ONE - On-device Neural Engine
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ElementwiseActivationLayer.h
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/*
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* Copyright (c) 2023 Samsung Electronics Co., Ltd. All Rights Reserved
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef __ONERT_BACKEND_TRAIN_OPS_ELEMENTWISEACTIVATIONLAYER_H__
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#define __ONERT_BACKEND_TRAIN_OPS_ELEMENTWISEACTIVATIONLAYER_H__
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#include <
backend/IPortableTensor.h
>
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#include <ops/ElementwiseActivationLayer.h>
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#include <
exec/train/ITrainableFunction.h
>
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namespace
onert
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{
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namespace
backend
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{
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namespace
train
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{
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namespace
ops
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{
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enum class
ElementwiseActivationType
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{
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kReLU
,
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};
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class
ElementwiseActivationLayer
:
public
::onert::exec::train::ITrainableFunction
,
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public
cpu::ops::ElementwiseActivationLayer
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{
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public
:
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ElementwiseActivationLayer
();
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void
configureBackward
(
const
IPortableTensor
*input,
IPortableTensor
*back_prop_input,
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const
IPortableTensor
*back_prop_output,
float
alpha,
float
beta,
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ElementwiseActivationType
op_type);
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void
forward
(
bool
training)
override
;
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void
backward
()
override
;
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private
:
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IPortableTensor
*_back_prop_input =
nullptr
;
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const
IPortableTensor
*_back_prop_output =
nullptr
;
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ElementwiseActivationType
_op_type =
ElementwiseActivationType::kReLU
;
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std::function<void(
const
IPortableTensor
*output,
const
IPortableTensor
*incoming,
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IPortableTensor
*outgoing)>
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_backward_kernel;
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};
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}
// namespace ops
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}
// namespace train
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}
// namespace backend
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}
// namespace onert
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#endif
// __ONERT_BACKEND_TRAIN_OPS_ELEMENTWISEACTIVATIONLAYER_H__
IPortableTensor.h
ITrainableFunction.h
onert::backend::IPortableTensor
A tensor class that is portable for other backends.
Definition
IPortableTensor.h:39
onert::backend::cpu::ops::ElementwiseActivationLayer
Definition
ElementwiseActivationLayer.h:43
onert::backend::train::ops::ElementwiseActivationLayer
Definition
ElementwiseActivationLayer.h:41
onert::backend::train::ops::ElementwiseActivationLayer::backward
void backward() override
Definition
ElementwiseActivationLayer.cc:94
onert::backend::train::ops::ElementwiseActivationLayer::forward
void forward(bool training) override
Definition
ElementwiseActivationLayer.cc:92
onert::backend::train::ops::ElementwiseActivationLayer::configureBackward
void configureBackward(const IPortableTensor *input, IPortableTensor *back_prop_input, const IPortableTensor *back_prop_output, float alpha, float beta, ElementwiseActivationType op_type)
Definition
ElementwiseActivationLayer.cc:38
onert::backend::train::ops::ElementwiseActivationLayer::ElementwiseActivationLayer
ElementwiseActivationLayer()
Definition
ElementwiseActivationLayer.cc:33
onert::exec::train::ITrainableFunction
Definition
ITrainableFunction.h:33
mir::ops
Definition
AbsOp.h:25
onert::backend::train::ops::ElementwiseActivationType
ElementwiseActivationType
Definition
ElementwiseActivationLayer.h:35
onert::backend::train::ops::ElementwiseActivationType::kReLU
@ kReLU
onert
Definition
CustomKernel.cc:20
runtime
onert
backend
train
ops
ElementwiseActivationLayer.h
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