Compute Library
 22.08
NEFuseBatchNormalization.h
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24 #ifndef ARM_COMPUTE_NEFUSEBATCHNORMALIZATION_H
25 #define ARM_COMPUTE_NEFUSEBATCHNORMALIZATION_H
26 
28 #include "arm_compute/core/Types.h"
30 
31 namespace arm_compute
32 {
33 // Forward declarations
34 class ITensor;
35 class NEFuseBatchNormalizationKernel;
36 
37 /** Basic function to fuse the batch normalization node to a preceding convolution node */
39 {
40 public:
41  /** Default constructor */
43  /** Prevent instances of this class from being copied (As this class contains pointers) */
45  /** Prevent instances of this class from being copied (As this class contains pointers) */
47  /** Allow instances of this class to be moved */
49  /** Allow instances of this class to be moved */
51  /** Default destructor */
53  /** Set the input and output tensors.
54  *
55  * Valid data layouts:
56  * - NHWC
57  * - NCHW
58  *
59  * Valid data type configurations:
60  * |src |dst |
61  * |:--------------|:--------------|
62  * |F32 |F32 |
63  * |F16 |F16 |
64  *
65  * @param[in] input_weights Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC
66  * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p input_weights
67  * @param[in] bn_var Batch normalization layer variance tensor. Same as @p input_weights
68  * @param[out] fused_weights (Optional) Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights
69  * @param[out] fused_bias (Optional) Output fused bias tensor. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights
70  * @param[in] input_bias (Optional) Input bias tensor for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights
71  * @param[in] bn_beta (Optional) Batch normalization layer beta tensor. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights
72  * @note if nullptr, bn_beta is set to 0.0
73  * @param[in] bn_gamma (Optional) Batch normalization layer gamma tensor. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights
74  * @note if nullptr, bn_gamma is set to 1.0
75  * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f.
76  * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to Convolution.
77  */
78  void configure(const ITensor *input_weights, const ITensor *bn_mean, const ITensor *bn_var, ITensor *fused_weights, ITensor *fused_bias,
79  const ITensor *input_bias = nullptr, const ITensor *bn_beta = nullptr, const ITensor *bn_gamma = nullptr,
81  /** Static function to check if given info will lead to a valid configuration of @ref NEFuseBatchNormalization
82  *
83  * @param[in] input_weights Input weights tensor info for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC
84  * @param[in] bn_mean Batch normalization layer mean tensor info. Same as @p input_weights
85  * @param[in] bn_var Batch normalization layer variance tensor info. Same as @p input_weights
86  * @param[in] fused_weights (Optional) Output fused weights tensor info. It can be a nullptr in case of in-place computation. Same as @p input_weights
87  * @param[in] fused_bias (Optional) Output fused bias tensor info. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights
88  * @param[in] input_bias (Optional) Input bias tensor info for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights
89  * @param[in] bn_beta (Optional) Batch normalization layer beta tensor info. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights
90  * @note if nullptr, bn_beta is set to 0.0
91  * @param[in] bn_gamma (Optional) Batch normalization layer gamma tensor info. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights
92  * @note if nullptr, bn_gamma is set to 1.0
93  * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f.
94  * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to Convolution.
95  *
96  * @return a status
97  */
98  static Status validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var,
99  const ITensorInfo *fused_weights, const ITensorInfo *fused_bias,
100  const ITensorInfo *input_bias = nullptr, const ITensorInfo *bn_beta = nullptr, const ITensorInfo *bn_gamma = nullptr,
102 
103  // Inherited methods overridden:
104  void run() override;
105 
106 private:
107  std::unique_ptr<NEFuseBatchNormalizationKernel> _fuse_bn_kernel;
108 };
109 } // namespace arm_compute
110 #endif /*ARM_COMPUTE_NEFUSEBATCHNORMALIZATION_H */
FuseBatchNormalizationType fbn_type
void configure(const ITensor *input_weights, const ITensor *bn_mean, const ITensor *bn_var, ITensor *fused_weights, ITensor *fused_bias, const ITensor *input_bias=nullptr, const ITensor *bn_beta=nullptr, const ITensor *bn_gamma=nullptr, float epsilon=0.001f, FuseBatchNormalizationType fbn_type=FuseBatchNormalizationType::CONVOLUTION)
Set the input and output tensors.
Base class for all functions.
Definition: IFunction.h:30
void run() override
Run the kernels contained in the function.
NEFuseBatchNormalization & operator=(const NEFuseBatchNormalization &)=delete
Prevent instances of this class from being copied (As this class contains pointers) ...
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
Status class.
Definition: Error.h:52
Interface for CPU tensor.
Definition: ITensor.h:36
Basic function to fuse the batch normalization node to a preceding convolution node.
Copyright (c) 2017-2022 Arm Limited.
FuseBatchNormalizationType
Available FuseBatchNormalizationType.
Definition: Types.h:158
~NEFuseBatchNormalization()
Default destructor.
static Status validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var, const ITensorInfo *fused_weights, const ITensorInfo *fused_bias, const ITensorInfo *input_bias=nullptr, const ITensorInfo *bn_beta=nullptr, const ITensorInfo *bn_gamma=nullptr, float epsilon=0.001f, FuseBatchNormalizationType fbn_type=FuseBatchNormalizationType::CONVOLUTION)
Static function to check if given info will lead to a valid configuration of NEFuseBatchNormalization...