1 /* 2 * Copyright (c) 2018-2020 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_NECONVOLUTIONLAYER_H 25 #define ARM_COMPUTE_NECONVOLUTIONLAYER_H 26 27 #include "arm_compute/runtime/IFunction.h" 28 29 #include "arm_compute/core/ITensorInfo.h" 30 #include "arm_compute/core/Types.h" 31 #include "arm_compute/runtime/MemoryGroup.h" 32 33 #include <memory> 34 35 namespace arm_compute 36 { 37 // Forward declarations 38 class ITensor; 39 40 /** Basic function to simulate a convolution layer. This function calls one of the following NEON functions: 41 * -# @ref NEGEMMConvolutionLayer (executed only in case GEMM is required for the operation) 42 * -# @ref NEWinogradConvolutionLayer (executed only in case Winograd is required for the operation) 43 * -# @ref NEDirectConvolutionLayer (executed only in case Direct Convolution is required for the operation) 44 * -# @ref NEFFTConvolutionLayer (executed only in case FFT is required for the operation) 45 * 46 * 47 * The function selects one of the algorithms mentioned above based on: 48 * - The size of the kernel 49 * - Number of input/output feature maps 50 * - Amount of memory needed 51 * 52 * Generally GEMM-based convolution is executed when neither Winograd nor FFT nor Direct convolution can be performed. 53 * 54 * FP32 Algorithm| Filter Size | Input/Output feature maps | 55 * --------------|----------------------------------------------------|-------------------------------------------| 56 * Winograd | 3x3 1x3 3x1 5x1 1x5 5x5(fast maths) 7x1 1x7 | Input channels is greater than 3 | 57 * FFT | Squared kernels and greater than 9x9 | Input feature maps > Output feature maps | 58 * DirectConv | 9x9 | | 59 * GEMM | Any size | | 60 * 61 * Winograd 5x5 requires fast maths enabled. 62 * 63 * FP16 Algorithm| Filter Size | 64 * --------------|------------------| 65 * Winograd | Not supported | 66 * FFT | Not supported | 67 * DirectConv | 9x9 | 68 * GEMM | Any size | 69 * 70 * 71 */ 72 class NEConvolutionLayer : public IFunction 73 { 74 public: 75 /** Constructor */ 76 NEConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); 77 /** Prevent instances of this class from being copied (As this class contains pointers) */ 78 NEConvolutionLayer(const NEConvolutionLayer &) = delete; 79 /** Prevent instances of this class from being copied (As this class contains pointers) */ 80 NEConvolutionLayer &operator=(const NEConvolutionLayer &) = delete; 81 /** Prevent instances of this class from being moved (As this class contains non movable objects) */ 82 NEConvolutionLayer(NEConvolutionLayer &&) = delete; 83 /** Prevent instances of this class from being moved (As this class contains non movable objects) */ 84 NEConvolutionLayer &operator=(NEConvolutionLayer &&) = delete; 85 /** Default destructor */ 86 ~NEConvolutionLayer() = default; 87 /** Set the input and output tensors. 88 * 89 * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], 90 * while every optional dimension from 4 and above represent a batch of inputs. 91 * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. 92 * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input. 93 * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. 94 * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED type where biases should be of S32 type. 95 * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. 96 * Data types supported: Same as @p input. 97 * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. 98 * @param[in] weights_info Specifies if the weights tensor has been reshaped with NEWeightsReshapeKernel. If this is not part of the fully connected layer the weights 99 * tensor has also been transposed with NEGEMMTranspose1xWKernel. Data type supported: Same as @p input. 100 * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). 101 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported. 102 * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation 103 * available which may introduce a drop of accuracy as well. Default is false 104 * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported 105 */ 106 void configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(), 107 const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false, unsigned int num_groups = 1); 108 /** Static function to check if given info will lead to a valid configuration of @ref NEConvolutionLayer 109 * 110 * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], 111 * while every optional dimension from 4 and above represent a batch of inputs. 112 * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. 113 * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input. 114 * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. 115 * Data type supported: Should match @p input data type, except for input of QASYMM8/QASYMM8_SIGNED type where biases should be of S32 type. 116 * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. 117 * Data types supported: Same as @p input. 118 * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. 119 * @param[in] weights_info Specifies if the weights tensor has been reshaped with NEWeightsReshapeKernel. If this is not part of the fully connected layer the weights 120 * tensor has also been transposed with NEGEMMTranspose1xWKernel. Data type supported: Same as @p input. 121 * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). 122 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. 123 * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation 124 * available which may introduce a drop of accuracy as well. Default is false 125 * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is not supported 126 * 127 * @return a status 128 */ 129 static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, 130 const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false, 131 unsigned int num_groups = 1); 132 /** Static function to check if given info will return the convolution called by @ref NEConvolutionLayer 133 * 134 * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], 135 * while every optional dimension from 4 and above represent a batch of inputs. 136 * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. 137 * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input. 138 * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. 139 * Data types supported: Same as @p input. 140 * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. 141 * @param[in] weights_info Specifies if the weights tensor has been reshaped with NEWeightsReshapeKernel. If this is not part of the fully connected layer the weights 142 * tensor has also been transposed with NEGEMMTranspose1xWKernel. Data type supported: Same as @p input. 143 * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). 144 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. 145 * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation 146 * available which may introduce a drop of accuracy as well. Default is false 147 * 148 * @return the Convolution Method Hint 149 */ 150 static ConvolutionMethod get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output, const PadStrideInfo &conv_info, 151 const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false); 152 // Inherited methods overridden: 153 void run() override; 154 void prepare() override; 155 156 private: 157 std::shared_ptr<IMemoryManager> _memory_manager; 158 std::unique_ptr<IFunction> _function; /**< Function to run */ 159 }; 160 } // namespace arm_compute 161 #endif /* ARM_COMPUTE_NECONVOLUTIONLAYER_H */