/* * Copyright (c) 2019-2021 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_CLFFTCONVOLUTIONLAYER_H #define ARM_COMPUTE_CLFFTCONVOLUTIONLAYER_H #include "arm_compute/runtime/IFunction.h" #include "arm_compute/core/Types.h" #include "arm_compute/runtime/CL/functions/CLActivationLayer.h" #include "arm_compute/runtime/CL/functions/CLElementwiseOperations.h" #include "arm_compute/runtime/CL/functions/CLFFT2D.h" #include "arm_compute/runtime/CL/functions/CLPadLayer.h" #include "arm_compute/runtime/CL/functions/CLPermute.h" #include "arm_compute/runtime/CL/functions/CLPixelWiseMultiplication.h" #include "arm_compute/runtime/CL/functions/CLReductionOperation.h" #include "arm_compute/runtime/CL/functions/CLReshapeLayer.h" #include "arm_compute/runtime/CL/functions/CLReverse.h" #include "arm_compute/runtime/CL/functions/CLSlice.h" namespace arm_compute { // Forward declarations class ICLTensor; /** Basic function to execute FFT-based convolution on OpenCL. This function calls the following OpenCL functions/kernels: * * -# @ref CLPermute Permute input if NHWC(only NCHW is supported). * -# @ref CLPadLayer Pad input. * -# @ref CLFFT2D Forward transform to the frequency domain. * -# @ref CLComplexPixelWiseMultiplication Complex element-wise product of input and the weights. * -# @ref CLReductionOperation Reduction across channels. * -# @ref CLFFT2D Inverse transform back to the time domain. * -# @ref CLStridedSlice Extract valid output. * -# @ref CLArithmeticAddition Add bias. * -# @ref CLActivationLayer Perform activation. * -# @ref CLPermute Permute output if NHWC(only NCHW is supported). */ class CLFFTConvolutionLayer : public IFunction { public: /** Default constructor */ CLFFTConvolutionLayer(std::shared_ptr memory_manager = nullptr); /** Prevent instances of this class from being copied (As this class contains pointers) */ CLFFTConvolutionLayer(const CLFFTConvolutionLayer &) = delete; /** Default move constructor */ CLFFTConvolutionLayer(CLFFTConvolutionLayer &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ CLFFTConvolutionLayer &operator=(const CLFFTConvolutionLayer &) = delete; /** Default move assignment operator */ CLFFTConvolutionLayer &operator=(CLFFTConvolutionLayer &&) = default; /** Set the input and output tensors. * * Valid data layouts: * - All * * Valid data type configurations: * |src |dst | * |:------|:------| * |F32 |F32 | * |F16 |F16 | * * @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: F16/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. * @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(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false); /** 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] compile_context The compile context to be used. * @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: F16/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. * @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 CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false); /** Static function to check if given info will lead to a valid configuration of @ref CLFFTConvolutionLayer * * @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: F16/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. * @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); // Inherited methods overridden: void run() override; void prepare() override; private: MemoryGroup _memory_group; CLReverse _flip_weights_func; CLPermute _permute_input_func; CLPermute _permute_output_func; CLPermute _permute_weights_func; CLPermute _permute_bias_func; CLPadLayer _pad_input_func; CLPadLayer _pad_weights_func; CLFFT2D _transform_input_func; std::unique_ptr _transform_weights_func; CLFFT2D _itransform_output_func; CLComplexPixelWiseMultiplication _prod_func; CLReductionOperation _reduce_func; CLSlice _extract_output_func; CLArithmeticAddition _bias_add_func; CLActivationLayer _activation_layer_func; CLTensor _permuted_input; CLTensor _permuted_weights; CLTensor _permuted_bias; CLTensor _permuted_output; CLTensor _padded_input; CLTensor _padded_weights; CLTensor _flip_axis; CLTensor _flipped_weights; CLTensor _transformed_input; CLTensor _transformed_weights; CLTensor _input_weights_product; CLTensor _output_product; CLTensor _output_reduced; CLTensor _itransformed_output; CLTensor _reshaped_output; CLTensor _bias_output; const ICLTensor *_original_weights; const ICLTensor *_original_bias; bool _is_activationlayer_enabled; bool _needs_permute; bool _has_bias; bool _is_prepared; }; } // namespace arm_compute #endif /* ARM_COMPUTE_CLFFTCONVOLUTIONLAYER_H */