ArmNN
 23.02
RefWorkloadFactory.cpp
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1 //
2 // Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 #include <Layer.hpp>
10 #include "RefWorkloadFactory.hpp"
11 #include "RefBackendId.hpp"
13 #include "RefTensorHandle.hpp"
14 
15 
16 namespace armnn
17 {
18 
19 namespace
20 {
21 static const BackendId s_Id{RefBackendId()};
22 }
23 template <typename F32Workload, typename U8Workload, typename QueueDescriptorType>
24 std::unique_ptr<IWorkload> RefWorkloadFactory::MakeWorkload(const QueueDescriptorType& descriptor,
25  const WorkloadInfo& info) const
26 {
27  return MakeWorkloadHelper<NullWorkload, F32Workload, U8Workload, NullWorkload, NullWorkload, NullWorkload>
28  (descriptor, info);
29 }
30 
31 template <DataType ArmnnType>
32 bool IsDataType(const WorkloadInfo& info)
33 {
34  auto checkType = [](const TensorInfo& tensorInfo) {return tensorInfo.GetDataType() == ArmnnType;};
35  auto it = std::find_if(std::begin(info.m_InputTensorInfos), std::end(info.m_InputTensorInfos), checkType);
36  if (it != std::end(info.m_InputTensorInfos))
37  {
38  return true;
39  }
40  it = std::find_if(std::begin(info.m_OutputTensorInfos), std::end(info.m_OutputTensorInfos), checkType);
41  if (it != std::end(info.m_OutputTensorInfos))
42  {
43  return true;
44  }
45  return false;
46 }
47 
48 bool IsSigned32(const WorkloadInfo& info)
49 {
50  return IsDataType<DataType::Signed32>(info);
51 }
52 
53 bool IsBFloat16(const WorkloadInfo& info)
54 {
55  return IsDataType<DataType::BFloat16>(info);
56 }
57 
58 bool IsFloat16(const WorkloadInfo& info)
59 {
60  return IsDataType<DataType::Float16>(info);
61 }
62 
63 bool IsQSymmS16(const WorkloadInfo& info)
64 {
65  return IsDataType<DataType::QSymmS16>(info);
66 }
67 
68 bool IsQSymmS8(const WorkloadInfo& info)
69 {
70  return IsDataType<DataType::QSymmS8>(info);
71 }
72 
73 bool IsQAsymmS8(const WorkloadInfo& info)
74 {
75  return IsDataType<DataType::QAsymmS8>(info);
76 }
77 
78 bool IsQAsymmU8(const WorkloadInfo& info)
79 {
80  return IsDataType<DataType::QAsymmU8>(info);
81 }
82 
83 RefWorkloadFactory::RefWorkloadFactory(const std::shared_ptr<RefMemoryManager>& memoryManager)
84  : m_MemoryManager(memoryManager)
85 {
86 }
87 
89  : m_MemoryManager(new RefMemoryManager())
90 {
91 }
92 
94 {
95  return s_Id;
96 }
97 
99  Optional<DataType> dataType,
100  std::string& outReasonIfUnsupported)
101 {
102  return IWorkloadFactory::IsLayerSupported(s_Id, layer, dataType, outReasonIfUnsupported);
103 }
104 
106  Optional<DataType> dataType,
107  std::string& outReasonIfUnsupported,
108  const ModelOptions& modelOptions)
109 {
110  return IWorkloadFactory::IsLayerSupported(s_Id, layer, dataType, outReasonIfUnsupported, modelOptions);
111 }
112 
113 std::unique_ptr<ITensorHandle> RefWorkloadFactory::CreateTensorHandle(const TensorInfo& tensorInfo,
114  const bool isMemoryManaged) const
115 {
116  if (isMemoryManaged)
117  {
118  return std::make_unique<RefTensorHandle>(tensorInfo, m_MemoryManager);
119  }
120  else
121  {
122  return std::make_unique<RefTensorHandle>(tensorInfo);
123  }
124 }
125 
126 std::unique_ptr<ITensorHandle> RefWorkloadFactory::CreateTensorHandle(const TensorInfo& tensorInfo,
127  DataLayout dataLayout,
128  const bool isMemoryManaged) const
129 {
130  // For Ref it is okay to make the TensorHandle memory managed as it can also store a pointer
131  // to unmanaged memory. This also ensures memory alignment.
