Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 1 | // |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 2 | // Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved. |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #pragma once |
| 7 | |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 8 | #include <armnn/StrategyBase.hpp> |
| 9 | #include <armnn/Descriptors.hpp> |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 10 | #include <optimizations/FoldPadIntoLayer2d.hpp> |
| 11 | |
| 12 | namespace armnn |
| 13 | { |
| 14 | |
| 15 | namespace |
| 16 | { |
| 17 | |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 18 | /// Checks if a Layer has a DataLayout that is either NCHW or NCDHW. |
| 19 | class CheckForNCHW : public StrategyBase<NoThrowStrategy> |
| 20 | { |
| 21 | public: |
| 22 | CheckForNCHW() |
| 23 | {} |
| 24 | |
| 25 | void ExecuteStrategy(const armnn::IConnectableLayer* layer, |
| 26 | const armnn::BaseDescriptor& descriptor, |
| 27 | const std::vector<armnn::ConstTensor>& constants, |
| 28 | const char* name, |
| 29 | const armnn::LayerBindingId id = 0) override |
| 30 | { |
| 31 | armnn::IgnoreUnused(layer, constants, id, name); |
| 32 | switch (layer->GetType()) |
| 33 | { |
| 34 | case armnn::LayerType::BatchMatMul: |
| 35 | { |
Mike Kelly | b6de7a1 | 2023-07-18 12:03:41 +0100 | [diff] [blame] | 36 | auto desc = static_cast<const armnn::BatchMatMulDescriptor&>(descriptor); |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 37 | m_Result = desc.m_DataLayoutX == DataLayout::NCHW || desc.m_DataLayoutY == DataLayout::NCHW; |
| 38 | break; |
| 39 | } |
| 40 | case armnn::LayerType::BatchNormalization: |
| 41 | { |
| 42 | CheckDescForNCHW(static_cast<const armnn::BatchNormalizationDescriptor&>(descriptor)); |
| 43 | break; |
| 44 | } |
| 45 | case armnn::LayerType::BatchToSpaceNd: |
| 46 | { |
| 47 | CheckDescForNCHW(static_cast<const armnn::BatchToSpaceNdDescriptor&>(descriptor)); |
| 48 | break; |
| 49 | } |
| 50 | case armnn::LayerType::Convolution2d: |
| 51 | { |
| 52 | CheckDescForNCHW(static_cast<const armnn::Convolution2dDescriptor&>(descriptor)); |
| 53 | break; |
| 54 | } |
| 55 | case armnn::LayerType::Convolution3d: |
| 56 | { |
| 57 | CheckDescForNCHW(static_cast<const armnn::Convolution3dDescriptor&>(descriptor)); |
| 58 | break; |
| 59 | } |
| 60 | case armnn::LayerType::DepthwiseConvolution2d: |
| 61 | { |
| 62 | CheckDescForNCHW(static_cast<const armnn::DepthwiseConvolution2dDescriptor&>(descriptor)); |
| 63 | break; |
| 64 | } |
| 65 | case armnn::LayerType::InstanceNormalization: |
| 66 | { |
| 67 | CheckDescForNCHW(static_cast<const armnn::InstanceNormalizationDescriptor&>(descriptor)); |
| 68 | break; |
| 69 | } |
| 70 | case armnn::LayerType::L2Normalization: |
| 71 | { |
| 72 | CheckDescForNCHW(static_cast<const armnn::L2NormalizationDescriptor&>(descriptor)); |
| 73 | break; |
| 74 | } |
| 75 | case armnn::LayerType::Normalization: |
| 76 | { |
| 77 | CheckDescForNCHW(static_cast<const armnn::NormalizationDescriptor&>(descriptor)); |
| 78 | break; |
| 79 | } |
| 80 | case armnn::LayerType::Pooling2d: |
| 81 | { |
