telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
David Beck | ecb56cd | 2018-09-05 12:52:57 +0100 | [diff] [blame] | 3 | // SPDX-License-Identifier: MIT |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 4 | // |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 5 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 6 | #include "Network.hpp" |
| 7 | #include "Graph.hpp" |
| 8 | #include "Layer.hpp" |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 9 | #include "DeviceSpec.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 10 | #include "Optimizer.hpp" |
Derek Lamberti | ff05cc5 | 2019-04-26 13:05:17 +0100 | [diff] [blame] | 11 | #include "SubgraphViewSelector.hpp" |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 12 | #include "BackendSettings.hpp" |
David Beck | ac42efd | 2018-09-26 17:41:13 +0100 | [diff] [blame] | 13 | #include "optimizations/All.hpp" |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 14 | |
Aron Virginas-Tar | c9cc804 | 2018-11-01 16:15:57 +0000 | [diff] [blame] | 15 | #include <backendsCommon/CpuTensorHandle.hpp> |
| 16 | #include <backendsCommon/WorkloadFactory.hpp> |
David Beck | 263e349 | 2018-11-09 14:46:40 +0000 | [diff] [blame] | 17 | #include <backendsCommon/IBackendInternal.hpp> |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 18 | #include <backendsCommon/TensorHandleFactoryRegistry.hpp> |
David Beck | ac42efd | 2018-09-26 17:41:13 +0100 | [diff] [blame] | 19 | |
| 20 | #include <armnn/Exceptions.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 21 | #include <armnn/Utils.hpp> |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 22 | #include <armnn/TypesUtils.hpp> |
Matteo Martincigh | c601aa6 | 2019-10-29 15:03:22 +0000 | [diff] [blame] | 23 | #include <armnn/BackendRegistry.hpp> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 24 | |
Jan Eilers | 99d9d4a | 2019-11-06 10:02:16 +0000 | [diff] [blame^] | 25 | #include <ProfilingService.hpp> |
| 26 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 27 | #include <fcntl.h> |
| 28 | #include <algorithm> |
| 29 | #include <fstream> |
| 30 | #include <memory> |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 31 | #include <vector> |
| 32 | #include <algorithm> |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 33 | |
| 34 | #include <boost/assert.hpp> |
| 35 | #include <boost/format.hpp> |
| 36 | #include <boost/log/trivial.hpp> |
| 37 | #include <boost/numeric/conversion/converter_policies.hpp> |
| 38 | #include <boost/cast.hpp> |
| 39 | |
| 40 | namespace armnn |
| 41 | { |
| 42 | |
| 43 | armnn::INetwork* INetwork::CreateRaw() |
| 44 | { |
| 45 | return new Network(); |
| 46 | } |
| 47 | |
| 48 | armnn::INetworkPtr INetwork::Create() |
| 49 | { |
| 50 | return INetworkPtr(CreateRaw(), &INetwork::Destroy); |
| 51 | } |
| 52 | |
| 53 | void INetwork::Destroy(INetwork* network) |
| 54 | { |
| 55 | delete boost::polymorphic_downcast<Network*>(network); |
| 56 | } |
| 57 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 58 | void IOptimizedNetwork::Destroy(IOptimizedNetwork* network) |
| 59 | { |
| 60 | delete boost::polymorphic_downcast<OptimizedNetwork*>(network); |
| 61 | } |
| 62 | |
| 63 | Status OptimizedNetwork::PrintGraph() |
| 64 | { |
| 65 | m_Graph->Print(); |
| 66 | return Status::Success; |
| 67 | } |
| 68 | |
surmeh01 | bceff2f | 2018-03-29 16:29:27 +0100 | [diff] [blame] | 69 | Status OptimizedNetwork::SerializeToDot(std::ostream& stream) const |
| 70 | { |
| 71 | return m_Graph->SerializeToDot(stream); |
| 72 | } |
| 73 | |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 74 | |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 75 | |
| 76 | void ReportError(const std::string& errorMessage, |
| 77 | Optional<std::vector<std::string>&> errorMessages) |
| 78 | { |
| 79 | std::stringstream fullErrorMessage; |
| 80 | fullErrorMessage << "ERROR: " << errorMessage; |
| 81 | BOOST_LOG_TRIVIAL(warning) << fullErrorMessage.str(); |
| 82 | if (errorMessages) |
| 83 | { |
| 84 | errorMessages.value().push_back(fullErrorMessage.str()); |
| 85 | } |
| 86 | } |
| 87 | |
| 88 | void ReportWarning(const std::string& warningMessage, |
| 89 | Optional<std::vector<std::string>&> warningMessages) |
| 90 | { |
| 91 | std::stringstream fullWarningMessage; |
| 92 | fullWarningMessage << "WARNING: " << warningMessage; |
| 93 | BOOST_LOG_TRIVIAL(warning) << fullWarningMessage.str(); |
| 94 | if (warningMessages) |
| 95 | { |
| 96 | warningMessages.value().push_back(fullWarningMessage.str()); |
| 97 | } |
| 98 | } |
| 99 | |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 100 | bool CheckScaleSetOnQuantizedType(Layer* layer, Optional<std::vector<std::string>&> errMessages) |
| 101 | { |
| 102 | bool noErrors = true; |
| 103 | unsigned int numOutputs = layer->GetNumOutputSlots(); |
| 104 | for (unsigned int i = 0; i < numOutputs; i++) { |
David Monahan | b855470 | 2019-04-25 16:03:38 +0100 | [diff] [blame] | 105 | OutputSlot& outputSlot = layer->GetOutputSlot(i); |
| 106 | TensorInfo info = outputSlot.GetTensorInfo(); |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 107 | if (DataType::QuantisedAsymm8 == info.GetDataType()) { |
| 108 | if (0.f == info.GetQuantizationScale()) { |
| 109 | noErrors = false; |
| 110 | std::stringstream ss; |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 111 | ss << "output " << i << " of layer " << GetLayerTypeAsCString(layer->GetType()) |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 112 | << " (" << layer->GetNameStr() << ") is of type" |
| 113 | << " Quantized 8 bit but its scale parameter has not been set"; |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 114 | ReportError(ss.str(), errMessages); |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 115 | } |
David Monahan | b855470 | 2019-04-25 16:03:38 +0100 | [diff] [blame] | 116 | // Softmax under QuantisedAsymm8 must always be scale (1.0f/256.0f) and offset 0 |
| 117 | if ((info.GetQuantizationScale() != (1.0f / 256.0f) || |
| 118 | info.GetQuantizationOffset() != 0) && |
| 119 | layer->GetType() == armnn::LayerType::Softmax) |
| 120 | { |
| 121 | std::stringstream ss; |
| 122 | ss << "Quantization parameters for Softmax layer (Scale: " << |
| 123 | info.GetQuantizationScale() << " and Offset: " << info.GetQuantizationOffset() << |
| 124 | ") are incorrect and have been updated to Scale: 0.00390625 and Offset: 0"; |
| 125 | BOOST_LOG_TRIVIAL(warning) << ss.str(); |
| 126 | info.SetQuantizationScale((1.0f /256.0f)); |
| 127 | info.SetQuantizationOffset(0); |
| 128 | outputSlot.SetTensorInfo(info); |
| 129 | } |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 130 | } |
| 131 | } |
| 132 | return noErrors; |
| 133 | } |
| 134 | |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 135 | OptimizationResult AssignBackends(OptimizedNetwork* optNetObjPtr, |
| 136 | BackendSettings& backendSettings, |
| 137 | Graph::Iterator& firstLayer, |
| 138 | Graph::Iterator& lastLayer, |
| 139 | Optional<std::vector<std::string>&> errMessages) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 140 | { |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 141 | OptimizationResult result; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 142 | |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 143 | // Helper lambda to compose meaningful error message before returning with error |
| 144 | auto ReturnWithError = [&](const Layer* layer) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 145 | { |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 146 | std::stringstream failureMsg; |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 147 | failureMsg << "Layer of type " << GetLayerTypeAsCString(layer->GetType()) |
| 148 | << " is not supported on any preferred backend " << backendSettings.m_PreferredBackends; |
| 149 | ReportError(failureMsg.str(), errMessages); |
| 150 | |
| 151 | result.m_Error = true; |
| 152 | return result; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 153 | }; |
| 154 | |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 155 | auto availablePreferredBackends = backendSettings.GetAvailablePreferredBackends(); |
| 156 | if (availablePreferredBackends.empty()) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 157 | { |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 158 | std::stringstream failureMsg; |
| 159 | failureMsg << "No preferred backends are available"; |
| 160 | ReportError(failureMsg.str(), errMessages); |
| 161 | |
| 162 | result.m_Error = true; |
| 163 | return result; |
| 164 | } |
| 165 | |
| 166 | for (auto it = firstLayer; it != lastLayer; ++it) |
| 167 | { |
| 168 | auto layer = *it; |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 169 | DataType dataType = layer->GetDataType(); |
| 170 | std::string reasonIfUnsupported; |
| 171 | bool found = false; |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 172 | if (!CheckScaleSetOnQuantizedType(layer, errMessages)) |
| 173 | { |
| 174 | // don't bomb immediately, find all the quantized outputs |
| 175 | // which haven't had a scale set and report them all back. |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 176 | result.m_Error = true; |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 177 | } |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 178 | |
David Beck | f0b4845 | 2018-10-19 15:20:56 +0100 | [diff] [blame] | 179 | for (const auto& backend : availablePreferredBackends) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 180 | { |
| 181 | // need to set the compute device on the layer |
| 182 | // before we can check if it is supported |
David Beck | 33f0ae0 | 2018-10-18 15:13:56 +0100 | [diff] [blame] | 183 | layer->SetBackendId(backend); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 184 | if (!IWorkloadFactory::IsLayerSupported(*layer, dataType, reasonIfUnsupported)) |
| 185 | { |
| 186 | if (dataType == DataType::Float16) |
| 187 | { |
| 188 | if (IWorkloadFactory::IsLayerSupported(*layer, DataType::Float32, reasonIfUnsupported) |
| 189 | && layer->GetType() != LayerType::ConvertFp32ToFp16 |
| 190 | && layer->GetType() != LayerType::ConvertFp16ToFp32) |
| 191 | { |
| 192 | // Insert FP16 -> FP32 conversion layer before current layer |
| 193 | std::vector<ConvertFp16ToFp32Layer*> convertFp16ToFp32Layers = |
| 194 | InsertConvertFp16ToFp32LayersBefore(optNetObjPtr->GetGraph(), *layer); |
| 195 | |
| 196 | // Insert FP32 -> FP16 conversion layer after current layer |
| 197 | std::vector<ConvertFp32ToFp16Layer*> convertFp32ToFp16Layers = |
| 198 | InsertConvertFp32ToFp16LayersAfter(optNetObjPtr->GetGraph(), *layer); |
| 199 | |
