From 57c033bb5400ef19e5952f191da3e878e21bba91 Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Thu, 15 Feb 2018 12:29:44 +0000 Subject: COMPMID-906: Use fused activation in NEON Batch normalization Change-Id: I5a6413548b2c9b8972c91ddba57395509dffd87e Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/120656 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- .../NEON/kernels/NEBatchNormalizationLayerKernel.h | 107 +++++++++++++++------ 1 file changed, 78 insertions(+), 29 deletions(-) (limited to 'arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h') diff --git a/arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h b/arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h index f748830b81..63eb739487 100644 --- a/arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h +++ b/arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h @@ -55,49 +55,98 @@ public: * * @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: QS8/QS16/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 Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input - * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input - * @param[in] epsilon Small value to avoid division with zero. + * @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: QS8/QS16/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 Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] epsilon Small value to avoid division with zero. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. + * Data types supported: F32 */ - void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon); + void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon, + 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: QS8/QS16/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 Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input - * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input - * @param[in] epsilon Small value to avoid division with zero. + * @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: QS8/QS16/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 Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input + * @param[in] epsilon Small value to avoid division with zero. + * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. + * Data types supported: F32 * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *var, const ITensorInfo *beta, const ITensorInfo *gamma, - float epsilon); + float epsilon, ActivationLayerInfo act_info); // Inherited methods overridden: void run(const Window &window, const ThreadInfo &info) override; private: - using BatchNormFunction = void(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon, const Window &window); - BatchNormFunction *_func; - ITensor *_input; - ITensor *_output; - const ITensor *_mean; - const ITensor *_var; - const ITensor *_gamma; - const ITensor *_beta; - float _epsilon; + /** 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 8-bit fixed point + * + * @tparam fused_activation Boolean that flags if its a fused activation or not + * + * @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_qs8(const Window &window); + /** Template function to run batch normalization on 16-bit fixed point + * + * @tparam fused_activation Boolean that flags if its a fused activation or not + * + * @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_qs16(const Window &window); + /** Template function to run batch normalization on fp16 + * + * @tparam fused_activation Boolean that flags if its a fused activation or not + * + * @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_fp16(const Window &window); + /** Template function to run batch normalization on fp32 + * + * @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_fp32(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__ */ -- cgit v1.2.1