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1// Copyright 2020 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$assert BATCH_TILE % 4 == 0
7$assert BATCH_TILE >= 4
8$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
9#include <assert.h>
10
11#include <wasm_simd128.h>
12
13#include <xnnpack/common.h>
14#include <xnnpack/hswish.h>
15
16
17void xnn_f32_hswish_ukernel__wasmsimd_x${BATCH_TILE}(
18    size_t n,
19    const float* x,
20    float* y,
21    const union xnn_f32_hswish_params params[restrict XNN_MIN_ELEMENTS(1)]) XNN_DISABLE_TSAN
22{
23  assert(n != 0);
24  assert(n % sizeof(float) == 0);
25
26  const v128_t vsixth = wasm_v32x4_load_splat(&params->scalar.sixth);
27  const v128_t vthree = wasm_v32x4_load_splat(&params->scalar.three);
28  const v128_t vsix = wasm_v32x4_load_splat(&params->scalar.six);
29  const v128_t vzero = wasm_f32x4_splat(0.0f);
30
31  $if BATCH_TILE > 4:
32    for (; n >= ${BATCH_TILE} * sizeof(float); n -= ${BATCH_TILE} * sizeof(float)) {
33      v128_t vx${ABC[0:4]} = wasm_v128_load(x);
34      $for N in range(4, BATCH_TILE, 4):
35        v128_t vx${ABC[N:N+4]} = wasm_v128_load(x + ${N});
36      x += ${BATCH_TILE};
37
38      $for N in range(0, BATCH_TILE, 4):
39        v128_t vacc${ABC[N:N+4]} = wasm_f32x4_add(vx${ABC[N:N+4]}, vthree);
40        vx${ABC[N:N+4]} = wasm_f32x4_mul(vx${ABC[N:N+4]}, vsixth);
41
42      $for N in range(0, BATCH_TILE, 4):
43        vacc${ABC[N:N+4]} = wasm_i32x4_max(vacc${ABC[N:N+4]}, vzero);
44
45      $for N in range(0, BATCH_TILE, 4):
46        vacc${ABC[N:N+4]} = wasm_i32x4_min(vacc${ABC[N:N+4]}, vsix);
47
48      $for N in range(0, BATCH_TILE, 4):
49        vacc${ABC[N:N+4]} = wasm_f32x4_mul(vacc${ABC[N:N+4]}, vx${ABC[N:N+4]});
50
51      wasm_v128_store(y, vacc${ABC[0:4]});
52      $for N in range(4, BATCH_TILE, 4):
53        wasm_v128_store(y + ${N}, vacc${ABC[N:N+4]});
54      y += ${BATCH_TILE};
55    }
56  for (; n >= 4 * sizeof(float); n -= 4 * sizeof(float)) {
57    v128_t vx = wasm_v128_load(x);
58    x += 4;
59
60    v128_t vacc = wasm_f32x4_add(vx, vthree);
61    vx = wasm_f32x4_mul(vx, vsixth);
62    vacc = wasm_i32x4_max(vacc, vzero);
63    vacc = wasm_i32x4_min(vacc, vsix);
64    vacc = wasm_f32x4_mul(vacc, vx);
65
66    wasm_v128_store(y, vacc);
67    y += 4;
68  }
69  if XNN_UNLIKELY(n != 0) {
70    v128_t vx = wasm_v128_load(x);
71
72    v128_t vacc = wasm_f32x4_add(vx, vthree);
73    vx = wasm_f32x4_mul(vx, vsixth);
74    vacc = wasm_i32x4_max(vacc, vzero);
75    vacc = wasm_i32x4_min(vacc, vsix);
76    vacc = wasm_f32x4_mul(vacc, vx);
77
78    if (n & (2 * sizeof(float))) {
79      *((double*) y) = wasm_f64x2_extract_lane(vacc, 0);
80      vacc = wasm_v32x4_shuffle(vacc, vacc, 2, 3, 2, 3);
81      y += 2;
82    }
83    if (n & (1 * sizeof(float))) {
84      *y = wasm_f32x4_extract_lane(vacc, 0);
85    }
86  }
87}
88