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/*
* Copyright (c) 2018 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 "Pad.h"
#include "Common.h"
#include "mir/ShapeRange.h"
#include "mir/Tensor.h"
namespace mir_interpreter
{
using namespace mir;
template <typename T> struct PadImpl
{
static void run(const mir::TensorVariant &inputv, const mir::ops::PadOp &op,
mir::TensorVariant &result);
};
template <typename T>
void PadImpl<T>::run(const TensorVariant &inputv, const ops::PadOp &op, TensorVariant &result)
{
Tensor<T> result_accessor(result);
Tensor<T> input(inputv);
Shape out_shape = result_accessor.getShape();
ShapeRange out_range(out_shape);
const int rank = op.getInputShape(0).rank();
const auto &padding_before = op.getPaddingBefore();
const auto &padding_after = op.getPaddingAfter();
Index temp_index;
temp_index.resize(rank);
bool index_on_padding(false);
for (const Index &ind : out_range)
{
index_on_padding = false;
for (int32_t i = 0; i < rank; i++)
{
// index on input values
if (ind.at(i) >= padding_before[i] && ind.at(i) < out_shape.dim(i) - padding_after[i])
{
temp_index.at(i) = ind.at(i) - padding_before[i];
}
else
{ // not in input
index_on_padding = true;
break;
}
}
if (index_on_padding)
{
result_accessor.at(ind) = op.getPaddingValue();
}
else
{
result_accessor.at(ind) = input.at(temp_index);
}
}
}
void Pad(const mir::TensorVariant &input, const mir::ops::PadOp &op, mir::TensorVariant &result)
{
dispatch<PadImpl>(input.getElementType(), input, op, result);
};
} // namespace mir_interpreter
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