1 /* 2 * Copyright (c) 2017-2021 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_CLGEMMCONVOLUTIONLAYER_H 25 #define ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H 26 27 #include "arm_compute/core/experimental/IPostOp.h" 28 #include "arm_compute/runtime/CL/CLTensor.h" 29 #include "arm_compute/runtime/CL/CLTypes.h" 30 #include "arm_compute/runtime/IFunction.h" 31 #include "arm_compute/runtime/IMemoryManager.h" 32 #include "arm_compute/runtime/IWeightsManager.h" 33 34 #include <memory> 35 36 namespace arm_compute 37 { 38 // Forward declarations 39 class CLCompileContext; 40 class ICLTensor; 41 class ITensorInfo; 42 43 /** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions: 44 * 45 * -# @ref opencl::ClGemmConv2d 46 */ 47 class CLGEMMConvolutionLayer : public IFunction 48 { 49 public: 50 /** Constructor 51 * 52 * @param[in] memory_manager (Optional) Memory manager. 53 * @param[in] weights_manager (Optional) Weights manager. 54 */ 55 CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr); 56 /** Prevent instances of this class from being copied (As this class contains pointers) */ 57 CLGEMMConvolutionLayer(const CLGEMMConvolutionLayer &) = delete; 58 /** Default move constructor */ 59 CLGEMMConvolutionLayer(CLGEMMConvolutionLayer &&) = default; 60 /** Prevent instances of this class from being copied (As this class contains pointers) */ 61 CLGEMMConvolutionLayer &operator=(const CLGEMMConvolutionLayer &) = delete; 62 /** Default move assignment operator */ 63 CLGEMMConvolutionLayer &operator=(CLGEMMConvolutionLayer &&) = default; 64 /**Default destructor */ 65 ~CLGEMMConvolutionLayer(); 66 /** Set the input and output tensors. 67 * 68 * Valid data layouts: 69 * - NHWC 70 * - NCHW 71 * 72 * Valid data type configurations: 73 * |src0 |src1 |src2 |dst | 74 * |:--------------|:------------------|:--------|:--------------| 75 * |F16 |F16 |F16 |F16 | 76 * |F32 |F32 |F32 |F32 | 77 * |QASYMM8 |QASYMM8 |S32 |QASYMM8 | 78 * |QASYMM8 |QSYMM8_PER_CHANNEL |S32 |QASYMM8 | 79 * |QASYMM8_SIGNED |QASYMM8_SIGNED |S32 |QASYMM8_SIGNED | 80 * |QASYMM8_SIGNED |QSYMM8_PER_CHANNEL |S32 |QASYMM8_SIGNED | 81 * 82 * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], 83 * while every optional dimension from 4 and above represent a batch of inputs. 84 * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. 85 * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. 86 * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED. 87 * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. 88 * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type. 89 * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. 90 * Data types supported: Same as @p input. 91 * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. 92 * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights 93 * tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input. 94 * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). 95 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. 96 * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout 97 * @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation. 98 */ 99 void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo(), 100 const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1, 101 const experimental::PostOpList<ICLTensor *> &post_ops = experimental::PostOpList<ICLTensor *> {}); 102 /** Set the input and output tensors. 103 * 104 * @param[in] compile_context The compile context to be used. 105 * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], 106 * while every optional dimension from 4 and above represent a batch of inputs. 107 * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. 108 * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. 109 * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED. 110 * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. 111 * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type. 112 * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. 113 * Data types supported: Same as @p input. 114 * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. 115 * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights 116 * tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input. 117 * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). 118 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. 119 * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout 120 * @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation. 121 */ 122 void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, 123 const WeightsInfo &weights_info = WeightsInfo(), 124 const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1, 125 const experimental::PostOpList<ICLTensor *> &post_ops = experimental::PostOpList<ICLTensor *> {}); 126 /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMConvolutionLayer. 127 * 128 * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], 129 * while every optional dimension from 4 and above represent a batch of inputs. 130 * Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32. 131 * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. 132 * Data type supported: Same as @p input or QASYMM8/QSYMM8_PER_CHANNEL when @p input is QASYMM8 or QASYMM8_SIGNED/QSYMM8_PER_CHANNEL when @p input is QASYMM8_SIGNED. 133 * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. 134 * Data type supported: Should match @p input data type, except for input of quantized type where biases should be of S32 type. 135 * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. 136 * Data types supported: Same as @p input. 137 * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. 138 * @param[in] weights_info Specifies if the weights tensor has been reshaped with CLWeightsReshapeKernel. If this is not part of the fully connected layer the weights 139 * tensor has also been transposed with CLGEMMReshapeRHSMatrixKernel. Data type supported: Same as @p input. 140 * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1). 141 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. 142 * @param[in] num_groups (Optional) Number of groups when performing a grouped convolution. num_groups != 1 is only supported for NCHW data layout 143 * @param[in] post_ops (Optional) A sequence of post operations that are performed after the main operation. 144 * 145 * @return a status 146 */ 147 static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, 148 const WeightsInfo &weights_info = WeightsInfo(), const Size2D &dilation = Size2D(1U, 1U), const ActivationLayerInfo &act_info = ActivationLayerInfo(), unsigned int num_groups = 1, 149 const experimental::PostOpList<ITensorInfo *> &post_ops = experimental::PostOpList<ITensorInfo *> {}); 150 151 // Inherited methods overridden: 152 void run() override; 153 void prepare() override; 154 155 private: 156 struct Impl; 157 std::unique_ptr<Impl> _impl; 158 }; 159 } // namespace arm_compute 160 #endif /* ARM_COMPUTE_CLGEMMCONVOLUTIONLAYER_H */ 161