| /* |
| * Copyright (c) 2017-2020 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/runtime/NEON/functions/NEGEMMLowpOutputStage.h" |
| |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ScaleKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h" |
| #include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h" |
| #include "arm_compute/core/Validate.h" |
| #include "support/MemorySupport.h" |
| |
| namespace arm_compute |
| { |
| void NEGEMMLowpQuantizeDownInt32ToUint8Scale::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_offset, int result_mult_int, int result_shift, int min, int max) |
| { |
| GEMMLowpOutputStageInfo info = GEMMLowpOutputStageInfo(); |
| info.gemmlowp_offset = result_offset; |
| info.gemmlowp_multiplier = result_mult_int; |
| info.gemmlowp_shift = result_shift; |
| info.gemmlowp_min_bound = min; |
| info.gemmlowp_max_bound = max; |
| |
| auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ScaleKernel>(); |
| k->configure(input, bias, output, &info); |
| _kernel = std::move(k); |
| } |
| |
| Status NEGEMMLowpQuantizeDownInt32ToUint8Scale::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) |
| { |
| GEMMLowpOutputStageInfo info = GEMMLowpOutputStageInfo(); |
| info.gemmlowp_min_bound = min; |
| info.gemmlowp_max_bound = max; |
| |
| return NEGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); |
| } |
| |
| void NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, |
| int result_offset_after_shift, int min, int max) |
| { |
| auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); |
| k->configure(input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max); |
| _kernel = std::move(k); |
| } |
| |
| Status NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) |
| { |
| return NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, min, max); |
| } |
| |
| void NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, |
| int result_offset_after_shift, int min, int max) |
| { |
| auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); |
| k->configure(input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max); |
| _kernel = std::move(k); |
| } |
| |
| Status NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) |
| { |
| return NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, min, max); |
| } |
| |
| void NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int min, int max) |
| { |
| auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>(); |
| k->configure(input, bias, output, result_fixedpoint_multiplier, result_shift, min, max); |
| _kernel = std::move(k); |
| } |
| |
| Status NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min, int max) |
| { |
| return NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::validate(input, bias, output, min, max); |
| } |
| |
| void NEGEMMLowpOutputStage::configure(const ITensor *input, const ITensor *bias, ITensor *output, const GEMMLowpOutputStageInfo &info) |
| { |
| // Perform validate step |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_ERROR_THROW_ON(NEGEMMLowpOutputStage::validate(input->info(), bias != nullptr ? bias->info() : nullptr, output->info(), info)); |
| |
| switch(info.type) |
| { |
| case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: |
| { |
| switch(info.output_data_type) |
| { |
| case DataType::QASYMM8: |
| { |
| auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); |
| k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); |
| _kernel = std::move(k); |
| break; |
| } |
| case DataType::QASYMM8_SIGNED: |
| { |
| auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); |
| k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); |
| _kernel = std::move(k); |
| break; |
| } |
| case DataType::QSYMM16: |
| { |
| auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>(); |
| k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_min_bound, info.gemmlowp_max_bound); |
| _kernel = std::move(k); |
| break; |
| } |
| default: |
| { |
| ARM_COMPUTE_ERROR("Unsupported output data type."); |
| break; |
| } |
| } |
| break; |
| } |
| case GEMMLowpOutputStageType::QUANTIZE_DOWN: |
| { |
| switch(info.output_data_type) |
| { |
| case DataType::QASYMM8: |
| case DataType::QASYMM8_SIGNED: |
| { |
| auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ScaleKernel>(); |
| k->configure(input, bias, output, &info); |
| _kernel = std::move(k); |
| break; |
| } |
| default: |
| { |
| ARM_COMPUTE_ERROR("Unsupported output data type."); |
| break; |
| } |
| } |
| break; |
| } |
| default: |
| ARM_COMPUTE_ERROR("Unsupported GEMMLowpOutputStage type."); |
| } |
| } |
| |
| Status NEGEMMLowpOutputStage::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo &info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::UNKNOWN, "NEGEMMLowpQuantizeDownScaleByFixedPoint cannot be used with UNKNOWN output data type."); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON((info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN) && (info.type != GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT)); |
| |
| switch(info.type) |
| { |
| case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: |
| { |
| switch(output->data_type()) |
| { |
| case DataType::QASYMM8: |
| return NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); |
| case DataType::QASYMM8_SIGNED: |
| return NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); |
| case DataType::QSYMM16: |
| return NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel::validate(input, bias, output, info.gemmlowp_min_bound, info.gemmlowp_max_bound); |
| default: |
| return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); |
| } |
| } |
| case GEMMLowpOutputStageType::QUANTIZE_DOWN: |
| { |
| switch(output->data_type()) |
| { |
| case DataType::QASYMM8: |
| case DataType::QASYMM8_SIGNED: |
| return NEGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info); |
| default: |
| return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported output data type."); |
| } |
| } |
| default: |
| return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported GEMMLowpOutputStage type."); |
| } |
| } |
| } // namespace arm_compute |