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/*
* Copyright (c) 2020-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Window.h"
#include "arm_compute/function_info/ActivationLayerInfo.h"
#include "src/core/NEON/wrapper/wrapper.h"
namespace arm_compute
{
namespace cpu
{
/** Constant parameters needed by the activation implementation.
* These parameters differ for each floating type
*
* @note This are passed as a struct as C++ does not allow float as a template parameter until C++20
**/
struct ActFpImplParams
{
float delta; /**< Minimum delta needed to avoid NaN on corner-cases of elementary functions */
int step_x; /**< Window step at the x dimension */
};
#ifndef __aarch64__
inline float32x4_t mask_float_vector(const float32x4_t &in, const uint32x4_t &mask)
{
auto int_in = vreinterpretq_u32_f32(in);
return vreinterpretq_f32_u32(wrapper::vand(int_in, mask));
}
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
inline float16x8_t mask_float_vector(const float16x8_t &in, const uint16x8_t &mask)
{
auto int_in = vreinterpretq_u16_f16(in);
return vreinterpretq_f16_u16(wrapper::vand(int_in, mask));
}
#endif //defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
#endif /* __aarch64__ */
template <typename T, const ActFpImplParams &P>
void fp_neon_activation_impl(const ITensor *src,
ITensor *dst,
const ActivationLayerInfo &act_info,
const Window &window)
{
/** SIMD vector tag type. */
using ExactTagType =
typename arm_compute::wrapper::traits::neon_bitvector_tag_t<T, wrapper::traits::BitWidth::W128>;
constexpr int window_step_x = P.step_x;
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
const ActivationLayerInfo::ActivationFunction act = act_info.activation();
Window win_collapsed = window.collapse_if_possible(window, Window::DimZ);
win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1));
Iterator input(src, win_collapsed);
Iterator output(dst, win_collapsed);
// In case of non-aarch64, a small delta value is added to the input
// to prevent NAN values caused by zeros in inputs to SQRT.
// In case of aarh64, we call vsqrt directly, so we don't use delta.
#ifndef __aarch64__
const auto delta = wrapper::vdup_n(static_cast<T>(P.delta), ExactTagType{});
#else /* #ifndef __aarch64__ */
const auto const_inv_2 = wrapper::vdup_n(static_cast<T>(0.5f), ExactTagType{});
const auto const_inv_sqrt_2 = wrapper::vdup_n(static_cast<T>(0.70710678118f), ExactTagType{});
#endif /* __aarch64__ */
const auto const_1 = wrapper::vdup_n(static_cast<T>(1.f), ExactTagType{});
const auto const_0 = wrapper::vdup_n(static_cast<T>(0.f), ExactTagType{});
const auto const_6 = wrapper::vdup_n(static_cast<T>(6.f), ExactTagType{});
const auto const_3 = wrapper::vdup_n(static_cast<T>(3.f), ExactTagType{});
const auto const_inv_6 = wrapper::vdup_n(static_cast<T>(0.166666667f), ExactTagType{});
constexpr float soft_relu_thresh = 12.f;
const auto vsoft_relu_thresh = wrapper::vdup_n(static_cast<T>(soft_relu_thresh), ExactTagType{});
const auto va = wrapper::vdup_n(static_cast<T>(act_info.a()), ExactTagType{});
const auto vb = wrapper::vdup_n(static_cast<T>(act_info.b()), ExactTagType{});
const auto a = static_cast<T>(act_info.a());
const auto b = static_cast<T>(act_info.b());
execute_window_loop(
win_collapsed,
[&](const Coordinates &)
{
const auto input_ptr = reinterpret_cast<const T *>(input.ptr());
const auto output_ptr = reinterpret_cast<T *>(output.ptr());
wrapper::traits::neon_bitvector_t<T, wrapper::traits::BitWidth::W128> tmp;
// Compute S elements per iteration
int x = window_start_x;
for (; x <= (window_end_x - window_step_x); x += window_step_x)
{
const auto vin = wrapper::vloadq(input_ptr + x);
switch (act)
{
case ActivationLayerInfo::ActivationFunction::ABS:
tmp = wrapper::vabs(vin);
break;
case ActivationLayerInfo::ActivationFunction::LINEAR:
tmp = wrapper::vmla(vb, va, vin);
break;
case ActivationLayerInfo::ActivationFunction::LOGISTIC:
tmp = wrapper::vinv(wrapper::vadd(const_1, wrapper::vexpq(wrapper::vneg(vin))));
break;
case ActivationLayerInfo::ActivationFunction::RELU:
tmp = wrapper::vmax(const_0, vin);
break;
case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
