Anthony Barbier | 6ff3b19 | 2017-09-04 18:44:23 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2017 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_TEST_DATASET_CONVOLUTION_LAYER_DATASET_H__ |
| 25 | #define __ARM_COMPUTE_TEST_DATASET_CONVOLUTION_LAYER_DATASET_H__ |
| 26 | |
| 27 | #include "TypePrinter.h" |
| 28 | |
| 29 | #include "arm_compute/core/TensorShape.h" |
| 30 | #include "dataset/GenericDataset.h" |
| 31 | #include "dataset/ShapeDatasets.h" |
| 32 | |
| 33 | #include <sstream> |
| 34 | #include <type_traits> |
| 35 | |
| 36 | #ifdef BOOST |
| 37 | #include "boost_wrapper.h" |
| 38 | #endif |
| 39 | |
| 40 | namespace arm_compute |
| 41 | { |
| 42 | namespace test |
| 43 | { |
| 44 | /** Convolution Layer data object */ |
| 45 | class ConvolutionLayerDataObject |
| 46 | { |
| 47 | public: |
| 48 | operator std::string() const |
| 49 | { |
| 50 | std::stringstream ss; |
| 51 | ss << "ConvolutionLayer"; |
| 52 | ss << "_I" << src_shape; |
| 53 | ss << "_K" << weights_shape; |
| 54 | ss << "_PS" << info; |
| 55 | return ss.str(); |
| 56 | } |
| 57 | |
| 58 | friend std::ostream &operator<<(std::ostream &os, const ConvolutionLayerDataObject &obj) |
| 59 | { |
| 60 | os << static_cast<std::string>(obj); |
| 61 | return os; |
| 62 | } |
| 63 | |
| 64 | public: |
| 65 | TensorShape src_shape; |
| 66 | TensorShape weights_shape; |
| 67 | TensorShape bias_shape; |
| 68 | TensorShape dst_shape; |
| 69 | PadStrideInfo info; |
| 70 | }; |
| 71 | |
| 72 | template <unsigned int Size> |
| 73 | using ConvolutionLayerDataset = GenericDataset<ConvolutionLayerDataObject, Size>; |
| 74 | |
| 75 | /** Data set containing small convolution layer shapes */ |
| 76 | class SmallConvolutionLayerDataset final : public ConvolutionLayerDataset<3> |
| 77 | { |
| 78 | public: |
| 79 | SmallConvolutionLayerDataset() |
| 80 | : GenericDataset |
| 81 | { |
| 82 | ConvolutionLayerDataObject{ TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0) }, |
| 83 | ConvolutionLayerDataObject{ TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 11U), TensorShape(11U), TensorShape(11U, 12U, 11U), PadStrideInfo(3, 2, 1, 0) }, |
| 84 | ConvolutionLayerDataObject{ TensorShape(17U, 31U, 2U, 7U), TensorShape(5U, 5U, 2U, 5U), TensorShape(5U), TensorShape(15U, 15U, 5U, 7U), PadStrideInfo(1, 2, 1, 1) } |
| 85 | } |
| 86 | { |
| 87 | } |
| 88 | |
| 89 | ~SmallConvolutionLayerDataset() = default; |
| 90 | }; |
| 91 | |
| 92 | /** Data set containing direct convolution tensor shapes. */ |
| 93 | class DirectConvolutionShapes final : public ShapeDataset<3> |
| 94 | { |
| 95 | public: |
| 96 | DirectConvolutionShapes() |
| 97 | : ShapeDataset(TensorShape(3U, 3U, 3U, 2U, 4U, 5U), |
| 98 | TensorShape(32U, 37U, 3U), |
| 99 | TensorShape(13U, 15U, 8U, 3U)) |
| 100 | { |
| 101 | } |
| 102 | }; |
| 103 | |
| 104 | /** AlexNet's convolution layers tensor shapes. */ |
| 105 | class AlexNetConvolutionLayerDataset final : public ConvolutionLayerDataset<5> |
| 106 | { |
| 107 | public: |
| 108 | AlexNetConvolutionLayerDataset() |
| 109 | : GenericDataset |
| 110 | { |
| 111 | ConvolutionLayerDataObject{ TensorShape(227U, 227U, 3U), TensorShape(11U, 11U, 3U, 96U), TensorShape(96U), TensorShape(55U, 55U, 96U), PadStrideInfo(4, 4, 0, 0) }, |
| 112 | ConvolutionLayerDataObject{ TensorShape(27U, 27U, 96U), TensorShape(5U, 5U, 96U, 256U), TensorShape(256U), TensorShape(27U, 27U, 256U), PadStrideInfo(1, 1, 2, 2) }, |
| 113 | ConvolutionLayerDataObject{ TensorShape(13U, 13U, 256U), TensorShape(3U, 3U, 256U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1) }, |
| 114 | ConvolutionLayerDataObject{ TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 384U, 384U), TensorShape(384U), TensorShape(13U, 13U, 384U), PadStrideInfo(1, 1, 1, 1) }, |