| 200 | // Assign a supported backend to the newly introduced conversion layers |
David Beck | f0b4845 | 2018-10-19 15:20:56 +0100 | [diff] [blame] | 201 | auto AssignFirstSupportedBackend = [&](Layer* layer, BackendId preferredBackend) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 202 | { |
| 203 | bool supportedBackendFound = false; |
| 204 | std::string reasonIfUnsupported; |
| 205 | |
| 206 | // Try preferred backend first |
David Beck | 33f0ae0 | 2018-10-18 15:13:56 +0100 | [diff] [blame] | 207 | layer->SetBackendId(preferredBackend); |
David Beck | 29c75de | 2018-10-23 13:35:58 +0100 | [diff] [blame] | 208 | if (IWorkloadFactory::IsLayerSupported(*layer, |
| 209 | EmptyOptional(), |
| 210 | reasonIfUnsupported)) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 211 | { |
| 212 | supportedBackendFound = true; |
| 213 | } |
| 214 | else |
| 215 | { |
David Beck | f0b4845 | 2018-10-19 15:20:56 +0100 | [diff] [blame] | 216 | for (const auto& backend : availablePreferredBackends) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 217 | { |
| 218 | // Skip preferred backend (we already determined that it is not supported) |
| 219 | if (backend == preferredBackend) |
| 220 | { |
| 221 | continue; |
| 222 | } |
| 223 | |
David Beck | 33f0ae0 | 2018-10-18 15:13:56 +0100 | [diff] [blame] | 224 | layer->SetBackendId(backend); |
David Beck | 29c75de | 2018-10-23 13:35:58 +0100 | [diff] [blame] | 225 | if (IWorkloadFactory::IsLayerSupported(*layer, |
| 226 | EmptyOptional(), |
| 227 | reasonIfUnsupported)) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 228 | { |
| 229 | supportedBackendFound = true; |
| 230 | break; |
| 231 | } |
| 232 | } |
| 233 | } |
| 234 | |
| 235 | return supportedBackendFound; |
| 236 | }; |
| 237 | |
| 238 | for (ConvertFp16ToFp32Layer* convertLayer : convertFp16ToFp32Layers) |
| 239 | { |
| 240 | if (!AssignFirstSupportedBackend(convertLayer, backend)) |
| 241 | { |
| 242 | return ReturnWithError(convertLayer); |
| 243 | } |
| 244 | } |
| 245 | |
| 246 | for (ConvertFp32ToFp16Layer* convertLayer : convertFp32ToFp16Layers) |
| 247 | { |
| 248 | if (!AssignFirstSupportedBackend(convertLayer, backend)) |
| 249 | { |
| 250 | return ReturnWithError(convertLayer); |
| 251 | } |
| 252 | } |
| 253 | |
| 254 | found = true; |
| 255 | break; |
| 256 | } |
| 257 | } |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 258 | std::stringstream warningMsg; |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 259 | warningMsg << "Layer of type " << GetLayerTypeAsCString(layer->GetType()) |
David Beck | 33f0ae0 | 2018-10-18 15:13:56 +0100 | [diff] [blame] | 260 | << " is not supported on requested backend " << layer->GetBackendId().Get() |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 261 | << " for data type " << GetDataTypeName(dataType) |
| 262 | << " (reason: " << reasonIfUnsupported |
| 263 | << "), falling back to the next backend."; |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 264 | ReportWarning(warningMsg.str(), errMessages); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 265 | } |
| 266 | else |
| 267 | { |
| 268 | found = true; |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 269 | backendSettings.m_SelectedBackends.insert(backend); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 270 | break; |
| 271 | } |
| 272 | } |
| 273 | |
| 274 | // If the layer is unsupported by any devices, log and return a null network. |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 275 | if (!found) |
| 276 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 277 | // NOTE: if the layer is not an operation queue type AND we have not got CpuRef as a |
| 278 | // fallback we should set the compute device on the layer to CpuRef (these are not |
| 279 | // available as accelerated operations, or are only available under certain |
| 280 | // conditions, currently they comprise MemCopy, Constant, Permute) |
| 281 | armnn::LayerType layerType = layer->GetType(); |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 282 | if (!backendSettings.IsCpuRefUsed() && (layerType == armnn::LayerType::MemCopy || |
| 283 | layerType == armnn::LayerType::Constant || |
| 284 | layerType == armnn::LayerType::Permute)) |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 285 | { |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 286 | BackendId cpuBackendId(armnn::Compute::CpuRef); |
| 287 | layer->SetBackendId(cpuBackendId); |
| 288 | backendSettings.m_SelectedBackends.insert(cpuBackendId); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 289 | } |
| 290 | else |
| 291 | { |
| 292 | return ReturnWithError(layer); |
| 293 | } |
| 294 | } |
| 295 | } |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 296 | |
| 297 | return result; |
| 298 | } |
| 299 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 300 | OptimizationResult AssignBackends(OptimizedNetwork* optNetObjPtr, |
| 301 | BackendSettings& backendSettings, |
Derek Lamberti | ff05cc5 | 2019-04-26 13:05:17 +0100 | [diff] [blame] | 302 | SubgraphView& subgraph, |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 303 | Optional<std::vector<std::string>&> errMessages) |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 304 | { |
Derek Lamberti | ff05cc5 | 2019-04-26 13:05:17 +0100 | [diff] [blame] | 305 | Graph::Iterator firstLayer = subgraph.begin(); |
| 306 | Graph::Iterator lastLayer = subgraph.end(); |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 307 | return AssignBackends(optNetObjPtr, |
| 308 | backendSettings, |
| 309 | firstLayer, |
| 310 | lastLayer, |
| 311 | errMessages); |
| 312 | } |
| 313 | |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 314 | BackendsMap CreateSupportedBackends(TensorHandleFactoryRegistry& handleFactoryRegistry, |
| 315 | BackendSettings& backendSettings) |
| 316 | { |
| 317 | BackendsMap backends; |
| 318 | auto const& backendRegistry = BackendRegistryInstance(); |
| 319 | for (auto&& selectedBackend : backendSettings.m_SupportedBackends) |
| 320 | { |
| 321 | auto backendFactory = backendRegistry.GetFactory(selectedBackend); |
| 322 | auto backendObjPtr = backendFactory(); |
| 323 | BOOST_ASSERT(backendObjPtr); |
| 324 | |
| 325 | backendObjPtr->RegisterTensorHandleFactories(handleFactoryRegistry); |
| 326 | |
| 327 | backends[backendObjPtr->GetId()] = std::move(backendObjPtr); |
| 328 | } |
| 329 | |
| 330 | return backends; |
| 331 | } |
| 332 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 333 | OptimizationResult ApplyBackendOptimizations(OptimizedNetwork* optNetObjPtr, |
| 334 | BackendSettings& backendSettings, |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 335 | BackendsMap& backends, |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 336 | Optional<std::vector<std::string>&> errMessages) |
| 337 | { |
| 338 | BOOST_ASSERT(optNetObjPtr); |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 339 | |
| 340 | OptimizationResult result; |
| 341 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 342 | // Get the optimized graph |
| 343 | Graph& optGraph = optNetObjPtr->GetGraph(); |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 344 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 345 | // Run backend specific optimizations |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 346 | for (auto&& selectedBackend : backendSettings.m_SelectedBackends) |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 347 | { |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 348 | auto backendObjPtr = backends.find(selectedBackend)->second.get(); |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 349 | BOOST_ASSERT(backendObjPtr); |
| 350 | |
| 351 | // Select sub-graphs based on backend |
Derek Lamberti | ff05cc5 | 2019-04-26 13:05:17 +0100 | [diff] [blame] | 352 | SubgraphViewSelector::Subgraphs subgraphs = |
Rob Hughes | 65c3226 | 2019-07-23 15:33:39 +0100 | [diff] [blame] | 353 | SubgraphViewSelector::SelectSubgraphs(optGraph, |
Matteo Martincigh | 602af09 | 2019-05-01 10:31:27 +0100 | [diff] [blame] | 354 | // Select layers assigned to the requested backend |
| 355 | [&backendObjPtr](const Layer& layer) |
| 356 | { |
| 357 | return layer.GetType() != LayerType::Input && |
| 358 | layer.GetType() != LayerType::Output && |
| 359 | layer.GetBackendId() == backendObjPtr->GetId(); |
| 360 | }); |
Derek Lamberti | ff05cc5 | 2019-04-26 13:05:17 +0100 | [diff] [blame] | 361 | if (subgraphs.empty()) |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 362 | { |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 363 | // No sub-graphs found, try with next selected backend |
| 364 | continue; |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 365 | } |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 366 | |
| 367 | // Try to optimize each sub-graph |
Derek Lamberti | ff05cc5 | 2019-04-26 13:05:17 +0100 | [diff] [blame] | 368 | for (auto& subgraph : subgraphs) |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 369 | { |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 370 | // Try to optimize the current sub-graph |
Matteo Martincigh | 8492433 | 2019-05-09 12:46:16 +0100 | [diff] [blame] | 371 | OptimizationViews optimizationViews = backendObjPtr->OptimizeSubgraphView(*subgraph); |
| 372 | BOOST_ASSERT(optimizationViews.Validate(*subgraph)); |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 373 | |
| 374 | // Optimization attempted, check the resulting optimized sub-graph |
Matteo Martincigh | 8492433 | 2019-05-09 12:46:16 +0100 | [diff] [blame] | 375 | for (auto& substitution : optimizationViews.GetSubstitutions()) |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 376 | { |
| 377 | // Sub-graph optimized, substitute the sub-graph with the new optimized one in the main optimized graph |
Matteo Martincigh | 8492433 | 2019-05-09 12:46:16 +0100 | [diff] [blame] | 378 | SubgraphView& replacementSubgraph = substitution.m_ReplacementSubgraph; |
| 379 | SubgraphView& substitutableSubgraph = substitution.m_SubstitutableSubgraph; |
| 380 | optGraph.SubstituteSubgraph(substitutableSubgraph, replacementSubgraph); |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 381 | |
| 382 | // Assign the current backend to the optimized sub-graph |
Matteo Martincigh | 8492433 | 2019-05-09 12:46:16 +0100 | [diff] [blame] | 383 | std::for_each(replacementSubgraph.begin(), replacementSubgraph.end(), [&selectedBackend](Layer* l) |
Derek Lamberti | c2fe5fb | 2019-05-08 10:23:08 +0100 | [diff] [blame] | 384 | { |
| 385 | BOOST_ASSERT(l); |
| 386 | l->SetBackendId(selectedBackend); |
| 387 | }); |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 388 | } |
