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/*
* 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_CLCONVOLUTIONLAYER_H__
#define __ARM_COMPUTE_CLCONVOLUTIONLAYER_H__
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/core/CL/kernels/CLCol2ImKernel.h"
#include "arm_compute/core/CL/kernels/CLFillBorderKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h"
#include "arm_compute/core/CL/kernels/CLGEMMTranspose1xWKernel.h"
#include "arm_compute/core/CL/kernels/CLIm2ColKernel.h"
#include "arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/CL/CLMemoryGroup.h"
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/functions/CLGEMM.h"
#include "arm_compute/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.h"
#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
#include "arm_compute/runtime/IMemoryManager.h"
#include <memory>
namespace arm_compute
{
class ICLTensor;
/** Function to reshape and transpose the weights. This function calls the following kernels:
* -# @ref CLWeightsReshapeKernel
* -# @ref CLGEMMTranspose1xWKernel
*/
class CLConvolutionLayerReshapeWeights : public IFunction
{
public:
/** Constructor */
CLConvolutionLayerReshapeWeights(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** 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/QASYMM8/QS16/F16/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 ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, bool transpose1xW);
// Inherited methods overridden:
void run() override;
private:
CLMemoryGroup _memory_group;
CLWeightsReshapeKernel _weights_reshape_kernel;
CLGEMMTranspose1xWKernel _weights_transposed_kernel;
CLTensor _weights_reshaped;
bool _transpose1xW;
};
/** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
*
* Note: weights already reshaped for quantized asymmetric is not supported
*
* -# @ref CLIm2ColKernel
* -# @ref CLGEMMLowpMatrixMultiplyCore (if quantized asymmetric)
* -# @ref CLGEMMLowpQuantizeDownInt32ToUint8Scale (if quantized asymmetric)
* -# @ref CLCol2ImKernel
*
* if the weights are already reshaped:
* -# @ref CLGEMMInterleave4x4Kernel
* -# @ref CLGEMMMatrixMultiplyKernel
* else
* -# @ref CLGEMM
*/
class CLConvolutionLayer : public IFunction
{
public:
/** Default constructor */
CLConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
/** 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/QASYMM8/QS16/F16/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: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
* @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 CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights
* tensor has also been transposed with CLGEMMTranspose1xWKernel. Data type supported: Same as @p input.
*/
void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo());
// Inherited methods overridden:
void run() override;
private:
/** Configures the appropriate matrix multiply routine
*
* @param input Input tensor. Data types supported: QS8/QASYMM8/QS16/F16/F32.
* @param weights Weights tensor. Data type supported: Same as @p input.
* @param output Output tensor. Data types supported: Same as @p input,
* except for input of QASYMM8 type where output should be of S32 type.
* @param is_interleaved_transposed Flag that signals if matrix is interleaved transposed
*/
void configure_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output, bool is_interleaved_transposed, bool are_weights_reshaped);
private:
CLMemoryGroup _memory_group;
CLConvolutionLayerReshapeWeights _reshape_weights;
CLIm2ColKernel _im2col_kernel;
CLGEMMInterleave4x4Kernel _interleave_kernel;
CLGEMMMatrixMultiplyKernel _mm_kernel;
CLGEMM _mm_gemm;
CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage;
CLCol2ImKernel _col2im_kernel;
CLTensor _im2col_output;
CLTensor _interleave_output;
CLTensor _weights_reshaped;
CLTensor _weights_transposed;
CLTensor _gemm_output;
CLTensor _tmp_output;
bool _are_weights_reshaped;
bool _is_quantized;
bool _is_interleaved_transposed;
};
}
#endif /* __ARM_COMPUTE_CLCONVOLUTIONLAYER_H__ */
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