132  IgnoreUnused(isMemoryManaged, dataLayout);
133 
134  if (isMemoryManaged)
135  {
136  return std::make_unique<RefTensorHandle>(tensorInfo, m_MemoryManager);
137  }
138  else
139  {
140  return std::make_unique<RefTensorHandle>(tensorInfo);
141  }
142 }
143 
144 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateWorkload(LayerType type,
145  const QueueDescriptor& descriptor,
146  const WorkloadInfo& info) const
147 {
148  switch(type)
149  {
150  case LayerType::Activation :
151  {
152  auto activationQueueDescriptor = PolymorphicDowncast<const ActivationQueueDescriptor*>(&descriptor);
153  return std::make_unique<RefActivationWorkload>(*activationQueueDescriptor, info);
154  }
155  case LayerType::Addition :
156  {
157  auto additionQueueDescriptor = PolymorphicDowncast<const AdditionQueueDescriptor*>(&descriptor);
158 
159  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
160  {
161  return std::make_unique<RefAdditionWorkload<int32_t>>(*additionQueueDescriptor, info);
162  }
163  else
164  {
165  return std::make_unique<RefAdditionWorkload<float>>(*additionQueueDescriptor, info);
166  }
167  }
168  case LayerType::ArgMinMax :
169  {
170  auto argMinMaxQueueDescriptor = PolymorphicDowncast<const ArgMinMaxQueueDescriptor*>(&descriptor);
171  return std::make_unique<RefArgMinMaxWorkload>(*argMinMaxQueueDescriptor, info);
172  }
174  {
175  auto batchMatMulQueueDescriptor = PolymorphicDowncast<const BatchMatMulQueueDescriptor*>(&descriptor);
176  return std::make_unique<RefBatchMatMulWorkload>(*batchMatMulQueueDescriptor, info);
177  }
179  {
180  auto batchNormQueueDescriptor = PolymorphicDowncast<const BatchNormalizationQueueDescriptor*>(&descriptor);
181  return std::make_unique<RefBatchNormalizationWorkload>(*batchNormQueueDescriptor, info);
182  }
184  {
185  auto batchToSpaceNdQueueDescriptor
186  = PolymorphicDowncast<const BatchToSpaceNdQueueDescriptor*>(&descriptor);
187  return std::make_unique<RefBatchToSpaceNdWorkload>(*batchToSpaceNdQueueDescriptor, info);
188  }
189  case LayerType::Cast :
190  {
191  auto castQueueDescriptor = PolymorphicDowncast<const CastQueueDescriptor*>(&descriptor);
192  return std::make_unique<RefCastWorkload>(*castQueueDescriptor, info);
193  }
195  {
196  auto channelShuffleQueueDescriptor
197  = PolymorphicDowncast<const ChannelShuffleQueueDescriptor*>(&descriptor);
198  return std::make_unique<RefChannelShuffleWorkload>(*channelShuffleQueueDescriptor, info);
199  }
200  case LayerType::Comparison :
201  {
202  auto comparisonQueueDescriptor = PolymorphicDowncast<const ComparisonQueueDescriptor*>(&descriptor);
203  return std::make_unique<RefComparisonWorkload>(*comparisonQueueDescriptor, info);
204  }
205  case LayerType::Concat :
206  {
207  auto concatQueueDescriptor = PolymorphicDowncast<const ConcatQueueDescriptor*>(&descriptor);
208  return std::make_unique<RefConcatWorkload>(*concatQueueDescriptor, info);
209  }
210  case LayerType::Constant :
211  {
212  auto constantQueueDescriptor = PolymorphicDowncast<const ConstantQueueDescriptor*>(&descriptor);
213  return std::make_unique<RefConstantWorkload>(*constantQueueDescriptor, info);
214  }
216  {
217  auto convertFp16ToFp32QueueDescriptor
218  = PolymorphicDowncast<const ConvertFp16ToFp32QueueDescriptor*>(&descriptor);
219  return std::make_unique<RefConvertFp16ToFp32Workload>(*convertFp16ToFp32QueueDescriptor, info);
220  }
222  {
223  auto convertFp32ToFp16QueueDescriptor
224  = PolymorphicDowncast<const ConvertFp32ToFp16QueueDescriptor*>(&descriptor);
