text: /*
   * 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/CL/functions/CLGEMMLowpOutputStage.h"
  
  #include "arm_compute/core/CL/ICLTensor.h"
  #include "arm_compute/core/Types.h"
  #include "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel.h"
  #include "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.h"
  #include "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h"
  
  #include <algorithm>
  
  namespace arm_compute
  {
  void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
                                                                      int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
                                                                      int min, int max)
  {
      configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
  }
  
  void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
                                                                      int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
                                                                      int min, int max)
  {
      GEMMLowpOutputStageInfo info{};
      info.gemmlowp_multiplier = result_fixedpoint_multiplier;
      info.gemmlowp_shift      = result_shift;
      info.gemmlowp_offset     = result_offset_after_shift;
      info.gemmlowp_min_bound  = min;
      info.gemmlowp_max_bound  = max;
      info.output_data_type    = DataType::QASYMM8;
      auto k                   = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>();
      k->configure(compile_context, input, bias, output, &info);
      _kernel = std::move(k);
  }
  
  Status CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output,
                                                                       int min, int max)
  {
      GEMMLowpOutputStageInfo info{};
      info.gemmlowp_min_bound = min;
      info.gemmlowp_max_bound = max;
      info.output_data_type   = DataType::QASYMM8;
      return CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel::validate(input, bias, output, &info);
  }
  
  void CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
                                                                     int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
                                                                     int min, int max)
  {
      configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max);
  }
  
  void CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
                                                                     int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift,
                                                                     int min, int max)
  {
      GEMMLowpOutputStageInfo info{};
      info.gemmlowp_multiplier = result_fixedpoint_multiplier;
      info.gemmlowp_shift      = result_shift;
      info.gemmlowp_offset     = result_offset_after_shift;
      info.gemmlowp_min_bound  = min;
      info.gemmlowp_max_bound  = max;
      info.output_data_type    = DataType::QASYMM8_SIGNED;
      auto k                   = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>();
      k->configure(compile_context, input, bias, output, &info);
      _kernel = std::move(k);
  }
  
  Status CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output,
                                                                      int min, int max)
  {
      GEMMLowpOutputStageInfo info{};
      info.gemmlowp_min_bound = min;
      info.gemmlowp_max_bound = max;
      info.output_data_type   = DataType::QASYMM8_SIGNED;
      return CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel::validate(input, bias, output, &info);
  }
  
  void CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
                                                                      int result_fixedpoint_multiplier, int result_shift,
                                                                      int min, int max)
  {
      configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, result_fixedpoint_multiplier, result_shift, min, max);
  }
  
  void CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output,
                                                                      int result_fixedpoint_multiplier, int result_shift,
                                                                      int min, int max)
  {
      GEMMLowpOutputStageInfo info{};
      info.gemmlowp_multiplier = result_fixedpoint_multiplier;
      info.gemmlowp_shift      = result_shift;
      info.gemmlowp_min_bound  = min;
      info.gemmlowp_max_bound  = max;
      info.output_data_type    = DataType::QSYMM16;
      auto k                   = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>();
      k->configure(compile_context, input, bias, output, &info);
      _kernel = std::move(k);
  }
  
  Status CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output,
                                                                       int min, int max)
  {
      GEMMLowpOutputStageInfo info{};
      info.gemmlowp_min_bound = min;
      info.gemmlowp_max_bound = max;
      info.output_data_type   = DataType::QSYMM16;
      return CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel::validate(input, bias, output, &info);
  }
  
  void CLGEMMLowpOutputStage::configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo &info)
  {
      configure(CLKernelLibrary::get().get_compile_context(), input, bias, output, info);
  }
  
  void CLGEMMLowpOutputStage::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const GEMMLowpOutputStageInfo &info)
  {
      ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
  
      switch(info.type)
      {
          case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT:
          {
              auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>();
              k->configure(compile_context, input, bias, output, &info);
              _kernel = std::move(k);
              break;
          }
          case GEMMLowpOutputStageType::QUANTIZE_DOWN:
          {
              auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleKernel>();
              k->configure(compile_context, input, bias, output, &info);
              _kernel = std::move(k);
              break;
          }
          case GEMMLowpOutputStageType::QUANTIZE_DOWN_FLOAT:
          {
              auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel>();
              k->configure(compile_context, input, bias, output, &info);
              _kernel = std::move(k);
              break;
          }
          default:
              ARM_COMPUTE_ERROR("Unsupported GEMMLowpOutputStage type.");
      }
  }
  
  Status CLGEMMLowpOutputStage::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_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM16);
  
      switch(info.type)
      {
          case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT:
              return CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel::validate(input, bias, output, &info);
          case GEMMLowpOutputStageType::QUANTIZE_DOWN:
              return CLGEMMLowpQuantizeDownInt32ScaleKernel::validate(input, bias, output, &info);
          case GEMMLowpOutputStageType::QUANTIZE_DOWN_FLOAT:
              return CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel::validate(input, bias, output, &info);
          default:
              return ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Unsupported GEMMLowpOutputStage type.");
      }
  }
  } // namespace arm_compute
  