| 115 | ConvolutionLayerDataObject{ TensorShape(13U, 13U, 384U), TensorShape(3U, 3U, 384U, 256U), TensorShape(256U), TensorShape(13U, 13U, 256U), PadStrideInfo(1, 1, 1, 1) } |
| 116 | } |
| 117 | { |
| 118 | } |
| 119 | |
| 120 | ~AlexNetConvolutionLayerDataset() = default; |
| 121 | }; |
| 122 | |
| 123 | /** LeNet5's convolution layers tensor shapes. */ |
| 124 | class LeNet5ConvolutionLayerDataset final : public ConvolutionLayerDataset<2> |
| 125 | { |
| 126 | public: |
| 127 | LeNet5ConvolutionLayerDataset() |
| 128 | : GenericDataset |
| 129 | { |
| 130 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 1U), TensorShape(5U, 5U, 1U, 20U), TensorShape(20U), TensorShape(24U, 24U, 20U), PadStrideInfo(1, 1, 0, 0) }, |
| 131 | ConvolutionLayerDataObject{ TensorShape(12U, 12U, 20U), TensorShape(5U, 5U, 20U, 50U), TensorShape(50U), TensorShape(8U, 8U, 50U), PadStrideInfo(1, 1, 0, 0) }, |
| 132 | } |
| 133 | { |
| 134 | } |
| 135 | |
| 136 | ~LeNet5ConvolutionLayerDataset() = default; |
| 137 | }; |
| 138 | |
| 139 | /** GoogleLeNet v1 convolution layers tensor shapes (Part 1). |
| 140 | * |
| 141 | * @note Dataset is split into two to avoid a register allocation failure produced by clang in Android debug builds. |
| 142 | */ |
| 143 | class GoogLeNetConvolutionLayerDataset1 final : public ConvolutionLayerDataset<32> |
| 144 | { |
| 145 | public: |
| 146 | GoogLeNetConvolutionLayerDataset1() |
| 147 | : GenericDataset |
| 148 | { |
| 149 | // conv1/7x7_s2 |
| 150 | ConvolutionLayerDataObject{ TensorShape(224U, 224U, 3U), TensorShape(7U, 7U, 3U, 64U), TensorShape(64U), TensorShape(112U, 112U, 64U), PadStrideInfo(2, 2, 3, 3) }, |
| 151 | // conv2/3x3_reduce |
| 152 | ConvolutionLayerDataObject{ TensorShape(56U, 56U, 64U), TensorShape(1U, 1U, 64U, 64U), TensorShape(64U), TensorShape(56U, 56U, 64U), PadStrideInfo(1, 1, 0, 0) }, |
| 153 | // conv2/3x3 |
| 154 | ConvolutionLayerDataObject{ TensorShape(56U, 56U, 64U), TensorShape(3U, 3U, 64U, 192U), TensorShape(192U), TensorShape(56U, 56U, 192U), PadStrideInfo(1, 1, 1, 1) }, |
| 155 | // inception_3a/1x1 |
| 156 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U), PadStrideInfo(1, 1, 0, 0) }, |
| 157 | // inception_3a/3x3_reduce |
| 158 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 96U), TensorShape(96U), TensorShape(28U, 28U, 96U), PadStrideInfo(1, 1, 0, 0) }, |
| 159 | // inception_3a/3x3 |
| 160 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 96U), TensorShape(3U, 3U, 96U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 1, 1) }, |
| 161 | // inception_3a/5x5_reduce |
| 162 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 16U), TensorShape(16U), TensorShape(28U, 28U, 16U), PadStrideInfo(1, 1, 0, 0) }, |
| 163 | // inception_3a/5x5 |
| 164 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 16U), TensorShape(5U, 5U, 16U, 32U), TensorShape(32U), TensorShape(28U, 28U, 32U), PadStrideInfo(1, 1, 2, 2) }, |
| 165 | // inception_3a/pool_proj |
| 166 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 192U), TensorShape(1U, 1U, 192U, 32U), TensorShape(32U), TensorShape(28U, 28U, 32U), PadStrideInfo(1, 1, 0, 0) }, |
| 167 | // inception_3b/1x1, inception_3b/3x3_reduce |
| 168 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 128U), TensorShape(128U), TensorShape(28U, 28U, 128U), PadStrideInfo(1, 1, 0, 0) }, |
| 169 | // inception_3b/3x3 |
| 170 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 128U), TensorShape(3U, 3U, 128U, 192U), TensorShape(192U), TensorShape(28U, 28U, 192U), PadStrideInfo(1, 1, 1, 1) }, |
| 171 | // inception_3b/5x5_reduce |
| 172 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 32U), TensorShape(32U), TensorShape(28U, 28U, 32U), PadStrideInfo(1, 1, 0, 0) }, |
| 173 | // inception_3b/5x5 |
| 174 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 32U), TensorShape(5U, 5U, 32U, 96U), TensorShape(96U), TensorShape(28U, 28U, 96U), PadStrideInfo(1, 1, 2, 2) }, |
