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Diffstat (limited to 'src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.cpp | 320 |
1 files changed, 0 insertions, 320 deletions
diff --git a/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.cpp b/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.cpp deleted file mode 100644 index 84365ba25b..0000000000 --- a/src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.cpp +++ /dev/null @@ -1,320 +0,0 @@ -/* - * Copyright (c) 2020-2021 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 "src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.h" - -#include "arm_compute/core/Error.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/ITensor.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.h" -#include "arm_compute/core/utils/quantization/AsymmHelpers.h" -#include "src/core/AccessWindowStatic.h" -#include "src/core/NEON/wrapper/wrapper.h" -#include "src/core/helpers/AutoConfiguration.h" -#include "src/core/helpers/WindowHelpers.h" - -#include <arm_neon.h> -#include <cstddef> -#include <cstdint> - -namespace arm_compute -{ -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage) -{ - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::S32); - - ARM_COMPUTE_RETURN_ERROR_ON(output_stage->gemmlowp_max_bound > std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))); - ARM_COMPUTE_RETURN_ERROR_ON(output_stage->gemmlowp_min_bound < std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type)) - || output_stage->gemmlowp_min_bound > output_stage->gemmlowp_max_bound); - - // Check biases if exist - if(bias != nullptr) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); - ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1); - ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(0) != bias->dimension(0)); - } - - if(output->total_size() != 0) - { - if(output->data_type() != output_stage->output_data_type && (output_stage->output_data_type == DataType::QASYMM8 || output_stage->output_data_type == DataType::QASYMM8_SIGNED)) - { - ARM_COMPUTE_RETURN_ERROR_MSG("Mismatching data types"); - } - - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); - } - - return Status{}; -} - -inline void scale_input(int32x4x4_t &in_s32, int32x4_t result_offset_s32, int32_t result_mult_int) -{ - // Add the offset terms to GEMM's result - in_s32.val[0] = vaddq_s32(in_s32.val[0], result_offset_s32); - in_s32.val[1] = vaddq_s32(in_s32.val[1], result_offset_s32); - in_s32.val[2] = vaddq_s32(in_s32.val[2], result_offset_s32); - in_s32.val[3] = vaddq_s32(in_s32.val[3], result_offset_s32); - - // Multiply by result_mult_int - in_s32.val[0] = vmulq_n_s32(in_s32.val[0], result_mult_int); - in_s32.val[1] = vmulq_n_s32(in_s32.val[1], result_mult_int); - in_s32.val[2] = vmulq_n_s32(in_s32.val[2], result_mult_int); - in_s32.val[3] = vmulq_n_s32(in_s32.val[3], result_mult_int); -} - -template <typename T> -inline typename std::enable_if<std::is_same<T, uint8_t>::value, - typename wrapper::traits::neon_vector<T, 16>::type>::type - convert_to_8bit(const int16x8x2_t in_s16) -{ - return wrapper::vcombine(wrapper::vqmovun(in_s16.val[0]), wrapper::vqmovun(in_s16.val[1])); -} - -template <typename T> -inline typename std::enable_if<std::is_same<T, int8_t>::value, - typename wrapper::traits::neon_vector<T, 16>::type>::type - convert_to_8bit(const int16x8x2_t in_s16) -{ - return wrapper::vcombine(wrapper::vqmovn(in_s16.val[0]), wrapper::vqmovn(in_s16.val[1])); -} - -template <typename T> -inline typename wrapper::traits::neon_vector<T, 16>::type finalize_quantization(int32x4x4_t &in_s32, int32x4_t result_shift_s32, typename wrapper::traits::neon_vector<T, 16>::type min, - typename wrapper::traits::neon_vector<T, 16>::type max) -{ - // Shift final result (negative value shift right) - in_s32.val[0] = vshlq_s32(in_s32.val[0], result_shift_s32); - in_s32.val[1] = vshlq_s32(in_s32.val[1], result_shift_s32); - in_s32.val[2] = vshlq_s32(in_s32.val[2], result_shift_s32); - in_s32.val[3] = vshlq_s32(in_s32.val[3], result_shift_s32); - - // Convert S32 to S16 - const int16x8x2_t in_s16 = - { - { - vcombine_s16(vqmovn_s32(in_s32.val[0]), vqmovn_s32(in_s32.val[1])), - vcombine_s16(vqmovn_s32(in_s32.val[2]), vqmovn_s32(in_s32.val[3])) - } - }; - - // Convert S16 to S8 or U8 - typename wrapper::traits::neon_vector<T, 16>::type out = convert_to_8bit<T>(in_s16); - - out = wrapper::vmax(out, min); - out = wrapper::vmin(out, max); - - return out; -} - -class Coordinates; - -template <typename T> -void NEGEMMLowpQuantizeDownInt32ScaleKernel::run(const Window &window) -{ - using VectorType = typename wrapper::traits::neon_vector<T, 16>::type; - - const int32x4_t result_offset_s32 = vdupq_n_s32(_output_stage->gemmlowp_offset); - const int32x4_t result_shift_s32 = vdupq_n_s32(-_output_stage->gemmlowp_shift); - const int window_step_x = 16; - const auto window_start_x = static_cast<int>(window.x().start()); - const auto window_end_x = static_cast<int>(window.x().end()); - - const int clamp_min = (_is_bounded_relu) ? _output_stage->gemmlowp_min_bound : std::numeric_limits<T>::lowest(); - const int clamp_max = (_is_bounded_relu) ? _output_stage->gemmlowp_max_bound : std::numeric_limits<T>::max(); - - VectorType min = wrapper::vdup_n(static_cast<T>(clamp_min), wrapper::traits::vector_128_tag{}); - VectorType max = wrapper::vdup_n(static_cast<T>(clamp_max), wrapper::traits::vector_128_tag{}); - - Window