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/*
* Copyright (c) 2018-2020 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_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H
#define ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H
#include "src/core/NEON/INEKernel.h"
namespace arm_compute
{
// Forward declarations
class ITensor;
/** Interface to convert the 2D Fully Connected weights from NCHW to NHWC or vice versa.
*
* @note This function can be applied to the 2D weights used by a Fully Connected layer if:
* - It follows a Convolution layer
* - The data layout used by the network does not match the one the model has been trained in.
*
* @note This function assumes the weights are already reshaped (transposed)
*/
class NEConvertFullyConnectedWeightsKernel : public INEKernel
{
public:
const char *name() const override
{
return "NEConvertFullyConnectedWeightsKernel";
}
/** Default constructor */
NEConvertFullyConnectedWeightsKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEConvertFullyConnectedWeightsKernel(const NEConvertFullyConnectedWeightsKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
NEConvertFullyConnectedWeightsKernel &operator=(const NEConvertFullyConnectedWeightsKernel &) = delete;
/** Allow instances of this class to be moved */
NEConvertFullyConnectedWeightsKernel(NEConvertFullyConnectedWeightsKernel &&) = default;
/** Allow instances of this class to be moved */
NEConvertFullyConnectedWeightsKernel &operator=(NEConvertFullyConnectedWeightsKernel &&) = default;
/** Default destructor */
~NEConvertFullyConnectedWeightsKernel() = default;
/** Set the input and output tensor.
*
* @param[in] input Source weights tensor to convert. Must be 2 dimensional. Data types supported: All.
* @param[out] output The converted weights tensor. Shape and Data Type: Same as @p input.
* @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
* @param[in] data_layout The data layout the weights have been trained in.
*/
void configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout);
/** Static function to check if given info will lead to a valid configuration of @ref NEConvertFullyConnectedWeightsKernel
*
* @param[in] input Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
* @param[in] output The converted weights tensor info. Shape and Data Type: Same as @p input.
* @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
* @param[in] data_layout The data layout the weights have been trained in.
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, DataLayout data_layout);
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
private:
/** Template function to run the permute
*
* @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
*/
template <typename T>
void run_convert_fc_weights(const Window &window);
const ITensor *_input;
ITensor *_output;
unsigned int _factor1; /* equals to the number of elements per original input plane if @p data_layout == NCHW; its number of channels otherwise */
unsigned int _factor2; /* equals to the number of elements per original input plane if @p data_layout == NHWC; its number of channels otherwise */
};
} // namespace arm_compute
#endif /*ARM_COMPUTE_NECONVERTFULLYCONNECTEDWEIGHTSKERNEL_H */