/* * Copyright (c) 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_NEFFTCONVOLUTIONLAYER_H__ #define __ARM_COMPUTE_NEFFTCONVOLUTIONLAYER_H__ #include "arm_compute/runtime/IFunction.h" #include "arm_compute/core/Types.h" #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" #include "arm_compute/runtime/NEON/functions/NEArithmeticAddition.h" #include "arm_compute/runtime/NEON/functions/NEFFT2D.h" #include "arm_compute/runtime/NEON/functions/NEPadLayer.h" #include "arm_compute/runtime/NEON/functions/NEPermute.h" #include "arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h" #include "arm_compute/runtime/NEON/functions/NEReductionOperation.h" #include "arm_compute/runtime/NEON/functions/NEReshapeLayer.h" #include "arm_compute/runtime/NEON/functions/NEReverse.h" #include "arm_compute/runtime/NEON/functions/NESlice.h" namespace arm_compute { // Forward declarations class ITensor; /** Basic function to execute FFT-based convolution on NEON. This function calls the following NEON functions/kernels: * * -# @ref NEPermute Permute input if NHWC(only NCHW is supported). * -# @ref NEPadLayer Pad input. * -# @ref NEFFT2D Forward transform to the frequency domain. * -# @ref NEComplexPixelWiseMultiplication Complex element-wise product of input and the weights. * -# @ref NEReductionOperation Reduction across channels. * -# @ref NEFFT2D Inverse transform back to the time domain. * -# @ref NEStridedSlice Extract valid output. * -# @ref NEArithmeticAddition Add bias. * -# @ref NEActivationLayer Perform activation. * -# @ref NEPermute Permute output if NHWC(only NCHW is supported). */ class NEFFTConvolutionLayer : public IFunction { public: /** Default constructor */ NEFFTConvolutionLayer(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ NEFFTConvolutionLayer(const NEFFTConvolutionLayer &) = delete; /** Default move constructor */ NEFFTConvolutionLayer(NEFFTConvolutionLayer &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ NEFFTConvolutionLayer &operator=(const NEFFTConvolutionLayer &) = delete; /** Default move assignment operator */ NEFFTConvolutionLayer &operator=(NEFFTConvolutionLayer &&) = default; /** Set the input and output tensors. * * @note: This function only works with any square kernel size and unit strides for both NCHW and NHWC data layout * * @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. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input * @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] act_info (Optional) Activation layer information in case of a fused activation. */ void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo()); /** Static function to check if given info will lead to a valid configuration of @ref NEFFTConvolutionLayer * * @note: This function only works with any square kernel size and unit strides for both NCHW and NHWC data layout * * @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. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM].Data type supported: Same as @p input * @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. * @param[in] act_info (Optional) Activation layer information in case of a fused activation. * * @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()); // Inherited methods overridden: void run() override; void prepare() override; private: MemoryGroup _memory_group; NEReverse _flip_weights_func; NEPermute _permute_input_func; NEPermute _permute_output_func; NEPermute _permute_weights_func; NEPermute _permute_bias_func; NEPadLayer _pad_input_func; NEPadLayer _pad_weights_func; NEFFT2D _transform_input_func; std::unique_ptr _transform_weights_func; NEFFT2D _itransform_output_func; NEComplexPixelWiseMultiplication _prod_func; NEReductionOperation _reduce_func; NESlice _extract_output_func; NEArithmeticAddition _bias_add_func; NEActivationLayer _activation_layer_func; Tensor _permuted_input; Tensor _permuted_weights; Tensor _permuted_bias; Tensor _permuted_output; Tensor _padded_input; Tensor _padded_weights; Tensor _flip_axis; Tensor _flipped_weights; Tensor _transformed_input; Tensor _transformed_weights; Tensor _input_weights_product; Tensor _output_product; Tensor _output_reduced; Tensor _itransformed_output; Tensor _reshaped_output; Tensor _bias_output; const ITensor *_original_weights; const ITensor *_original_bias; bool _is_activationlayer_enabled; bool _needs_permute; bool _has_bias; bool _is_prepared; }; } // namespace arm_compute #endif /* __ARM_COMPUTE_NEFFTCONVOLUTIONLAYER_H__ */