162 lines
7.9 KiB
C++
162 lines
7.9 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_GCCONVOLUTIONLAYER_H
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#define ARM_COMPUTE_GCCONVOLUTIONLAYER_H
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#include "arm_compute/core/GLES_COMPUTE/kernels/GCCol2ImKernel.h"
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#include "arm_compute/core/GLES_COMPUTE/kernels/GCFillBorderKernel.h"
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#include "arm_compute/core/GLES_COMPUTE/kernels/GCIm2ColKernel.h"
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#include "arm_compute/core/GLES_COMPUTE/kernels/GCWeightsReshapeKernel.h"
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#include "arm_compute/core/Types.h"
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#include "arm_compute/runtime/GLES_COMPUTE/GCTensor.h"
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#include "arm_compute/runtime/GLES_COMPUTE/functions/GCActivationLayer.h"
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#include "arm_compute/runtime/GLES_COMPUTE/functions/GCGEMM.h"
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#include "arm_compute/runtime/IFunction.h"
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#include "arm_compute/runtime/MemoryGroup.h"
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#include <memory>
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namespace arm_compute
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{
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class IGCTensor;
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/** Function to reshape and transpose the weights. This function calls the following kernels:
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* -# @ref GCWeightsReshapeKernel
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*
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* @deprecated This function is deprecated and is intended to be removed in 21.05 release
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*
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*/
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class GCConvolutionLayerReshapeWeights : public IFunction
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{
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public:
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/** Constructor */
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GCConvolutionLayerReshapeWeights();
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/** Set the input and output tensors.
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*
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* @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM].
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* Data type supported: F16/F32.
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* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights.
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* @param[out] output Destination tensor. Data types supported: Same as @p weights.
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*/
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void configure(const IGCTensor *weights, const IGCTensor *biases, IGCTensor *output);
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// Inherited methods overridden:
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void run() override;
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private:
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GCWeightsReshapeKernel _weights_reshape_kernel;
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};
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/** Basic function to compute the convolution layer. This function calls the following GLES kernels:
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*
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* -# @ref GCWeightsReshapeKernel (executed only once for each configuration)
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* -# @ref GCGEMMTranspose1xWKernel (executed only once for each configuration)
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* -# @ref GCIm2ColKernel
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* -# @ref GCGEMMInterleave4x4Kernel
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* -# @ref GCCol2ImKernel
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*
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* @deprecated This function is deprecated and is intended to be removed in 21.05 release
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*
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*/
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class GCConvolutionLayer : public IFunction
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{
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public:
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/** Default constructor */
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GCConvolutionLayer(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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GCConvolutionLayer(const GCConvolutionLayer &) = delete;
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/** Default move constructor */
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GCConvolutionLayer(GCConvolutionLayer &&) = default;
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/** Prevent instances of this class from being copied (As this class contains pointers) */
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GCConvolutionLayer &operator=(const GCConvolutionLayer &) = delete;
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/** Default move assignment operator */
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GCConvolutionLayer &operator=(GCConvolutionLayer &&) = default;
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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 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input.
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* @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].
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* Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type.
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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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* @param[in] weights_info Specifies if the weights tensor has been reshaped with GCWeightsReshapeKernel. If this is not part of the fully connected layer the weights
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* tensor has also been transposed with GCGEMMTranspose1xWKernel. Data type supported: Same as @p input.
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* @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
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* @param[in] act_info (Optional) Activation layer information in case of a fused activation.
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* @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported
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*/
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void configure(const IGCTensor *input, const IGCTensor *weights, const IGCTensor *biases, IGCTensor *output, const PadStrideInfo &conv_info,
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const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1);
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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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/** Configures the appropriate matrix multiply routine
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*
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* @param input Input tensor. Data types supported: F16/F32.
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* @param weights Weights tensor. Data type supported: Same as @p input.
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* @param output Output tensor. Data types supported: Same as @p input,
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*/
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void configure_mm(const IGCTensor *input, const IGCTensor *weights, IGCTensor *output);
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/** Static function to check if given info will lead to a valid configuration of @ref GCGEMMConvolutionLayer matrix multiply routines
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*
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* @param[in] input Input tensor. Data types supported: QASYMM8/F16/F32.
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* @param[in] weights Weights tensor. Data type supported: Same as @p input.
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* @param[in] output Output tensor. Data types supported: Same as @p input,
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* except for input of QASYMM8 type where output should be of S32 type.
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*
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* @return a status
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*/
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static Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output);
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private:
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MemoryGroup _memory_group;
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GCConvolutionLayerReshapeWeights _reshape_weights;
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GCIm2ColKernel _input_im2col_kernel;
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GCGEMM _mm_gemm;
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GCCol2ImKernel _output_col2im_kernel;
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GCFillBorderKernel _fill_border;
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GCActivationLayer _activationlayer_function;
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const IGCTensor *_original_weights;
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GCTensor _input_im2col_reshaped;
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GCTensor _input_interleaved_reshaped;
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GCTensor _weights_reshaped;
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GCTensor _weights_transposed;
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GCTensor _gemm_output;
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GCTensor _tmp_output;
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bool _is_activationlayer_enabled;
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bool _is_prepared;
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};
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}
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#endif /* ARM_COMPUTE_GCCONVOLUTIONLAYER_H */
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