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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__
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