225  return std::make_unique<RefConvertFp32ToFp16Workload>(*convertFp32ToFp16QueueDescriptor, info);
226  }
228  {
229  auto convolution2dQueueDescriptor = PolymorphicDowncast<const Convolution2dQueueDescriptor*>(&descriptor);
230  return std::make_unique<RefConvolution2dWorkload>(*convolution2dQueueDescriptor, info);
231  }
233  {
234  auto convolution3dQueueDescriptor = PolymorphicDowncast<const Convolution3dQueueDescriptor*>(&descriptor);
235  return std::make_unique<RefConvolution3dWorkload>(*convolution3dQueueDescriptor, info);
236  }
237  case LayerType::Debug:
238  {
239  auto debugQueueDescriptor = PolymorphicDowncast<const DebugQueueDescriptor*>(&descriptor);
240  if (IsBFloat16(info))
241  {
242  return std::make_unique<RefDebugBFloat16Workload>(*debugQueueDescriptor, info);
243  }
244  if (IsFloat16(info))
245  {
246  return std::make_unique<RefDebugFloat16Workload>(*debugQueueDescriptor, info);
247  }
248  if (IsQSymmS16(info))
249  {
250  return std::make_unique<RefDebugQSymmS16Workload>(*debugQueueDescriptor, info);
251  }
252  if (IsQSymmS8(info))
253  {
254  return std::make_unique<RefDebugQSymmS8Workload>(*debugQueueDescriptor, info);
255  }
256  if (IsQAsymmU8(info))
257  {
258  return std::make_unique<RefDebugQAsymmU8Workload>(*debugQueueDescriptor, info);
259  }
260  if (IsQAsymmS8(info))
261  {
262  return std::make_unique<RefDebugQAsymmS8Workload>(*debugQueueDescriptor, info);
263  }
264  if (IsSigned32(info))
265  {
266  return std::make_unique<RefDebugSigned32Workload>(*debugQueueDescriptor, info);
267  }
268 
269  return MakeWorkload<RefDebugFloat32Workload, RefDebugQAsymmU8Workload>(*debugQueueDescriptor, info);
270  }
272  {
273  auto depthToSpaceQueueDescriptor = PolymorphicDowncast<const DepthToSpaceQueueDescriptor*>(&descriptor);
274  return std::make_unique<RefDepthToSpaceWorkload>(*depthToSpaceQueueDescriptor, info);
275  }
277  {
278  auto depthwiseConvolution2DQueueDescriptor
279  = PolymorphicDowncast<const DepthwiseConvolution2dQueueDescriptor*>(&descriptor);
280  return std::make_unique<RefDepthwiseConvolution2dWorkload>(*depthwiseConvolution2DQueueDescriptor, info);
281  }
283  {
284  auto dequantizeQueueDescriptor = PolymorphicDowncast<const DequantizeQueueDescriptor*>(&descriptor);
285  return std::make_unique<RefDequantizeWorkload>(*dequantizeQueueDescriptor, info);
286  }
288  {
289  auto detectionPostProcessQueueDescriptor
290  = PolymorphicDowncast<const DetectionPostProcessQueueDescriptor*>(&descriptor);
291  return std::make_unique<RefDetectionPostProcessWorkload>(*detectionPostProcessQueueDescriptor, info);
292  }
293  case LayerType::Division:
294  {
295  auto divisionQueueDescriptor = PolymorphicDowncast<const DivisionQueueDescriptor*>(&descriptor);
296  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
297  {
298  return std::make_unique<RefDivisionWorkload<int32_t>>(*divisionQueueDescriptor, info);
299  }
300  else
301  {
302  return std::make_unique<RefDivisionWorkload<float>>(*divisionQueueDescriptor, info);
303  }
304  }
306  {
307  auto elementwiseUnaryQueueDescriptor
308  = PolymorphicDowncast<const ElementwiseUnaryQueueDescriptor*>(&descriptor);
309  if ((*elementwiseUnaryQueueDescriptor).m_Parameters.m_Operation == UnaryOperation::LogicalNot)
310  {
311  return std::make_unique<RefLogicalUnaryWorkload>(*elementwiseUnaryQueueDescriptor, info);
312  }
313  return std::make_unique<RefElementwiseUnaryWorkload>(*elementwiseUnaryQueueDescriptor, info);
314  }
316  {
317  auto fakeQuantizationQueueDescriptor
318  = PolymorphicDowncast<const FakeQuantizationQueueDescriptor*>(&descriptor);
