ONE - On-device Neural Engine
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SoftMaxLayer.cc
Go to the documentation of this file.
1
/*
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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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#include "
SoftMaxLayer.h
"
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#include "
OperationUtils.h
"
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#include <
cker/train/operation/SoftMax.h
>
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namespace
onert::backend::train::ops
24
{
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SoftMaxLayer::SoftMaxLayer
()
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: cpu::
ops
::
SoftMaxLayer
(), _back_prop_input{nullptr}, _back_prop_output{nullptr}
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{
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// DO NOTHING
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}
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SoftMaxLayer::SoftMaxLayer
() {
…
}
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void
SoftMaxLayer::configureBackward
(
IPortableTensor
*back_prop_input,
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const
IPortableTensor
*back_prop_output)
34
{
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_back_prop_input = back_prop_input;
36
_back_prop_output = back_prop_output;
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}
32
void
SoftMaxLayer::configureBackward
(
IPortableTensor
*back_prop_input, {
…
}
38
39
void
SoftMaxLayer::forward
(
bool
) {
cpu::ops::SoftMaxLayer::run
(); }
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void
SoftMaxLayer::backward
()
42
{
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assert(_back_prop_output->
data_type
() ==
_input
->
data_type
());
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switch
(_back_prop_output->
data_type
())
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{
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case
OperandType::FLOAT32:
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{
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nnfw::cker::train::SoftMaxGrad
(
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getShape
(
_output
), getBuffer<float>(
_output
),
getShape
(_back_prop_output),
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getBuffer<float>(_back_prop_output),
getShape
(_back_prop_input),
51
getBuffer<float>(_back_prop_input));
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break
;
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}
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default
:
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throw
std::runtime_error(
"train SoftMaxLayer: unsupported data type"
);
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}
57
}
41
void
SoftMaxLayer::backward
() {
…
}
58
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}
// namespace onert::backend::train::ops
onert::backend::IPortableTensor
A tensor class that is portable for other backends.
Definition
IPortableTensor.h:37
onert::backend::IPortableTensor::data_type
ir::DataType data_type() const override final
Definition
IPortableTensor.h:54
onert::backend::cpu::ops::SoftMaxLayer::run
void run() override
Definition
SoftMaxLayer.cc:103
onert::backend::cpu::ops::SoftMaxLayer::_input
const IPortableTensor * _input
Definition
SoftMaxLayer.h:42
onert::backend::cpu::ops::SoftMaxLayer::_output
IPortableTensor * _output
Definition
SoftMaxLayer.h:43
onert::backend::train::ops::SoftMaxLayer
Definition
SoftMaxLayer.h:29
onert::backend::train::ops::SoftMaxLayer::forward
void forward(bool training) override
Definition
SoftMaxLayer.cc:39
onert::backend::train::ops::SoftMaxLayer::configureBackward
void configureBackward(IPortableTensor *back_prop_input, const IPortableTensor *back_prop_output)
Definition
SoftMaxLayer.cc:32
onert::backend::train::ops::SoftMaxLayer::backward
void backward() override
Definition
SoftMaxLayer.cc:41
onert::backend::train::ops::SoftMaxLayer::SoftMaxLayer
SoftMaxLayer()
Definition
SoftMaxLayer.cc:26
mir::ops
Definition
AbsOp.h:25
nnfw::cker::train::SoftMaxGrad
void SoftMaxGrad(const Shape &output_shape, const float *output_data, const Shape &incoming_shape, const float *incoming_data, const Shape &grad_shape, float *grad_data)
Definition
SoftMax.h:30
onert::backend::train::ops
Definition
BackPropAccumulator.cc:25
onert::backend::train::ops::getShape
nnfw::cker::Shape getShape(const IPortableTensor *tensor)
Get shape of tensor.
Definition
OperationUtils.cc:26
SoftMax.h
OperationUtils.h
SoftMaxLayer.h
runtime
onert
backend
train
ops
SoftMaxLayer.cc
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