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
|
/*
* 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.
*/
#ifndef _NNC_SOFT_BACKEND_SEQUENCED_IR_H_
#define _NNC_SOFT_BACKEND_SEQUENCED_IR_H_
#include "mir/Shape.h"
#include "mir/Operation.h"
#include <string>
#include <vector>
#include <cstdint>
#include <limits>
#include <list>
namespace nnc
{
namespace sir
{
const size_t INVALID_TENSOR_ID = std::numeric_limits<size_t>::max();
/**
* @brief Represents variable used in artifact.
* This variable can store inputs, outputs of network and temporary data.
*/
struct TensorDescriptor
{
/**
* input tensors of this type supposed to be set outside of artifact
* persistent tensors store data after inference process is over, this include NN outputs
* temporary tensors are not accessible outside artifact in any way,
* they are created and destructed on demand
*/
enum class Type
{
input,
persistent,
temporary
};
size_t id;
Type type;
std::string name;
// if _shape.rank() == 0 - assume shape is not known for this tensor on compilation
mir::Shape shape;
};
/**
* @brief Action represents operation in inference sequence that is needed to
*/
struct Action
{
/**
* Defines which type of action to perform
* createTmp responsible for creation of temporary tensor in inference sequence
* destroyTmp responsible for deletion of temporary tensor
* transpose
*/
enum class Type
{
createTmp,
destroyTmp,
callFunction,
transposeTensor
};
explicit Action(Type t) : type(t) {}
virtual ~Action() = default;
Type type;
};
struct TransposeTensor : public Action
{
TransposeTensor(size_t input, size_t output, std::vector<int32_t> &&perm)
: Action(Type::transposeTensor), perm(std::move(perm)), input(input), output(output)
{
}
std::vector<int32_t> perm;
size_t input;
size_t output;
};
struct CreateTmp : public Action
{
explicit CreateTmp(size_t tid) : Action(Type::createTmp), tensorId(tid) {}
size_t tensorId;
};
struct DestroyTmp : public Action
{
explicit DestroyTmp(size_t tid) : Action(Type::destroyTmp), tensorId(tid) {}
size_t tensorId;
};
struct CallFunction : public Action
{
CallFunction(mir::Operation *op, std::string func_name, std::vector<size_t> &&inputs,
std::vector<size_t> &&outputs)
: Action(Type::callFunction), mirOp(op), funcName(std::move(func_name)), inputs(inputs),
outputs(outputs), paramStartOffset(0)
{
}
CallFunction() : Action(Type::callFunction), mirOp(nullptr), paramStartOffset(0) {}
mir::Operation *mirOp;
std::string funcName;
// list of input tensors
std::vector<size_t> inputs;
// list of output tensors
std::vector<size_t> outputs;
size_t paramStartOffset;
};
} // namespace sir
} // namespace nnc
#endif // _NNC_SOFT_BACKEND_SEQUENCED_IR_H_
|
