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/*
* Copyright (c) 2022 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 "src/core/NEON/NEAsymm.h"
#include "src/core/NEON/NEMath.h"
#include "src/core/NEON/wrapper/wrapper.h"
#include <arm_neon.h>
namespace
{
inline float32x4_t clamp_v4f32(float32x4_t block, float32x4_t quant_min_vec, float32x4_t quant_max_vec)
{
return vminq_f32(vmaxq_f32(block, quant_min_vec), quant_max_vec);
}
inline uint16x8_t fuse_words_f32(float32x4_t fb1, float32x4_t fb2)
{
return vcombine_u16(vmovn_u32(vcvtq_u32_f32(fb1)), vmovn_u32(vcvtq_u32_f32(fb2)));
}
inline uint8x16_t fuse_shorts_u16(uint16x8_t sb1, uint16x8_t sb2)
{
return vcombine_u8(vmovn_u16(sb1), vmovn_u16(sb2));
}
} // namespace
namespace arm_compute
{
namespace cpu
{
void neon_qasymm8_meanstddevnorm(ITensor *input, ITensor *output, float epsilon, const Window &window)
{
Window win = window;
win.set(Window::DimX, Window::Dimension(0, 1, 1));
const int window_step_x = 16;
const int window_start_x = static_cast<int>(window.x().start());
const int window_end_x = static_cast<int>(window.x().end());
const UniformQuantizationInfo qi_out = output->info()->quantization_info().uniform();
const float output_scale = qi_out.scale;
const int output_offset = qi_out.offset;
Iterator input_itr(input, win);
Iterator output_itr(output, win);
const float output_inv_scale = 1.0f / output_scale;
const float32x4_t quant_max_vec = vdupq_n_f32(255.0f);
const float32x4_t quant_min_vec = vdupq_n_f32(0.0f);
execute_window_loop(
win,
[&](const Coordinates &)
{
int x = window_start_x;
auto in_ptr = reinterpret_cast<const uint8_t *>(input_itr.ptr());
auto out_ptr = reinterpret_cast<uint8_t *>(output_itr.ptr());
uint32x4_t sum_vec = vdupq_n_u32(0);
uint32x4_t sum_sq_vec = vdupq_n_u32(0);
for (; x <= (window_end_x - window_step_x); x += window_step_x)
{
const uint8x16_t data = vld1q_u8(in_ptr + x);
sum_vec = vaddq_u32(sum_vec, vpaddlq_u16(vpaddlq_u8(data)));
const uint16x8_t squares_low = vmull_u8(vget_low_u8(data), vget_low_u8(data));
const uint16x8_t squares_high = vmull_u8(vget_high_u8(data), vget_high_u8(data));
sum_sq_vec = vaddq_u32(sum_sq_vec, vaddq_u32(vpaddlq_u16(squares_low), vpaddlq_u16(squares_high)));
}
#ifdef __aarch64__
sum_vec = vpaddq_u32(sum_vec, sum_vec);
sum_vec = vpaddq_u32(sum_vec, sum_vec);
uint32_t sum = vgetq_lane_u32(sum_vec, 0);
sum_sq_vec = vpaddq_u32(sum_sq_vec, sum_sq_vec);
sum_sq_vec = vpaddq_u32(sum_sq_vec, sum_sq_vec);
uint32_t sum_sq = vgetq_lane_u32(sum_sq_vec, 0);
#elif __arm__ // #ifdef __aarch64__
uint32_t sum = vgetq_lane_u32(sum_vec, 0) + vgetq_lane_u32(sum_vec, 1) + vgetq_lane_u32(sum_vec, 2) +
vgetq_lane_u32(sum_vec, 3);
uint32_t sum_sq = vgetq_lane_u32(sum_sq_vec, 0) + vgetq_lane_u32(sum_sq_vec, 1) +
vgetq_lane_u32(sum_sq_vec, 2) + vgetq_lane_u32(sum_sq_vec, 3);
#endif // #ifdef __aarch64__
for (; x < window_end_x; ++x)
{
auto data = static_cast<uint32_t>(*(in_ptr + x));
sum += data;
sum_sq += (data * data);
}
const float mean = (static_cast<float>(sum) / static_cast<float>(input->info()->dimension(0)));
const float var =
(static_cast<float>(sum_sq) / static_cast<float>(input->info()->dimension(0))) - (mean * mean);
const float stdev_inv = 1.0f / sqrtf(var + epsilon);
const float32x4_t v_scale = vdupq_n_f32(stdev_inv * output_inv_scale);
const float32x4_t v_offset = vdupq_n_f32(-mean * stdev_inv * output_inv_scale + output_offset);
for (x = window_start_x; x <= (window_end_x - window_step_x); x += window_step_x)
{
const uint8x16_t data = vld1q_u8(in_ptr + x);
float32x4_t db1 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(data)))));
float32x4_t db2 = vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(data)))));
float32x4_t db3 = vcvtq_f32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(data)))));
float32x4_t db4 = vcvtq_f32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(data)))));
db1 = clamp_v4f32(vaddq_f32(vmulq_f32(db1, v_scale), v_offset), quant_min_vec, quant_max_vec);
db2 = clamp_v4f32(vaddq_f32(vmulq_f32(db2, v_scale), v_offset), quant_min_vec, quant_max_vec);
db3 = clamp_v4f32(vaddq_f32(vmulq_f32(db3, v_scale), v_offset), quant_min_vec, quant_max_vec);
db4 = clamp_v4f32(vaddq_f32(vmulq_f32(db4, v_scale), v_offset), quant_min_vec, quant_max_vec);
const uint8x16_t out = fuse_shorts_u16(fuse_words_f32(db1, db2), fuse_words_f32(db3, db4));
vst1q_u8(out_ptr + x, out);
}
for (; x < window_end_x; ++x)
{
auto data = static_cast<float32_t>(*(in_ptr + x));
const uint8_t res =
data * (stdev_inv * output_inv_scale) + (-mean * stdev_inv * output_inv_scale + output_offset);
*(out_ptr + x) = res;
}
},
input_itr, output_itr);
}
} // namespace cpu
} // namespace arm_compute
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