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
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
|
/*
* 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 "nnkit/support/moco/tf/Backend.h"
#include "InputTensorContext.h"
#include "OutputTensorContext.h"
#include "nnkit/TensorContext.h"
#include "nnkit/support/tftestinfo/ParsedTensor.h"
#include "nnkit/support/tftestinfo/TensorInfoParser.h"
#include <moco/tf/Frontend.h>
#include <moco/Names.h>
#include <stdex/Memory.h>
#include <nncc/core/ADT/tensor/Buffer.h>
#include <nncc/core/ADT/tensor/LexicalLayout.h>
#include <utility> // std::move
#include <stdexcept>
namespace nnkit
{
namespace support
{
namespace moco
{
namespace tf
{
void Backend::setInputOutputFromGraph(const std::unique_ptr<loco::Graph> &loco_graph,
ParsedTensors &parsed_tensors)
{
auto inputs = loco_graph.get()->inputs();
auto outputs = loco_graph.get()->outputs();
uint32_t input_idx = 0;
uint32_t output_idx = 0;
for (auto &parsed_tensor : parsed_tensors)
{
if (parsed_tensor->kind() == ParsedTensor::Kind::Input)
{
if (!parsed_tensor->hasShape())
{
auto input_shape = inputs->at(input_idx++)->shape();
uint32_t size = input_shape->rank();
parsed_tensor->mutable_shape().resize(size);
for (uint32_t d = 0; d < size; d++)
{
parsed_tensor->mutable_shape().dim(d) = input_shape->dim(d).value();
}
}
_inputs.emplace_back(std::move(parsed_tensor));
}
else // Output
{
if (!parsed_tensor->hasShape())
{
auto output_shape = outputs->at(output_idx++)->shape();
uint32_t size = output_shape->rank();
parsed_tensor->mutable_shape().resize(size);
for (uint32_t d = 0; d < size; d++)
{
parsed_tensor->mutable_shape().dim(d) = output_shape->dim(d).value();
}
}
_outputs.emplace_back(std::move(parsed_tensor));
}
}
}
Backend::Backend(const char *pb_path, const char *info_path)
{
// read test.info
::moco::ModelSignature sig;
auto parsed_tensors = nnkit::support::tftestinfo::parse(info_path);
for (auto &parsed_tensor : parsed_tensors)
{
if (parsed_tensor->kind() == ParsedTensor::Kind::Input)
{
sig.add_input(::moco::TensorName(parsed_tensor->name()));
}
else
{
sig.add_output(::moco::TensorName(parsed_tensor->name()));
}
if (parsed_tensor->hasShape())
sig.shape(parsed_tensor->name(), parsed_tensor->shape());
}
// get loco::Graph
::moco::tf::Frontend moco;
// After converting, all shapes will be determined.
auto loco_graph = moco.load(sig, pb_path, ::moco::tf::Frontend::FileType::Binary);
// Set input and output from loco graph.
setInputOutputFromGraph(loco_graph, parsed_tensors);
// set member vars
_loco_graph = std::move(loco_graph);
_sess = stdex::make_unique<locomotiv::Session>(_loco_graph.get());
}
void Backend::prepare(const std::function<void(nnkit::TensorContext &)> &f)
{
using nncc::core::ADT::tensor::Buffer;
using nncc::core::ADT::tensor::make_buffer;
using nncc::core::ADT::tensor::LexicalLayout;
// allocate memory for inputs of loco interpreter
std::vector<std::unique_ptr<Buffer<float>>> buf_list; // TODO Support more types other than float
for (int n = 0; n < _inputs.size(); n++)
{
auto buf = make_buffer<float, LexicalLayout>(_inputs.at(n)->shape());
buf_list.emplace_back(stdex::make_unique<nncc::core::ADT::tensor::Buffer<float>>(buf));
}
// fill test input values
InputTensorContext ctx(_inputs, buf_list);
f(ctx);
// set input of locomotiv
for (int n = 0; n < buf_list.size(); n++)
{
auto buf = buf_list.at(n).get();
auto node_data = locomotiv::make_data(*buf);
_sess->set_input(n, std::move(node_data));
}
}
void Backend::run(void) { _sess->infer(); }
void Backend::teardown(const std::function<void(nnkit::TensorContext &)> &f)
{
// get output
OutputTensorContext ctx(_outputs, _sess.get());
f(ctx);
}
} // namespace tf
} // namespace moco
} // namespace support
} // namespace nnkit
|
