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/*
* Copyright (c) 2018-2022 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_CPU_CONVERT_FULLYCONNECTED_WEIGHTS_KERNEL_H
#define ARM_COMPUTE_CPU_CONVERT_FULLYCONNECTED_WEIGHTS_KERNEL_H
#include "src/core/common/Macros.h"
#include "src/cpu/ICpuKernel.h"
namespace arm_compute
{
namespace cpu
{
namespace kernels
{
/** 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 CpuConvertFullyConnectedWeightsKernel : public ICpuKernel<CpuConvertFullyConnectedWeightsKernel>
{
public:
CpuConvertFullyConnectedWeightsKernel() = default;
ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuConvertFullyConnectedWeightsKernel);
/** Set the src and dst tensor.
*
* @param[in] src Source weights tensor info to convert. Must be 2 dimensional. Data types supported: All.
* @param[in] dst The converted weights tensor info. Shape and Data Type: Same as @p src.
* @param[in] original_input_shape Shape of the original src tensor (the one entering fully connected layer).
* @param[in] data_layout The data layout the weights have been trained in.
*/
void configure(const ITensorInfo *src,
ITensorInfo *dst,
const TensorShape &original_input_shape,
DataLayout data_layout);
/** Static function to check if given info will lead to a valid configuration
*
* Similar to @ref CpuConvertFullyConnectedWeightsKernel::configure()
*
* @return a status
*/
static Status validate(const ITensorInfo *src,
const ITensorInfo *dst,
const TensorShape &original_input_shape,
DataLayout data_layout);
// Inherited methods overridden:
void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
const char *name() const override;
private:
unsigned int _factor1{
0}; /* equals to the number of elements per original src plane if @p data_layout == NCHW; its number of channels otherwise */
unsigned int _factor2{
0}; /* equals to the number of elements per original src plane if @p data_layout == NHWC; its number of channels otherwise */
};
} // namespace kernels
} // namespace cpu
} // namespace arm_compute
#endif /* ARM_COMPUTE_CPU_CONVERT_FULLYCONNECTED_WEIGHTS_KERNEL_H */
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