| 82 | CheckDescForNCHW(static_cast<const armnn::Pooling2dDescriptor&>(descriptor)); |
| 83 | break; |
| 84 | } |
| 85 | case armnn::LayerType::Pooling3d: |
| 86 | { |
| 87 | CheckDescForNCHW(static_cast<const armnn::Pooling3dDescriptor&>(descriptor)); |
| 88 | break; |
| 89 | } |
| 90 | case armnn::LayerType::SpaceToBatchNd: |
| 91 | { |
| 92 | CheckDescForNCHW(static_cast<const armnn::SpaceToBatchNdDescriptor&>(descriptor)); |
| 93 | break; |
| 94 | } |
| 95 | case armnn::LayerType::SpaceToDepth: |
| 96 | { |
| 97 | CheckDescForNCHW(static_cast<const armnn::SpaceToDepthDescriptor&>(descriptor)); |
| 98 | break; |
| 99 | } |
| 100 | case armnn::LayerType::StridedSlice: |
| 101 | { |
| 102 | CheckDescForNCHW(static_cast<const armnn::StridedSliceDescriptor&>(descriptor)); |
| 103 | break; |
| 104 | } |
| 105 | default: |
| 106 | { |
| 107 | m_Result = false; |
| 108 | } |
| 109 | } |
| 110 | } |
| 111 | |
| 112 | /// Returns true if the Layer had a DataLayout and it was NCHW or NCDHW. |
| 113 | /// Returns false if the Layer either doesn't have a DataLayout or if it |
| 114 | /// had a DataLayout that was neither NCHW nor NCDHW. |
| 115 | bool Result() |
| 116 | { |
| 117 | return m_Result; |
| 118 | } |
| 119 | |
| 120 | private: |
| 121 | template<typename Descriptor> |
| 122 | void CheckDescForNCHW(const Descriptor& descriptor) |
| 123 | { |
| 124 | m_Result = (descriptor.m_DataLayout == DataLayout::NCHW) || (descriptor.m_DataLayout == DataLayout::NCDHW); |
| 125 | } |
| 126 | |
| 127 | bool m_Result = false; |
| 128 | }; |
| 129 | |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 130 | // |
| 131 | // this helper only works if all layers where the inputs connect to are not selected |
| 132 | // |
| 133 | |
| 134 | SubgraphView::IInputSlots CreateIInputsFrom(const std::vector<armnn::IConnectableLayer*>& layers) |
| 135 | { |
| 136 | SubgraphView::IInputSlots result; |
| 137 | for (auto&& layer : layers) |
| 138 | { |
| 139 | for (unsigned int i = 0 ; i < layer->GetNumInputSlots(); ++i) |
| 140 | { |
| 141 | result.push_back(&(layer->GetInputSlot(i))); |
| 142 | } |
| 143 | } |
| 144 | return result; |
| 145 | } |
| 146 | |
| 147 | // |
| 148 | // this helper only works if all layers where the outputs connect to are not selected |
| 149 | // |
| 150 | |
| 151 | SubgraphView::IOutputSlots CreateIOutputsFrom(const std::vector<armnn::IConnectableLayer*>& layers) |
| 152 | { |
| 153 | SubgraphView::IOutputSlots result; |
| 154 | for (auto &&layer: layers) |
| 155 | { |
| 156 | for (unsigned int i = 0; i < layer->GetNumOutputSlots(); ++i) |
| 157 | { |
| 158 | result.push_back(&(layer->GetOutputSlot(i))); |
| 159 | } |
| 160 | } |
| 161 | return result; |
| 162 | } |
| 163 | |
Tracy Narine | 6440ce8 | 2023-09-20 14:19:07 +0100 | [diff] [blame] | 164 | // Type used to hold the slot numbers to create the lists from. There should |
| 165 | // be a SlotList for each layer in the layers list |
| 166 | typedef std::vector<int> SlotList; |
| 167 | |
| 168 | template<typename ILayerType> |
| 169 | SubgraphView::IInputSlots CreateIInputsFromSlotLists(const std::vector<ILayerType*>& layers, |
