Compute Library
 21.02
NEFuseBatchNormalizationKernel.h
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24 #ifndef ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H
25 #define ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H
26 
28 
29 namespace arm_compute
30 {
31 // Forward declarations
32 class ITensor;
33 
34 /** OpenNE kernel to fuse the batch normalization node to a preceding convolution node */
36 {
37 public:
38  const char *name() const override
39  {
40  return "NEFuseBatchNormalizationKernel";
41  }
42  /** Default constructor */
44  /** Prevent instances of this class from being copied (As this class contains pointers) */
46  /** Prevent instances of this class from being copied (As this class contains pointers) */
48  /** Allow instances of this class to be moved */
50  /** Allow instances of this class to be moved */
52  /** Default destructor */
54  /** Set the source, destination of the kernel
55  *
56  * @param[in] input_weights Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC
57  * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p input_weights
58  * @param[in] bn_var Batch normalization layer variance tensor. Same as @p input_weights
59  * @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
60  * @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
61  * @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
62  * @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
63  * @note if nullptr, bn_beta is set to 0.0
64  * @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
65  * @note if nullptr, bn_gamma is set to 1.0
66  * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f.
67  * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to CONVOLUTION.
68  */
69  void configure(const ITensor *input_weights, const ITensor *bn_mean, const ITensor *bn_var, ITensor *fused_weights, ITensor *fused_bias,
70  const ITensor *input_bias = nullptr, const ITensor *bn_beta = nullptr, const ITensor *bn_gamma = nullptr,
72  /** Static function to check if given info will lead to a valid configuration of @ref NEFuseBatchNormalizationKernel
73  *
74  * @param[in] input_weights Input weights tensor info for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC
75  * @param[in] bn_mean Batch normalization layer mean tensor info. Same as @p input_weights
76  * @param[in] bn_var Batch normalization layer variance tensor info. Same as @p input_weights
77  * @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
78  * @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
79  * @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
80  * @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
81  * @note if nullptr, bn_beta is set to 0.0
82  * @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
83  * @note if nullptr, bn_gamma is set to 1.0
84  * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f.
85  * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to CONVOLUTION.
86  *
87  * @return a status
88  */
89  static Status validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var,
90  const ITensorInfo *fused_weights, const ITensorInfo *fused_bias,
91  const ITensorInfo *input_bias = nullptr, const ITensorInfo *bn_beta = nullptr, const ITensorInfo *bn_gamma = nullptr,
93 
94  // Inherited methods overridden:
95  void run(const Window &window, const ThreadInfo &info) override;
96 
97 private:
98  const ITensor *_input_weights;
99  const ITensor *_input_bias;
100  const ITensor *_bn_mean;
101  const ITensor *_bn_var;
102  const ITensor *_bn_gamma;
103  const ITensor *_bn_beta;
104  ITensor *_fused_weights;
105  ITensor *_fused_bias;
106  float _epsilon;
107  bool _run_in_place_weights;
108  bool _run_in_place_bias;
109 
110  using FuseBatchNormFunction = void(const ITensor *input_weights, const ITensor *input_bias, ITensor *fused_weights, ITensor *fused_bias,
111  const ITensor *bn_mean, const ITensor *bn_var, const ITensor *bn_beta, const ITensor *bn_gamma, float epsilon, const Window &window);
112 
113  FuseBatchNormFunction *_func;
114 };
115 } // namespace arm_compute
116 #endif /*ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H */
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...
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
~NEFuseBatchNormalizationKernel()=default
Default destructor.
OpenNE kernel to fuse the batch normalization node to a preceding convolution node.
const char * name() const override
Name of the kernel.
Common interface for all kernels implemented in C++.
Definition: ICPPKernel.h:38
NEFuseBatchNormalizationKernel & operator=(const NEFuseBatchNormalizationKernel &)=delete
Prevent instances of this class from being copied (As this class contains pointers) ...
Store the tensor's metadata.
Definition: ITensorInfo.h:40
Status class.
Definition: Error.h:52
Interface for Neon tensor.
Definition: ITensor.h:36
Copyright (c) 2017-2021 Arm Limited.
void run(const Window &window, const ThreadInfo &info) override
Execute the kernel on the passed window.
FuseBatchNormalizationType
Available FuseBatchNormalizationType.
Definition: Types.h:162
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 source, destination of the kernel.
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
Information about executing thread and CPU.
Definition: CPPTypes.h:235
Describe a multidimensional execution window.
Definition: Window.h:39