1 /* 2 * Copyright (c) 2021-2022 Arm Limited. 3 * 4 * SPDX-License-Identifier: MIT 5 * 6 * Permission is hereby granted, free of charge, to any person obtaining a copy 7 * of this software and associated documentation files (the "Software"), to 8 * deal in the Software without restriction, including without limitation the 9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or 10 * sell copies of the Software, and to permit persons to whom the Software is 11 * furnished to do so, subject to the following conditions: 12 * 13 * The above copyright notice and this permission notice shall be included in all 14 * copies or substantial portions of the Software. 15 * 16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 * SOFTWARE. 23 */ 24 #ifndef ARM_COMPUTE_CPU_WINOGRAD_CONV2D_KERNEL_H 25 #define ARM_COMPUTE_CPU_WINOGRAD_CONV2D_KERNEL_H 26 27 #include "arm_compute/core/TensorInfo.h" 28 #include "arm_compute/runtime/FunctionDescriptors.h" 29 #include "src/core/common/Macros.h" 30 #include "src/cpu/ICpuOperator.h" 31 #include "src/cpu/kernels/CpuWinogradConv2dKernel.h" 32 #include "src/cpu/kernels/assembly/gemm_common.hpp" 33 #include "src/cpu/operators/CpuActivation.h" 34 #include "src/cpu/operators/CpuGemm.h" 35 #include "src/cpu/operators/CpuPermute.h" 36 #include "src/cpu/operators/internal/CpuGemmAssemblyDispatch.h" 37 38 namespace arm_compute 39 { 40 namespace cpu 41 { 42 class CpuWinogradConv2d : public ICpuOperator 43 { 44 public: 45 /** Constructor */ 46 CpuWinogradConv2d(); 47 ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuWinogradConv2d); 48 /** Destructor */ 49 ~CpuWinogradConv2d(); 50 51 /** Set the input and output tensors. 52 * 53 * Valid data layouts: 54 * - NHWC 55 * - NCHW 56 * 57 * Valid data type configurations: 58 * |src0 |src1 |src2 |dst | 59 * |:--------------|:--------------|:------|:--------------| 60 * |F16 |F16 |F16 |F16 | 61 * |F32 |F32 |F32 |F32 | 62 * 63 * @param[in] src Source tensor Info. 3 lower dimensions represent a single input [width, height, IFM], 64 * while every optional dimension from 4 and above represent a batch of inputs. 65 * Data types supported: F16/F32. 66 * @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. 67 * Currently only 3x3 and 5x5 kernels are supported. 68 * @param[in] biases Biases tensor Info. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. 69 * @param[out] dst Destination tensor Info. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. 70 * Data types supported: Same as @p input. 71 * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. Currently only unit strides are supported. 72 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. 73 * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation 74 * available which may introduce a drop of accuracy as well. Default is false 75 */ 76 void configure(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, ITensorInfo *dst, const PadStrideInfo &conv_info, 77 const ActivationLayerInfo &act_info = ActivationLayerInfo(), 78 bool enable_fast_math = false); 79 /** Static function to check if given info will lead to a valid configuration of @ref CpuWinogradConv2d 80 * 81 * Similar to CpuWinogradConv2d::configure() 82 * 83 * @return a status 84 */ 85 static Status validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const PadStrideInfo &conv_info, 86 const ActivationLayerInfo &act_info = ActivationLayerInfo(), 87 bool enable_fast_math = false); 88 89 // Inherited methods overridden: 90 void run(ITensorPack &tensors) override; 91 void prepare(ITensorPack &constants) override; 92 experimental::MemoryRequirements workspace() const override; 93 94 private: 95 enum AuxTensorIdx 96 { 97 GemmWorkspace = 0, 98 Pretranspose = 1, 99 InterleavedLHS = 2, 100 TransposedRHS = 3, 101 TempResult = 4, 102 TransformedInput = 5, 103 TransformedOutput = 6, 104 WorkspaceIO = 7, 105 TransformedWeights = 8, 106 PermutedWeights = 9, 107 PermutedInput = TransformedOutput, 108 PermutedOutput = TransformedInput, 109 Count = 10 110 }; 111 std::unique_ptr<CpuGemm> _gemm_function; 112 std::unique_ptr<CpuActivation> _activation_func; 113 std::unique_ptr<ICPPKernel> _transform_input_kernel; 114 std::unique_ptr<ICPPKernel> _transform_output_kernel; 115 std::unique_ptr<CpuPermute> _permute_input; 116 std::unique_ptr<CpuPermute> _permute_output; 117 std::unique_ptr<CpuPermute> _permute_weights; 118 experimental::MemoryRequirements _aux_mem{ Count }; 119 std::unique_ptr<arm_conv::ConvolutionArgs> _conv_args; // Make it unique ptr because this type does not have a default constructor 120 arm_conv::winograd::WinogradImpl _winograd_impl; 121 DataLayout _data_layout; 122 TensorInfo _winograd_transformed_input; 123 TensorInfo _winograd_transformed_output; 124 TensorInfo _winograd_transformed_weights; 125 TensorInfo _input_workspace; 126 TensorInfo _output_workspace; 127 TensorInfo _weights_hwio; 128 TensorInfo _input_nhwc; 129 TensorInfo _output_nhwc; 130 bool _is_prepared; 131 bool _run_activation; 132 }; 133 } // namespace cpu 134 } // namespace arm_compute 135 136 #endif /* ARM_COMPUTE_CPU_WINOGRAD_CONV2D_KERNEL_H */ 137