LeakyRelu.cpp

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/*
 * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 
#include "kernels/LeakyRelu.h"
 
#include "kernels/Utils.h"
 
#include <tensorflow/lite/kernels/internal/reference/leaky_relu.h>
 
#include "PALLeakyRelu.h"
 
#include <stdexcept>
 
namespace luci_interpreter
{
 
namespace kernels
{
 
LeakyRelu::LeakyRelu(const Tensor *input, Tensor *output, const LeakyReluParams &params)
  : KernelWithParams<LeakyReluParams>({input}, {output}, params)
{
}
 
void LeakyRelu::configure()
{
  LUCI_INTERPRETER_CHECK(input()->element_type() == output()->element_type());
  if (input()->element_type() == DataType::U8)
  {
    double alpha_multiplier = input()->scale() * params().alpha / output()->scale();
    quantizeMultiplier(alpha_multiplier, &_output_multiplier_alpha, &_output_shift_alpha);
    double identity_multiplier = input()->scale() / output()->scale();
    quantizeMultiplier(identity_multiplier, &_output_multiplier_identity, &_output_shift_identity);
  }
  output()->resize(input()->shape());
}
 
void LeakyRelu::execute() const
{
  switch (input()->element_type())
  {
    case DataType::FLOAT32:
      evalFloat();
      break;
    case DataType::U8:
      evalQuantized();
      break;
    default:
      throw std::runtime_error("luci-intp LeakyRelu Unsupported type.");
  }
}
 
void LeakyRelu::evalFloat() const
{
  tflite::LeakyReluParams op_params{};
  op_params.alpha = params().alpha;
  luci_interpreter_pal::LeakyRelu(op_params, getTensorShape(input()), getTensorData<float>(input()),
                                  getTensorShape(output()), getTensorData<float>(output()));
}
 
void LeakyRelu::evalQuantized() const
{
  tflite::LeakyReluParams op_params{};
  op_params.input_offset = input()->zero_point();
  op_params.output_offset = output()->zero_point();
  op_params.output_multiplier_alpha = _output_multiplier_alpha;
  op_params.output_shift_alpha = _output_shift_alpha;
  op_params.output_multiplier_identity = _output_multiplier_identity;
  op_params.output_shift_identity = _output_shift_identity;
 
  tflite::reference_ops::QuantizeLeakyRelu(
    op_params, getTensorShape(input()), getTensorData<uint8_t>(input()), getTensorShape(output()),
    getTensorData<uint8_t>(output()));
}
 
} // namespace kernels
} // namespace luci_interpreter