Derek Lamberti | c2fe5fb | 2019-05-08 10:23:08 +0100 | [diff] [blame] | 389 | |
Matteo Martincigh | 8492433 | 2019-05-09 12:46:16 +0100 | [diff] [blame] | 390 | if (!optimizationViews.GetFailedSubgraphs().empty()) |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 391 | { |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 392 | std::stringstream warningMsg; |
Derek Lamberti | c2fe5fb | 2019-05-08 10:23:08 +0100 | [diff] [blame] | 393 | warningMsg << "Some sub-graph(s) failed to optimized on " << backendObjPtr->GetId() << " backend."; |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 394 | ReportWarning(warningMsg.str(), errMessages); |
| 395 | |
| 396 | // Failed to optimize the given sub-graph, re-assign the sub-graph layers to other available backends |
Derek Lamberti | c2fe5fb | 2019-05-08 10:23:08 +0100 | [diff] [blame] | 397 | BackendSettings settingsCopy(backendSettings); |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 398 | if (!backendObjPtr->GetId().IsCpuRef()) |
| 399 | { |
| 400 | // Add the current backend to the list of backends to ignore |
Derek Lamberti | c2fe5fb | 2019-05-08 10:23:08 +0100 | [diff] [blame] | 401 | settingsCopy.m_IgnoredBackends.insert(backendObjPtr->GetId()); |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 402 | } |
Derek Lamberti | c2fe5fb | 2019-05-08 10:23:08 +0100 | [diff] [blame] | 403 | |
| 404 | int count=0; |
Matteo Martincigh | 8492433 | 2019-05-09 12:46:16 +0100 | [diff] [blame] | 405 | for (auto& failedSubgraph : optimizationViews.GetFailedSubgraphs()) |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 406 | { |
Derek Lamberti | c2fe5fb | 2019-05-08 10:23:08 +0100 | [diff] [blame] | 407 | // An error occurred: the optimization was attempted but not performed, try different backends |
| 408 | std::stringstream subgraphMsg; |
| 409 | subgraphMsg << "Re-assigning backends to " << failedSubgraph.GetLayers().size() |
| 410 | << " layers inside sub-graph " << count++; |
Matteo Martincigh | 328d92b | 2019-07-04 17:52:55 +0100 | [diff] [blame] | 411 | ReportWarning(subgraphMsg.str(), errMessages); |
Derek Lamberti | c2fe5fb | 2019-05-08 10:23:08 +0100 | [diff] [blame] | 412 | |
| 413 | OptimizationResult reassignmentResult = AssignBackends(optNetObjPtr, |
| 414 | settingsCopy, |
| 415 | *subgraph, |
| 416 | errMessages); |
| 417 | if (reassignmentResult.m_Error) |
| 418 | { |
| 419 | // Failed to re-assign one of the remaining backends to each layer of the sub-graph |
| 420 | result.m_Error = true; |
| 421 | return result; |
| 422 | } |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 423 | } |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 424 | } |
| 425 | } |
| 426 | } |
| 427 | |
| 428 | return result; |
| 429 | } |
| 430 | |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 431 | bool RequiresCopy(ITensorHandleFactory::FactoryId src, |
| 432 | ITensorHandleFactory::FactoryId dst, |
| 433 | TensorHandleFactoryRegistry& registry) |
| 434 | { |
| 435 | if (src != dst) |
| 436 | { |
| 437 | ITensorHandleFactory* srcFactory = registry.GetFactory(src); |
| 438 | ITensorHandleFactory* dstFactory = registry.GetFactory(dst); |
| 439 | |
Matteo Martincigh | a6539ed | 2019-08-27 13:43:32 +0100 | [diff] [blame] | 440 | if (srcFactory && dstFactory && |
| 441 | (srcFactory->GetExportFlags() & dstFactory->GetImportFlags()) != 0) |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 442 | { |
| 443 | return false; |
| 444 | } |
| 445 | return true; |
| 446 | } |
| 447 | return false; |
| 448 | } |
| 449 | |
| 450 | // Find the handle factory for the input layer which results in fewest required copies. |
| 451 | ITensorHandleFactory::FactoryId CalculateSlotOptionForInput(BackendsMap& backends, |
| 452 | OutputSlot& slot, |
| 453 | TensorHandleFactoryRegistry& registry) |
| 454 | { |
| 455 | Layer& layer = slot.GetOwningLayer(); |
| 456 | BOOST_ASSERT(layer.GetType() == LayerType::Input); |
| 457 | |
| 458 | // Explicitly select the tensorhandle factory for InputLayer because the rules for it are slightly different. It |
| 459 | // doesn't matter which backend it is assigned to because they all use the same implementation, which |
| 460 | // requires Map/Unmap support. This means that, so long as the handle type supports map/unmap semantics, we can |
| 461 | // select a factory with maximum compatibility with the layers connected to the InputLayer. |
| 462 | |
| 463 | // First ensure the from backends can support the TensorHandeAPI |
| 464 | auto frmBackend = backends.find(layer.GetBackendId()); |
| 465 | if (frmBackend == backends.end() || |
| 466 | !frmBackend->second->SupportsTensorAllocatorAPI()) |
| 467 | { |
| 468 | return ITensorHandleFactory::LegacyFactoryId; |
| 469 | } |
| 470 | |
| 471 | // Go through all connections to the output slot and determine the TensorHandleFactory which results in the |
| 472 | // fewest copies. |
| 473 | std::map<ITensorHandleFactory::FactoryId, int> factoryScores; |
| 474 | int topScore = 0; |
| 475 | ITensorHandleFactory::FactoryId topChoice = ITensorHandleFactory::LegacyFactoryId; |
| 476 | |
| 477 | for (auto&& connection : slot.GetConnections()) |
| 478 | { |
| 479 | const Layer& connectedLayer = connection->GetOwningLayer(); |
| 480 | |
| 481 | auto toBackend = backends.find(connectedLayer.GetBackendId()); |
| 482 | BOOST_ASSERT_MSG(toBackend != backends.end(), "Backend id not found for the connected layer"); |
| 483 | |
| 484 | if (!toBackend->second.get()->SupportsTensorAllocatorAPI()) |
| 485 | { |
| 486 | // The destination backend does not support the tensor allocator API, move to the next one |
| 487 | continue; |
| 488 | } |
| 489 | |
| 490 | auto dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences(); |
| 491 | for (auto&& dst : dstPrefs) |
| 492 | { |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 493 | // Input layers use the mem copy workload or import, so the selected factory must |
| 494 | // support either the map/unmap API or Import API |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 495 | ITensorHandleFactory* factory = registry.GetFactory(dst); |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 496 | if (!factory->SupportsMapUnmap() && |
| 497 | !CheckFlag(factory->GetImportFlags(), MemorySource::Malloc)) // Just support cpu mem imports for now |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 498 | { |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 499 | // The current tensor handle factory does not support the map/unmap or import |
| 500 | // strategy, move to the next one |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 501 | continue; |
| 502 | } |
| 503 | |
| 504 | auto it = factoryScores.find(dst); |
| 505 | if (it == factoryScores.end()) |
| 506 | { |
| 507 | // Add new score to the table |
| 508 | factoryScores[dst] = 0; |
| 509 | if (topChoice == ITensorHandleFactory::LegacyFactoryId) |
| 510 | { |
| 511 | topChoice = dst; |
| 512 | } |
| 513 | } |
| 514 | else |
| 515 | { |
| 516 | // Increase the score |
| 517 | factoryScores[dst]++; |
| 518 | |
| 519 | // Track the best option |
| 520 | if (factoryScores[dst] > topScore) |
| 521 | { |
| 522 | topScore = factoryScores[dst]; |
| 523 | topChoice = dst; |
| 524 | } |
| 525 | } |
| 526 | } |
| 527 | } |
| 528 | |
| 529 | return topChoice; |
| 530 | } |
| 531 | |
| 532 | // Find the handle factory for the output layer which results in fewest required copies. |
| 533 | ITensorHandleFactory::FactoryId CalculateSlotOptionForOutput(BackendsMap& backends, |
| 534 | OutputSlot& slot, |
| 535 | TensorHandleFactoryRegistry& registry) |
| 536 | { |
| 537 | return ITensorHandleFactory::DeferredFactoryId; |
| 538 | } |
| 539 | |
| 540 | // For all handle factories supported on the source backend, we wish to find the one which requires the fewest copies |
| 541 | // when considering all connections. |
| 542 | ITensorHandleFactory::FactoryId CalculateSlotOption(BackendsMap& backends, |
| 543 | OutputSlot& outputSlot, |
| 544 | TensorHandleFactoryRegistry& registry) |
| 545 | { |
| 546 | // First ensure the from backends can support the TensorHandeAPI |
| 547 | Layer& layer = outputSlot.GetOwningLayer(); |
| 548 | auto frmBackend = backends.find(layer.GetBackendId()); |
| 549 | if (frmBackend == backends.end() || |
| 550 | !frmBackend->second->SupportsTensorAllocatorAPI()) |
| 551 | { |
| 552 | return ITensorHandleFactory::LegacyFactoryId; |
| 553 | } |
| 554 | |
| 555 | // Connections to Output Layers requires support for map/unmap on the TensorHandle. |
| 556 | bool requiresMapUnmap = false; |
| 557 | for (auto&& connection : outputSlot.GetConnections()) |
| 558 | { |
| 559 | const Layer& connectedLayer = connection->GetOwningLayer(); |
| 560 | if (connectedLayer.GetType() == LayerType::Output) |
| 561 | { |
| 562 | requiresMapUnmap = true; |
| 563 | } |
| 564 | } |
| 565 | |
| 566 | IBackendInternal* srcBackend = frmBackend->second.get(); |
| 567 | auto srcPrefs = srcBackend->GetHandleFactoryPreferences(); |
| 568 | |
| 569 | // Initialize the scores |
| 570 | std::map<ITensorHandleFactory::FactoryId, int> factoryScores; |
| 571 | for (auto&& pref : srcPrefs) |
| 572 | { |
| 573 | if (requiresMapUnmap) // Only consider factories that support map/unmap if required |
| 574 | { |
| 575 | ITensorHandleFactory* factory = registry.GetFactory(pref); |
| 576 | if (!factory->SupportsMapUnmap()) |
| 577 | { |
| 578 | // The current tensor handle factory does not support the map/unmap strategy, move to the next one |
| 579 | continue; |
| 580 | } |
| 581 | } |
| 582 | |
| 583 | auto it = factoryScores.find(pref); |
| 584 | if (it == factoryScores.end()) |
| 585 | { |
| 586 | // Add new score to the table |
| 587 | factoryScores[pref] = 0; |
| 588 | } |
| 589 | } |
| 590 | |
| 591 | // Score each handle factory based on how many times it requires copies on the slot connections |
| 592 | for (auto&& connection : outputSlot.GetConnections()) |
| 593 | { |
| 594 | const Layer& connectedLayer = connection->GetOwningLayer(); |
| 595 | |
| 596 | auto toBackend = backends.find(connectedLayer.GetBackendId()); |
| 597 | BOOST_ASSERT_MSG(toBackend != backends.end(), "Backend id not found for the connected layer"); |
| 598 | |
| 599 | auto dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences(); |
| 600 | for (auto&& src : srcPrefs) |
| 601 | { |
| 602 | if (factoryScores.find(src) == factoryScores.end()) // Don't consider excluded factories |
| 603 | { |
| 604 | continue; |
| 605 | } |
| 606 | |
| 607 | for (auto&& dst : dstPrefs) |
| 608 | { |
| 609 | if (RequiresCopy(src, dst, registry)) |
| 610 | { |
| 611 | // Copy avoided, increase the score |
| 612 | factoryScores[src]++; |
