PALAveragePool2D.h

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/*
 * Copyright (c) 2023 Samsung Electronics Co., Ltd. All Rights Reserved
 * Copyright 2020 The TensorFlow Authors. 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.
 */
 
#ifndef LUCI_INTERPRETER_PAL_CMSIS_NN_AVERAGE_POOL_2D_H
#define LUCI_INTERPRETER_PAL_CMSIS_NN_AVERAGE_POOL_2D_H
 
#include "PALAveragePool2DCommon.h"
 
#include <arm_nnfunctions.h>
 
namespace luci_interpreter_pal
{
inline void AveragePool(const PoolParams &params, const luci_interpreter::RuntimeShape &input_shape,
                        const uint8_t *input_data,
                        const luci_interpreter::RuntimeShape &output_shape, uint8_t *output_data,
                        luci_interpreter::DataType data_type)
{
  cmsis_nn_dims input_dims;
  cmsis_nn_dims output_dims;
  cmsis_nn_pool_params pool_params;
  cmsis_nn_dims filter_dims;
  cmsis_nn_context ctx;
 
  const int depth = input_shape.dims(3);
  const int output_width = output_shape.dims(2);
 
  input_dims.n = 1;
  input_dims.h = input_shape.dims(1);
  input_dims.w = input_shape.dims(2);
  input_dims.c = depth;
 
  output_dims.n = 1;
  output_dims.h = output_shape.dims(1);
  output_dims.w = output_width;
  output_dims.c = depth;
 
  pool_params.stride.h = params.stride_height;
  pool_params.stride.w = params.stride_width;
  pool_params.padding.h = params.padding_values.height;
  pool_params.padding.w = params.padding_values.width;
  pool_params.activation.min = params.quantized_activation_min;
  pool_params.activation.max = params.quantized_activation_max;
 
  filter_dims.n = 1;
  filter_dims.h = params.filter_height;
  filter_dims.w = params.filter_width;
  filter_dims.c = 1;
 
  const int32_t buffer_size = data_type == luci_interpreter::DataType::S16
                                ? arm_avgpool_s16_get_buffer_size(output_width, depth)
                                : arm_avgpool_s8_get_buffer_size(output_width, depth);
  int8_t *buffer = nullptr;
  if (buffer_size > 0)
  {
    buffer = new int8_t[buffer_size];
  }
 
  ctx.buf = buffer;
  ctx.size = buffer_size;
 
  if (data_type == luci_interpreter::DataType::S8)
  {
    arm_avgpool_s8(&ctx, &pool_params, &input_dims,
                   luci_interpreter::kernels::getTensorData<int8_t>(input_data), &filter_dims,
                   &output_dims, luci_interpreter::kernels::getTensorData<int8_t>(output_data));
  }
  else
  {
    arm_avgpool_s16(&ctx, &pool_params, &input_dims,
                    luci_interpreter::kernels::getTensorData<int16_t>(input_data), &filter_dims,
                    &output_dims, luci_interpreter::kernels::getTensorData<int16_t>(output_data));
  }
 
  if (buffer_size > 0)
    delete[] buffer;
}
} // namespace luci_interpreter_pal
 
#endif // LUCI_INTERPRETER_PAL_CMSIS_NN_AVERAGE_POOL_2D_H