319  return std::make_unique<RefFakeQuantizationFloat32Workload>(*fakeQuantizationQueueDescriptor, info);
320  }
321  case LayerType::Fill:
322  {
323  auto fillQueueDescriptor = PolymorphicDowncast<const FillQueueDescriptor*>(&descriptor);
324  return std::make_unique<RefFillWorkload>(*fillQueueDescriptor, info);
325  }
326  case LayerType::Floor:
327  {
328  auto floorQueueDescriptor = PolymorphicDowncast<const FloorQueueDescriptor*>(&descriptor);
329  if(IsQuantizedType(info.m_InputTensorInfos[0].GetDataType()))
330  {
331  return nullptr;
332  }
333  else
334  {
335  return std::make_unique<RefFloorWorkload>(*floorQueueDescriptor, info);
336  }
337  }
339  {
340  auto fullyConnectedQueueDescriptor
341  = PolymorphicDowncast<const FullyConnectedQueueDescriptor*>(&descriptor);
342  return std::make_unique<RefFullyConnectedWorkload>(*fullyConnectedQueueDescriptor, info);
343  }
344  case LayerType::Gather:
345  {
346  auto gatherQueueDescriptor = PolymorphicDowncast<const GatherQueueDescriptor*>(&descriptor);
347  return std::make_unique<RefGatherWorkload>(*gatherQueueDescriptor, info);
348  }
349  case LayerType::GatherNd:
350  {
351  auto gatherNdQueueDescriptor = PolymorphicDowncast<const GatherNdQueueDescriptor*>(&descriptor);
352  return std::make_unique<RefGatherNdWorkload>(*gatherNdQueueDescriptor, info);
353  }
354  case LayerType::Input:
355  {
356  auto inputQueueDescriptor = PolymorphicDowncast<const InputQueueDescriptor*>(&descriptor);
357  if (info.m_InputTensorInfos.empty() )
358  {
359  throw InvalidArgumentException("RefWorkloadFactory::CreateInput: Input cannot be zero length");
360  }
361  if (info.m_OutputTensorInfos.empty())
362  {
363  throw InvalidArgumentException("RefWorkloadFactory::CreateInput: Output cannot be zero length");
364  }
365 
366  if (info.m_InputTensorInfos[0].GetNumBytes() != info.m_OutputTensorInfos[0].GetNumBytes())
367  {
368  throw InvalidArgumentException("RefWorkloadFactory::CreateInput: "
369  "data input and output differ in byte count.");
370  }
371 
372  return std::make_unique<CopyMemGenericWorkload>(*inputQueueDescriptor, info);
373  }
375  {
376  auto instanceNormalizationQueueDescriptor
377  = PolymorphicDowncast<const InstanceNormalizationQueueDescriptor*>(&descriptor);
378  return std::make_unique<RefInstanceNormalizationWorkload>(*instanceNormalizationQueueDescriptor, info);
379  }
381  {
382  auto l2NormalizationQueueDescriptor
383  = PolymorphicDowncast<const L2NormalizationQueueDescriptor*>(&descriptor);
384  return std::make_unique<RefL2NormalizationWorkload>(*l2NormalizationQueueDescriptor, info);
385  }
387  {
388  auto logicalBinaryQueueDescriptor = PolymorphicDowncast<const LogicalBinaryQueueDescriptor*>(&descriptor);
389  return std::make_unique<RefLogicalBinaryWorkload>(*logicalBinaryQueueDescriptor, info);
390  }
392  {
393  auto logSoftmaxQueueDescriptor = PolymorphicDowncast<const LogSoftmaxQueueDescriptor*>(&descriptor);
394  return std::make_unique<RefLogSoftmaxWorkload>(*logSoftmaxQueueDescriptor, info);
395  }
396  case LayerType::Lstm:
397  {
398  auto lstmQueueDescriptor = PolymorphicDowncast<const LstmQueueDescriptor*>(&descriptor);
399  return std::make_unique<RefLstmWorkload>(*lstmQueueDescriptor, info);
400  }
401  case LayerType::Maximum:
402  {
403  auto maximumQueueDescriptor = PolymorphicDowncast<const MaximumQueueDescriptor*>(&descriptor);
404  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
405  {
406  return std::make_unique<RefMaximumWorkload<int32_t>>(*maximumQueueDescriptor, info);
