xref: /aosp_15_r20/external/ComputeLibrary/tests/validation/reference/L2NormalizeLayer.cpp (revision c217d954acce2dbc11938adb493fc0abd69584f3)
1 /*
2  * Copyright (c) 2017-2019 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
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6  * Permission is hereby granted, free of charge, to any person obtaining a copy
7  * of this software and associated documentation files (the "Software"), to
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10  * sell copies of the Software, and to permit persons to whom the Software is
11  * furnished to do so, subject to the following conditions:
12  *
13  * The above copyright notice and this permission notice shall be included in all
14  * copies or substantial portions of the Software.
15  *
16  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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22  * SOFTWARE.
23  */
24 #include "L2NormalizeLayer.h"
25 #include "ReductionOperation.h"
26 
27 #include "tests/validation/Helpers.h"
28 
29 #include <algorithm>
30 #include <cmath>
31 
32 namespace arm_compute
33 {
34 namespace test
35 {
36 namespace validation
37 {
38 namespace reference
39 {
40 namespace
41 {
get_output_shape(TensorShape shape,unsigned int axis)42 TensorShape get_output_shape(TensorShape shape, unsigned int axis)
43 {
44     TensorShape output_shape(shape);
45     output_shape.set(axis, 1);
46     return output_shape;
47 }
48 } // namespace
49 
50 template <typename T>
l2_normalize(const SimpleTensor<T> & src,unsigned int axis,float epsilon)51 SimpleTensor<T> l2_normalize(const SimpleTensor<T> &src, unsigned int axis, float epsilon)
52 {
53     // Create reference
54     SimpleTensor<T> dst{ src.shape(), src.data_type() };
55 
56     // Reduce across given axis
57     SimpleTensor<T> sum = reduction_operation<T, T>(src, get_output_shape(src.shape(), axis), axis, ReductionOperation::SUM_SQUARE);
58 
59     // Compute reference
60     const int upper_dims     = src.shape().total_size_upper(axis + 1);
61     const int lower_dims     = src.shape().total_size_lower(axis + 1);
62     const int lower_dims_sum = sum.shape().total_size_lower(axis + 1);
63 
64     for(int du = 0; du < upper_dims; ++du)
65     {
66         const T *src_row_ptr = src.data() + du * lower_dims;
67         T       *dst_row_ptr = dst.data() + du * lower_dims;
68         switch(axis)
69         {
70             case 0:
71             {
72                 const int elems               = src.shape()[0];
73                 const T   normalization_value = sqrt(std::max(sum[du], static_cast<T>(epsilon)));
74                 std::transform(src_row_ptr, src_row_ptr + elems, dst_row_ptr, [normalization_value](T val)
75                 {
76                     return val / normalization_value;
77                 });
78             }
79             break;
80             case 1:
81             case 2:
82             {
83                 for(int ld = 0; ld < lower_dims; ++ld)
84                 {
85                     const T normalization_value = sqrt(std::max(sum[ld % lower_dims_sum + du * lower_dims_sum], static_cast<T>(epsilon)));
86                     dst_row_ptr[ld]             = src_row_ptr[ld] / normalization_value;
87                 }
88             }
89             break;
90             default:
91                 ARM_COMPUTE_ERROR("Axis not supported");
92         }
93     }
94 
95     return dst;
96 }
97 
98 template SimpleTensor<float> l2_normalize(const SimpleTensor<float> &src, unsigned int axis, float epsilon);
99 template SimpleTensor<half> l2_normalize(const SimpleTensor<half> &src, unsigned int axis, float epsilon);
100 } // namespace reference
101 } // namespace validation
102 } // namespace test
103 } // namespace arm_compute
104