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
|
/*
* Copyright (c) 2019 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 "InstanceNormalizationLayer.h"
#include "tests/validation/Helpers.h"
#include <algorithm>
#include <cmath>
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
template <typename T>
SimpleTensor<T> instance_normalization(const SimpleTensor<T> &src, float gamma, float beta, float epsilon)
{
SimpleTensor<T> dst{ src.shape(), src.data_type() };
//NCHW
const size_t w_size = src.shape()[0];
const size_t h_size = src.shape()[1];
const size_t c_size = src.shape()[2];
const size_t n_size = src.shape()[3];
for(size_t n_i = 0; n_i < n_size; ++n_i)
{
for(size_t c_i = 0; c_i < c_size; ++c_i)
{
float sum_h_w = 0;
//Compute mean
for(size_t h_i = 0; h_i < h_size; ++h_i)
{
for(size_t w_i = 0; w_i < w_size; ++w_i)
{
sum_h_w += src[coord2index(src.shape(), Coordinates(w_i, h_i, c_i, n_i))];
}
}
const float mean_h_w = sum_h_w / (h_size * w_size);
//Compute variance
float partial_var_h_w = 0;
for(size_t h_i = 0; h_i < h_size; ++h_i)
{
for(size_t w_i = 0; w_i < w_size; ++w_i)
{
partial_var_h_w += std::pow(src[coord2index(src.shape(), Coordinates(w_i, h_i, c_i, n_i))] - mean_h_w, 2);
}
}
const float var_h_w = partial_var_h_w / (h_size * w_size);
//Apply mean
for(size_t h_i = 0; h_i < h_size; ++h_i)
{
for(size_t w_i = 0; w_i < w_size; ++w_i)
{
//Compute output
size_t index = coord2index(src.shape(), Coordinates(w_i, h_i, c_i, n_i));
dst[index] = (src[index] - mean_h_w) * gamma / std::sqrt(var_h_w + epsilon) + beta;
}
}
}
}
return dst;
}
template SimpleTensor<float> instance_normalization(const SimpleTensor<float> &src, float gamma, float beta, float epsilon);
template SimpleTensor<half> instance_normalization(const SimpleTensor<half> &src, float gamma, float beta, float epsilon);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
|