407  }
408  else
409  {
410  return std::make_unique<RefMaximumWorkload<float>>(*maximumQueueDescriptor, info);
411  }
412  }
413  case LayerType::Mean:
414  {
415  auto meanQueueDescriptor = PolymorphicDowncast<const MeanQueueDescriptor*>(&descriptor);
416  return std::make_unique<RefMeanWorkload>(*meanQueueDescriptor, info);
417  }
418  case LayerType::MemCopy:
419  {
420  auto memCopyQueueDescriptor = PolymorphicDowncast<const MemCopyQueueDescriptor*>(&descriptor);
421  if (descriptor.m_Inputs.empty())
422  {
423  throw InvalidArgumentException("RefWorkloadFactory: CreateMemCopy() expected an input tensor.");
424  }
425  return std::make_unique<CopyMemGenericWorkload>(*memCopyQueueDescriptor, info);
426  }
428  {
429  auto memImportQueueDescriptor = PolymorphicDowncast<const MemImportQueueDescriptor*>(&descriptor);
430  if (descriptor.m_Inputs.empty())
431  {
432  throw InvalidArgumentException("RefWorkloadFactory: CreateMemImport() expected an input tensor.");
433  }
434  return std::make_unique<ImportMemGenericWorkload>(*memImportQueueDescriptor, info);
435  }
436  case LayerType::Minimum:
437  {
438  auto minimumQueueDescriptor = PolymorphicDowncast<const MinimumQueueDescriptor*>(&descriptor);
439  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
440  {
441  return std::make_unique<RefMinimumWorkload<int32_t>>(*minimumQueueDescriptor, info);
442  }
443  else
444  {
445  return std::make_unique<RefMinimumWorkload<float>>(*minimumQueueDescriptor, info);
446  }
447  }
449  {
450  auto multiplicationQueueDescriptor
451  = PolymorphicDowncast<const MultiplicationQueueDescriptor*>(&descriptor);
452  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
453  {
454  return std::make_unique<RefMultiplicationWorkload<int32_t>>(*multiplicationQueueDescriptor, info);
455  }
456  else
457  {
458  return std::make_unique<RefMultiplicationWorkload<float>>(*multiplicationQueueDescriptor, info);
459  }
460  }
462  {
463  auto normalizationQueueDescriptor = PolymorphicDowncast<const NormalizationQueueDescriptor*>(&descriptor);
464  return std::make_unique<RefNormalizationWorkload>(*normalizationQueueDescriptor, info);
465  }
466  case LayerType::Output:
467  {
468  auto outputQueueDescriptor = PolymorphicDowncast<const OutputQueueDescriptor*>(&descriptor);
469  if (info.m_InputTensorInfos.empty() )
470  {
471  throw InvalidArgumentException("RefWorkloadFactory::CreateOutput: Input cannot be zero length");
472  }
473  if (info.m_OutputTensorInfos.empty())
474  {
475  throw InvalidArgumentException("RefWorkloadFactory::CreateOutput: Output cannot be zero length");
476  }
477  if (info.m_InputTensorInfos[0].GetNumBytes() != info.m_OutputTensorInfos[0].GetNumBytes())
478  {
479  throw InvalidArgumentException("RefWorkloadFactory::CreateOutput: data input and output "
480  "differ in byte count.");
481  }
482 
483  return std::make_unique<CopyMemGenericWorkload>(*outputQueueDescriptor, info);
484  }
485  case LayerType::Pad:
486  {
487  auto padQueueDescriptor = PolymorphicDowncast<const PadQueueDescriptor*>(&descriptor);
488  return std::make_unique<RefPadWorkload>(*padQueueDescriptor, info);
489  }
490  case LayerType::Permute:
491  {
492  auto permuteQueueDescriptor = PolymorphicDowncast<const PermuteQueueDescriptor*>(&descriptor);
493  if (IsQSymmS16(info))
494  {
495  return std::make_unique<RefPermuteQSymm16Workload>(*permuteQueueDescriptor, info);
496  }
497  else if (IsBFloat16(info))
498  {
499  return std::make_unique<RefPermuteBFloat16Workload>(*permuteQueueDescriptor, info);
500  }