| 175 | // inception_3b/pool_proj |
| 176 | ConvolutionLayerDataObject{ TensorShape(28U, 28U, 256U), TensorShape(1U, 1U, 256U, 64U), TensorShape(64U), TensorShape(28U, 28U, 64U), PadStrideInfo(1, 1, 0, 0) }, |
| 177 | // inception_4a/1x1 |
| 178 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 192U), TensorShape(192U), TensorShape(14U, 14U, 192U), PadStrideInfo(1, 1, 0, 0) }, |
| 179 | // inception_4a/3x3_reduce |
| 180 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 96U), TensorShape(96U), TensorShape(14U, 14U, 96U), PadStrideInfo(1, 1, 0, 0) }, |
| 181 | // inception_4a/3x3 |
| 182 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 96U), TensorShape(3U, 3U, 96U, 208U), TensorShape(208U), TensorShape(14U, 14U, 208U), PadStrideInfo(1, 1, 1, 1) }, |
| 183 | // inception_4a/5x5_reduce |
| 184 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 16U), TensorShape(16U), TensorShape(14U, 14U, 16U), PadStrideInfo(1, 1, 0, 0) }, |
| 185 | // inception_4a/5x5 |
| 186 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 16U), TensorShape(5U, 5U, 16U, 48U), TensorShape(48U), TensorShape(14U, 14U, 48U), PadStrideInfo(1, 1, 2, 2) }, |
| 187 | // inception_4a/pool_proj |
| 188 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 480U), TensorShape(1U, 1U, 480U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 0, 0) }, |
| 189 | // inception_4b/1x1 |
| 190 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 160U), TensorShape(160U), TensorShape(14U, 14U, 160U), PadStrideInfo(1, 1, 0, 0) }, |
| 191 | // inception_4b/3x3_reduce, inception_4d/1x1 |
| 192 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 112U), TensorShape(112U), TensorShape(14U, 14U, 112U), PadStrideInfo(1, 1, 0, 0) }, |
| 193 | // inception_4b/3x3 |
| 194 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 112U), TensorShape(3U, 3U, 112U, 224U), TensorShape(224U), TensorShape(14U, 14U, 224U), PadStrideInfo(1, 1, 1, 1) }, |
| 195 | // inception_4b/5x5_reduce, inception_4c/5x5_reduce |
| 196 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 24U), TensorShape(24U), TensorShape(14U, 14U, 24U), PadStrideInfo(1, 1, 0, 0) }, |
| 197 | // inception_4b/5x5, inception_4c/5x5 |
| 198 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 24U), TensorShape(5U, 5U, 24U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 2, 2) }, |
| 199 | // inception_4b/pool_proj, inception_4c/pool_proj, inception_4d/pool_proj |
| 200 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 0, 0) }, |
| 201 | // inception_4c/1x1, inception_4c/3x3_reduce |
| 202 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 128U), TensorShape(128U), TensorShape(14U, 14U, 128U), PadStrideInfo(1, 1, 0, 0) }, |
| 203 | // inception_4c/3x3 |
| 204 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 128U), TensorShape(3U, 3U, 128U, 256U), TensorShape(256U), TensorShape(14U, 14U, 256U), PadStrideInfo(1, 1, 1, 1) }, |
| 205 | // inception_4d/3x3_reduce |
| 206 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 144U), TensorShape(144U), TensorShape(14U, 14U, 144U), PadStrideInfo(1, 1, 0, 0) }, |
| 207 | // inception_4d/3x3 |
| 208 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 144U), TensorShape(3U, 3U, 144U, 288U), TensorShape(288U), TensorShape(14U, 14U, 288U), PadStrideInfo(1, 1, 1, 1) }, |
| 209 | // inception_4d/5x5_reduce |
| 210 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 512U), TensorShape(1U, 1U, 512U, 32U), TensorShape(32U), TensorShape(14U, 14U, 32U), PadStrideInfo(1, 1, 0, 0) }, |
| 211 | // inception_4d/5x5 |
| 212 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 32U), TensorShape(5U, 5U, 32U, 64U), TensorShape(64U), TensorShape(14U, 14U, 64U), PadStrideInfo(1, 1, 2, 2) }, |
| 213 | } |
| 214 | { |
| 215 | } |
| 216 | |
| 217 | ~GoogLeNetConvolutionLayerDataset1() = default; |
| 218 | }; |
