arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h

/*
 * 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: 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,
                   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: 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, ActivationLayerInfo act_info);

    // 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__ */