1 /* 2 * Copyright (c) 2018-2020 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_NEFUSEBATCHNORMALIZATIONKERNEL_H 25 #define ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H 26 27 #include "src/core/NEON/INEKernel.h" 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 */ 35 class NEFuseBatchNormalizationKernel : public INEKernel 36 { 37 public: name()38 const char *name() const override 39 { 40 return "NEFuseBatchNormalizationKernel"; 41 } 42 /** Default constructor */ 43 NEFuseBatchNormalizationKernel(); 44 /** Prevent instances of this class from being copied (As this class contains pointers) */ 45 NEFuseBatchNormalizationKernel(const NEFuseBatchNormalizationKernel &) = delete; 46 /** Prevent instances of this class from being copied (As this class contains pointers) */ 47 NEFuseBatchNormalizationKernel &operator=(const NEFuseBatchNormalizationKernel &) = delete; 48 /** Allow instances of this class to be moved */ 49 NEFuseBatchNormalizationKernel(NEFuseBatchNormalizationKernel &&) = default; 50 /** Allow instances of this class to be moved */ 51 NEFuseBatchNormalizationKernel &operator=(NEFuseBatchNormalizationKernel &&) = default; 52 /** Default destructor */ 53 ~NEFuseBatchNormalizationKernel() = default; 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, 71 float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); 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, 92 float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); 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 */ 117