MatrixBandPart.h

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/*
 * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
 * Copyright 2017 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 __NNFW_CKER_MATRIX_BAND_PART_H__
#define __NNFW_CKER_MATRIX_BAND_PART_H__
 
#include "cker/Shape.h"
 
#include <algorithm>
 
namespace nnfw
{
namespace cker
{
template <typename T>
void MatrixBandPart(const T num_lower_diags, const T num_upper_diags, const Shape &input_shape,
                    const float *input_data, const Shape &output_shape, float *output_data)
{
  auto last_dim = input_shape.DimensionsCount() - 1;
 
  T batch_num = 1;
  for (int dim = 0; dim < input_shape.DimensionsCount() - 2; dim++)
  {
    batch_num *= input_shape.Dims(dim);
  }
 
  const T row_num = input_shape.Dims(last_dim - 1);
  const T col_num = input_shape.Dims(last_dim);
 
  if (!(num_lower_diags <= row_num))
    throw std::runtime_error(
      "MatrixBandPart : num_lower must be negative or less or equal to number of rows");
 
  if (!(num_upper_diags <= col_num))
    throw std::runtime_error(
      "MatrixBandPart : num_upper must be negative or less or equal to number of columns");
 
  std::fill(output_data, output_data + output_shape.FlatSize(), 0); // output matrix init
 
  // reference code, without multithreading
  for (T batch = 0; batch < batch_num; ++batch)
  {
    for (T row = 0; row < row_num; ++row)
    {
      auto output = output_data + (batch * row_num * col_num + row * col_num);
      auto input = input_data + (batch * row_num * col_num + row * col_num);
 
      const T band_start =
        num_lower_diags < 0 ? 0 : std::min(col_num, std::max(T{0}, row - num_lower_diags));
      const T band_end = num_upper_diags < 0
                           ? col_num
                           : std::min(static_cast<T>(col_num), row + num_upper_diags + 1);
 
      for (T band_idx = band_start; band_idx < band_end; band_idx++)
      {
        output[band_idx] = input[band_idx];
      }
    }
  }
}
} // namespace cker
} // namespace nnfw
 
#endif // __NNFW_CKER_MATRIX_BAND_PART_H__