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/*
* Copyright (c) 2019 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.
*/
#ifndef __LOCO_IR_FILTER_CODEC_H__
#define __LOCO_IR_FILTER_CODEC_H__
#include "loco/IR/FilterShape.h"
#include "loco/IR/FilterIndex.h"
#include "loco/IR/TensorShape.h"
#include "loco/IR/TensorIndex.h"
namespace loco
{
/**
* @brief Decribe how to build a (convolution) filter from a tensor
*
* Let us assume that "enc" is a filter encoder.
*
* Given a tensor "inp" and its shape "inp.shape", "enc" builds a filter
* "out" as follows:
*
* for each valid filter index (referred to as filter_index below) for enc.shape(inp.shape)
* out.at(filter_index) = inp.at(enc.value(filter_index))
*/
struct FilterEncoder
{
virtual ~FilterEncoder() = default;
virtual FilterShape shape(const TensorShape &shape) const = 0;
virtual TensorIndex value(const FilterIndex &index) const = 0;
};
/**
* @brief Decribe how to build a a tensor from a filter
*/
struct FilterDecoder
{
virtual ~FilterDecoder() = default;
virtual TensorShape shape(const FilterShape &shape) const = 0;
virtual FilterIndex value(const TensorIndex &index) const = 0;
};
} // namespace loco
#endif // __LOCO_IR_FILTER_CODEC_H__
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