1 /* 2 * Copyright (c) 2017-2021, 2023 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_NEDECONVOLUTIONLAYER_H 25 #define ARM_COMPUTE_NEDECONVOLUTIONLAYER_H 26 27 #include "arm_compute/runtime/CPP/functions/CPPUpsample.h" 28 #include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h" 29 #include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h" 30 #include "arm_compute/runtime/NEON/functions/NEReverse.h" 31 32 #include "arm_compute/core/Types.h" 33 #include "arm_compute/runtime/IFunction.h" 34 #include "arm_compute/runtime/IMemoryManager.h" 35 #include "arm_compute/runtime/MemoryGroup.h" 36 #include "arm_compute/runtime/Tensor.h" 37 38 #include <memory> 39 40 namespace arm_compute 41 { 42 /** Function to run the deconvolution layer. 43 * 44 * Deconvolution Layer is the backward pass of Convolution Layer. First we transform the input depending on the stride and pad info and then perfrom a 1x1 45 * convolution pass. Input stride defines how many zeroes we should put between each element of the input, pad is the amount of padding and finaly a is a user 46 * specified value where a < stride - 1 that increases the padding top and right of the input image. 47 * 48 * The relation between input to output is as follows: 49 * \f[ 50 * width\_output = (width\_input - 1) \cdot stride\_x - 2 \cdot padding\_x + kernel\_x 51 * \f] 52 * \f[ 53 * height\_output = (height\_input - 1) \cdot stride\_y - 2 \cdot padding\_y + kernel\_y 54 * \f] 55 * 56 * where 57 * width is the size of the first input dimension. 58 * height is the size of the second input dimension. 59 * width_output is the size of the first output dimension. 60 * height_output is the size of the second output dimension. 61 * kernel_x and kernel_y are the convolution sizes in x and y. 62 * stride_x and stride_y is the input stride of the first and second dimension. 63 * 64 * The weights used by Deconvolution are supposed to be the same as the ones used for Convolution. Therefore, it will be necessary to use the weights in the 65 * reverse order to perform an actual convolution. This is achieved by using @ref NEReverse. 66 * 67 * This function calls the following kernels/functions: 68 * 69 * -# @ref CPPUpsample 70 * -# @ref NEConvolutionLayer 71 * -# @ref NEReverse 72 * 73 */ 74 class NEDeconvolutionLayer : public IFunction 75 { 76 public: 77 /** Constructor */ 78 NEDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); 79 /** Prevent instances of this class from being copied (As this class contains pointers) */ 80 NEDeconvolutionLayer(const NEDeconvolutionLayer &) = delete; 81 /** Default move constructor */ 82 NEDeconvolutionLayer(NEDeconvolutionLayer &&) = default; 83 /** Prevent instances of this class from being copied (As this class contains pointers) */ 84 NEDeconvolutionLayer &operator=(const NEDeconvolutionLayer &) = delete; 85 /** Default move assignment operator */ 86 NEDeconvolutionLayer &operator=(NEDeconvolutionLayer &&) = default; 87 /** Default destructor */ 88 ~NEDeconvolutionLayer() = default; 89 90 /** Set the input, weights, biases and output tensors. 91 * 92 * Valid data layouts: 93 * - NHWC 94 * - NCHW 95 * 96 * Valid data type configurations: 97 * |src0 |src1 |src2 |dst | 98 * |:--------------|:------------------|:------|:--------------| 99 * |F16 |F16 |F16 |F16 | 100 * |F32 |F32 |F32 |F32 | 101 * |QASYMM8 |QASYMM8 |S32 |QASYMM8 | 102 * |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 | 103 * |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED | 104 * |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED | 105 * 106 * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. 107 * Data types supported: F32/F16/QASYMM8/QASYMM8_SIGNED. 108 * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. 109 * Data type supported: Same as @p input, also could be QSYMM8_PER_CHANNEL if input is QASYMM8/QASYMM8_SIGNED. 110 * @param[in] bias Optional, ignored if NULL. The biases have one dimension. 111 * Data type supported: Data types supported: S32 for QASYMM8/QASYMM8_SIGNED input, F32 for F32 input, F16 for F16 input. 112 * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. 113 * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. 114 * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation 115 * available which may introduce a drop of accuracy as well. Default is false 116 * 117 */ 118 void configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info, bool enable_fast_math = false); 119 /** Static function to check if given info will lead to a valid configuration of @ref NEDeconvolutionLayer 120 * 121 * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. 122 * Data types supported: F32/F16/QASYMM8/QASYMM8_SIGNED. 123 * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. 124 * Data type supported: Same as @p input, also could be QSYMM8_PER_CHANNEL if input is QASYMM8/QASYMM8_SIGNED. 125 * @param[in] bias (Optional) The biases have one dimension. Data type supported: Data types supported: S32 for QASYMM8/QASYMM8_SIGNED input, F32 for F32 input, F16 for F16 input. 126 * @param[in] output Output tensor info. The output has the same number of dimensions as the @p input. 127 * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. 128 * @param[in] enable_fast_math (Optional) Enable fast math computation. In case this flag were set, the function could dispatch the fastest implementation 129 * available which may introduce a drop of accuracy as well. Default is false 130 * 131 * @return a status 132 */ 133 static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &info, bool enable_fast_math = false); 134 135 // Inherited methods overridden: 136 void run() override; 137 void prepare() override; 138 139 private: 140 MemoryGroup _memory_group; 141 NEConvolutionLayer _conv_f; 142 CPPUpsample _upsample_f; 143 NEReverse _flip_weights; 144 Tensor _scaled_output; 145 Tensor _weights_flipped; 146 Tensor _flip_axis; 147 const ITensor *_original_weights; 148 ITensor *_input; 149 PadStrideInfo _info; 150 bool _is_prepared; 151 bool _do_upsampling; 152 }; 153 } // arm_compute 154 #endif /* ARM_COMPUTE_NEDECONVOLUTIONLAYER_H */ 155