| 170 | const std::vector<SlotList>& layersSlotLists) |
| 171 | { |
| 172 | ARMNN_THROW_INVALIDARG_IF_FALSE(layersSlotLists.size() == layers.size()); |
| 173 | |
| 174 | SubgraphView::IInputSlots result; |
| 175 | |
| 176 | for (unsigned int layerIdx = 0; layerIdx < layers.size(); ++layerIdx) |
| 177 | { |
| 178 | const SlotList& slotList = layersSlotLists[layerIdx]; |
| 179 | for (unsigned int slotIdx = 0 ; slotIdx < layers[layerIdx]->GetNumInputSlots(); ++slotIdx) |
| 180 | { |
| 181 | if (std::find(slotList.begin(), slotList.end(), slotIdx) != slotList.end()) |
| 182 | { |
| 183 | result.push_back(&(layers[layerIdx]->GetInputSlot(slotIdx))); |
| 184 | } |
| 185 | } |
| 186 | } |
| 187 | return result; |
| 188 | } |
| 189 | |
| 190 | template<typename ILayerType> |
| 191 | SubgraphView::IOutputSlots CreateIOutputsFromSlotLists(const std::vector<ILayerType*>& layers, |
| 192 | const std::vector<SlotList>& layersSlotLists) |
| 193 | { |
| 194 | ARMNN_THROW_INVALIDARG_IF_FALSE(layersSlotLists.size() == layers.size()); |
| 195 | |
| 196 | SubgraphView::IOutputSlots result; |
| 197 | for (unsigned int layerIdx = 0; layerIdx < layers.size(); ++layerIdx) |
| 198 | { |
| 199 | const SlotList& slotList = layersSlotLists[layerIdx]; |
| 200 | for (unsigned int slotIdx = 0; slotIdx < layers[layerIdx]->GetNumOutputSlots(); ++slotIdx) |
| 201 | { |
| 202 | bool foundIt = std::find(slotList.begin(), slotList.end(), slotIdx) != slotList.end(); |
| 203 | if (foundIt) |
| 204 | { |
| 205 | result.push_back(&(layers[layerIdx]->GetOutputSlot(slotIdx))); |
| 206 | } |
| 207 | } |
| 208 | } |
| 209 | return result; |
| 210 | } |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 211 | } |
| 212 | |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 213 | inline bool IsNCHW(armnn::Layer& layer) |
| 214 | { |
| 215 | CheckForNCHW check; |
| 216 | layer.ExecuteStrategy(check); |
| 217 | return check.Result(); |
| 218 | } |
| 219 | |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 220 | inline void ReportUntouchedLayers(OptimizationViews& optimizationViews, std::map<LayerGuid, Layer*> untouched) |
| 221 | { |
| 222 | std::vector<Layer*> untouchedVector; |
| 223 | for (const auto& pair : untouched) |
| 224 | { |
| 225 | Layer* layer = pair.second; |
| 226 | SubgraphView subgraphView({layer}, |
| 227 | CreateIInputsFrom({layer}), |
| 228 | CreateIOutputsFrom({layer})); |
| 229 | optimizationViews.AddUntouchedSubgraph(std::move(subgraphView)); |
| 230 | } |
| 231 | } |
| 232 | |
| 233 | template<typename LayerType> |
| 234 | LayerType* FoldPadLayer(OptimizationViews& optimizationViews, |
| 235 | LayerType* baseLayer, |
| 236 | LayerType* replacementLayer, |
| 237 | PadLayer* padLayer) |
| 238 | { |
| 239 | SubgraphView substitutionSubgraph({padLayer, baseLayer}, |
| 240 | CreateIInputsFrom({padLayer}), |
| 241 | CreateIOutputsFrom({baseLayer})); |
| 242 | SubgraphView replacementSubgraph(replacementLayer); |
| 243 | |
| 244 | optimizationViews.AddSubstitution({substitutionSubgraph, replacementSubgraph}); |
| 245 | |
| 246 | return replacementLayer; |
| 247 | } |
| 248 | |
