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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_KERNEL_ACL_CL_CONCAT_LAYER_H__
#define __NEURUN_KERNEL_ACL_CL_CONCAT_LAYER_H__
#include <NeuralNetworks.h>
#include <arm_compute/runtime/IFunction.h>
#include "model/operand/DataType.h"
#include "backend/acl_cl/operand/ICLTensor.h"
using OperandType = neurun::model::operand::DataType;
namespace neurun
{
namespace kernel
{
namespace acl_cl
{
//
// neurun::kernel::acl_cl::ConcatLayer
// A naive implementation of ConcatLayer for ACL
//
class ConcatLayer : public ::arm_compute::IFunction
{
public:
ConcatLayer();
public:
void configure(const std::vector<::neurun::backend::acl_cl::operand::ICLTensor *> &input_allocs,
int32_t axis /* NNAPI tensor axis from NHWC order */,
::neurun::backend::acl_cl::operand::ICLTensor *output_alloc);
void run();
private:
bool concatenationFloat32();
private:
std::vector<::neurun::backend::acl_cl::operand::ICLTensor *> _input_allocs;
::neurun::backend::acl_cl::operand::ICLTensor *_output_alloc;
int32_t _axis;
OperandType _input_type;
};
} // namespace acl_cl
} // namespace kernel
} // namespace neurun
#endif // __NEURUN_KERNEL_ACL_CL_CONCAT_LAYER_H__
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