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Diffstat (limited to 'arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h')
-rw-r--r-- | arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h | 107 |
1 files changed, 78 insertions, 29 deletions
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 <bool fused_activation> + 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 <bool fused_activation> + 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 <bool fused_activation> + 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 <bool fused_activation, typename F> + 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__ */ |