Mike Kelly | be06f10 | 2023-07-17 17:49:55 +0100 | [diff] [blame] | 249 | /// Checks if the Layer is connected to any Layer that has an NCHW layout. |
| 250 | inline bool ConnectedToLayerWithNCHW(Layer* baseLayer) |
| 251 | { |
| 252 | Layer& parentLayer = baseLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer(); |
| 253 | |
| 254 | if (IsNCHW(parentLayer)) |
| 255 | { |
| 256 | return true; |
| 257 | } |
| 258 | for (unsigned int i = 0; i < baseLayer->GetOutputSlot(0).GetNumConnections(); ++i) |
| 259 | { |
| 260 | Layer& nextLayer = baseLayer->GetOutputSlot(0).GetConnection(i)->GetOwningLayer(); |
| 261 | if (IsNCHW(nextLayer)) |
| 262 | { |
| 263 | return true; |
| 264 | } |
| 265 | } |
| 266 | return false; |
| 267 | } |
| 268 | |
Mike Kelly | b6de7a1 | 2023-07-18 12:03:41 +0100 | [diff] [blame] | 269 | /// Checks the Layer's Connections to see if it's connected to a Layer with the provided layerType. If dimSize is |
| 270 | /// provided will also check if the connecting Tensor has more than that number of dimensions |
| 271 | inline bool ConnectedToLayerType(Layer* baseLayer, LayerType layerType, unsigned int dimSize = 0) |
Mike Kelly | be06f10 | 2023-07-17 17:49:55 +0100 | [diff] [blame] | 272 | { |
| 273 | Layer& parentLayer = baseLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer(); |
Mike Kelly | b6de7a1 | 2023-07-18 12:03:41 +0100 | [diff] [blame] | 274 | TensorInfo parentTensorInfo = baseLayer->GetInputSlot(0).GetTensorInfo(); |
| 275 | |
| 276 | if (parentTensorInfo.GetNumDimensions() > dimSize && parentLayer.GetType() == layerType) |
Mike Kelly | be06f10 | 2023-07-17 17:49:55 +0100 | [diff] [blame] | 277 | { |
| 278 | return true; |
| 279 | } |
| 280 | for (unsigned int i = 0; i < baseLayer->GetOutputSlot(0).GetNumConnections(); ++i) |
| 281 | { |
| 282 | Layer& nextLayer = baseLayer->GetOutputSlot(0).GetConnection(i)->GetOwningLayer(); |
| 283 | TensorInfo nextTensorInfo = baseLayer->GetOutputSlot(0).GetConnection(i)->GetTensorInfo(); |
Mike Kelly | b6de7a1 | 2023-07-18 12:03:41 +0100 | [diff] [blame] | 284 | |
| 285 | if (nextTensorInfo.GetNumDimensions() > dimSize && nextLayer.GetType() == layerType) |
Mike Kelly | be06f10 | 2023-07-17 17:49:55 +0100 | [diff] [blame] | 286 | { |
| 287 | return true; |
| 288 | } |
| 289 | } |
| 290 | return false; |
| 291 | } |
| 292 | |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 293 | inline void RemoveReshapeLayer(ReshapeLayer* baseLayer, |
| 294 | std::map<LayerGuid, Layer*>& untouched, |
| 295 | OptimizationViews& optimizationViews) |
| 296 | { |
| 297 | if (baseLayer == nullptr) |
| 298 | { |
| 299 | return; |
| 300 | } |
| 301 | ReshapeDescriptor reshapeDescriptor = baseLayer->GetParameters(); |
| 302 | Layer& parentLayer = baseLayer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer(); |
| 303 | |
| 304 | // Cannot currently remove the Reshape if it's connected to an Input, Constant or Splitter |
| 305 | if (parentLayer.GetType() == LayerType::Input || parentLayer.GetType() == LayerType::Constant) |
| 306 | { |
| 307 | return; |
| 308 | } |
| 309 | |
| 310 | // Cannot currently remove the Reshape if it's connected to an OutputSlot or Concat |
