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
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
|
/*
* Copyright (c) 2017-2021, 2023-2024 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 ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLBATCHNORMALIZATIONLAYER_H
#define ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLBATCHNORMALIZATIONLAYER_H
#include "arm_compute/core/Types.h"
#include "arm_compute/function_info/ActivationLayerInfo.h"
#include "arm_compute/runtime/IFunction.h"
#include <memory>
namespace arm_compute
{
class CLCompileContext;
class ICLTensor;
class ITensorInfo;
class CLBatchNormalizationLayerKernel;
/** Basic function to run CLNormalizationLayerKernel and simulate a batch normalization layer.
*
* Batch normalization is calculated by:
* @f[ out_i = \gamma * (\frac{in_i - \mu_{B}}{\sqrt{\sigma^2_{B} + \epsilon}}) + \beta \equiv BN_{\gamma,\beta}(in_i) @f]
*
*/
class CLBatchNormalizationLayer : public IFunction
{
public:
/** Default constructor */
CLBatchNormalizationLayer();
/** Prevent instances of this class from being copied */
CLBatchNormalizationLayer(const CLBatchNormalizationLayer &) = delete;
/** Prevent instances of this class from being copied */
CLBatchNormalizationLayer &operator=(const CLBatchNormalizationLayer &) = delete;
/** Prevent instances of this class to be moved */
CLBatchNormalizationLayer(CLBatchNormalizationLayer &&) = delete;
/** Prevent instances of this class to be moved */
CLBatchNormalizationLayer &operator=(CLBatchNormalizationLayer &&) = delete;
/** Default destructor */
~CLBatchNormalizationLayer();
/** Set the input and output tensors.
*
* Valid data layouts:
* - NHWC
* - NCHW
*
* Valid data type configurations:
* |src |dst |
* |:--------------|:--------------|
* |F32 |F32 |
* |F16 |F16 |
*
* @note If the output tensor is a nullptr or is equal to the input, 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: F16/F32. Data layouts supported: NCHW/NHWC.
* @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 (Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input
* @param[in] gamma (Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input
* @param[in] epsilon (Optional) Small value to avoid division with zero. Default value is 0.001f.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*/
void configure(ICLTensor *input,
ICLTensor *output,
const ICLTensor *mean,
const ICLTensor *var,
const ICLTensor *beta = nullptr,
const ICLTensor *gamma = nullptr,
float epsilon = 0.001f,
ActivationLayerInfo act_info = ActivationLayerInfo());
/** Set the input and output tensors.
*
* @note If the output tensor is a nullptr or is equal to the input, the batch normalization function will be performed in-place
*
* @param[in] compile_context The compile context to be used.
* @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: F16/F32. Data layouts supported: NCHW/NHWC.
* @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 (Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input
* @param[in] gamma (Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input
* @param[in] epsilon (Optional) Small value to avoid division with zero. Default value is 0.001f.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*/
void configure(const CLCompileContext &compile_context,
ICLTensor *input,
ICLTensor *output,
const ICLTensor *mean,
const ICLTensor *var,
const ICLTensor *beta = nullptr,
const ICLTensor *gamma = nullptr,
float epsilon = 0.001f,
ActivationLayerInfo act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLBatchNormalizationLayer
*
* @param[in] input Source tensor info. In case of @p output tensor info = 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: F16/F32. Data layouts supported: NCHW/NHWC.
* @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 (Optional) Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for beta is 0. Data types supported: Same as @p input
* @param[in] gamma (Optional) Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. If not provided, default value for gamma is 1. Data types supported: Same as @p input
* @param[in] epsilon (Optional) Small value to avoid division with zero. Default value is 0.001f.
* @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*
* @return a status
*/
static Status validate(const ITensorInfo *input,
const ITensorInfo *output,
const ITensorInfo *mean,
const ITensorInfo *var,
const ITensorInfo *beta = nullptr,
const ITensorInfo *gamma = nullptr,
float epsilon = 0.001f,
ActivationLayerInfo act_info = ActivationLayerInfo());
// Inherited methods overridden:
void run() override;
private:
std::unique_ptr<CLBatchNormalizationLayerKernel> _norm_kernel; /**< BatchNormalization layer kernel to run */
};
} // namespace arm_compute
#endif // ACL_ARM_COMPUTE_RUNTIME_CL_FUNCTIONS_CLBATCHNORMALIZATIONLAYER_H
|
