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/*
* Copyright (c) 2017 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_NEBATCHNORMALIZATIONLAYER_H__
#define __ARM_COMPUTE_NEBATCHNORMALIZATIONLAYER_H__
#include "arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/IFunction.h"
namespace arm_compute
{
class ITensor;
/** Basic function to run @ref NENormalizationLayerKernel and simulate a batch normalization layer.
*
* Batch normalization is calculated by:
* @f[ out_i = \gamma * (\frac{in_i - \mu_{B}}{\sqrt{\sigma^2_{B} + \epsilon}}) + \beta \equiv BN_{\gamma,\beta}(in_i) @f]
*
*/
class NEBatchNormalizationLayer : public IFunction
{
public:
/** Default constructor */
NEBatchNormalizationLayer();
/** 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: QS8/F32.
* @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] gamma Gamma 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] epsilon Small value to avoid division with zero.
* @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
*/
void configure(const ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon);
// Inherited methods overridden:
void run() override;
private:
NEBatchNormalizationLayerKernel _norm_kernel; /**< Batch normalization layer kernel */
};
}
#endif /* __ARM_COMPUTE_NEBATCHNORMALIZATIONLAYER_H__ */
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