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
|
/*
* 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.
*/
#ifndef __ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H__
#define __ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H__
#include "arm_compute/core/NEON/INEKernel.h"
namespace arm_compute
{
class ITensor;
/** Interface for the batch normalization layer kernel.
*/
class NEBatchNormalizationLayerKernel : public INEKernel
{
public:
/** Default constructor */
NEBatchNormalizationLayerKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEBatchNormalizationLayerKernel(const NEBatchNormalizationLayerKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEBatchNormalizationLayerKernel &operator=(const NEBatchNormalizationLayerKernel &) = delete;
/** Default Move Constructor. */
NEBatchNormalizationLayerKernel(NEBatchNormalizationLayerKernel &&) = default;
/** Default move assignment operator. */
NEBatchNormalizationLayerKernel &operator=(NEBatchNormalizationLayerKernel &&) = default;
/** Default destructor */
~NEBatchNormalizationLayerKernel() = default;
/** Set the input and output tensors.
*
* @note If the output tensor is a nullptr, the batch normalization function will be performed in-place
*
* @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
* 3 lower dimensions represent a single input with dimensions [width, height, FM].
* The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
* @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
* @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
* @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
* @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
* @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
* @param[in] epsilon Small value to avoid division with zero.
*/
void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon);
/** Static function to check if given info will lead to a valid configuration of @ref NEBatchNormalizationLayerKernel
*
* @param[in] input Source tensor info. In case of @p output tensor = nullptr, this tensor will store the result.
* 3 lower dimensions represent a single input with dimensions [width, height, FM].
* The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
* @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input
* @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
* @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
* @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
* @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
* @param[in] epsilon Small value to avoid division with zero.
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output,
const ITensorInfo *mean, const ITensorInfo *var,
const ITensorInfo *beta, const ITensorInfo *gamma,
float epsilon);
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
private:
using BatchNormFunction = void(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon, const Window &window);
BatchNormFunction *_func;
ITensor *_input;
ITensor *_output;
const ITensor *_mean;
const ITensor *_var;
const ITensor *_gamma;
const ITensor *_beta;
float _epsilon;
};
} // namespace arm_compute
#endif /*__ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H__ */
|