| 219 | |
| 220 | /** GoogleLeNet v1 convolution layers tensor shapes (Part 2). */ |
| 221 | class GoogLeNetConvolutionLayerDataset2 final : public ConvolutionLayerDataset<17> |
| 222 | { |
| 223 | public: |
| 224 | GoogLeNetConvolutionLayerDataset2() |
| 225 | : GenericDataset |
| 226 | { |
| 227 | // inception_4e/1x1 |
| 228 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 256U), TensorShape(256U), TensorShape(14U, 14U, 256U), PadStrideInfo(1, 1, 0, 0) }, |
| 229 | // inception_4e/3x3_reduce |
| 230 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 160U), TensorShape(160U), TensorShape(14U, 14U, 160U), PadStrideInfo(1, 1, 0, 0) }, |
| 231 | // inception_4e/3x3 |
| 232 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 160U), TensorShape(3U, 3U, 160U, 320U), TensorShape(320U), TensorShape(14U, 14U, 320U), PadStrideInfo(1, 1, 1, 1) }, |
| 233 | // inception_4e/5x5_reduce |
| 234 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 32U), TensorShape(32U), TensorShape(14U, 14U, 32U), PadStrideInfo(1, 1, 0, 0) }, |
| 235 | // inception_4e/5x5 |
| 236 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 32U), TensorShape(5U, 5U, 32U, 128U), TensorShape(128U), TensorShape(14U, 14U, 128U), PadStrideInfo(1, 1, 2, 2) }, |
| 237 | // inception_4e/pool_proj |
| 238 | ConvolutionLayerDataObject{ TensorShape(14U, 14U, 528U), TensorShape(1U, 1U, 528U, 128U), TensorShape(128U), TensorShape(14U, 14U, 128U), PadStrideInfo(1, 1, 0, 0) }, |
| 239 | // inception_5a/1x1 |
| 240 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 256U), TensorShape(256U), TensorShape(7U, 7U, 256U), PadStrideInfo(1, 1, 0, 0) }, |
| 241 | // inception_5a/3x3_reduce |
| 242 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 160U), TensorShape(160U), TensorShape(7U, 7U, 160U), PadStrideInfo(1, 1, 0, 0) }, |
| 243 | // inception_5a/3x3 |
| 244 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 160U), TensorShape(3U, 3U, 160U, 320U), TensorShape(320U), TensorShape(7U, 7U, 320U), PadStrideInfo(1, 1, 1, 1) }, |
| 245 | // inception_5a/5x5_reduce |
| 246 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 32U), TensorShape(32U), TensorShape(7U, 7U, 32U), PadStrideInfo(1, 1, 0, 0) }, |
| 247 | // inception_5a/5x5 |
| 248 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 32U), TensorShape(5U, 5U, 32U, 128U), TensorShape(128U), TensorShape(7U, 7U, 128U), PadStrideInfo(1, 1, 2, 2) }, |
| 249 | // inception_5a/pool_proj, inception_5b/pool_proj |
| 250 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 128U), TensorShape(128U), TensorShape(7U, 7U, 128U), PadStrideInfo(1, 1, 0, 0) }, |
| 251 | // inception_5b/1x1 |
| 252 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 384U), TensorShape(384U), TensorShape(7U, 7U, 384U), PadStrideInfo(1, 1, 0, 0) }, |
| 253 | // inception_5b/3x3_reduce |
| 254 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 192U), TensorShape(192U), TensorShape(7U, 7U, 192U), PadStrideInfo(1, 1, 0, 0) }, |
| 255 | // inception_5b/3x3 |
| 256 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 192U), TensorShape(3U, 3U, 192U, 384U), TensorShape(384U), TensorShape(7U, 7U, 384U), PadStrideInfo(1, 1, 1, 1) }, |
| 257 | // inception_5b/5x5_reduce |
| 258 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 832U), TensorShape(1U, 1U, 832U, 48U), TensorShape(48U), TensorShape(7U, 7U, 48U), PadStrideInfo(1, 1, 0, 0) }, |
| 259 | // inception_5b/5x5 |
| 260 | ConvolutionLayerDataObject{ TensorShape(7U, 7U, 48U), TensorShape(5U, 5U, 48U, 128U), TensorShape(128U), TensorShape(7U, 7U, 128U), PadStrideInfo(1, 1, 2, 2) } |
| 261 | } |
| 262 | { |
| 263 | } |
| 264 | |
| 265 | ~GoogLeNetConvolutionLayerDataset2() = default; |
| 266 | }; |
| 267 | } // namespace test |
| 268 | } // namespace arm_compute |
| 269 | #endif //__ARM_COMPUTE_TEST_DATASET_CONVOLUTION_LAYER_DATASET_H__ |