501  else if (IsQAsymmS8(info))
502  {
503  return std::make_unique<RefPermuteQAsymmS8Workload>(*permuteQueueDescriptor, info);
504  }
506  NullWorkload, NullWorkload, NullWorkload>(*permuteQueueDescriptor, info);
507  }
509  {
510  auto pooling2dQueueDescriptor = PolymorphicDowncast<const Pooling2dQueueDescriptor*>(&descriptor);
511  return std::make_unique<RefPooling2dWorkload>(*pooling2dQueueDescriptor, info);
512  }
514  {
515  auto pooling3dQueueDescriptor = PolymorphicDowncast<const Pooling3dQueueDescriptor*>(&descriptor);
516  return std::make_unique<RefPooling3dWorkload>(*pooling3dQueueDescriptor, info);
517  }
519  {
520  return nullptr;
521  }
522  case LayerType::Prelu:
523  {
524  auto preluQueueDescriptor = PolymorphicDowncast<const PreluQueueDescriptor*>(&descriptor);
525  return std::make_unique<RefPreluWorkload>(*preluQueueDescriptor, info);
526  }
527  case LayerType::QLstm:
528  {
529  auto qlstmQueueDescriptor = PolymorphicDowncast<const QLstmQueueDescriptor*>(&descriptor);
530  return std::make_unique<RefQLstmWorkload>(*qlstmQueueDescriptor, info);
531  }
532  case LayerType::Quantize:
533  {
534  auto quantizeQueueDescriptor = PolymorphicDowncast<const QuantizeQueueDescriptor*>(&descriptor);
535  return std::make_unique<RefQuantizeWorkload>(*quantizeQueueDescriptor, info);
536  }
537  case LayerType::Rank:
538  {
539  auto rankQueueDescriptor = PolymorphicDowncast<const RankQueueDescriptor*>(&descriptor);
540  return std::make_unique<RefRankWorkload>(*rankQueueDescriptor, info);
541  }
542  case LayerType::Reduce:
543  {
544  auto reduceQueueDescriptor = PolymorphicDowncast<const ReduceQueueDescriptor*>(&descriptor);
545  return std::make_unique<RefReduceWorkload>(*reduceQueueDescriptor, info);
546  }
547  case LayerType::Reshape:
548  {
549  auto reshapeQueueDescriptor = PolymorphicDowncast<const ReshapeQueueDescriptor*>(&descriptor);
550  return std::make_unique<RefReshapeWorkload>(*reshapeQueueDescriptor, info);
551  }
552  case LayerType::Resize:
553  {
554  auto resizeQueueDescriptor = PolymorphicDowncast<const ResizeQueueDescriptor*>(&descriptor);
555  return std::make_unique<RefResizeWorkload>(*resizeQueueDescriptor, info);
556  }
557  case LayerType::Shape:
558  {
559  auto shapeQueueDescriptor = PolymorphicDowncast<const ShapeQueueDescriptor*>(&descriptor);
560  return std::make_unique<RefShapeWorkload>(*shapeQueueDescriptor, info);
561  }
562  case LayerType::Slice:
563  {
564  auto sliceQueueDescriptor = PolymorphicDowncast<const SliceQueueDescriptor*>(&descriptor);
565  return std::make_unique<RefSliceWorkload>(*sliceQueueDescriptor, info);
566  }
567  case LayerType::Softmax:
568  {
569  auto softmaxQueueDescriptor = PolymorphicDowncast<const SoftmaxQueueDescriptor*>(&descriptor);
570  return std::make_unique<RefSoftmaxWorkload>(*softmaxQueueDescriptor, info);
571  }
573  {
574  auto spaceToBatchNdQueueDescriptor
575  = PolymorphicDowncast<const SpaceToBatchNdQueueDescriptor*>(&descriptor);
576  return std::make_unique<RefSpaceToBatchNdWorkload>(*spaceToBatchNdQueueDescriptor, info);
577  }
579  {
580  auto spaceToDepthQueueDescriptor = PolymorphicDowncast<const SpaceToDepthQueueDescriptor*>(&descriptor);
581  return std::make_unique<RefSpaceToDepthWorkload>(*spaceToDepthQueueDescriptor, info);
582  }
583  case LayerType::Splitter:
584  {
585  auto splitterQueueDescriptor = PolymorphicDowncast<const SplitterQueueDescriptor*>(&descriptor);
586  return std::make_unique<RefSplitterWorkload>(*splitterQueueDescriptor, info);
587  }
588  case LayerType::Stack:
589  {