win(window); - win.set(Window::DimX, Window::Dimension(0, 1, 1)); - - Iterator in(_input, win); - Iterator out(_output, win); - - if(_bias != nullptr) - { - Window win_biases; - win_biases.set(Window::DimX, Window::Dimension(0, 1, 1)); - win_biases.set(Window::DimY, Window::Dimension(0, 1, 1)); - - Iterator bias(_bias, win_biases); - execute_window_loop(win, [&](const Coordinates &) - { - // Compute 16 elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - int32x4x4_t in_s32 = - { - { - vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 0), - vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 4), - vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 8), - vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 12) - } - }; - - const int32x4x4_t bias_s32 = - { - { - vld1q_s32(reinterpret_cast<const int32_t *>(bias.ptr()) + x + 0), - vld1q_s32(reinterpret_cast<const int32_t *>(bias.ptr()) + x + 4), - vld1q_s32(reinterpret_cast<const int32_t *>(bias.ptr()) + x + 8), - vld1q_s32(reinterpret_cast<const int32_t *>(bias.ptr()) + x + 12) - } - }; - - // Add the bias to GEMM's result - in_s32.val[0] = vaddq_s32(in_s32.val[0], bias_s32.val[0]); - in_s32.val[1] = vaddq_s32(in_s32.val[1], bias_s32.val[1]); - in_s32.val[2] = vaddq_s32(in_s32.val[2], bias_s32.val[2]); - in_s32.val[3] = vaddq_s32(in_s32.val[3], bias_s32.val[3]); - - // Add the offset terms to GEMM's result and multiply by result_mult_int - scale_input(in_s32, result_offset_s32, _output_stage->gemmlowp_multiplier); - - wrapper::vstore(reinterpret_cast<T *>(out.ptr() + x), finalize_quantization<T>(in_s32, result_shift_s32, min, max)); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - const int bias_value = *(reinterpret_cast<const int *>(bias.ptr()) + x); - int in_value = *(reinterpret_cast<const int *>(in.ptr()) + x); - - // Quantize - in_value = ((in_value + bias_value + _output_stage->gemmlowp_offset) * _output_stage->gemmlowp_multiplier) >> _output_stage->gemmlowp_shift; - - // Store the result - *(out.ptr() + x) = static_cast<T>(utility::clamp<int>(in_value, clamp_min, clamp_max)); - } - }, - in, bias, out); - } - else - { - execute_window_loop(win, [&](const Coordinates &) - { - // Compute 16 elements per iteration - int x = window_start_x; - for(; x <= (window_end_x - window_step_x); x += window_step_x) - { - int32x4x4_t in_s32 = - { - { - vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 0), - vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 4), - vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 8), - vld1q_s32(reinterpret_cast<const int32_t *>(in.ptr()) + x + 12) - } - }; - - // Add the offset terms to GEMM's result and multiply by result_mult_int - scale_input(in_s32, result_offset_s32, _output_stage->gemmlowp_multiplier); - - wrapper::vstore(reinterpret_cast<T *>(out.ptr() + x), finalize_quantization<T>(in_s32, result_shift_s32, min, max)); - } - - // Compute left-over elements - for(; x < window_end_x; ++x) - { - int in_value = *(reinterpret_cast<const int *>(in.ptr()) + x); - - // Quantize - in_value = ((in_value + _output_stage->gemmlowp_offset) * _output_stage->gemmlowp_multiplier) >> _output_stage->gemmlowp_shift; - - // Store the result - *(out.ptr() + x) = static_cast<T>(utility::clamp<int>(in_value, clamp_min, clamp_max)); - } - }, - in, out); - } -} - -NEGEMMLowpQuantizeDownInt32ScaleKernel::NEGEMMLowpQuantizeDownInt32ScaleKernel() - : _func(nullptr), _input(nullptr), _bias(nullptr), _output(nullptr), _output_stage(nullptr), _is_bounded_relu(false) -{ -} - -void NEGEMMLowpQuantizeDownInt32ScaleKernel::configure(const ITensor *input, const ITensor *bias, ITensor *output, const GEMMLowpOutputStageInfo *output_stage) -{ - // Perform validate step - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, output_stage); - - // Output auto inizialitation if not yet initialized - auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(output_stage->output_data_type)); - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), - (bias != nullptr) ? bias->info() : nullptr, - output->info(), - output_stage)); - - _input = input; - _bias = bias; - _output = output; - _output_stage = output_stage; - - // Configure kernel window - Window win = calculate_max_window(*input->info(), Steps()); - - INEKernel::configure(win); - - // Check if we need to clamp the result using min and max - _is_bounded_relu = ((_output_stage->gemmlowp_min_bound != _output_stage->gemmlowp_max_bound) - && !(_output_stage->gemmlowp_min_bound == std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type)) - && _output_stage->gemmlowp_max_bound == std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type)))); - if(_output_stage->output_data_type == DataType::QASYMM8) - { - _func = &NEGEMMLowpQuantizeDownInt32ScaleKernel::run<uint8_t>; - } - else if(_output_stage->output_data_type == DataType::QASYMM8_SIGNED) - { - _func = &NEGEMMLowpQuantizeDownInt32ScaleKernel::run<int8_t>; - } - else - { - ARM_COMPUTE_ERROR("Data type not supported"); - } -} - -Status NEGEMMLowpQuantizeDownInt32ScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, bias, output, output_stage)); - - return Status{}; -} - -void NEGEMMLowpQuantizeDownInt32ScaleKernel::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); - - (this->*_func)(window); -} -} // namespace arm_compute
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