112 lines
6.1 KiB
C++
112 lines
6.1 KiB
C++
/*
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* Copyright (c) 2017-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#ifndef ARM_COMPUTE_NELOCALLYCONNECTEDLAYER_H
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#define ARM_COMPUTE_NELOCALLYCONNECTEDLAYER_H
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#include "arm_compute/runtime/IFunction.h"
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#include "arm_compute/core/Types.h"
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#include "arm_compute/runtime/IMemoryManager.h"
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#include "arm_compute/runtime/MemoryGroup.h"
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#include "arm_compute/runtime/NEON/functions/NECol2Im.h"
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#include "arm_compute/runtime/NEON/functions/NEIm2Col.h"
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#include "arm_compute/runtime/Tensor.h"
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#include <memory>
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namespace arm_compute
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{
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class INETensor;
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class NEWeightsReshapeKernel;
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class NELocallyConnectedMatrixMultiplyKernel;
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/** Basic function to compute the locally connected layer. This function calls the following NEON kernels:
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*
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* -# @ref NEWeightsReshapeKernel (executed only once for each configuration)
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* -# @ref NEIm2ColKernel
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* -# @ref NELocallyConnectedMatrixMultiplyKernel
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* -# @ref NECol2ImKernel
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*/
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class NELocallyConnectedLayer : public IFunction
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{
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public:
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/** Default constructor */
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NELocallyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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NELocallyConnectedLayer(const NELocallyConnectedLayer &) = delete;
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/** Prevent instances of this class from being moved (As this class contains pointers) */
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NELocallyConnectedLayer(NELocallyConnectedLayer &&) = delete;
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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NELocallyConnectedLayer &operator=(const NELocallyConnectedLayer &) = delete;
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/** Prevent instances of this class from being moved (As this class contains pointers) */
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NELocallyConnectedLayer &operator=(NELocallyConnectedLayer &&) = delete;
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/** Default destructor */
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~NELocallyConnectedLayer();
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/** Set the input and output tensors.
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*
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* @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
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* while every optional dimension from 4 and above represent a batch of inputs.
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* Data types supported: F16, F32.
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* @param[in] weights Weights tensor. Weights are 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches]. Data type supported:Same as @p input.
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* @param[in] biases Biases tensor. Shared biases supported. Biases are 2D tensor with dimensions [OFM, num_patches]. Data type supported:Same as @p input.
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* @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
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* Data types supported: Same as @p input.
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* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
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*/
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ARM_COMPUTE_DEPRECATED_REL(20.11)
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void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info);
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/** Static function to check if given info will lead to a valid configuration of @ref NELocallyConnectedLayer
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*
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* @param[in] input Input tensor info. 3 lower dimensions represent a single input [width, height, IFM],
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* while every optional dimension from 4 and above represent a batch of inputs.
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* Data types supported: F16, F32.
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* @param[in] weights Weights tensor info. Weights are 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM, num_patches]. Data type supported:Same as @p input.
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* @param[in] biases Biases tensor info. Shared biases supported. Biases are 2D tensor with dimensions [OFM, num_patches]. Data type supported:Same as @p input.
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* @param[in] output Output tensor info. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs.
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* Data types supported: Same as @p input.
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* @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo.
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*
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* @return a status
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*/
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static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info);
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// Inherited methods overridden:
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void run() override;
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void prepare() override;
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private:
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MemoryGroup _memory_group;
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NEIm2Col _input_im2col;
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std::unique_ptr<NEWeightsReshapeKernel> _weights_reshape_kernel;
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std::unique_ptr<NELocallyConnectedMatrixMultiplyKernel> _mm_kernel;
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NECol2Im _output_col2im;
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Tensor _input_im2col_reshaped;
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Tensor _weights_reshaped;
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Tensor _gemm_output;
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bool _is_prepared;
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const ITensor *_original_weights;
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};
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}
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#endif /* ARM_COMPUTE_NELOCALLYCONNECTEDLAYER_H */
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