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
|
/*
* Copyright (c) 2017 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "QuantizationLayer.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
SimpleTensor<uint8_t> quantization_layer(const SimpleTensor<T> &src)
{
// Create reference
SimpleTensor<uint8_t> dst{ src.shape(), DataType::U8 };
const int width = src.shape().x();
const int height = src.shape().y();
const int depth = src.shape().z();
const int stride_w = width * height * depth;
const int num_batches = src.shape().total_size_upper(3);
for(int k = 0; k < num_batches; ++k)
{
// Compute min and max of the 3D tensor
float min = src[0];
float max = src[0];
// Look for min and max values
for(int i = 1; i < stride_w; ++i)
{
float val = src[i + k * stride_w];
if(val < min)
{
min = val;
}
if(val > max)
{
max = val;
}
}
// Saturate the result in case min = max
if(min == max)
{
min = 0.0f;
max = 1.0f;
}
const float range = max - min;
for(int i = 0; i < stride_w; ++i)
{
// map values to range [0.0, 1.0]
float val = src[i + k * stride_w];
const float normalized = (val - min) / range;
dst[i + k * stride_w] = static_cast<uint8_t>(std::min(255.0f, normalized * 256.0f));
}
}
return dst;
}
template SimpleTensor<uint8_t> quantization_layer(const SimpleTensor<float> &src);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
|