| 613 | break; |
| 614 | } |
| 615 | } |
| 616 | } |
| 617 | } |
| 618 | |
| 619 | // Find the lowest score |
| 620 | int minScore = std::numeric_limits<int>::max(); |
| 621 | for (auto it : factoryScores) |
| 622 | { |
| 623 | minScore = std::min(minScore, it.second); |
| 624 | } |
| 625 | |
| 626 | // Collect factories matching the best(lowest) score |
| 627 | std::vector<ITensorHandleFactory::FactoryId> optimalFactories; |
| 628 | for (auto it : factoryScores) |
| 629 | { |
| 630 | if (it.second == minScore) |
| 631 | { |
| 632 | optimalFactories.push_back(it.first); |
| 633 | } |
| 634 | } |
| 635 | |
| 636 | // For all compatible Factories matching the best score, find the preferred one for the current layer. |
| 637 | for (auto&& srcPref : srcPrefs) |
| 638 | { |
| 639 | for (auto&& comp : optimalFactories) |
| 640 | { |
| 641 | if (comp == srcPref) |
| 642 | { |
| 643 | return comp; |
| 644 | } |
| 645 | } |
| 646 | } |
| 647 | |
| 648 | return ITensorHandleFactory::LegacyFactoryId; |
| 649 | } |
| 650 | |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 651 | EdgeStrategy CalculateEdgeStrategy(BackendsMap& backends, |
| 652 | ITensorHandleFactory::FactoryId srcFactoryId, |
| 653 | const Layer& layer, |
| 654 | const Layer& connectedLayer, |
| 655 | TensorHandleFactoryRegistry& registry) |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 656 | { |
| 657 | auto toBackend = backends.find(connectedLayer.GetBackendId()); |
| 658 | BOOST_ASSERT_MSG(toBackend != backends.end(), "Backend id not found for the connected layer"); |
| 659 | |
| 660 | auto dstPrefs = toBackend->second.get()->GetHandleFactoryPreferences(); |
| 661 | |
| 662 | // Legacy API check for backward compatibility |
| 663 | if (srcFactoryId == ITensorHandleFactory::LegacyFactoryId || dstPrefs.empty()) |
| 664 | { |
| 665 | if (layer.GetBackendId() != connectedLayer.GetBackendId()) |
| 666 | { |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 667 | return EdgeStrategy::CopyToTarget; |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 668 | } |
| 669 | else |
| 670 | { |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 671 | return EdgeStrategy::DirectCompatibility; |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 672 | } |
| 673 | } |
| 674 | |
| 675 | // TensorHandleFactory API present, so perform more sophisticated strategies. |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 676 | // Dst Output layers don't require copy because they use import or map/unmap |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 677 | if (connectedLayer.GetType() == LayerType::Output) |
| 678 | { |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 679 | return EdgeStrategy::DirectCompatibility; |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 680 | } |
| 681 | |
| 682 | // Search for direct match in prefs |
| 683 | for (auto&& pref : dstPrefs) |
| 684 | { |
| 685 | if (pref == srcFactoryId) |
| 686 | { |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 687 | return EdgeStrategy::DirectCompatibility; |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 688 | } |
| 689 | } |
| 690 | |
| 691 | // Search for export/import options |
| 692 | ITensorHandleFactory* srcFactory = registry.GetFactory(srcFactoryId); |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 693 | if (srcFactory->GetExportFlags() != 0) |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 694 | { |
| 695 | for (auto&& pref : dstPrefs) |
| 696 | { |
| 697 | ITensorHandleFactory* dstFactory = registry.GetFactory(pref); |
James Conroy | ffab16f | 2019-11-07 14:37:09 +0000 | [diff] [blame] | 698 | |
| 699 | // Handles some cases where dstFactory is null when Neon memory import is disabled |
| 700 | if (!dstFactory) { |
| 701 | return EdgeStrategy::CopyToTarget; |
| 702 | } |
| 703 | |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 704 | if ((dstFactory->GetImportFlags() & srcFactory->GetExportFlags()) != 0) |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 705 | { |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 706 | return EdgeStrategy::ExportToTarget; |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 707 | } |
| 708 | } |
| 709 | } |
| 710 | |
| 711 | // Search for copy options via map/unmap |
| 712 | if (srcFactory->SupportsMapUnmap()) |
| 713 | { |
| 714 | for (auto&& pref : dstPrefs) |
| 715 | { |
| 716 | ITensorHandleFactory* dstFactory = registry.GetFactory(pref); |
| 717 | if (dstFactory->SupportsMapUnmap()) |
| 718 | { |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 719 | return EdgeStrategy::CopyToTarget; |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 720 | } |
| 721 | } |
| 722 | } |
| 723 | |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 724 | return EdgeStrategy::Undefined; |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 725 | } |
| 726 | |
| 727 | // Select the TensorHandleFactories and the corresponding memory strategy |
| 728 | OptimizationResult SelectTensorHandleStrategy(Graph& optGraph, |
| 729 | BackendsMap& backends, |
| 730 | TensorHandleFactoryRegistry& registry, |
| 731 | Optional<std::vector<std::string>&> errMessages) |
| 732 | { |
| 733 | OptimizationResult result; |
| 734 | |
| 735 | optGraph.ForEachLayer([&backends, ®istry, &result, &errMessages](Layer* layer) |
| 736 | { |
| 737 | BOOST_ASSERT(layer); |
| 738 | |
| 739 | // Lets make sure the backend is in our list of supported backends. Something went wrong during backend |
| 740 | // assignment if this check fails |
| 741 | BOOST_ASSERT(backends.find(layer->GetBackendId()) != backends.end()); |
| 742 | |
| 743 | // Check each output separately |
| 744 | for (unsigned int slotIdx = 0; slotIdx < layer->GetNumOutputSlots(); slotIdx++) |
| 745 | { |
| 746 | OutputSlot& outputSlot = layer->GetOutputSlot(slotIdx); |
| 747 | |
| 748 | ITensorHandleFactory::FactoryId slotOption = ITensorHandleFactory::LegacyFactoryId; |
| 749 | |
| 750 | // Calculate the factory to use which results in the fewest copies being made. |
| 751 | switch(layer->GetType()) |
| 752 | { |
| 753 | case LayerType::Input: |
| 754 | slotOption = CalculateSlotOptionForInput(backends, outputSlot, registry); |
| 755 | break; |
| 756 | case LayerType::Output: |
| 757 | slotOption = CalculateSlotOptionForOutput(backends, outputSlot, registry); |
| 758 | break; |
| 759 | default: |
| 760 | slotOption = CalculateSlotOption(backends, outputSlot, registry); |
| 761 | break; |
| 762 | } |
| 763 | outputSlot.SetTensorHandleFactory(slotOption); |
| 764 | |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 765 | // Now determine the "best" edge strategy for each connection given the slotOption. |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 766 | unsigned int connectionIdx = 0; |
| 767 | for (auto&& connection : outputSlot.GetConnections()) |
| 768 | { |
| 769 | const Layer& connectedLayer = connection->GetOwningLayer(); |
| 770 | |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 771 | EdgeStrategy strategy = CalculateEdgeStrategy(backends, slotOption, *layer, connectedLayer, registry); |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 772 | |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 773 | if (strategy == EdgeStrategy::Undefined) |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 774 | { |
| 775 | result.m_Error = true; |
| 776 | if (errMessages) |
| 777 | { |
| 778 | errMessages.value().emplace_back("Could not find valid strategy required for compatibility" |
| 779 | " between backends."); |
| 780 | } |
| 781 | return; |
| 782 | } |
| 783 | |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 784 | outputSlot.SetEdgeStrategy(connectionIdx, strategy); |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 785 | |
| 786 | connectionIdx++; |
| 787 | } |
| 788 | } |
| 789 | }); |
| 790 | |
| 791 | return result; |
| 792 | } |
| 793 | |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 794 | IOptimizedNetworkPtr Optimize(const INetwork& inNetwork, |
| 795 | const std::vector<BackendId>& backendPreferences, |
| 796 | const IDeviceSpec& deviceSpec, |
| 797 | const OptimizerOptions& options, |
Rob Hughes | 2321443 | 2019-11-05 11:27:36 +0000 | [diff] [blame] | 798 | Optional<std::vector<std::string>&> messages) |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 799 | { |
| 800 | if (backendPreferences.empty()) |
| 801 | { |
| 802 | throw armnn::InvalidArgumentException("Invoked Optimize with no backends specified"); |
| 803 | } |
| 804 | |
| 805 | const Network& network = *boost::polymorphic_downcast<const Network*>(&inNetwork); |
| 806 | std::unique_ptr<Graph> graph = std::make_unique<Graph>(network.GetGraph()); |
| 807 | |
| 808 | auto optNet = IOptimizedNetworkPtr(new OptimizedNetwork(std::move(graph)), &IOptimizedNetwork::Destroy); |
| 809 | |
| 810 | OptimizedNetwork* optNetObjPtr = boost::polymorphic_downcast<OptimizedNetwork*>(optNet.get()); |
| 811 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 812 | // Get the optimized graph |
| 813 | Graph& optGraph = optNetObjPtr->GetGraph(); |
| 814 | |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 815 | // Perform optimisation passes |
| 816 | using namespace optimizations; |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 817 | Optimizer::Pass(optGraph, MakeOptimizations(SquashEqualPermuteSiblings(), |
| 818 | SquashEqualReshapeSiblings(), |
| 819 | OptimizeInversePermutes(), |
| 820 | MovePermuteUp(), |
| 821 | PermuteAsReshape(), |
Nina Drozd | 861985f | 2019-04-18 14:48:51 +0100 | [diff] [blame] | 822 | OptimizeConsecutiveReshapes(), |
Rob Hughes | 3a7d3a7 | 2019-09-24 16:59:56 +0100 | [diff] [blame] | 823 | FoldPadIntoConvolution2d(), |
| 824 | PermuteAndBatchToSpaceAsDepthToSpace())); |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 825 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 826 | // Infer the tensor infos for all output slots. Throws an exception on failure |
| 827 | optGraph.InferTensorInfos(); |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 828 | |
| 829 | // If Fp32 to Fp16 optimization is set convert Fp32 network to Fp16 |
| 830 | if (options.m_ReduceFp32ToFp16) |
| 831 | { |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 832 | Optimizer::Pass(optGraph, MakeOptimizations(Fp32NetworkToFp16Converter())); |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 833 | } |
| 834 | |
| 835 | // Initialize backend settings |
| 836 | BackendSettings backendSettings(backendPreferences, deviceSpec); |
| 837 | if (backendSettings.GetAvailablePreferredBackends().empty()) |
| 838 | { |
| 839 | std::stringstream failureMsg; |
| 840 | failureMsg << "None of the preferred backends " << backendPreferences |
