blob: 77038682643f423c1ddbae5e477107fd1ab6bd9f (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
|
/*
* Copyright (c) 2020 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.
*/
#include "AbsLayer.h"
#include "OperationUtils.h"
#include <cker/operation/Elementwise.h>
namespace onert
{
namespace backend
{
namespace cpu
{
namespace kernel
{
AbsLayer::AbsLayer() : _input(nullptr), _output(nullptr)
{
// DO NOTHING
}
void AbsLayer::absFloat32()
{
nnfw::cker::Abs(convertTensorToCkerShape(_input),
reinterpret_cast<const float *>(_input->buffer()),
convertTensorToCkerShape(_output), reinterpret_cast<float *>(_output->buffer()));
}
void AbsLayer::absQuant8() { throw std::runtime_error{"NYI"}; }
void AbsLayer::configure(const operand::Tensor *input, operand::Tensor *output)
{
_input = input;
_output = output;
}
void AbsLayer::run()
{
if (_input->data_type() == OperandType::FLOAT32)
{
absFloat32();
}
else if (_input->data_type() == OperandType::QUANT8_ASYMM)
{
absQuant8();
}
}
} // namespace kernel
} // namespace cpu
} // namespace backend
} // namespace onert
|
