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
68
69
70
71
72
73
74
75
76
|
/*
* Copyright (c) 2019 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 "PadLayer.h"
#include "OperationUtils.h"
#include <cker/operation/Pad.h>
namespace neurun
{
namespace backend
{
namespace cpu
{
namespace kernel
{
PadLayer::PadLayer()
: _inputData(), _outputData(), _inputDescr(), _outputDescr(), _padData(), _padRank(),
_constantValueData(), _inputType(OperandType::FLOAT32)
{
// DO NOTHING
}
void PadLayer::padFloat32()
{
nnfw::cker::Pad(_padData, _padRank, convertTensorDescriptorToCkerShape(_inputDescr), _inputData.f,
convertTensorDescriptorToCkerShape(_outputDescr), _outputData.f,
_constantValueData.f);
}
void PadLayer::padQuant8() { throw std::runtime_error("Quantized Pad isn't supported NYI"); }
void PadLayer::configure(uint8_t *inputData, const TensorDescriptor inputDescr, uint8_t *outputData,
const TensorDescriptor outputDescr, const int32_t *padData,
int32_t padRank, uint8_t *constantValueData)
{
_inputData.u8 = inputData;
_inputDescr = inputDescr;
_inputType = inputDescr.type;
_outputData.u8 = outputData;
_outputDescr = outputDescr;
_padData = padData;
_padRank = padRank;
_constantValueData.u8 = constantValueData;
}
void PadLayer::run()
{
if (_inputType == OperandType::FLOAT32)
{
padFloat32();
}
else if (_inputType == OperandType::QUANT8_ASYMM)
{
padQuant8();
}
}
} // namespace kernel
} // namespace cpu
} // namespace backend
} // namespace neurun
|