| 841 | << " are supported. Current platform provides " << backendSettings.m_SupportedBackends; |
Rob Hughes | 2321443 | 2019-11-05 11:27:36 +0000 | [diff] [blame] | 842 | ReportError(failureMsg.str(), messages); |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 843 | return IOptimizedNetworkPtr(nullptr, &IOptimizedNetwork::Destroy); |
| 844 | } |
| 845 | |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 846 | // Create a map to temporarily hold initialized backend objects |
| 847 | TensorHandleFactoryRegistry tensorHandleFactoryRegistry; |
| 848 | BackendsMap backends = CreateSupportedBackends(tensorHandleFactoryRegistry, backendSettings); |
| 849 | |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 850 | // Assign an available backend to each layer |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 851 | Graph::Iterator firstLayer = optGraph.begin(); |
| 852 | Graph::Iterator lastLayer = optGraph.end(); |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 853 | OptimizationResult assignBackendsResult = AssignBackends(optNetObjPtr, |
| 854 | backendSettings, |
| 855 | firstLayer, |
| 856 | lastLayer, |
Rob Hughes | 2321443 | 2019-11-05 11:27:36 +0000 | [diff] [blame] | 857 | messages); |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 858 | if (assignBackendsResult.m_Error) |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 859 | { |
| 860 | // Failed to assign a backend to each layer |
jimfly01 | 6b0b53d | 2018-10-08 14:43:01 +0100 | [diff] [blame] | 861 | return IOptimizedNetworkPtr(nullptr, &IOptimizedNetwork::Destroy); |
| 862 | } |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 863 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 864 | Optimizer::Pass(optGraph, MakeOptimizations(OptimizeInverseConversionsFp16(), |
| 865 | OptimizeInverseConversionsFp32())); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 866 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 867 | // Apply the backend-specific optimizations |
| 868 | OptimizationResult backendOptimizationResult = ApplyBackendOptimizations(optNetObjPtr, |
| 869 | backendSettings, |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 870 | backends, |
Rob Hughes | 2321443 | 2019-11-05 11:27:36 +0000 | [diff] [blame] | 871 | messages); |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 872 | if (backendOptimizationResult.m_Error) |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 873 | { |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 874 | // Failed to apply the backend-specific optimizations |
| 875 | return IOptimizedNetworkPtr(nullptr, &IOptimizedNetwork::Destroy); |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 876 | } |
| 877 | |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 878 | // If the debug flag is set, then insert a DebugLayer after each layer |
| 879 | // Doing this after applying the backend optimizations as they might have changed some layers |
| 880 | if (options.m_Debug) |
| 881 | { |
| 882 | Optimizer::Pass(optGraph, MakeOptimizations(InsertDebugLayer())); |
| 883 | } |
| 884 | |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 885 | // Calculate the compatibility strategies for tensor handles |
| 886 | OptimizationResult strategyResult = SelectTensorHandleStrategy(optGraph, |
| 887 | backends, |
| 888 | tensorHandleFactoryRegistry, |
Rob Hughes | 2321443 | 2019-11-05 11:27:36 +0000 | [diff] [blame] | 889 | messages); |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 890 | if (strategyResult.m_Error) |
| 891 | { |
| 892 | // Failed to apply the backend-specific optimizations |
| 893 | return IOptimizedNetworkPtr(nullptr, &IOptimizedNetwork::Destroy); |
| 894 | } |
| 895 | |
| 896 | // Based on the tensor handle strategy determined above, insert copy layers where required. |
Derek Lamberti | f674aa0 | 2019-08-01 15:56:25 +0100 | [diff] [blame] | 897 | optGraph.AddCompatibilityLayers(backends, tensorHandleFactoryRegistry); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 898 | |
| 899 | // Convert constants |
Matteo Martincigh | adddddb | 2019-01-24 14:06:23 +0000 | [diff] [blame] | 900 | Optimizer::Pass(optGraph, MakeOptimizations(ConvertConstantsFloatToHalf())); |
| 901 | Optimizer::Pass(optGraph, MakeOptimizations(ConvertConstantsHalfToFloat())); |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 902 | |
Derek Lamberti | 84da38b | 2019-06-13 11:40:08 +0100 | [diff] [blame] | 903 | // Run backend specific optimizations (deprecated) |
Matteo Martincigh | 4912402 | 2019-01-11 13:25:59 +0000 | [diff] [blame] | 904 | for (auto&& chosenBackend : backendSettings.m_SelectedBackends) |
David Beck | 263e349 | 2018-11-09 14:46:40 +0000 | [diff] [blame] | 905 | { |
| 906 | auto factoryFun = BackendRegistryInstance().GetFactory(chosenBackend); |
| 907 | auto backendPtr = factoryFun(); |
| 908 | BOOST_ASSERT(backendPtr.get() != nullptr); |
| 909 | |
Matteo Martincigh | ed73504 | 2019-05-22 09:42:43 +0100 | [diff] [blame] | 910 | ARMNN_NO_DEPRECATE_WARN_BEGIN |
David Beck | 263e349 | 2018-11-09 14:46:40 +0000 | [diff] [blame] | 911 | auto backendSpecificOptimizations = backendPtr->GetOptimizations(); |
Matteo Martincigh | ed73504 | 2019-05-22 09:42:43 +0100 | [diff] [blame] | 912 | ARMNN_NO_DEPRECATE_WARN_END |
| 913 | |
David Beck | 263e349 | 2018-11-09 14:46:40 +0000 | [diff] [blame] | 914 | if (!backendSpecificOptimizations.empty()) |
| 915 | { |
| 916 | Optimizer::Pass(optNetObjPtr->GetGraph(), backendSpecificOptimizations); |
| 917 | } |
| 918 | } |
| 919 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 920 | return optNet; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 921 | } |
| 922 | |
| 923 | Network::Network() |
Jan Eilers | 99d9d4a | 2019-11-06 10:02:16 +0000 | [diff] [blame^] | 924 | : m_Graph(std::make_unique<Graph>()), |
| 925 | m_Guid(profiling::ProfilingService::Instance().NextGuid()) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 926 | { |
| 927 | } |
| 928 | |
| 929 | Network::~Network() |
| 930 | { |
| 931 | } |
| 932 | |
Jan Eilers | 99d9d4a | 2019-11-06 10:02:16 +0000 | [diff] [blame^] | 933 | Status Network::PrintGraph() |
| 934 | { |
| 935 | m_Graph->Print(); |
| 936 | return Status::Success; |
| 937 | } |
| 938 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 939 | IConnectableLayer* Network::AddInputLayer(LayerBindingId id, const char* name) |
| 940 | { |
| 941 | return m_Graph->AddLayer<InputLayer>(id, name); |
| 942 | } |
| 943 | |
Éanna Ó Catháin | 4e1e136 | 2018-11-12 11:36:34 +0000 | [diff] [blame] | 944 | IConnectableLayer* Network::AddBatchToSpaceNdLayer(const BatchToSpaceNdDescriptor& batchToSpaceNdDescriptor, |
| 945 | const char* name) |
| 946 | { |
| 947 | return m_Graph->AddLayer<BatchToSpaceNdLayer>(batchToSpaceNdDescriptor, name); |
| 948 | } |
| 949 | |
Aron Virginas-Tar | 77bfb5e | 2019-10-16 17:45:38 +0100 | [diff] [blame] | 950 | IConnectableLayer* Network::AddComparisonLayer(const ComparisonDescriptor& comparisonDescriptor, |
| 951 | const char* name) |
| 952 | { |
| 953 | return m_Graph->AddLayer<ComparisonLayer>(comparisonDescriptor, name); |
| 954 | } |
| 955 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 956 | IConnectableLayer* Network::AddFullyConnectedLayerImpl(const FullyConnectedDescriptor& fullyConnectedDescriptor, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 957 | const ConstTensor& weights, |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 958 | const Optional<ConstTensor>& biases, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 959 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 960 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 961 | if (fullyConnectedDescriptor.m_BiasEnabled && !biases.has_value()) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 962 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 963 | throw InvalidArgumentException("AddFullyConnectedLayer: biases cannot be empty"); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 964 | } |
| 965 | |
| 966 | const auto layer = m_Graph->AddLayer<FullyConnectedLayer>(fullyConnectedDescriptor, name); |
| 967 | |
| 968 | layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights); |
| 969 | |
| 970 | if (fullyConnectedDescriptor.m_BiasEnabled) |
| 971 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 972 | layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.value()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 973 | } |
| 974 | |
| 975 | return layer; |
| 976 | } |
| 977 | |
| 978 | IConnectableLayer* Network::AddFullyConnectedLayer(const FullyConnectedDescriptor& fullyConnectedDescriptor, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 979 | const ConstTensor& weights, |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 980 | const Optional<ConstTensor>& biases, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 981 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 982 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 983 | return AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, biases, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 984 | } |
| 985 | |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 986 | IConnectableLayer* Network::AddFullyConnectedLayer(const FullyConnectedDescriptor& fullyConnectedDescriptor, |
| 987 | const ConstTensor& weights, |
| 988 | const char* name) |
| 989 | { |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 990 | Optional<ConstTensor> biases; |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 991 | return AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, biases, name); |
| 992 | } |
| 993 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 994 | IConnectableLayer* Network::AddFullyConnectedLayer(const FullyConnectedDescriptor& fullyConnectedDescriptor, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 995 | const ConstTensor& weights, |
| 996 | const ConstTensor& biases, |
| 997 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 998 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 999 | Optional<ConstTensor> optionalBiases(biases); |
| 1000 | return AddFullyConnectedLayerImpl(fullyConnectedDescriptor, weights, optionalBiases, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1001 | } |
| 1002 | |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1003 | IConnectableLayer* Network::AddConcatLayer(const ConcatDescriptor& concatDescriptor, |
Jim Flynn | 906f946 | 2019-05-10 13:55:21 +0100 | [diff] [blame] | 1004 | const char* name) |
| 1005 | { |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1006 | return m_Graph->AddLayer<ConcatLayer>(concatDescriptor, name); |
