/* * Copyright (c) 2017-2019 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_NEWINOGRADCONVOLUTIONLAYER_H__ #define __ARM_COMPUTE_NEWINOGRADCONVOLUTIONLAYER_H__ #include "arm_compute/runtime/IFunction.h" #include "arm_compute/core/NEON/INEKernel.h" #include "arm_compute/core/Types.h" #include "arm_compute/runtime/CPP/functions/CPPPermute.h" #include "arm_compute/runtime/MemoryGroup.h" #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" #include "arm_compute/runtime/NEON/functions/NEGEMM.h" #include "arm_compute/runtime/Tensor.h" #include namespace arm_compute { class ITensor; /** Basic function to simulate a convolution layer. This function calls the following NEON kernels: * -# @ref NEWinogradLayerTransformWeightsKernel (executed only once in the first call to the run() method ) * -# @ref NEWinogradLayerTransformInputKernel * -# @ref NEWinogradLayerTransformOutputKernel * -# @ref NEGEMMAssemblyDispatch * -# @ref CPPPermute (three times: weights, input and output) * * @note Some Winograd configurations (i.e. F(2x2, 5x5), F(4x4, 5x5)) are supported only with enable_fast_math = true */ class NEWinogradConvolutionLayer : public IFunction { public: /** Constructor */ NEWinogradConvolutionLayer(const std::shared_ptr &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: 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. * Currently only 3x3 and 5x5 kernels are supported. * @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. 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. Currently only unit strides are supported. * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation * available which may introduce a drop of accuracy as well. Default is false */ void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false); // Inherited methods overridden: void run() override; void prepare() override; /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMConvolutionLayer * * @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: 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. * Currently only 3x3 and 5x5 kernels are supported. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. * @param[in] 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. Currently only unit strides are supported. * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation * available which may introduce a drop of accuracy as well. Default is false * * @return a status */ static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false); /** Prevent instances of this class from being copied (As this class contains pointers) */ NEWinogradConvolutionLayer(const NEWinogradConvolutionLayer &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ NEWinogradConvolutionLayer &operator=(const NEWinogradConvolutionLayer &) = delete; private: MemoryGroup _memory_group; NEGEMM _gemm_function; std::unique_ptr _transform_input_kernel; std::unique_ptr _transform_output_kernel; std::unique_ptr _transform_weights_kernel; NEActivationLayer _activationlayer_function; CPPPermute _permute_input; CPPPermute _permute_weights; CPPPermute _permute_output; Tensor _input_transformed; Tensor _output_transformed; Tensor _input_workspace; Tensor _output_workspace; Tensor _kernel_storage; Tensor _input_nhwc; Tensor _output_nhwc; Tensor _weights_hwio; const ITensor *_input; const ITensor *_weights; ITensor *_output; bool _is_prepared; bool _is_activationlayer_enabled; }; } #endif /* __ARM_COMPUTE_NEWINOGRADCONVOLUTIONLAYER_H__ */