| /* |
| * Copyright (c) 2018-2020 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #ifndef ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H |
| #define ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H |
| |
| #include "src/core/NEON/INEKernel.h" |
| |
| namespace arm_compute |
| { |
| // Forward declarations |
| class ITensor; |
| |
| /** OpenNE kernel to fuse the batch normalization node to a preceding convolution node */ |
| class NEFuseBatchNormalizationKernel : public INEKernel |
| { |
| public: |
| const char *name() const override |
| { |
| return "NEFuseBatchNormalizationKernel"; |
| } |
| /** Default constructor */ |
| NEFuseBatchNormalizationKernel(); |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEFuseBatchNormalizationKernel(const NEFuseBatchNormalizationKernel &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NEFuseBatchNormalizationKernel &operator=(const NEFuseBatchNormalizationKernel &) = delete; |
| /** Allow instances of this class to be moved */ |
| NEFuseBatchNormalizationKernel(NEFuseBatchNormalizationKernel &&) = default; |
| /** Allow instances of this class to be moved */ |
| NEFuseBatchNormalizationKernel &operator=(NEFuseBatchNormalizationKernel &&) = default; |
| /** Default destructor */ |
| ~NEFuseBatchNormalizationKernel() = default; |
| /** Set the source, destination of the kernel |
| * |
| * @param[in] input_weights Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC |
| * @param[in] bn_mean Batch normalization layer mean tensor. Same as @p input_weights |
| * @param[in] bn_var Batch normalization layer variance tensor. Same as @p input_weights |
| * @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 |
| * @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 |
| * @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 |
| * @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 |
| * @note if nullptr, bn_beta is set to 0.0 |
| * @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 |
| * @note if nullptr, bn_gamma is set to 1.0 |
| * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. |
| * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to CONVOLUTION. |
| */ |
| 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); |
| /** Static function to check if given info will lead to a valid configuration of @ref NEFuseBatchNormalizationKernel |
| * |
| * @param[in] input_weights Input weights tensor info for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC |
| * @param[in] bn_mean Batch normalization layer mean tensor info. Same as @p input_weights |
| * @param[in] bn_var Batch normalization layer variance tensor info. Same as @p input_weights |
| * @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 |
| * @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 |
| * @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 |
| * @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 |
| * @note if nullptr, bn_beta is set to 0.0 |
| * @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 |
| * @note if nullptr, bn_gamma is set to 1.0 |
| * @param[in] epsilon (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f. |
| * @param[in] fbn_type (Optional) Fused batch normalization type. Defaults to CONVOLUTION. |
| * |
| * @return a status |
| */ |
| 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); |
| |
| // Inherited methods overridden: |
| void run(const Window &window, const ThreadInfo &info) override; |
| |
| private: |
| const ITensor *_input_weights; |
| const ITensor *_input_bias; |
| const ITensor *_bn_mean; |
| const ITensor *_bn_var; |
| const ITensor *_bn_gamma; |
| const ITensor *_bn_beta; |
| ITensor *_fused_weights; |
| ITensor *_fused_bias; |
| float _epsilon; |
| bool _run_in_place_weights; |
| bool _run_in_place_bias; |
| |
| using FuseBatchNormFunction = void(const ITensor *input_weights, const ITensor *input_bias, ITensor *fused_weights, ITensor *fused_bias, |
| const ITensor *bn_mean, const ITensor *bn_var, const ITensor *bn_beta, const ITensor *bn_gamma, float epsilon, const Window &window); |
| |
| FuseBatchNormFunction *_func; |
| }; |
| } // namespace arm_compute |
| #endif /*ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H */ |