Jim Flynn | 906f946 | 2019-05-10 13:55:21 +0100 | [diff] [blame] | 1007 | } |
| 1008 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1009 | IConnectableLayer* Network::AddConvolution2dLayerImpl(const Convolution2dDescriptor& convolution2dDescriptor, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1010 | const ConstTensor& weights, |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1011 | const Optional<ConstTensor>& biases, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1012 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1013 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1014 | if (convolution2dDescriptor.m_BiasEnabled && !biases.has_value()) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1015 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1016 | throw InvalidArgumentException("AddConvolution2dLayer: biases cannot be empty"); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1017 | } |
| 1018 | |
| 1019 | const auto layer = m_Graph->AddLayer<Convolution2dLayer>(convolution2dDescriptor, name); |
| 1020 | |
| 1021 | layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights); |
| 1022 | |
| 1023 | if (convolution2dDescriptor.m_BiasEnabled) |
| 1024 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1025 | layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.value()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1026 | } |
| 1027 | |
| 1028 | return layer; |
| 1029 | } |
| 1030 | |
| 1031 | IConnectableLayer* Network::AddConvolution2dLayer(const Convolution2dDescriptor& convolution2dDescriptor, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1032 | const ConstTensor& weights, |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1033 | const Optional<ConstTensor>& biases, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1034 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1035 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1036 | return AddConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1037 | } |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1038 | |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1039 | IConnectableLayer* Network::AddConvolution2dLayer(const Convolution2dDescriptor& convolution2dDescriptor, |
| 1040 | const ConstTensor& weights, |
| 1041 | const char* name) |
| 1042 | { |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 1043 | Optional<ConstTensor> biases; |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1044 | return AddConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name); |
| 1045 | } |
| 1046 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1047 | IConnectableLayer* Network::AddConvolution2dLayer(const Convolution2dDescriptor& convolution2dDescriptor, |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1048 | const ConstTensor& weights, |
| 1049 | const ConstTensor& biases, |
| 1050 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1051 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1052 | Optional<ConstTensor> optionalBiases(biases); |
| 1053 | return AddConvolution2dLayerImpl(convolution2dDescriptor, weights, optionalBiases, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1054 | } |
| 1055 | |
| 1056 | IConnectableLayer* Network::AddDepthwiseConvolution2dLayerImpl( |
| 1057 | const DepthwiseConvolution2dDescriptor& convolution2dDescriptor, |
| 1058 | const ConstTensor& weights, |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1059 | const Optional<ConstTensor>& biases, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1060 | const char* name) |
| 1061 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1062 | if (convolution2dDescriptor.m_BiasEnabled && !biases.has_value()) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1063 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1064 | throw InvalidArgumentException("AddDepthwiseConvolution2dLayer: biases cannot be empty"); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1065 | } |
| 1066 | |
Matteo Martincigh | 3d6898c | 2019-01-15 16:11:44 +0000 | [diff] [blame] | 1067 | const auto layer = m_Graph->AddLayer<DepthwiseConvolution2dLayer>(convolution2dDescriptor, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1068 | |
| 1069 | layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights); |
| 1070 | |
| 1071 | if (convolution2dDescriptor.m_BiasEnabled) |
| 1072 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1073 | layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.value()); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1074 | } |
| 1075 | |
| 1076 | return layer; |
| 1077 | } |
| 1078 | |
Aron Virginas-Tar | dd6247f | 2019-09-19 14:31:17 +0100 | [diff] [blame] | 1079 | IConnectableLayer* Network::AddDepthToSpaceLayer(const DepthToSpaceDescriptor& depthToSpaceDescriptor, |
| 1080 | const char* name) |
| 1081 | { |
| 1082 | return m_Graph->AddLayer<DepthToSpaceLayer>(depthToSpaceDescriptor, name); |
| 1083 | } |
| 1084 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1085 | IConnectableLayer* Network::AddDepthwiseConvolution2dLayer( |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1086 | const DepthwiseConvolution2dDescriptor& convolution2dDescriptor, |
| 1087 | const ConstTensor& weights, |
| 1088 | const Optional<ConstTensor>& biases, |
| 1089 | const char* name) |
| 1090 | { |
| 1091 | return AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name); |
| 1092 | } |
| 1093 | |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1094 | IConnectableLayer* Network::AddDepthwiseConvolution2dLayer( |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1095 | const DepthwiseConvolution2dDescriptor& convolution2dDescriptor, |
| 1096 | const ConstTensor& weights, |
| 1097 | const char* name) |
| 1098 | { |
Matteo Martincigh | fc598e1 | 2019-05-14 10:36:13 +0100 | [diff] [blame] | 1099 | Optional<ConstTensor> biases; |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1100 | return AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, biases, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1101 | } |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1102 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1103 | IConnectableLayer* Network::AddDepthwiseConvolution2dLayer( |
| 1104 | const DepthwiseConvolution2dDescriptor& convolution2dDescriptor, |
| 1105 | const ConstTensor& weights, |
| 1106 | const ConstTensor& biases, |
| 1107 | const char* name) |
| 1108 | { |
Aron Virginas-Tar | ad40270 | 2019-02-22 17:03:44 +0000 | [diff] [blame] | 1109 | Optional<ConstTensor> optionalBiases(biases); |
| 1110 | return AddDepthwiseConvolution2dLayerImpl(convolution2dDescriptor, weights, optionalBiases, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1111 | } |
| 1112 | |
Narumol Prangnawarat | 94dd5d8 | 2019-01-23 18:06:26 +0000 | [diff] [blame] | 1113 | IConnectableLayer* Network::AddDetectionPostProcessLayer(const armnn::DetectionPostProcessDescriptor& descriptor, |
Narumol Prangnawarat | 6d302bf | 2019-02-04 11:46:26 +0000 | [diff] [blame] | 1114 | const ConstTensor& anchors, const char* name) |
Narumol Prangnawarat | 94dd5d8 | 2019-01-23 18:06:26 +0000 | [diff] [blame] | 1115 | { |
Narumol Prangnawarat | 6d302bf | 2019-02-04 11:46:26 +0000 | [diff] [blame] | 1116 | const auto layer = m_Graph->AddLayer<DetectionPostProcessLayer>(descriptor, name); |
| 1117 | |
| 1118 | layer->m_Anchors = std::make_unique<ScopedCpuTensorHandle>(anchors); |
| 1119 | |
| 1120 | return layer; |
Narumol Prangnawarat | 94dd5d8 | 2019-01-23 18:06:26 +0000 | [diff] [blame] | 1121 | } |
| 1122 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1123 | IConnectableLayer* Network::AddPermuteLayer(const PermuteDescriptor& permuteDescriptor, |
| 1124 | const char* name) |
| 1125 | { |
| 1126 | return m_Graph->AddLayer<PermuteLayer>(permuteDescriptor, name); |
| 1127 | } |
| 1128 | |
| 1129 | IConnectableLayer* Network::AddPooling2dLayer(const Pooling2dDescriptor& pooling2dDescriptor, |
| 1130 | const char* name) |
| 1131 | { |
| 1132 | return m_Graph->AddLayer<Pooling2dLayer>(pooling2dDescriptor, name); |
| 1133 | } |
| 1134 | |
| 1135 | IConnectableLayer* Network::AddActivationLayer(const ActivationDescriptor& activationDescriptor, |
| 1136 | const char* name) |
| 1137 | { |
| 1138 | return m_Graph->AddLayer<ActivationLayer>(activationDescriptor, name); |
| 1139 | } |
| 1140 | |
Nikhil Raj | ee391d5 | 2019-09-05 17:50:44 +0100 | [diff] [blame] | 1141 | IConnectableLayer* Network::AddArgMinMaxLayer(const ArgMinMaxDescriptor& argMinMaxDescriptor, |
| 1142 | const char* name) |
| 1143 | { |
| 1144 | return m_Graph->AddLayer<ArgMinMaxLayer>(argMinMaxDescriptor, name); |
| 1145 | } |
| 1146 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1147 | IConnectableLayer* Network::AddNormalizationLayer(const NormalizationDescriptor& |
| 1148 | normalizationDescriptor, |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1149 | const char* name) |
| 1150 | { |
| 1151 | return m_Graph->AddLayer<NormalizationLayer>(normalizationDescriptor, name); |
| 1152 | } |
| 1153 | |
Aron Virginas-Tar | 636ab40 | 2019-09-16 14:27:45 +0100 | [diff] [blame] | 1154 | IConnectableLayer* Network::AddSliceLayer(const SliceDescriptor& sliceDescriptor, const char* name) |
| 1155 | { |
| 1156 | return m_Graph->AddLayer<SliceLayer>(sliceDescriptor, name); |
| 1157 | } |
| 1158 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1159 | IConnectableLayer* Network::AddSoftmaxLayer(const SoftmaxDescriptor& softmaxDescriptor, |
| 1160 | const char* name) |
| 1161 | { |
| 1162 | return m_Graph->AddLayer<SoftmaxLayer>(softmaxDescriptor, name); |
| 1163 | } |
| 1164 | |
| 1165 | IConnectableLayer* Network::AddSplitterLayer(const ViewsDescriptor& splitterDescriptor, |
| 1166 | const char* name) |
| 1167 | { |
| 1168 | return m_Graph->AddLayer<SplitterLayer>(splitterDescriptor, name); |
| 1169 | } |
| 1170 | |
Nattapat Chaimanowong | 5a4304a | 2018-11-28 10:44:37 +0000 | [diff] [blame] | 1171 | IConnectableLayer* Network::AddMaximumLayer(const char* name) |
| 1172 | { |
| 1173 | return m_Graph->AddLayer<MaximumLayer>(name); |
| 1174 | } |
| 1175 | |
Éanna Ó Catháin | 20e5880 | 2018-12-04 10:29:06 +0000 | [diff] [blame] | 1176 | IConnectableLayer* Network::AddMinimumLayer(const char* name) |
| 1177 | { |
| 1178 | return m_Graph->AddLayer<MinimumLayer>(name); |
| 1179 | } |
| 1180 | |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1181 | IConnectableLayer* Network::AddMergerLayer(const MergerDescriptor& mergerDescriptor, |
Jim Flynn | 906f946 | 2019-05-10 13:55:21 +0100 | [diff] [blame] | 1182 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1183 | { |
