blob: 2c388f7d82df42db8335304beb01e10c69c22024 (
plain)
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
|
/**
* 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 __INFERENCE_ENGINE_IMPL_TFLite_H__
#define __INFERENCE_ENGINE_IMPL_TFLite_H__
#include <inference_engine_common.h>
#include "tensorflow/contrib/lite/string.h"
#include "tensorflow/contrib/lite/kernels/register.h"
#include "tensorflow/contrib/lite/model.h"
#include "tensorflow/contrib/lite/context.h"
#include <memory>
#include <dlog.h>
/**
* @file inference_engine_tflite_private.h
* @brief This file contains the InferenceTFLite class which
* provide Tensorflow-lite based inference functionality
*/
#ifdef LOG_TAG
#undef LOG_TAG
#endif
#define LOG_TAG "INFERENCE_ENGINE_TFLITE"
using namespace InferenceEngineInterface::Common;
namespace InferenceEngineImpl {
namespace TFLiteImpl {
class InferenceTFLite : public IInferenceEngineCommon {
public:
InferenceTFLite(std::string protoFile,
std::string weightFile);
~InferenceTFLite();
// InputTensor
int SetInputTensorParam() override;
int SetInputTensorParamNode(std::string node = "input") override;
// Output Tensor Params
int SetOutputTensorParam() override;
int SetOutputTensorParamNodes(std::vector<std::string> nodes) override;
int SetTargetDevice(inference_target_type_e type) override;
// Load and Run
int Load() override;
int CreateInputLayerPassage() override;
int GetInputLayerAttrType() override;
void * GetInputDataPtr() override;
int SetInputDataBuffer(tensor_t data) override;
int Run() override;
int Run(std::vector<float> tensor) override;
int GetInferenceResult(tensor_t& results);
private:
std::unique_ptr<tflite::Interpreter> mInterpreter;
std::unique_ptr<tflite::FlatBufferModel> mFlatBuffModel;
std::string mInputLayer;
std::vector<std::string> mOutputLayer; /**< Output layer name */
int mInputLayerId;
std::vector<int> mOutputLayerId;
TfLiteType mInputAttrType;
void *mInputData;
std::string mConfigFile;
std::string mWeightFile;
};
} /* InferenceEngineImpl */
} /* TFLiteImpl */
#endif /* __INFERENCE_ENGINE_IMPL_TFLite_H__ */
|