| 311 | for (unsigned int i = 0; i < baseLayer->GetOutputSlot(0).GetNumConnections(); ++i) |
| 312 | { |
| 313 | Layer& nextLayer = baseLayer->GetOutputSlot(0).GetConnection(i)->GetOwningLayer(); |
| 314 | |
| 315 | if (nextLayer.GetType() == LayerType::Output) |
| 316 | { |
| 317 | return; |
| 318 | } |
| 319 | } |
| 320 | auto it = untouched.find(baseLayer->GetGuid()); |
| 321 | if (it == untouched.end()) |
| 322 | { |
| 323 | // Already removed from map |
| 324 | return; |
| 325 | } |
| 326 | untouched.erase(it); |
| 327 | |
| 328 | // Override the InputSlot TensorInfos for all the layers connected to the Reshape's OutputSlot |
| 329 | for (unsigned int i = 0; i < baseLayer->GetOutputSlot(0).GetNumConnections(); ++i) |
| 330 | { |
| 331 | Layer& nextLayer = baseLayer->GetOutputSlot(0).GetConnection(i)->GetOwningLayer(); |
| 332 | auto inputIndex = baseLayer->GetOutputSlot(0).GetConnection(i)->GetSlotIndex(); |
| 333 | TensorInfo reshapeInfo(baseLayer->GetOutputSlot(0).GetTensorInfo()); |
| 334 | reshapeInfo.SetShape(reshapeDescriptor.m_TargetShape); |
| 335 | nextLayer.GetInputSlot(inputIndex).SetTensorInfo(reshapeInfo); |
| 336 | } |
| 337 | optimizationViews.AddDeletedSubgraph(baseLayer); |
| 338 | } |
| 339 | |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 340 | template<typename LayerType> |
| 341 | LayerType* FoldPadIntoAveragePool2d(OptimizationViews& optimizationViews, |
| 342 | Pooling2dLayer* baseLayer, |
| 343 | Pooling2dDescriptor& poolDescriptor, |
| 344 | PadLayer* padLayer) |
| 345 | { |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 346 | IConnectableLayer* replacement = |
| 347 | optimizationViews.GetINetwork()->AddPooling2dLayer(poolDescriptor, "folded-pad-into-pool2d"); |
| 348 | LayerType* replacementLayer = PolymorphicDowncast<LayerType*>(replacement); |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 349 | |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 350 | FoldPadLayer(optimizationViews, |
| 351 | baseLayer, |
| 352 | replacementLayer, |
| 353 | padLayer); |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 354 | |
Mike Kelly | 4cc341c | 2023-07-07 15:43:06 +0100 | [diff] [blame] | 355 | return replacementLayer; |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 356 | } |
| 357 | |
Tracy Narine | 6440ce8 | 2023-09-20 14:19:07 +0100 | [diff] [blame] | 358 | // |
| 359 | // Layer sequence detection such as add + mul + add ( + optional activation ) |
| 360 | // |
| 361 | |
| 362 | inline bool IsSequenceLayerType(Layer& layer, LayerType type) |
| 363 | { |
| 364 | return layer.GetType() == type; |
| 365 | } |
| 366 | |
| 367 | inline bool IsSequenceLayerType(Layer& layer, BinaryOperation type) |
| 368 | { |
| 369 | return (layer.GetType() == LayerType::ElementwiseBinary) && |
| 370 | (PolymorphicDowncast<ElementwiseBinaryLayer*>(&layer)->GetParameters().m_Operation == type); |
| 371 | } |
| 372 | |
| 373 | // Detect a layer sequence and activation if specified. The activation must be at the end of the sequence. |
| 374 | template<typename TYPE> |
| 375 | bool IsLayerSequence(Layer& currentLayer, |
| 376 | TYPE first, |
| 377 | TYPE second, |
