39     float16x4_t vsum2 = vmov_n_f16(0);
40     float16x4_t vsum3 = vmov_n_f16(0);
41     size_t n = elements;
42     while (n >= 4 * sizeof(__fp16)) {
43       const float16x4_t vi0 = vld1_f16(i0); i0 += 4;
44       const float16x4_t vi1 = vld1_f16(i1); i1 += 4;
45       const float16x4_t vi2 = vld1_f16(i2); i2 += 4;
46       const float16x4_t vi3 = vld1_f16(i3); i3 += 4;
47 
48       vsum0 = vadd_f16(vsum0, vi0);
49       vsum1 = vadd_f16(vsum1, vi1);
50       vsum2 = vadd_f16(vsum2, vi2);
51       vsum3 = vadd_f16(vsum3, vi3);
52       n -= 4 * sizeof(__fp16);
53     }
54 
55     if XNN_UNLIKELY(n != 0) {
56       float16x4_t vi0 = vld1_f16(i0); i0 = (const __fp16*) ((uintptr_t) i0 + n);
57       float16x4_t vi1 = vld1_f16(i1); i1 = (const __fp16*) ((uintptr_t) i1 + n);
58       float16x4_t vi2 = vld1_f16(i2); i2 = (const __fp16*) ((uintptr_t) i2 + n);
59       float16x4_t vi3 = vld1_f16(i3); i3 = (const __fp16*) ((uintptr_t) i3 + n);
60 
61       vi0 = vreinterpret_f16_u16(vand_u16(vmask, vreinterpret_u16_f16(vi0)));
62       vi1 = vreinterpret_f16_u16(vand_u16(vmask, vreinterpret_u16_f16(vi1)));
63       vi2 = vreinterpret_f16_u16(vand_u16(vmask, vreinterpret_u16_f16(vi2)));
64       vi3 = vreinterpret_f16_u16(vand_u16(vmask, vreinterpret_u16_f16(vi3)));
65 
66       vsum0 = vadd_f16(vsum0, vi0);
67       vsum1 = vadd_f16(vsum1, vi1);
68       vsum2 = vadd_f16(vsum2, vi2);
69       vsum3 = vadd_f16(vsum3, vi3);
70     }
71 
72     // Having exactly 4 rows makes this work out nicely as we end up with
73     // the 4 totals in 4 different lanes of the same vector.
74     const float16x4_t vsum01 = vpadd_f16(vsum0, vsum1);
75     const float16x4_t vsum23 = vpadd_f16(vsum2, vsum3);
76     const float16x4_t vsum = vpadd_f16(vsum01, vsum23);
77 
78     float16x4_t vout = vmul_f16(vsum, vmultiplier);
79 
80     vout = vmax_f16(vout, voutput_min);
81     vout = vmin_f16(vout, voutput_max);
82 
83     vst1_f16(o, vout); o += 4;
84 
85     i0 = i3;
86     i1 = (const __fp16*) ((uintptr_t) i0 + elements);
87     i2 = (const __fp16*) ((uintptr_t) i1 + elements);
88     i3 = (const __fp16*) ((uintptr_t) i2 + elements);
89     channels -= 4;
90   }
91 
92   while (channels != 0) {
93     float16x4_t vsum0 = vmov_n_f16(0);
94     size_t n = elements;
95     while (n >= 4 * sizeof(__fp16)) {
96       const float16x4_t vi0 = vld1_f16(i0); i0 += 4;
97 
98       vsum0 = vadd_f16(vsum0, vi0);
99       n -= 4 * sizeof(__fp16);
100     }
101 
102     if XNN_UNLIKELY(n != 0) {
103       float16x4_t vi0 = vld1_f16(i0); i0 = (const __fp16*) ((uintptr_t) i0 + n);
104 
105       vi0 = vreinterpret_f16_u16(vand_u16(vmask, vreinterpret_u16_f16(vi0)));
106 
107       vsum0 = vadd_f16(vsum0, vi0);
108     }
109 
110     const float16x4_t vsum01 = vpadd_f16(vsum0, vsum0);
111     const float16x4_t vsum = vpadd_f16(vsum01, vsum01);
112 
113     float16x4_t vout = vmul_f16(vsum, vmultiplier);
114 
115     vout = vmax_f16(vout, voutput_min);
116     vout = vmin_f16(vout, voutput_max);
117 
118     vst1_lane_f16(o, vout, 0); o += 1;
119     channels -= 1;
120   }
121 }
122