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author | Giorgio Arena <giorgio.arena@arm.com> | 2018-02-07 15:38:12 +0000 |
---|---|---|
committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:47:18 +0000 |
commit | 1167487ea8e54a76d0a3625e0aa84e2ad9ffd317 (patch) | |
tree | 287dbc45e895c6b637fecc692c04bd4ae59580ae /arm_compute/runtime | |
parent | 4e1e7dcd581adecd5ad9c0f9503fc3c43f8222ef (diff) | |
download | ComputeLibrary-1167487ea8e54a76d0a3625e0aa84e2ad9ffd317.tar.gz |
COMPMID-897 Merge batch normalization with bounded relu
Change-Id: I9a607fe620f795cdea1a99fdd3f5f8c2fc76f980
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/119234
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'arm_compute/runtime')
3 files changed, 64 insertions, 52 deletions
diff --git a/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h b/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h index 127de10555..3d5145a697 100644 --- a/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h +++ b/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -48,35 +48,38 @@ 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. */ - void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon); + void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon, + ActivationLayerInfo act_info = ActivationLayerInfo()); /** Static function to check if given info will lead to a valid configuration of @ref CLBatchNormalizationLayer * - * @param[in] input Source tensor info. In case of @p output tensor info = 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 info = 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. * * @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() override; diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h index 9d81b9a7f7..01e53d26f5 100644 --- a/arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h +++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -46,16 +46,18 @@ public: GCBatchNormalizationLayer(); /** Set the input and output tensors. * - * @param[in] input Source tensor. 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 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] input Source tensor. 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 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. */ - void configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, float epsilon); + void configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, float epsilon, + ActivationLayerInfo act_info = ActivationLayerInfo()); // Inherited methods overridden: void run() override; diff --git a/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h b/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h index 1933468afc..5c8200beda 100644 --- a/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h +++ b/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -27,6 +27,7 @@ #include "arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h" #include "arm_compute/core/Types.h" #include "arm_compute/runtime/IFunction.h" +#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" namespace arm_compute { @@ -47,41 +48,47 @@ 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. */ - 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 NEBatchNormalizationLayer * - * @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. * * @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() override; private: NEBatchNormalizationLayerKernel _norm_kernel; /**< Batch normalization layer kernel */ + // COMPMID-906 Use fused activation in NEON Batch normalization + NEActivationLayer _act_func; + bool _act_info_enabled; }; } #endif /* __ARM_COMPUTE_NEBATCHNORMALIZATIONLAYER_H__ */ |