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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_NECONVOLUTIONLAYER_H__
#define __ARM_COMPUTE_NECONVOLUTIONLAYER_H__
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/core/NEON/kernels/NECol2ImKernel.h"
#include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMTranspose1xWKernel.h"
#include "arm_compute/core/NEON/kernels/NEIm2ColKernel.h"
#include "arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/Tensor.h"
namespace arm_compute
{
class ITensor;
/** Function to reshape and perform 1xW transposition on the weights. This function calls the following kernels:
* -# @ref NEWeightsReshapeKernel
* -# @ref NEGEMMTranspose1xWKernel (executed in case GEMM is required for the operation)
*/
class NEConvolutionLayerReshapeWeights : public IFunction
{
public:
/** Constructor */
NEConvolutionLayerReshapeWeights();
/** Set the input and output tensors.
*
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QS8/QS16/F32.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
* @param[out] output Destination tensor. Data types supported: Same as @p weights.
* @param[in] transpose1xW True if the weights are to undergo a 1xW transposition after reshaping (in case of GEMM operation), false otherwise.
* Data types supported: Same as @p weights.
*/
void configure(const ITensor *weights, const ITensor *biases, ITensor *output, bool transpose1xW);
// Inherited methods overridden:
void run() override;
private:
NEWeightsReshapeKernel _weights_reshape_kernel;
NEGEMMTranspose1xWKernel _weights_transposed_kernel;
Tensor _weights_reshaped;
bool _transpose1xW;
};
/** Basic function to simulate a convolution layer. This function calls the following NEON kernels:
* -# @ref NEWeightsReshapeKernel (executed only once for each configuration)
* -# @ref NEIm2ColKernel
* -# @ref NEGEMMInterleave4x4Kernel (executed only in case GEMM is required for the operation)
* -# @ref NEGEMMMatrixMultiplyKernel
* -# @ref NECol2ImKernel
*/
class NEConvolutionLayer : public IFunction
{
public:
/** Constructor */
NEConvolutionLayer();
/** Set the input and output tensors.
*
* @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
* while every optional dimension from 4 and above represent a batch of inputs.
* Data types supported: QS8/QS16/F32.
* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
* Data types supported: Same as @p input.
* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
* @param[in] weights_info Specifies if the weights tensor has been reshaped with NEWeightsReshapeKernel. If this is not part of the fully connected layer the weights
* tensor has also been transposed with NEGEMMTranspose1xWKernel. Data type supported: Same as @p input.
*/
void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo());
// Inherited methods overridden:
void run() override;
private:
NEIm2ColKernel _input_im2col_kernel;
NEGEMMInterleave4x4Kernel _input_interleave_kernel;
NEConvolutionLayerReshapeWeights _reshape_weights;
NEGEMMMatrixMultiplyKernel _mm_kernel;
NECol2ImKernel _output_col2im_kernel;
Tensor _input_im2col_reshaped;
Tensor _input_interleaved_reshaped;
Tensor _weights_reshaped;
Tensor _gemm_output;
bool _has_bias;
bool _is_fully_connected_convolution;
bool _are_weights_reshaped;
};
}
#endif /* __ARM_COMPUTE_NECONVOLUTIONLAYER_H__ */
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