| 378 | TYPE third, |
| 379 | Layer* layerList[4], |
| 380 | bool handleValidActivates, |
| 381 | const std::vector<ActivationFunction>& validActivates) |
| 382 | { |
| 383 | auto PreviousLayer = [](Layer& layer) |
| 384 | { |
| 385 | return &layer.GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer(); |
| 386 | }; |
| 387 | |
| 388 | auto NextLayer = [](Layer& layer) |
| 389 | { |
| 390 | return &layer.GetOutputSlot(0).GetConnection(0)->GetOwningLayer(); |
| 391 | }; |
| 392 | |
| 393 | auto LayerIncomingConnectionDataType = [](Layer& layer) |
| 394 | { |
| 395 | return layer.GetInputSlot(0).GetTensorInfo().GetDataType(); |
| 396 | }; |
| 397 | |
| 398 | bool result = false; |
| 399 | |
| 400 | // Match in reverse so there is only 1 connection to check |
| 401 | if (IsSequenceLayerType(currentLayer, third)) |
| 402 | { |
| 403 | // Save DataType of third layer |
| 404 | DataType dataType = LayerIncomingConnectionDataType(currentLayer); |
| 405 | |
| 406 | // Save third layer |
| 407 | layerList[2] = ¤tLayer; |
| 408 | |
| 409 | // Check the layers that proceed this one for the requested grouping |
| 410 | Layer *prevLayer = PreviousLayer(currentLayer); |
| 411 | if (prevLayer && IsSequenceLayerType(*prevLayer, second)) |
| 412 | { |
| 413 | bool dataTypesMatch = (dataType == LayerIncomingConnectionDataType(*prevLayer)); |
| 414 | if (! dataTypesMatch) |
| 415 | { |
| 416 | return result; |
| 417 | } |
| 418 | |
| 419 | layerList[1] = prevLayer; |
| 420 | prevLayer = PreviousLayer(*prevLayer); |
| 421 | if (prevLayer && IsSequenceLayerType(*prevLayer, first)) |
| 422 | { |
| 423 | dataTypesMatch = (dataType == LayerIncomingConnectionDataType(*prevLayer)); |
| 424 | if (! dataTypesMatch) |
| 425 | { |
| 426 | return result; |
| 427 | } |
| 428 | |
| 429 | layerList[0] = prevLayer; |
| 430 | |
| 431 | // Detected the first 3 layers if we get to this point so now |
| 432 | // check to see if we have a valid activation. If there is no activation |
| 433 | // then the sequence still matches. |
| 434 | if (handleValidActivates) |
| 435 | { |
| 436 | Layer *nextLayer = NextLayer(currentLayer); |
| 437 | if (nextLayer) |
| 438 | { |
| 439 | if (IsSequenceLayerType(*nextLayer, LayerType::Activation)) |
| 440 | { |
| 441 | // This layer is an activation, so it must be a valid type for the sequence |
| 442 | ActivationFunction activationFunction = |
| 443 | PolymorphicDowncast<ActivationLayer*>(nextLayer)->GetParameters().m_Function; |
| 444 | long count = std::count(validActivates.cbegin(), |
| 445 | validActivates.cend(), |
| 446 | activationFunction); |
| 447 | if (count > 0) |
| 448 | { |
| 449 | layerList[3] = nextLayer; |
| 450 | result = true; |
| 451 | } |
| 452 | } |
| 453 | else |
| 454 | { |
| 455 | // Next layer is not an activation so sequence still matches |
| 456 | result = true; |
| 457 | } |
| 458 | } |
| 459 | } |
| 460 | else |
| 461 | { |
| 462 | result = true; |
| 463 | } |
| 464 | } |
| 465 | } |
| 466 | } |
| 467 | |
| 468 | return result; |
| 469 | } |
| 470 | |
Cathal Corbett | 3883b27 | 2022-07-22 16:03:36 +0100 | [diff] [blame] | 471 | } // namespace armnn |