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
|
/*
* Copyright (c) 2017-2019 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 "L2NormalizeLayer.h"
#include "ReductionOperation.h"
#include "tests/validation/Helpers.h"
#include <algorithm>
#include <cmath>
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
namespace
{
TensorShape get_output_shape(TensorShape shape, unsigned int axis)
{
TensorShape output_shape(shape);
output_shape.set(axis, 1);
return output_shape;
}
} // namespace
template <typename T>
SimpleTensor<T> l2_normalize(const SimpleTensor<T> &src, unsigned int axis, float epsilon)
{
// Create reference
SimpleTensor<T> dst{ src.shape(), src.data_type() };
// Reduce across given axis
SimpleTensor<T> sum = reduction_operation<T, T>(src, get_output_shape(src.shape(), axis), axis, ReductionOperation::SUM_SQUARE);
// Compute reference
const int upper_dims = src.shape().total_size_upper(axis + 1);
const int lower_dims = src.shape().total_size_lower(axis + 1);
const int lower_dims_sum = sum.shape().total_size_lower(axis + 1);
for(int du = 0; du < upper_dims; ++du)
{
const T *src_row_ptr = src.data() + du * lower_dims;
T *dst_row_ptr = dst.data() + du * lower_dims;
switch(axis)
{
case 0:
{
const int elems = src.shape()[0];
const T normalization_value = sqrt(std::max(sum[du], static_cast<T>(epsilon)));
std::transform(src_row_ptr, src_row_ptr + elems, dst_row_ptr, [normalization_value](T val)
{
return val / normalization_value;
});
}
break;
case 1:
case 2:
{
for(int ld = 0; ld < lower_dims; ++ld)
{
const T normalization_value = sqrt(std::max(sum[ld % lower_dims_sum + du * lower_dims_sum], static_cast<T>(epsilon)));
dst_row_ptr[ld] = src_row_ptr[ld] / normalization_value;
}
}
break;
default:
ARM_COMPUTE_ERROR("Axis not supported");
}
}
return dst;
}
template SimpleTensor<float> l2_normalize(const SimpleTensor<float> &src, unsigned int axis, float epsilon);
template SimpleTensor<half> l2_normalize(const SimpleTensor<half> &src, unsigned int axis, float epsilon);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
|
