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_NEFUSEBATCHNORMALIZATION_H 25 #define ARM_COMPUTE_NEFUSEBATCHNORMALIZATION_H 26 27 #include "arm_compute/core/ITensor.h" 28 #include "arm_compute/core/Types.h" 29 #include "arm_compute/runtime/IFunction.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 */ 38 class NEFuseBatchNormalization : public IFunction 39 { 40 public: 41 /** Default constructor */ 42 NEFuseBatchNormalization(); 43 /** Prevent instances of this class from being copied (As this class contains pointers) */ 44 NEFuseBatchNormalization(const NEFuseBatchNormalization &) = delete; 45 /** Prevent instances of this class from being copied (As this class contains pointers) */ 46 NEFuseBatchNormalization &operator=(const NEFuseBatchNormalization &) = delete; 47 /** Allow instances of this class to be moved */ 48 NEFuseBatchNormalization(NEFuseBatchNormalization &&) = default; 49 /** Allow instances of this class to be moved */ 50 NEFuseBatchNormalization &operator=(NEFuseBatchNormalization &&) = default; 51 /** Default destructor */ 52 ~NEFuseBatchNormalization(); 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, 80 float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); 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, 101 float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION); 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 */ 111