Jim Flynn | e242f2d | 2019-05-22 14:24:13 +0100 | [diff] [blame] | 1184 | return AddConcatLayer(mergerDescriptor, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1185 | } |
| 1186 | |
Kevin May | 868eb14 | 2019-09-04 17:29:31 +0100 | [diff] [blame] | 1187 | IConnectableLayer* Network::AddAbsLayer(const char * name) |
| 1188 | { |
| 1189 | return m_Graph->AddLayer<AbsLayer>(name); |
| 1190 | } |
| 1191 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1192 | IConnectableLayer* Network::AddAdditionLayer(const char* name) |
| 1193 | { |
| 1194 | return m_Graph->AddLayer<AdditionLayer>(name); |
| 1195 | } |
| 1196 | |
| 1197 | IConnectableLayer* Network::AddMultiplicationLayer(const char* name) |
| 1198 | { |
| 1199 | return m_Graph->AddLayer<MultiplicationLayer>(name); |
| 1200 | } |
| 1201 | |
| 1202 | IConnectableLayer* Network::AddOutputLayer(LayerBindingId id, const char* name) |
| 1203 | { |
| 1204 | return m_Graph->AddLayer<OutputLayer>(id, name); |
| 1205 | } |
| 1206 | |
| 1207 | IConnectableLayer* Network::AddBatchNormalizationLayer(const BatchNormalizationDescriptor& desc, |
| 1208 | const ConstTensor& mean, |
| 1209 | const ConstTensor& variance, |
| 1210 | const ConstTensor& beta, |
| 1211 | const ConstTensor& gamma, |
| 1212 | const char* name) |
| 1213 | { |
| 1214 | const auto layer = m_Graph->AddLayer<BatchNormalizationLayer>(desc, name); |
| 1215 | |
| 1216 | layer->m_Mean = std::make_unique<ScopedCpuTensorHandle>(mean); |
| 1217 | layer->m_Variance = std::make_unique<ScopedCpuTensorHandle>(variance); |
| 1218 | layer->m_Beta = std::make_unique<ScopedCpuTensorHandle>(beta); |
| 1219 | layer->m_Gamma = std::make_unique<ScopedCpuTensorHandle>(gamma); |
| 1220 | |
| 1221 | return layer; |
| 1222 | } |
| 1223 | |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 1224 | IConnectableLayer* Network::AddResizeBilinearLayer(const ResizeBilinearDescriptor& descriptor, |
| 1225 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1226 | { |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 1227 | ResizeDescriptor resizeDescriptor; |
| 1228 | resizeDescriptor.m_Method = ResizeMethod::Bilinear; |
| 1229 | resizeDescriptor.m_DataLayout = descriptor.m_DataLayout; |
| 1230 | resizeDescriptor.m_TargetWidth = descriptor.m_TargetWidth; |
| 1231 | resizeDescriptor.m_TargetHeight = descriptor.m_TargetHeight; |
| 1232 | |
| 1233 | return m_Graph->AddLayer<ResizeLayer>(resizeDescriptor, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1234 | } |
| 1235 | |
Teresa Charlin | a9075df | 2019-06-27 15:41:57 +0100 | [diff] [blame] | 1236 | IConnectableLayer* Network::AddResizeLayer(const ResizeDescriptor& |
| 1237 | resizeDescriptor, const char* name) |
| 1238 | { |
Aron Virginas-Tar | 169d2f1 | 2019-07-01 19:01:44 +0100 | [diff] [blame] | 1239 | return m_Graph->AddLayer<ResizeLayer>(resizeDescriptor, name); |
Teresa Charlin | a9075df | 2019-06-27 15:41:57 +0100 | [diff] [blame] | 1240 | } |
| 1241 | |
Kevin May | ce5045a | 2019-10-02 14:07:47 +0100 | [diff] [blame] | 1242 | IConnectableLayer* Network::AddInstanceNormalizationLayer(const InstanceNormalizationDescriptor& desc, |
| 1243 | const char* name) |
| 1244 | { |
| 1245 | return m_Graph->AddLayer<InstanceNormalizationLayer>(desc, name); |
| 1246 | } |
| 1247 | |
Matteo Martincigh | bcd3c85 | 2018-09-28 14:14:12 +0100 | [diff] [blame] | 1248 | IConnectableLayer* Network::AddL2NormalizationLayer(const L2NormalizationDescriptor& desc, |
| 1249 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1250 | { |
Matteo Martincigh | bcd3c85 | 2018-09-28 14:14:12 +0100 | [diff] [blame] | 1251 | return m_Graph->AddLayer<L2NormalizationLayer>(desc, name); |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1252 | } |
| 1253 | |
Aron Virginas-Tar | f982dea | 2019-10-11 14:07:53 +0100 | [diff] [blame] | 1254 | IConnectableLayer* Network::AddLogSoftmaxLayer(const LogSoftmaxDescriptor& desc, |
| 1255 | const char* name) |
| 1256 | { |
| 1257 | return m_Graph->AddLayer<LogSoftmaxLayer>(desc, name); |
| 1258 | } |
| 1259 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1260 | IConnectableLayer* Network::AddConstantLayer(const ConstTensor& input, const char* name) |
| 1261 | { |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1262 | auto layer = m_Graph->AddLayer<ConstantLayer>(name); |
| 1263 | |
| 1264 | layer->m_LayerOutput = std::make_unique<ScopedCpuTensorHandle>(input); |
| 1265 | |
| 1266 | return layer; |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1267 | } |
| 1268 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1269 | IConnectableLayer* Network::AddReshapeLayer(const ReshapeDescriptor& reshapeDescriptor, |
| 1270 | const char* name) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1271 | { |
| 1272 | return m_Graph->AddLayer<ReshapeLayer>(reshapeDescriptor, name); |
| 1273 | } |
| 1274 | |
Nattapat Chaimanowong | 207ef9a | 2018-11-02 10:57:25 +0000 | [diff] [blame] | 1275 | IConnectableLayer* Network::AddSpaceToBatchNdLayer(const SpaceToBatchNdDescriptor& spaceToBatchNdDescriptor, |
| 1276 | const char* name) |
| 1277 | { |
| 1278 | return m_Graph->AddLayer<SpaceToBatchNdLayer>(spaceToBatchNdDescriptor, name); |
| 1279 | } |
| 1280 | |
Aron Virginas-Tar | 972af15 | 2019-06-11 14:14:03 +0100 | [diff] [blame] | 1281 | IConnectableLayer* Network::AddSpaceToDepthLayer(const SpaceToDepthDescriptor& spaceToDepthDescriptor, |
| 1282 | const char* name) |
| 1283 | { |
| 1284 | return m_Graph->AddLayer<SpaceToDepthLayer>(spaceToDepthDescriptor, name); |
| 1285 | } |
| 1286 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1287 | IConnectableLayer* Network::AddFloorLayer(const char* name) |
| 1288 | { |
| 1289 | return m_Graph->AddLayer<FloorLayer>(name); |
| 1290 | } |
| 1291 | |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1292 | IConnectableLayer* Network::AddLstmLayer(const LstmDescriptor& descriptor, |
| 1293 | const LstmInputParams& params, |
| 1294 | const char* name) |
| 1295 | { |
| 1296 | const auto layer = m_Graph->AddLayer<LstmLayer>(descriptor, name); |
| 1297 | |
| 1298 | //Lstm Basic Parameters |
| 1299 | layer->m_BasicParameters.m_InputToForgetWeights = |
| 1300 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToForgetWeights)); |
| 1301 | layer->m_BasicParameters.m_InputToCellWeights = |
| 1302 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToCellWeights)); |
| 1303 | layer->m_BasicParameters.m_InputToOutputWeights = |
| 1304 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToOutputWeights)); |
| 1305 | layer->m_BasicParameters.m_RecurrentToForgetWeights = |
| 1306 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToForgetWeights)); |
| 1307 | layer->m_BasicParameters.m_RecurrentToCellWeights = |
| 1308 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToCellWeights)); |
| 1309 | layer->m_BasicParameters.m_RecurrentToOutputWeights = |
| 1310 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToOutputWeights)); |
| 1311 | layer->m_BasicParameters.m_ForgetGateBias = |
| 1312 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_ForgetGateBias)); |
| 1313 | layer->m_BasicParameters.m_CellBias = |
| 1314 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellBias)); |
| 1315 | layer->m_BasicParameters.m_OutputGateBias = |
| 1316 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_OutputGateBias)); |
| 1317 | |
| 1318 | //Lstm Cifg parameters |
| 1319 | if(!descriptor.m_CifgEnabled) |
| 1320 | { |
| 1321 | if(params.m_InputToInputWeights == nullptr) |
| 1322 | { |
| 1323 | throw InvalidArgumentException("AddLstmLayer: Input To Input Weights cannot be NULL"); |
| 1324 | } |
| 1325 | if(params.m_RecurrentToInputWeights == nullptr) |
| 1326 | { |
| 1327 | throw InvalidArgumentException( |
| 1328 | "AddLstmLayer: Recurrent To Input Weights cannot be NULL"); |
| 1329 | } |
| 1330 | if(params.m_InputGateBias == nullptr) |
| 1331 | { |
| 1332 | throw InvalidArgumentException("AddLstmLayer: Input Gate Bias cannot be NULL"); |
| 1333 | } |
| 1334 | layer->m_CifgParameters.m_InputToInputWeights = |
| 1335 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToInputWeights)); |
| 1336 | layer->m_CifgParameters.m_RecurrentToInputWeights = |
| 1337 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToInputWeights)); |
| 1338 | // In the VTS tests, cell-to-input weights may be null, even if the other CIFG params are not. |
| 1339 | if(params.m_CellToInputWeights != nullptr) |
| 1340 | { |
| 1341 | layer->m_CifgParameters.m_CellToInputWeights = |
| 1342 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToInputWeights)); |
| 1343 | } |
| 1344 | layer->m_CifgParameters.m_InputGateBias = |
| 1345 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputGateBias)); |
| 1346 | } |
| 1347 | |
| 1348 | //Lstm projection parameters |
| 1349 | if(descriptor.m_ProjectionEnabled) |
| 1350 | { |
| 1351 | if(params.m_ProjectionWeights == nullptr) |
| 1352 | { |
| 1353 | throw InvalidArgumentException("AddLstmLayer: Projection Weights cannot be NULL"); |
| 1354 | } |
| 1355 | layer->m_ProjectionParameters.m_ProjectionWeights = |
| 1356 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_ProjectionWeights)); |
| 1357 | if(params.m_ProjectionBias != nullptr) |
| 1358 | { |
| 1359 | layer->m_ProjectionParameters.m_ProjectionBias = |
| 1360 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_ProjectionBias)); |
| 1361 | } |
| 1362 | } |
| 1363 | |
| 1364 | //Lstm Peephole params |
| 1365 | if(descriptor.m_PeepholeEnabled) |
| 1366 | { |
| 1367 | if(params.m_CellToForgetWeights == nullptr) |
| 1368 | { |
| 1369 | throw InvalidArgumentException("AddLstmLayer: Cell To Forget Weights cannot be NULL"); |
| 1370 | } |
| 1371 | if(params.m_CellToOutputWeights == nullptr) |
| 1372 | { |
| 1373 | throw InvalidArgumentException("AddLstmLayer: Cell To Output Weights cannot be NULL"); |
| 1374 | } |
| 1375 | layer->m_PeepholeParameters.m_CellToForgetWeights = |
| 1376 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToForgetWeights)); |
| 1377 | layer->m_PeepholeParameters.m_CellToOutputWeights = |
| 1378 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToOutputWeights)); |
| 1379 | } |
Jan Eilers | f8c6297 | 2019-07-17 11:07:49 +0100 | [diff] [blame] | 1380 | |
| 1381 | //Lstm Layer Normalization params |
| 1382 | if(descriptor.m_LayerNormEnabled) |
| 1383 | { |
| 1384 | if(!descriptor.m_CifgEnabled) |
| 1385 | { |
| 1386 | if(params.m_InputLayerNormWeights == nullptr) |
| 1387 | { |
| 1388 | throw InvalidArgumentException("AddLstmLayer: Input layer normalization weights cannot be NULL"); |
| 1389 | } |
| 1390 | layer->m_LayerNormParameters.m_InputLayerNormWeights = |
