wehub-resource-sync
264 lines
5.3 KiB
Markdown
264 lines
5.3 KiB
Markdown
# reorgPlugin [DEPRECATED]
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**This plugin is deprecated since TensorRT 10.12 and will be removed in a future release. No alternatives are planned to be provided.**
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**Table Of Contents**
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- [Description](#description)
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* [Structure](#structure)
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- [Parameters](#parameters)
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- [Additional resources](#additional-resources)
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- [License](#license)
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- [Changelog](#changelog)
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- [Known issues](#known-issues)
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## Description
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The`reorgPlugin` is specifically used for the reorg layer in the YOLOv2 model in TensorRT. It reorganizes the elements in the input tensor and generates an output tensor of a different shape. In YOLOv2, the output tensor from the reorg layer matches the shape of the output tensor from a downstream layer Conv20_1024 in the neural network. The two output tensors are then concatenated together as one single tensor.
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### Structure
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The `reorgPlugin` takes one input and generates one output. The tensor format must be in NCHW format.
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The input is a tensor that has a shape of `[N, C, H, W]` where:
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- `N` is the batch size
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- `C` is the number of channels
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- `H` is the height of tensor
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- `W` is the width of the tensor
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After a [unique one-to-one mapping](https://github.com/pjreddie/darknet/blob/8215a8864d4ad07e058acafd75b2c6ff6600b9e8/src/blas.c#L9), the output tensor of shape `[N, C x s x s, H / s, W / s]`, where s is the stride, is generated.
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For example, if we have an input tensor of shape `[2, 4, 6, 6]`.
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```
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[[[[ 0 1 2 3 4 5]
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[ 6 7 8 9 10 11]
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[ 12 13 14 15 16 17]
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[ 18 19 20 21 22 23]
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[ 24 25 26 27 28 29]
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[ 30 31 32 33 34 35]]
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[[ 36 37 38 39 40 41]
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[ 42 43 44 45 46 47]
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[ 48 49 50 51 52 53]
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[ 54 55 56 57 58 59]
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[ 60 61 62 63 64 65]
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[ 66 67 68 69 70 71]]
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[[ 72 73 74 75 76 77]
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[ 78 79 80 81 82 83]
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[ 84 85 86 87 88 89]
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[ 90 91 92 93 94 95]
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[ 96 97 98 99 100 101]
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[102 103 104 105 106 107]]
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[[108 109 110 111 112 113]
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[114 115 116 117 118 119]
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[120 121 122 123 124 125]
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[126 127 128 129 130 131]
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[132 133 134 135 136 137]
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[138 139 140 141 142 143]]]
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[[[144 145 146 147 148 149]
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[150 151 152 153 154 155]
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[156 157 158 159 160 161]
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[162 163 164 165 166 167]
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[168 169 170 171 172 173]
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[174 175 176 177 178 179]]
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[[180 181 182 183 184 185]
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[186 187 188 189 190 191]
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[192 193 194 195 196 197]
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[198 199 200 201 202 203]
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[204 205 206 207 208 209]
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[210 211 212 213 214 215]]
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[[216 217 218 219 220 221]
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[222 223 224 225 226 227]
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[228 229 230 231 232 233]
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[234 235 236 237 238 239]
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[240 241 242 243 244 245]
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[246 247 248 249 250 251]]
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[[252 253 254 255 256 257]
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[258 259 260 261 262 263]
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[264 265 266 267 268 269]
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[270 271 272 273 274 275]
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[276 277 278 279 280 281]
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[282 283 284 285 286 287]]]]
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```
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We set `stride = 2` and perform the reorganization, we will get the following output tensor of shape `[2, 16, 3, 3]`.
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```
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[[[[ 0 2 4]
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[ 6 8 10]
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[ 24 26 28]]
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[[ 30 32 34]
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[ 48 50 52]
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[ 54 56 58]]
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[[ 72 74 76]
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[ 78 80 82]
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[ 96 98 100]]
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[[102 104 106]
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[120 122 124]
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[126 128 130]]
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[[ 1 3 5]
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[ 7 9 11]
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[ 25 27 29]]
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[[ 31 33 35]
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[ 49 51 53]
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[ 55 57 59]]
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[[ 73 75 77]
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[ 79 81 83]
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[ 97 99 101]]
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[[103 105 107]
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[121 123 125]
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[127 129 131]]
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[[ 12 14 16]
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[ 18 20 22]
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[ 36 38 40]]
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[[ 42 44 46]
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[ 60 62 64]
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[ 66 68 70]]
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[[ 84 86 88]
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[ 90 92 94]
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[108 110 112]]
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[[114 116 118]
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[132 134 136]
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[138 140 142]]
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[[ 13 15 17]
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[ 19 21 23]
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[ 37 39 41]]
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[[ 43 45 47]
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[ 61 63 65]
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[ 67 69 71]]
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[[ 85 87 89]
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[ 91 93 95]
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[109 111 113]]
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[[115 117 119]
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[133 135 137]
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[139 141 143]]]
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[[[144 146 148]
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[150 152 154]
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[168 170 172]]
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[[174 176 178]
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[192 194 196]
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[198 200 202]]
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[[216 218 220]
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[222 224 226]
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[240 242 244]]
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[[246 248 250]
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[264 266 268]
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[270 272 274]]
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[[145 147 149]
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[151 153 155]
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[169 171 173]]
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[[175 177 179]
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[193 195 197]
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[199 201 203]]
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[[217 219 221]
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[223 225 227]
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[241 243 245]]
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[[247 249 251]
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[265 267 269]
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[271 273 275]]
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[[156 158 160]
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[162 164 166]
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[180 182 184]]
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[[186 188 190]
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[204 206 208]
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[210 212 214]]
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[[228 230 232]
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[234 236 238]
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[252 254 256]]
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[[258 260 262]
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[276 278 280]
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[282 284 286]]
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[[157 159 161]
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[163 165 167]
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[181 183 185]]
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[[187 189 191]
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[205 207 209]
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[211 213 215]]
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[[229 231 233]
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[235 237 239]
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[253 255 257]]
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[[259 261 263]
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[277 279 281]
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[283 285 287]]]]
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```
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## Parameters
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The `reorgPlugin` has plugin creator class `ReorgPluginCreator` and plugin class `Reorg`.
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The following parameters were used to create the `Reorg` instance.
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| Type | Parameter | Description
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|----------|--------------------------|--------------------------------------------------------
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|`int` |`stride` |Dimension reduction factor for the input tensor. The stride has to be divisible by the height and the width of the input tensor.
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## Additional resources
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The following resources provide a deeper understanding of the `reorgPlugin` plugin:
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- [YOLOv2 paper](https://arxiv.org/abs/1612.08242)
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- [Reorg layer in YOLOv2](https://github.com/pjreddie/darknet/blob/8215a8864d4ad07e058acafd75b2c6ff6600b9e8/src/blas.c#L9)
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- [YOLOv2 architecture](https://ethereon.github.io/netscope/#/gist/d08a41711e48cf111e330827b1279c31)
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## License
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For terms and conditions for use, reproduction, and distribution, see the [TensorRT Software License Agreement](https://docs.nvidia.com/deeplearning/sdk/tensorrt-sla/index.html)
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documentation.
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## Changelog
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May 2025
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Add deprecation note.
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Feb 2024
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Support IPluginV2DynamicExt in version 2.
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May 2019
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This is the first release of this `README.md` file.
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## Known issues
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There are no known issues in this plugin.
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