| /* |
| * Copyright (c) 2017 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/NEON/kernels/NEQuantizationLayerKernel.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| |
| #include <arm_neon.h> |
| |
| using namespace arm_compute; |
| |
| NEQuantizationLayerKernel::NEQuantizationLayerKernel() |
| : _input(nullptr), _output(nullptr), _min(nullptr), _max(nullptr) |
| { |
| } |
| |
| void NEQuantizationLayerKernel::configure(const ITensor *input, ITensor *output, const float *min, const float *max) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(output); |
| |
| // Output tensor auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, DataType::U8, 0); |
| |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| |
| _input = input; |
| _output = output; |
| _min = min; |
| _max = max; |
| |
| constexpr unsigned int num_elems_processed_per_iteration = 8; |
| |
| // Configure window |
| Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); |
| AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); |
| update_window_and_padding(win, AccessWindowHorizontal(input->info(), 0, num_elems_processed_per_iteration), output_access); |
| output_access.set_valid_region(win, input->info()->valid_region()); |
| |
| INEKernel::configure(win); |
| } |
| |
| void NEQuantizationLayerKernel::run(const Window &window, const ThreadInfo &info) |
| { |
| ARM_COMPUTE_UNUSED(info); |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); |
| |
| Iterator input(_input, window); |
| Iterator output(_output, window); |
| |
| const float32x4_t vmin = vdupq_n_f32(*_min); |
| const float32x4_t inv_range = vdupq_n_f32(1.0f / (*_max - *_min)); |
| const float32x4_t quantization_max = vdupq_n_f32(255.0f); |
| const float32x4_t quantization_mul = vdupq_n_f32(256.0f); |
| |
| // Uniformly map values to range 8bit integers, i.e. [min, max] -> [0, 255] |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| float32x4x2_t val = vld2q_f32(reinterpret_cast<const float *>(input.ptr())); |
| // Map float values to range [0.0, 1.0] |
| val.val[0] = vsubq_f32(val.val[0], vmin); |
| val.val[1] = vsubq_f32(val.val[1], vmin); |
| val.val[0] = vmulq_f32(val.val[0], inv_range); |
| val.val[1] = vmulq_f32(val.val[1], inv_range); |
| |
| // Quantize |
| val.val[0] = vmulq_f32(val.val[0], quantization_mul); |
| val.val[1] = vmulq_f32(val.val[1], quantization_mul); |
| val.val[0] = vminq_f32(val.val[0], quantization_max); |
| val.val[1] = vminq_f32(val.val[1], quantization_max); |
| |
| const uint32x4_t val_u32_low = vcvtq_u32_f32(val.val[0]); |
| const uint32x4_t val_u32_high = vcvtq_u32_f32(val.val[1]); |
| const uint16x4x2_t val_u16 = vzip_u16(vmovn_u32(val_u32_low), vmovn_u32(val_u32_high)); |
| |
| const uint8x8_t quantized = vmovn_u16(vcombine_u16(val_u16.val[0], val_u16.val[1])); |
| vst1_u8(reinterpret_cast<uint8_t *>(output.ptr()), quantized); |
| }, |
| input, output); |
| } |