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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.
*/
#ifndef __NEURUN_BACKEND_CPU_KERNEL_CONVOLUTIONLAYER_H__
#define __NEURUN_BACKEND_CPU_KERNEL_CONVOLUTIONLAYER_H__
#include <exec/IFunction.h>
#include "OperationUtils.h"
namespace neurun
{
namespace backend
{
namespace cpu
{
namespace kernel
{
class ConvolutionLayer : public ::neurun::exec::IFunction
{
public:
ConvolutionLayer();
public:
void convFloat32();
void convQuant8();
void configure(uint8_t *inputData, const Shape inputShape, uint8_t *kernelData,
const Shape kernelShape, uint8_t *biasData, const Shape biasShape,
const uint32_t paddingLeft, const uint32_t paddingRight, const uint32_t paddingTop,
const uint32_t paddingBottom, const uint32_t strideW, const uint32_t strideH,
const model::Activation activation, uint8_t *outputData, const Shape outputShape);
void run();
void runSync()
{
// this abstract method is used just for profiling and called for
// backend::acl_common::AclFunction
run();
}
private:
DataPtr _inputData;
DataPtr _kernelData;
DataPtr _outputData;
DataPtr _biasData;
Shape _inputShape;
Shape _kernelShape;
Shape _outputShape;
Shape _biasShape;
uint32_t _paddingLeft;
uint32_t _paddingTop;
uint32_t _paddingRight;
uint32_t _paddingBottom;
uint32_t _strideWidth;
uint32_t _strideHeight;
model::Activation _activation;
OperandType _inputType;
};
} // namespace kernel
} // namespace cpu
} // namespace backend
} // namespace neurun
#endif // __NEURUN_BACKEND_CPU_KERNEL_CONVOLUTIONLAYER_H__
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