1 /* 2 * Copyright (c) 2017-2020 Arm Limited. 3 * 4 * SPDX-License-Identifier: MIT 5 * 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 8 * deal in the Software without restriction, including without limitation the 9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or 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, 18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 * SOFTWARE. 23 */ 24 #ifndef ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H 25 #define ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H 26 27 #include "src/core/NEON/INEKernel.h" 28 29 namespace arm_compute 30 { 31 // Forward declarations 32 class ITensor; 33 34 /** Interface for the batch normalization layer kernel. 35 */ 36 class NEBatchNormalizationLayerKernel : public INEKernel 37 { 38 public: name()39 const char *name() const override 40 { 41 return "NEBatchNormalizationLayerKernel"; 42 } 43 /** Default constructor */ 44 NEBatchNormalizationLayerKernel(); 45 /** Prevent instances of this class from being copied (As this class contains pointers) */ 46 NEBatchNormalizationLayerKernel(const NEBatchNormalizationLayerKernel &) = delete; 47 /** Prevent instances of this class from being copied (As this class contains pointers) */ 48 NEBatchNormalizationLayerKernel &operator=(const NEBatchNormalizationLayerKernel &) = delete; 49 /** Default Move Constructor. */ 50 NEBatchNormalizationLayerKernel(NEBatchNormalizationLayerKernel &&) = default; 51 /** Default move assignment operator */ 52 NEBatchNormalizationLayerKernel &operator=(NEBatchNormalizationLayerKernel &&) = default; 53 /** Default destructor */ 54 ~NEBatchNormalizationLayerKernel() = default; 55 /** Set the input and output tensors. 56 * 57 * @note If the output tensor is a nullptr, the batch normalization function will be performed in-place 58 * 59 * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result. 60 * 3 lower dimensions represent a single input with dimensions [width, height, FM]. 61 * The rest are optional and used for representing batches. Data types supported: F16/F32. 62 * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input 63 * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input 64 * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input 65 * @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 66 * @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 67 * @param[in] epsilon (Optional) Small value to avoid division with zero. Default value is 0.001f. 68 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. 69 */ 70 void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta = nullptr, const ITensor *gamma = nullptr, float epsilon = 0.001f, 71 ActivationLayerInfo act_info = ActivationLayerInfo()); 72 /** Static function to check if given info will lead to a valid configuration of @ref NEBatchNormalizationLayerKernel 73 * 74 * @param[in] input Source tensor info. In case of @p output tensor = nullptr, this tensor will store the result. 75 * 3 lower dimensions represent a single input with dimensions [width, height, FM]. 76 * The rest are optional and used for representing batches. Data types supported: F16/F32. 77 * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input 78 * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input 79 * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input 80 * @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 81 * @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 82 * @param[in] epsilon (Optional) Small value to avoid division with zero. Default value is 0.001f. 83 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. 84 * 85 * @return a status 86 */ 87 static Status validate(const ITensorInfo *input, const ITensorInfo *output, 88 const ITensorInfo *mean, const ITensorInfo *var, 89 const ITensorInfo *beta = nullptr, const ITensorInfo *gamma = nullptr, 90 float epsilon = 0.001f, ActivationLayerInfo act_info = ActivationLayerInfo()); 91 92 // Inherited methods overridden: 93 void run(const Window &window, const ThreadInfo &info) override; 94 95 private: 96 /** Configure execution function in case of non-fused activation **/ 97 void configure_non_fused(); 98 /** Configure execution function in case of fused activation **/ 99 void configure_fused(); 100 101 /** Template function to run batch normalization on fp32 102 * 103 * @tparam T Specialization data type 104 * @tparam fused_activation Boolean that flags if its a fused activation or not 105 * @tparam F Activation function functor to run 106 * 107 * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). 108 */ 109 template <typename T, bool fused_activation, typename F> 110 void batch_normalization_nchw(const Window &window); 111 /** Template function to run batch normalization on fp32 on tensors with NHWC format 112 * 113 * @tparam T Specialization data type 114 * @tparam fused_activation Boolean that flags if its a fused activation or not 115 * @tparam F Activation function functor to run 116 * 117 * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). 118 */ 119 template <typename T, bool fused_activation, typename F> 120 void batch_normalization_nhwc(const Window &window); 121 /** Common signature for all the batch normalization functions 122 * 123 * @param[in] window Region on which to execute the kernel. 124 */ 125 using BatchNormFunctionPtr = void (NEBatchNormalizationLayerKernel::*)(const Window &window); 126 127 private: 128 BatchNormFunctionPtr _func; 129 ITensor *_input; 130 ITensor *_output; 131 const ITensor *_mean; 132 const ITensor *_var; 133 const ITensor *_gamma; 134 const ITensor *_beta; 135 float _epsilon; 136 ActivationLayerInfo _act_info; 137 }; 138 } // namespace arm_compute 139 #endif /*ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H */ 140