| 1391 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputLayerNormWeights)); |
| 1392 | } |
| 1393 | |
| 1394 | if(params.m_ForgetLayerNormWeights == nullptr) |
| 1395 | { |
| 1396 | throw InvalidArgumentException("AddLstmLayer: Forget layer normalization weights cannot be NULL"); |
| 1397 | } |
| 1398 | if(params.m_CellLayerNormWeights == nullptr) |
| 1399 | { |
| 1400 | throw InvalidArgumentException("AddLstmLayer: Cell layer normalization weights cannot be NULL"); |
| 1401 | } |
| 1402 | if(params.m_OutputLayerNormWeights == nullptr) |
| 1403 | { |
| 1404 | throw InvalidArgumentException("AddLstmLayer: Output layer normalization weights cannot be NULL"); |
| 1405 | } |
| 1406 | layer->m_LayerNormParameters.m_ForgetLayerNormWeights = |
| 1407 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_ForgetLayerNormWeights)); |
| 1408 | layer->m_LayerNormParameters.m_CellLayerNormWeights = |
| 1409 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellLayerNormWeights)); |
| 1410 | layer->m_LayerNormParameters.m_OutputLayerNormWeights = |
| 1411 | std::make_unique<ScopedCpuTensorHandle>(*(params.m_OutputLayerNormWeights)); |
| 1412 | } |
telsoa01 | c577f2c | 2018-08-31 09:22:23 +0100 | [diff] [blame] | 1413 | return layer; |
| 1414 | } |
| 1415 | |
Francis Murtagh | e7a86a4 | 2018-08-29 12:42:10 +0100 | [diff] [blame] | 1416 | IConnectableLayer* Network::AddDivisionLayer(const char* name) |
| 1417 | { |
| 1418 | return m_Graph->AddLayer<DivisionLayer>(name); |
| 1419 | } |
| 1420 | |
David Beck | 1952622 | 2018-09-12 16:00:08 +0100 | [diff] [blame] | 1421 | IConnectableLayer* Network::AddSubtractionLayer(const char* name) |
| 1422 | { |
| 1423 | return m_Graph->AddLayer<SubtractionLayer>(name); |
| 1424 | } |
| 1425 | |
narpra01 | 32b9046 | 2018-09-13 11:07:48 +0100 | [diff] [blame] | 1426 | IConnectableLayer* Network::AddMeanLayer(const MeanDescriptor& meanDescriptor, const char* name) |
| 1427 | { |
| 1428 | return m_Graph->AddLayer<MeanLayer>(meanDescriptor,name); |
| 1429 | } |
| 1430 | |
Mohamed Nour Abouelseoud | 5662c20 | 2018-09-24 13:30:09 +0100 | [diff] [blame] | 1431 | IConnectableLayer* Network::AddPadLayer(const PadDescriptor& padDescriptor, const char* name) |
| 1432 | { |
| 1433 | return m_Graph->AddLayer<PadLayer>(padDescriptor,name); |
| 1434 | } |
| 1435 | |
Derek Lamberti | a9cca6a | 2019-03-25 15:41:58 +0000 | [diff] [blame] | 1436 | IConnectableLayer *Network::AddQuantizeLayer(const char *name) |
| 1437 | { |
| 1438 | return m_Graph->AddLayer<QuantizeLayer>(name); |
| 1439 | } |
| 1440 | |
Nattapat Chaimanowong | e4294fd | 2019-03-28 09:56:53 +0000 | [diff] [blame] | 1441 | IConnectableLayer* Network::AddDequantizeLayer(const char* name) |
| 1442 | { |
| 1443 | return m_Graph->AddLayer<DequantizeLayer>(name); |
| 1444 | } |
| 1445 | |
Conor Kennedy | 430b5d8 | 2018-11-14 15:28:28 +0000 | [diff] [blame] | 1446 | IConnectableLayer* Network::AddStridedSliceLayer(const StridedSliceDescriptor& stridedSliceDescriptor, |
| 1447 | const char* name) |
| 1448 | { |
| 1449 | return m_Graph->AddLayer<StridedSliceLayer>(stridedSliceDescriptor, name); |
| 1450 | } |
| 1451 | |
Matteo Martincigh | 59a950c | 2018-12-13 12:48:25 +0000 | [diff] [blame] | 1452 | IConnectableLayer* Network::AddGreaterLayer(const char* name) |
| 1453 | { |
Aron Virginas-Tar | 77bfb5e | 2019-10-16 17:45:38 +0100 | [diff] [blame] | 1454 | return AddComparisonLayer(ComparisonDescriptor(ComparisonOperation::Greater), name); |
Matteo Martincigh | 59a950c | 2018-12-13 12:48:25 +0000 | [diff] [blame] | 1455 | } |
| 1456 | |
FrancisMurtagh | 2099595 | 2018-12-17 12:11:36 +0000 | [diff] [blame] | 1457 | IConnectableLayer* Network::AddEqualLayer(const char* name) |
| 1458 | { |
Aron Virginas-Tar | 77bfb5e | 2019-10-16 17:45:38 +0100 | [diff] [blame] | 1459 | return AddComparisonLayer(ComparisonDescriptor(ComparisonOperation::Equal), name); |
FrancisMurtagh | 2099595 | 2018-12-17 12:11:36 +0000 | [diff] [blame] | 1460 | } |
| 1461 | |
Mohamed Nour Abouelseoud | a1d3c6a | 2018-12-27 12:39:16 +0000 | [diff] [blame] | 1462 | IConnectableLayer* Network::AddRsqrtLayer(const char * name) |
| 1463 | { |
| 1464 | return m_Graph->AddLayer<RsqrtLayer>(name); |
| 1465 | } |
| 1466 | |
narpra01 | b89b05f | 2019-01-16 09:53:09 +0000 | [diff] [blame] | 1467 | IConnectableLayer* Network::AddGatherLayer(const char* name) |
| 1468 | { |
| 1469 | return m_Graph->AddLayer<GatherLayer>(name); |
| 1470 | } |
| 1471 | |
Nattapat Chaimanowong | 1f88630 | 2019-04-05 13:37:19 +0100 | [diff] [blame] | 1472 | IConnectableLayer* Network::AddMergeLayer(const char* name) |
| 1473 | { |
| 1474 | return m_Graph->AddLayer<MergeLayer>(name); |
| 1475 | } |
| 1476 | |
Sadik Armagan | eff363d | 2019-04-05 15:25:46 +0100 | [diff] [blame] | 1477 | IConnectableLayer* Network::AddSwitchLayer(const char* name) |
| 1478 | { |
| 1479 | return m_Graph->AddLayer<SwitchLayer>(name); |
| 1480 | } |
| 1481 | |
Matteo Martincigh | 0e406ee | 2019-06-12 15:42:18 +0100 | [diff] [blame] | 1482 | IConnectableLayer* Network::AddPreluLayer(const char* name) |
| 1483 | { |
| 1484 | return m_Graph->AddLayer<PreluLayer>(name); |
| 1485 | } |
| 1486 | |
Aron Virginas-Tar | 639fb04 | 2019-06-20 14:28:19 +0100 | [diff] [blame] | 1487 | IConnectableLayer* Network::AddTransposeConvolution2dLayer(const TransposeConvolution2dDescriptor& descriptor, |
| 1488 | const ConstTensor& weights, |
| 1489 | const Optional<ConstTensor>& biases, |
| 1490 | const char* name) |
| 1491 | { |
| 1492 | if (descriptor.m_BiasEnabled && !biases.has_value()) |
| 1493 | { |
| 1494 | throw InvalidArgumentException("AddTransposeConvolution2dLayer: Biases cannot be empty"); |
| 1495 | } |
| 1496 | |
| 1497 | const auto layer = m_Graph->AddLayer<TransposeConvolution2dLayer>(descriptor, name); |
| 1498 | |
| 1499 | layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights); |
| 1500 | |
| 1501 | if (descriptor.m_BiasEnabled) |
| 1502 | { |
| 1503 | layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.value()); |
| 1504 | } |
| 1505 | |
| 1506 | return layer; |
| 1507 | } |
| 1508 | |
Matthew Jackson | 2b8c1da | 2019-07-04 14:59:16 +0100 | [diff] [blame] | 1509 | IConnectableLayer* Network::AddStackLayer(const StackDescriptor& stackDescriptor, |
| 1510 | const char* name) |
| 1511 | { |
| 1512 | return m_Graph->AddLayer<StackLayer>(stackDescriptor, name); |
| 1513 | } |
| 1514 | |
Derek Lamberti | 013c390 | 2019-10-21 10:46:16 +0100 | [diff] [blame] | 1515 | |
| 1516 | IConnectableLayer* Network::AddStandInLayer(const StandInDescriptor& desc, |
| 1517 | const char* name) |
| 1518 | { |
| 1519 | return m_Graph->AddLayer<StandInLayer>(desc, name); |
| 1520 | } |
| 1521 | |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1522 | IConnectableLayer* Network::AddQuantizedLstmLayer(const QuantizedLstmInputParams& params, |
| 1523 | const char* name) |
| 1524 | { |
| 1525 | const auto layer = m_Graph->AddLayer<QuantizedLstmLayer>(name); |
| 1526 | |
| 1527 | // InputToX weights |
| 1528 | layer->m_QuantizedLstmParameters.m_InputToInputWeights = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1529 | std::make_unique<ScopedCpuTensorHandle>(params.GetInputToInputWeights()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1530 | layer->m_QuantizedLstmParameters.m_InputToForgetWeights = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1531 | std::make_unique<ScopedCpuTensorHandle>(params.GetInputToForgetWeights()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1532 | layer->m_QuantizedLstmParameters.m_InputToCellWeights = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1533 | std::make_unique<ScopedCpuTensorHandle>(params.GetInputToCellWeights()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1534 | layer->m_QuantizedLstmParameters.m_InputToOutputWeights = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1535 | std::make_unique<ScopedCpuTensorHandle>(params.GetInputToOutputWeights()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1536 | |
| 1537 | // RecurrentToX weights |
| 1538 | layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1539 | std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToInputWeights()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1540 | layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1541 | std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToForgetWeights()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1542 | layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1543 | std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToCellWeights()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1544 | layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1545 | std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToOutputWeights()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1546 | |
| 1547 | // Bias |
| 1548 | layer->m_QuantizedLstmParameters.m_InputGateBias = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1549 | std::make_unique<ScopedCpuTensorHandle>(params.GetInputGateBias()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1550 | layer->m_QuantizedLstmParameters.m_ForgetGateBias = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1551 | std::make_unique<ScopedCpuTensorHandle>(params.GetForgetGateBias()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1552 | layer->m_QuantizedLstmParameters.m_CellBias = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1553 | std::make_unique<ScopedCpuTensorHandle>(params.GetCellBias()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1554 | layer->m_QuantizedLstmParameters.m_OutputGateBias = |
Francis Murtagh | bb590b4 | 2019-08-14 09:51:36 +0100 | [diff] [blame] | 1555 | std::make_unique<ScopedCpuTensorHandle>(params.GetOutputGateBias()); |
James Conroy | ee18dc8 | 2019-07-17 11:27:46 +0100 | [diff] [blame] | 1556 | |
| 1557 | return layer; |
| 1558 | } |
| 1559 | |
Mike Kelly | 8c1701a | 2019-02-11 17:01:27 +0000 | [diff] [blame] | 1560 | void Network::Accept(ILayerVisitor& visitor) const |
| 1561 | { |
| 1562 | for (auto layer : GetGraph()) |
| 1563 | { |
| 1564 | layer->Accept(visitor); |
| 1565 | }; |
| 1566 | } |
| 1567 | |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1568 | OptimizedNetwork::OptimizedNetwork(std::unique_ptr<Graph> graph) |
Jan Eilers | 99d9d4a | 2019-11-06 10:02:16 +0000 | [diff] [blame^] | 1569 | : m_Graph(std::move(graph)), |
| 1570 | m_Guid(profiling::ProfilingService::Instance().NextGuid()) |
telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame] | 1571 | { |
| 1572 | } |
| 1573 | |
| 1574 | OptimizedNetwork::~OptimizedNetwork() |
| 1575 | { |
| 1576 | } |
| 1577 | |
| 1578 | } // namespace armnn |