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dnn: vectorize SigmoidFunctor using universal intrinsics

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(cherry picked from commit 4b1c861ab7)
This commit is contained in:
Teddy-Yangjiale
2026-05-12 02:22:19 +08:00
parent 14a475aa0b
commit 8e434d68f9
1 changed files with 22 additions and 4 deletions
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modules/dnn/src/layers/cpu_kernels/activation_kernels.simd.hpp
+22 -4
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@@ -97,12 +97,30 @@ static void activationSigmoid(const void* input, void* output,
size_t i = 0;
#if (CV_SIMD || CV_SIMD_SCALABLE)
const int vlanes = VTraits<v_float32>::vlanes();
v_float32 one = vx_setall_f32(1.f), z = vx_setzero_f32();
const size_t step2 = (size_t)vlanes * 2;
v_float32 one = vx_setall_f32(1.f);
v_float32 min_val = vx_setall_f32(-80.f), max_val = vx_setall_f32(88.f);
// Using identity: 1 / (1 + exp(-x)) == 1 - (1 / (1 + exp(x))).
// Clamping x to [-80.f, 88.f] prevents v_exp overflow and subnormal underflow.
for (; i + step2 <= len; i += step2) {
v_float32 x0 = vx_load(inp + i);
v_float32 x1 = vx_load(inp + i + vlanes);
x0 = v_min(v_max(x0, min_val), max_val);
x1 = v_min(v_max(x1, min_val), max_val);
v_float32 y0 = v_sub(one, v_div(one, v_add(one, v_exp(x0))));
v_float32 y1 = v_sub(one, v_div(one, v_add(one, v_exp(x1))));
vx_store(out + i, y0);
vx_store(out + i + vlanes, y1);
}
for (; i + vlanes <= len; i += vlanes) {
v_float32 x = vx_load(inp + i);
v_float32 t = v_exp(v_sub(z, x));
t = v_div(one, v_add(one, t));
vx_store(out + i, t);
x = v_min(v_max(x, min_val), max_val);
vx_store(out + i, v_sub(one, v_div(one, v_add(one, v_exp(x)))));
}
#endif
for (; i < len; i++) {