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
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
|
/*
* 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 "RecordMinMax.h"
#include "RecordFunction.h"
#include "CircleExpContract.h"
#include "MinMaxObserver.h"
#include "HDF5Importer.h"
#include <luci/Importer.h>
#include <luci/CircleExporter.h>
#include <luci/IR/CircleQuantParam.h>
#include <algorithm>
#include <cmath>
#include <fstream>
#include <numeric>
#include <stdexcept>
#include <iostream>
using Shape = luci_interpreter::Shape;
using DataType = luci_interpreter::DataType;
namespace
{
/**
* @brief getTensorSize will return size in bytes
*/
template <typename NodeT> size_t getTensorSize(const NodeT *node)
{
uint32_t tensor_size = loco::size(node->dtype());
for (uint32_t i = 0; i < node->rank(); ++i)
tensor_size *= node->dim(i).value();
return tensor_size;
}
/**
* @brief verifyTypeShape checks the type and the shape of CircleInput
* This throws an exception if type or shape does not match
*/
void verifyTypeShape(const luci::CircleInput *input_node, const DataType &dtype, const Shape &shape)
{
// Type check
if (dtype != input_node->dtype())
throw std::runtime_error("Wrong input type.");
if (shape.num_dims() != input_node->rank())
throw std::runtime_error("Input rank mismatch.");
for (uint32_t i = 0; i < shape.num_dims(); i++)
{
if (shape.dim(i) != input_node->dim(i).value())
throw std::runtime_error("Input shape mismatch.");
}
}
} // namespace
namespace record_minmax
{
void RecordMinMax::initialize(const std::string &input_model_path)
{
// Load model from the file
std::ifstream fs(input_model_path, std::ifstream::binary);
if (fs.fail())
{
throw std::runtime_error("Cannot open model file \"" + input_model_path + "\".\n");
}
std::vector<char> model_data((std::istreambuf_iterator<char>(fs)),
std::istreambuf_iterator<char>());
_module = luci::Importer().importModule(circle::GetModel(model_data.data()));
if (_module == nullptr)
{
throw std::runtime_error("ERROR: Failed to load '" + input_model_path + "'");
}
// Initialize interpreter
_interpreter = std::make_unique<luci_interpreter::Interpreter>(_module.get());
_observer = std::make_unique<MinMaxObserver>();
_interpreter->attachObserver(_observer.get());
}
void RecordMinMax::profileData(const std::string &mode, const std::string &input_data_path,
float min_percentile, float max_percentile)
{
HDF5Importer importer(input_data_path);
importer.importGroup();
bool is_raw_data = importer.isRawData();
const auto num_records = importer.numRecords();
if (num_records == 0)
throw std::runtime_error("The input data file does not contain any record.");
const auto input_nodes = loco::input_nodes(_module->graph());
const auto num_inputs = input_nodes.size();
for (int32_t record_idx = 0; record_idx < num_records; record_idx++)
{
if (num_inputs != importer.numInputs(record_idx))
throw std::runtime_error("Wrong number of inputs.");
if (record_idx % 100 == 0)
std::cout << "Recording " << record_idx << "'th data" << std::endl;
for (int32_t input_idx = 0; input_idx < num_inputs; input_idx++)
{
const auto *input_node = loco::must_cast<const luci::CircleInput *>(input_nodes[input_idx]);
assert(input_node->index() == input_idx);
std::vector<char> input_data(getTensorSize(input_node));
if (!is_raw_data)
{
DataType dtype;
Shape shape(input_node->rank());
importer.readTensor(record_idx, input_idx, &dtype, &shape, input_data.data());
// Check the type and the shape of the input data is valid
verifyTypeShape(input_node, dtype, shape);
}
else
{
// Skip type/shape check for raw data
importer.readTensor(record_idx, input_idx, input_data.data());
}
// TODO: Input data is copied twice (file -> buffer (input_data) -> interpreter inputs)
// We can redcue the copy by directly writing data from file to interpreter inputs
_interpreter->writeInputTensor(input_node, input_data.data(), input_data.size());
}
_interpreter->interpret();
}
std::cout << "Recording finished. Number of recorded data: " << num_records << std::endl;
auto minmax_map = _observer->minMaxData()->getMap();
for (auto iter = minmax_map->begin(); iter != minmax_map->end(); ++iter)
{
auto node = iter->first;
auto minmax = iter->second;
float min{0.0f}, max{0.0f};
if (mode == "percentile")
{
min = getNthPercentile(minmax.min_vector, min_percentile);
max = getNthPercentile(minmax.max_vector, max_percentile);
}
else if (mode == "moving_average")
{
min = getMovingAverage(minmax.min_vector, 0.9, 16, true);
max = getMovingAverage(minmax.max_vector, 0.9, 16, false);
}
assert(mode == "percentile" || mode == "moving_average");
auto quantparam = std::make_unique<luci::CircleQuantParam>();
quantparam->min.push_back(min);
quantparam->max.push_back(max);
assert(node->quantparam() == nullptr);
auto mutable_node = const_cast<luci::CircleNode *>(node);
mutable_node->quantparam(std::move(quantparam));
}
}
void RecordMinMax::saveModel(const std::string &output_model_path)
{
// Export to output Circle file
luci::CircleExporter exporter;
CircleExpContract contract(_module.get(), output_model_path);
if (!exporter.invoke(&contract))
{
throw std::runtime_error("ERROR: Failed to export '" + output_model_path + "'");
}
}
} // namespace record_minmax
|
