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
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
|
/*
* 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.
*/
#include "SoftMaxLayer.h"
#include "OperationUtils.h"
#include <cker/operation/SoftMax.h>
namespace onert
{
namespace backend
{
namespace cpu
{
namespace ops
{
SoftMaxLayer::SoftMaxLayer() : _input(nullptr), _output(nullptr), _beta(0.0)
{
// DO NOTHING
}
void SoftMaxLayer::softmaxFloat32()
{
if (getNumberOfDimensions(_input) == 1)
{
uint32_t input_size = getNumberOfElements(_input);
nnfw::cker::Softmax(getBuffer<float>(_input), input_size, 1, _beta, getBuffer<float>(_output));
}
else if (getNumberOfDimensions(_input) == 2)
{
uint32_t batch_size = getSizeOfDimension(_input, 0);
if (batch_size == 0)
throw std::runtime_error("batch_size should not be 0");
uint32_t input_size = getNumberOfElements(_input) / batch_size;
nnfw::cker::Softmax(getBuffer<float>(_input), input_size, batch_size, _beta,
getBuffer<float>(_output));
}
else if (getNumberOfDimensions(_input) == 4)
{
nnfw::cker::SoftmaxParams op_params;
op_params.beta = _beta;
nnfw::cker::Softmax(op_params, getShape(_input), getBuffer<float>(_input), getShape(_output),
getBuffer<float>(_output));
}
else
{
nnfw::cker::SoftmaxParams op_params;
op_params.beta = _beta;
nnfw::cker::reference::Softmax(op_params, getShape(_input), getBuffer<float>(_input),
getShape(_output), getBuffer<float>(_output));
}
}
template <typename T> void SoftMaxLayer::softmaxQuant8()
{
nnfw::cker::SoftmaxParams op_params;
op_params.scale = _output->data_scale();
op_params.zero_point = _output->data_zero_point();
op_params.uint8_table1 = _uint8_table1;
op_params.uint8_table2 = _uint8_table2;
op_params.table = _table;
#ifdef TFLITE_SOFTMAX_USE_UINT16_LUT
nnfw::cker::SoftmaxInt8LUT<T, T>(op_params, getShape(_input), getBuffer<T>(_input),
getShape(_output), getBuffer<T>(_output));
#else
nnfw::cker::Softmax<T, T>(op_params, getShape(_input), getBuffer<T>(_input), getShape(_output),
getBuffer<T>(_output));
#endif
}
void SoftMaxLayer::configure(const IPortableTensor *input, const float beta,
IPortableTensor *output)
{
_input = input;
_output = output;
_beta = beta;
if (_input->data_type() == OperandType::QUANT_UINT8_ASYMM ||
_input->data_type() == OperandType::QUANT_INT8_ASYMM)
{
#ifdef TFLITE_SOFTMAX_USE_UINT16_LUT
// Only apply when both input & output are uint8/int8 & build with clang
// on aarch64.
nnfw::cker::PopulateSoftmaxUInt8LookupTable(_uint8_table1, _uint8_table2, _input->data_scale(),
_beta);
#else
nnfw::cker::PopulateSoftmaxLookupTable(_table, _input->data_scale(), _beta);
#endif
}
}
void SoftMaxLayer::run()
{
switch (_input->data_type())
{
case OperandType::FLOAT32:
softmaxFloat32();
break;
case OperandType::QUANT_UINT8_ASYMM:
softmaxQuant8<uint8_t>();
break;
case OperandType::QUANT_INT8_ASYMM:
softmaxQuant8<int8_t>();
break;
default:
throw std::runtime_error{"SoftMax: unsupported data type"};
}
}
} // namespace ops
} // namespace cpu
} // namespace backend
} // namespace onert
|
