124 lines
6.8 KiB
C++
124 lines
6.8 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_NEDIRECTCONVOLUTIONLAYER_H
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#define ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYER_H
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#include "arm_compute/core/Types.h"
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#include "arm_compute/runtime/IFunction.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/NEActivationLayer.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 NEDirectConvolutionLayerOutputStageKernel;
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class NEDirectConvolutionLayerKernel;
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class NEFillBorderKernel;
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/** Function to run the direct convolution.
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*
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* This function calls the following NEON kernels:
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*
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* -# @ref NEFillBorderKernel for the input
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* -# @ref NEDirectConvolutionLayerOutputStageKernel
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* -# @ref NEDirectConvolutionLayerKernel
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*/
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class NEDirectConvolutionLayer : public IFunction
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{
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public:
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/** Constructor */
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NEDirectConvolutionLayer(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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NEDirectConvolutionLayer(const NEDirectConvolutionLayer &) = delete;
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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NEDirectConvolutionLayer &operator=(const NEDirectConvolutionLayer &) = delete;
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/** Prevent instances of this class from being moved (As this class contains non movable objects) */
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NEDirectConvolutionLayer(NEDirectConvolutionLayer &&) = delete;
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/** Prevent instances of this class from being moved (As this class contains non movable objects) */
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NEDirectConvolutionLayer &operator=(NEDirectConvolutionLayer &&) = delete;
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/** Default destructor */
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~NEDirectConvolutionLayer();
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/** Set the input, weights, biases and output tensors.
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*
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* @note: DirectConvolution only works in the following configurations:
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* 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
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* 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
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* 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32
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*
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* @param[in, out] input Input tensor. Data types supported: F16/F32.
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* @param[in] weights Set of kernels to convolve the input volume.
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* Supported sizes: 1x1, 3x3 and 5x5.
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* The 3rd dimension must be the same as the input's volume 3rd dimension.
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* Data type supported: Same as @p input.
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* @param[in] bias Set of biases. Can be nullptr. Data type supported: Same as @p input.
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* @param[out] output Output tensor.
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* The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. 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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* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
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*/
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void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo());
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/** Static function to check if given info will lead to a valid configuration of @ref NEDirectConvolutionLayer
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*
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* @note: DirectConvolution only works in the following configurations:
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* 1x1 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
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* 3x3 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F16/F32
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* 5x5 convolution with stride_x = 1/2/3, stride_y = 1/2/3 data type = F32
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*
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* @param[in] input Input tensor. Data types supported: F16/F32.
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* @param[in] weights Set of kernels to convolve the input volume.
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* Supported sizes: 1x1, 3x3 and 5x5.
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* The 3rd dimension must be the same as the input's volume 3rd dimension.
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* Data type supported: Same as @p input.
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* @param[in] bias Set of biases. Can be nullptr. Data type supported: Same as @p input.
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* @param[in] output Output tensor.
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* The 3rd dimensions must be equal to the 4th dimension of the @p kernels tensor. 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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* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
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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 *bias, const ITensorInfo *output, const PadStrideInfo &conv_info,
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const ActivationLayerInfo &act_info = ActivationLayerInfo());
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// Inherited methods overridden:
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void run() override;
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private:
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MemoryGroup _memory_group;
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std::unique_ptr<NEDirectConvolutionLayerOutputStageKernel> _output_stage_kernel;
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std::unique_ptr<NEDirectConvolutionLayerKernel> _conv_kernel;
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std::unique_ptr<NEFillBorderKernel> _input_border_handler;
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NEActivationLayer _activationlayer_function;
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Tensor _accumulator;
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bool _has_bias;
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bool _is_activationlayer_enabled;
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unsigned int _dim_split;
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bool _is_padding_required;
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};
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}
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#endif /* ARM_COMPUTE_NEDIRECTCONVOLUTIONLAYER_H */
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