1 /* 2 * Copyright (c) 2018-2021 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_CLFUSEBATCHNORMALIZATION_H 25 #define ARM_COMPUTE_CLFUSEBATCHNORMALIZATION_H 26 27 #include "arm_compute/core/Types.h" 28 #include "arm_compute/runtime/IFunction.h" 29 30 #include <memory> 31 32 namespace arm_compute 33 { 34 // Forward declarations 35 class CLCompileContext; 36 class CLFuseBatchNormalizationKernel; 37 class ICLTensor; 38 class ITensorInfo; 39 40 /** Basic function to fuse the batch normalization node to a preceding convolution node */ 41 class CLFuseBatchNormalization : public IFunction 42 { 43 public: 44 /** Default constructor */ 45 CLFuseBatchNormalization(); 46 /** Prevent instances of this class from being copied (As this class contains pointers) */ 47 CLFuseBatchNormalization(const CLFuseBatchNormalization &) = delete; 48 /** Prevent instances of this class from being copied (As this class contains pointers) */ 49 CLFuseBatchNormalization &operator=(const CLFuseBatchNormalization &) = delete; 50 /** Allow instances of this class to be moved */ 51 CLFuseBatchNormalization(CLFuseBatchNormalization &&) = default; 52 /** Allow instances of this class to be moved */ 53 CLFuseBatchNormalization &operator=(CLFuseBatchNormalization &&) = default; 54 /** Default destructor */ 55 ~CLFuseBatchNormalization(); 56 /** Set the input and output tensors. 57 * 58 * Valid data layouts: 59 * - NHWC 60 * - NCHW 61 * 62 * Valid data type configurations: 63 * |src |dst | 64 * |:--------------|:--------------| 65 * |F32 |F32 | 66 * |F16 |F16 | 67 * 68 * @param[in] input_weights Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC 69 * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p input_weights 70 * @param[in] bn_var Batch normalization layer variance tensor. Same as @p input_weights 71 * @param[out] fused_weights Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights 72 * @param[out] fused_bias Output fused bias tensor. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights 73 * @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 74 * @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 75 * @note if nullptr, bn_beta is set to 0.0 76 * @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 77 * @note if nullptr, bn_gamma is set to 1.0 78 * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. 79 * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to Convolution. 80 */ 81 void configure(const ICLTensor *input_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var, ICLTensor *fused_weights, ICLTensor *fused_bias, 82 const ICLTensor *input_bias = nullptr, const ICLTensor *bn_beta = nullptr, const ICLTensor *bn_gamma = nullptr, 83 float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); 84 /** Set the input and output tensors. 85 * 86 * @param[in] compile_context The compile context to be used. 87 * @param[in] input_weights Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC 88 * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p input_weights 89 * @param[in] bn_var Batch normalization layer variance tensor. Same as @p input_weights 90 * @param[out] fused_weights Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights 91 * @param[out] fused_bias Output fused bias tensor. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights 92 * @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 93 * @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 94 * @note if nullptr, bn_beta is set to 0.0 95 * @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 96 * @note if nullptr, bn_gamma is set to 1.0 97 * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. 98 * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to Convolution. 99 */ 100 void configure(const CLCompileContext &compile_context, const ICLTensor *input_weights, const ICLTensor *bn_mean, const ICLTensor *bn_var, ICLTensor *fused_weights, ICLTensor *fused_bias, 101 const ICLTensor *input_bias = nullptr, const ICLTensor *bn_beta = nullptr, const ICLTensor *bn_gamma = nullptr, 102 float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); 103 /** Static function to check if given info will lead to a valid configuration of @ref CLFuseBatchNormalization 104 * 105 * @param[in] input_weights Input weights tensor info for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC 106 * @param[in] bn_mean Batch normalization layer mean tensor info. Same as @p input_weights 107 * @param[in] bn_var Batch normalization layer variance tensor info. Same as @p input_weights 108 * @param[in] fused_weights Output fused weights tensor info. It can be a nullptr in case of in-place computation. Same as @p input_weights 109 * @param[in] fused_bias 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 110 * @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 111 * @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 112 * @note if nullptr, bn_beta is set to 0.0 113 * @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 114 * @note if nullptr, bn_gamma is set to 1.0 115 * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. 116 * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to Convolution. 117 * 118 * @return a status 119 */ 120 static Status validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var, 121 const ITensorInfo *fused_weights, const ITensorInfo *fused_bias, 122 const ITensorInfo *input_bias = nullptr, const ITensorInfo *bn_beta = nullptr, const ITensorInfo *bn_gamma = nullptr, 123 float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); 124 125 // Inherited methods overridden: 126 void run() override; 127 128 private: 129 std::unique_ptr<CLFuseBatchNormalizationKernel> _fuse_bn_kernel; 130 }; 131 } // namespace arm_compute 132 #endif /*ARM_COMPUTE_CLFUSEBATCHNORMALIZATION_H */ 133