/* * Copyright (c) 2021-2023 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 ACL_SRC_CPU_OPERATORS_CPUWINOGRADCONV2D_H #define ACL_SRC_CPU_OPERATORS_CPUWINOGRADCONV2D_H #include "arm_compute/core/TensorInfo.h" #include "arm_compute/runtime/FunctionDescriptors.h" #include "src/core/common/Macros.h" #include "src/cpu/ICpuOperator.h" #include "src/cpu/kernels/assembly/gemm_common.hpp" #include "src/cpu/kernels/CpuWinogradConv2dKernel.h" #include "src/cpu/operators/CpuActivation.h" #include "src/cpu/operators/CpuGemm.h" #include "src/cpu/operators/CpuPermute.h" #include "src/cpu/operators/internal/CpuGemmAssemblyDispatch.h" namespace arm_compute { namespace cpu { class CpuWinogradConv2d : public ICpuOperator { public: /** Constructor */ CpuWinogradConv2d(); ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuWinogradConv2d); /** Destructor */ ~CpuWinogradConv2d(); /** Set the input and output tensors. * * Valid data layouts: * - NHWC * - NCHW * * Valid data type configurations: * |src0 |src1 |src2 |dst | * |:--------------|:--------------|:------|:--------------| * |F16 |F16 |F16 |F16 | * |F32 |F32 |F32 |F32 | * * @param[in] src Source tensor Info. 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 Info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input. * For supported kernel sizes, see @ref arm_compute::NEWinogradConvolutionLayer * @param[in] biases Biases tensor Info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. * @param[out] dst Destination tensor Info. 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 ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, 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 CpuWinogradConv2d * * Similar to CpuWinogradConv2d::configure() * * @return a status */ static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false); // Inherited methods overridden: void run(ITensorPack &tensors) override; void prepare(ITensorPack &constants) override; experimental::MemoryRequirements workspace() const override; private: enum AuxTensorIdx { /** Slot 0 - 6 reserved for CpuGemm */ TransformedInput = 7, TransformedOutput, WorkspaceIO, TransformedWeights, PermutedWeights, Count, PermutedInput = TransformedOutput, PermutedOutput = TransformedInput }; std::unique_ptr _gemm_function; std::unique_ptr _activation_func; std::unique_ptr _transform_input_kernel; std::unique_ptr _transform_output_kernel; std::unique_ptr _permute_input; std::unique_ptr _permute_output; std::unique_ptr _permute_weights; experimental::MemoryRequirements _aux_mem{Count}; std::unique_ptr _conv_args; // Make it unique ptr because this type does not have a default constructor arm_conv::winograd::WinogradImpl _winograd_impl; DataLayout _data_layout; TensorInfo _winograd_transformed_input; TensorInfo _winograd_transformed_output; TensorInfo _winograd_transformed_weights; TensorInfo _input_workspace; TensorInfo _output_workspace; TensorInfo _weights_hwio; TensorInfo _input_nhwc; TensorInfo _output_nhwc; bool _is_prepared; bool _run_activation; }; } // namespace cpu } // namespace arm_compute #endif // ACL_SRC_CPU_OPERATORS_CPUWINOGRADCONV2D_H