/* * 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 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(window.x().start()); const int window_end_x = static_cast(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(input_itr.ptr()); auto out_ptr = reinterpret_cast(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(*(in_ptr + x)); sum += data; sum_sq += (data * data); } const float mean = (static_cast(sum) / static_cast(input->info()->dimension(0))); const float var = (static_cast(sum_sq) / static_cast(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(*(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