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/*
* Copyright (c) 2017-2018 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_CLBATCHNORMALIZATIONLAYERKERNEL_H__
#define __ARM_COMPUTE_CLBATCHNORMALIZATIONLAYERKERNEL_H__
#include "arm_compute/core/CL/ICLKernel.h"
namespace arm_compute
{
class ICLTensor;
/** Interface for the BatchNormalization layer kernel.
*/
class CLBatchNormalizationLayerKernel : public ICLKernel
{
public:
/** Constructor */
CLBatchNormalizationLayerKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLBatchNormalizationLayerKernel(const CLBatchNormalizationLayerKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLBatchNormalizationLayerKernel &operator=(const CLBatchNormalizationLayerKernel &) = delete;
/** Default Move Constructor. */
CLBatchNormalizationLayerKernel(CLBatchNormalizationLayerKernel &&) = default;
/** Default move assignment operator */
CLBatchNormalizationLayerKernel &operator=(CLBatchNormalizationLayerKernel &&) = default;
/** Default destructor */
~CLBatchNormalizationLayerKernel() = 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. Data layouts supported: NCHW/NHWC.
* @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(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta = nullptr, const ICLTensor *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 CLBatchNormalizationLayerKernel
*
* @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: F16/F32. Data layouts supported: NCHW/NHWC.
* @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, cl::CommandQueue &queue) override;
private:
ICLTensor *_input;
ICLTensor *_output;
const ICLTensor *_mean;
const ICLTensor *_var;
const ICLTensor *_beta;
const ICLTensor *_gamma;
float _epsilon;
bool _run_in_place;
};
} // namespace arm_compute
#endif /*__ARM_COMPUTE_CLBATCHNORMALIZATIONLAYERKERNEL_H__ */
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