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
|
/*
* 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 "EinsumLayer.h"
#include <cker/operation/Einsum.h>
namespace onert
{
namespace backend
{
namespace cpu
{
namespace ops
{
EinsumLayer::EinsumLayer()
: _inputs(), _output(nullptr), _equation(), _einsum_kernel(new nnfw::cker::Einsum())
{
// DO NOTHING
}
EinsumLayer::~EinsumLayer() = default;
void EinsumLayer::einsumFloat32()
{
uint32_t num_inputs = _inputs.size();
nnfw::cker::Einsum &kernel = *_einsum_kernel;
kernel.prepare(_equation);
std::vector<nnfw::cker::Shape> inputShapes;
std::vector<const float *> inputFloatPtrs;
for (uint32_t i = 0; i < num_inputs; i++)
{
inputShapes.emplace_back(getTensorShape(_inputs[i]));
inputFloatPtrs.emplace_back(reinterpret_cast<const float *>(_inputs[i]->buffer()));
}
kernel(_equation, inputShapes, inputFloatPtrs, getTensorShape(_output),
reinterpret_cast<float *>(_output->buffer()));
}
void EinsumLayer::run()
{
if (_output->data_type() == OperandType::FLOAT32)
{
einsumFloat32();
}
else
{
throw std::runtime_error{"Einsum: unsupported data type"};
}
}
void EinsumLayer::configure(const std::vector<const IPortableTensor *> &inputs,
std::string equation, IPortableTensor *output)
{
assert(inputs.size() > 0);
assert(output != nullptr);
_inputs = inputs;
_equation = equation;
_output = output;
}
} // namespace ops
} // namespace cpu
} // namespace backend
} // namespace onert
|