tmp = wrapper::vmin(va, wrapper::vmax(const_0, vin));
break;
case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
tmp = wrapper::vmin(va, wrapper::vmax(vb, vin));
break;
case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
tmp = wrapper::vbsl(wrapper::vcgt(vin, const_0), vin, wrapper::vmul(va, vin));
break;
case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
tmp = wrapper::vbsl(wrapper::vcgt(vin, vsoft_relu_thresh), vin,
wrapper::vlog(wrapper::vadd(const_1, wrapper::vexpq(vin))));
break;
case ActivationLayerInfo::ActivationFunction::ELU:
tmp = wrapper::vbsl(wrapper::vcge(vin, const_0), vin,
wrapper::vmul(va, wrapper::vsub(wrapper::vexpq(vin), const_1)));
break;
case ActivationLayerInfo::ActivationFunction::SQRT:
#ifdef __aarch64__
tmp = wrapper::vsqrt(vin);
#else /* __aarch64__ */
{
const auto bitmask = wrapper::vceq(vin, wrapper::vdup_n(0.f, ExactTagType{}));
tmp = wrapper::vinv(wrapper::vinvsqrt(wrapper::vadd(vin, mask_float_vector(delta, bitmask))));
tmp = mask_float_vector(tmp, wrapper::vnot(bitmask));
}
#endif /* __aarch64__ */
break;
case ActivationLayerInfo::ActivationFunction::SQUARE:
tmp = wrapper::vmul(vin, vin);
break;
case ActivationLayerInfo::ActivationFunction::TANH:
tmp = wrapper::vmul(va, wrapper::vtanh(wrapper::vmul(vb, vin)));
break;
case ActivationLayerInfo::ActivationFunction::IDENTITY:
tmp = vin;
break;
case ActivationLayerInfo::ActivationFunction::HARD_SWISH:
tmp = wrapper::vmul(
vin,
wrapper::vmul(const_inv_6,
wrapper::vmin(const_6, wrapper::vmax(const_0, wrapper::vadd(vin, const_3)))));
break;
case ActivationLayerInfo::ActivationFunction::SWISH:
tmp = wrapper::vmul(vin, wrapper::vinv(wrapper::vadd(
const_1, wrapper::vexpq(wrapper::vneg(wrapper::vmul(va, vin))))));
break;
#ifdef __aarch64__
case ActivationLayerInfo::ActivationFunction::GELU:
tmp = wrapper::vmul(
vin,
wrapper::vmul(const_inv_2,
wrapper::vadd(const_1, wrapper::verf(wrapper::vmul(vin, const_inv_sqrt_2)))));
break;
#endif /* __aarch64__ */
default:
ARM_COMPUTE_ERROR("Unsupported activation function");
}
wrapper::vstore(output_ptr + x, tmp);
}
// Compute left-over elements
for (; x < window_end_x; ++x)
{
const T in = *(reinterpret_cast<const T *>(input_ptr + x));
T tmp;
switch (act)
{
case ActivationLayerInfo::ActivationFunction::ABS:
tmp = std::abs(in);
break;
case ActivationLayerInfo::ActivationFunction::LINEAR:
tmp = a * in + b;
break;
case ActivationLayerInfo::ActivationFunction::LOGISTIC:
tmp = static_cast<T>(1) / (static_cast<T>(1) + std::exp(-in));
break;
case ActivationLayerInfo::ActivationFunction::RELU:
tmp = std::max<T>(static_cast<T>(0), in);
break;
case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:
tmp = std::min<T>(a, std::max(static_cast<T>(0), in));
break;
case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU:
tmp = std::min<T>(a, std::max<T>(b, in));
break;
case ActivationLayerInfo::ActivationFunction::LEAKY_RELU:
tmp = (in > 0) ? in : a * in;
break;
case ActivationLayerInfo::ActivationFunction::SOFT_RELU:
tmp = (in > soft_relu_thresh) ? in : std::log(static_cast<T>(1) + std::exp(in));
break;
case ActivationLayerInfo::ActivationFunction::ELU:
tmp = (in >= 0) ? in : a * (std::exp(in) - 1);
break;
case ActivationLayerInfo::ActivationFunction::SQRT:
tmp = std::sqrt(in);
break;
case ActivationLayerInfo::ActivationFunction::SQUARE:
tmp = in * in;
break;
case ActivationLayerInfo::ActivationFunction::TANH:
tmp = a * std::tanh(b * in);
break;
case ActivationLayerInfo::ActivationFunction::IDENTITY:
tmp = in;
break;
case ActivationLayerInfo::ActivationFunction::HARD_SWISH:
tmp = in * ((std::min(std::max((in + 3), 0.0f), 6.0f)) * 0.166666667f);
break;
case ActivationLayerInfo::ActivationFunction::SWISH:
tmp = in / (static_cast<T>(1) + std::exp(-a * in));
break;
case ActivationLayerInfo::ActivationFunction::GELU:
tmp = in * static_cast<T>(0.5f * (1.0f + erff(static_cast<float>(in) / 1.41421356237f)));
break;
default:
ARM_COMPUTE_ERROR("Unsupported activation function");
}
*(output_ptr + x) = tmp;
}
},
input, output);
}
} // namespace cpu
} // namespace arm_compute
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