/* * Copyright (c) 2017-2020 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_NEBATCHNORMALIZATIONLAYERKERNEL_H #define ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H #include "src/core/NEON/INEKernel.h" namespace arm_compute { // Forward declarations class ITensor; /** Interface for the batch normalization layer kernel. */ class NEBatchNormalizationLayerKernel : public INEKernel { public: const char *name() const override { return "NEBatchNormalizationLayerKernel"; } /** Default constructor */ NEBatchNormalizationLayerKernel(); /** Prevent instances of this class from being copied (As this class contains pointers) */ NEBatchNormalizationLayerKernel(const NEBatchNormalizationLayerKernel &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ NEBatchNormalizationLayerKernel &operator=(const NEBatchNormalizationLayerKernel &) = delete; /** Default Move Constructor. */ NEBatchNormalizationLayerKernel(NEBatchNormalizationLayerKernel &&) = default; /** Default move assignment operator */ NEBatchNormalizationLayerKernel &operator=(NEBatchNormalizationLayerKernel &&) = default; /** Default destructor */ ~NEBatchNormalizationLayerKernel() = default; /** Set the input and output tensors. * * @note If the output tensor is a nullptr, the batch normalization function will be performed in-place * * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result. * 3 lower dimensions represent a single input with dimensions [width, height, FM]. * The rest are optional and used for representing batches. Data types supported: F16/F32. * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @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 * @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 * @param[in] epsilon (Optional) Small value to avoid division with zero. Default value is 0.001f. * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. */ void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta = nullptr, const ITensor *gamma = nullptr, float epsilon = 0.001f, ActivationLayerInfo act_info = ActivationLayerInfo()); /** Static function to check if given info will lead to a valid configuration of @ref NEBatchNormalizationLayerKernel * * @param[in] input Source tensor info. In case of @p output tensor = nullptr, this tensor will store the result. * 3 lower dimensions represent a single input with dimensions [width, height, FM]. * The rest are optional and used for representing batches. Data types supported: F16/F32. * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input * @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 * @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 * @param[in] epsilon (Optional) Small value to avoid division with zero. Default value is 0.001f. * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *var, const ITensorInfo *beta = nullptr, const ITensorInfo *gamma = nullptr, float epsilon = 0.001f, ActivationLayerInfo act_info = ActivationLayerInfo()); // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; private: /** Configure execution function in case of non-fused activation **/ void configure_non_fused(); /** Configure execution function in case of fused activation **/ void configure_fused(); /** Template function to run batch normalization on fp32 * * @tparam T Specialization data type * @tparam fused_activation Boolean that flags if its a fused activation or not * @tparam F Activation function functor to run * * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). */ template void batch_normalization_nchw(const Window &window); /** Template function to run batch normalization on fp32 on tensors with NHWC format * * @tparam T Specialization data type * @tparam fused_activation Boolean that flags if its a fused activation or not * @tparam F Activation function functor to run * * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()). */ template void batch_normalization_nhwc(const Window &window); /** Common signature for all the batch normalization functions * * @param[in] window Region on which to execute the kernel. */ using BatchNormFunctionPtr = void (NEBatchNormalizationLayerKernel::*)(const Window &window); private: BatchNormFunctionPtr _func; ITensor *_input; ITensor *_output; const ITensor *_mean; const ITensor *_var; const ITensor *_gamma; const ITensor *_beta; float _epsilon; ActivationLayerInfo _act_info; }; } // namespace arm_compute #endif /*ARM_COMPUTE_NEBATCHNORMALIZATIONLAYERKERNEL_H */