590  auto stackQueueDescriptor = PolymorphicDowncast<const StackQueueDescriptor*>(&descriptor);
591  return std::make_unique<RefStackWorkload>(*stackQueueDescriptor, info);
592  }
594  {
595  auto stridedSliceQueueDescriptor = PolymorphicDowncast<const StridedSliceQueueDescriptor*>(&descriptor);
596  return std::make_unique<RefStridedSliceWorkload>(*stridedSliceQueueDescriptor, info);
597  }
599  {
600  auto subtractionQueueDescriptor = PolymorphicDowncast<const SubtractionQueueDescriptor*>(&descriptor);
601  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
602  {
603  return std::make_unique<RefSubtractionWorkload<int32_t>>(*subtractionQueueDescriptor, info);
604  }
605  else
606  {
607  return std::make_unique<RefSubtractionWorkload<float>>(*subtractionQueueDescriptor, info);
608  }
609  }
611  {
612  auto transposeQueueDescriptor = PolymorphicDowncast<const TransposeQueueDescriptor*>(&descriptor);
613  if (IsQSymmS16(info))
614  {
615  return std::make_unique<RefTransposeQSymm16Workload>(*transposeQueueDescriptor, info);
616  }
617  else if (IsBFloat16(info))
618  {
619  return std::make_unique<RefTransposeBFloat16Workload>(*transposeQueueDescriptor, info);
620  }
621  else if (IsQAsymmS8(info))
622  {
623  return std::make_unique<RefTransposeQAsymmS8Workload>(*transposeQueueDescriptor, info);
624  }
625  return MakeWorkloadHelper<RefTransposeFloat16Workload, RefTransposeFloat32Workload,
627  (*transposeQueueDescriptor, info);
628  }
630  {
631  auto transposeConvolution2dQueueDescriptor
632  = PolymorphicDowncast<const TransposeConvolution2dQueueDescriptor*>(&descriptor);
633  return std::make_unique<RefTransposeConvolution2dWorkload>(*transposeConvolution2dQueueDescriptor, info);
634  }
636  {
637  auto unidirectionalSequenceLstmQueueDescriptor
638  = PolymorphicDowncast<const UnidirectionalSequenceLstmQueueDescriptor*>(&descriptor);
639  return std::make_unique<RefUnidirectionalSequenceLstmWorkload>(*unidirectionalSequenceLstmQueueDescriptor,
640  info);
641  }
642  default:
643  return nullptr;
644  }
645 }
646 
647 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateActivation(const ActivationQueueDescriptor& descriptor,
648  const WorkloadInfo& info) const
649 {
650  return std::make_unique<RefActivationWorkload>(descriptor, info);
651 }
652 
653 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateAddition(const AdditionQueueDescriptor& descriptor,
654  const WorkloadInfo& info) const
655 {
656  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
657  {
658  return std::make_unique<RefAdditionWorkload<int32_t>>(descriptor, info);
659  }
660  else
661  {
662  return std::make_unique<RefAdditionWorkload<float>>(descriptor, info);
663  }
664 }
665 
666 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateArgMinMax(const ArgMinMaxQueueDescriptor& descriptor,
667  const WorkloadInfo& info) const
668 {
669  return std::make_unique<RefArgMinMaxWorkload>(descriptor, info);
670 }
671 
672 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateBatchNormalization(
673  const BatchNormalizationQueueDescriptor& descriptor,
674  const WorkloadInfo& info) const
675 {
676  return std::make_unique<RefBatchNormalizationWorkload>(descriptor, info);
677 }
678 
679 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateBatchToSpaceNd(const BatchToSpaceNdQueueDescriptor& descriptor,
680  const WorkloadInfo& info) const
681 {
682  return std::make_unique<RefBatchToSpaceNdWorkload>(descriptor, info);
683 }
684 
685 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateCast(const CastQueueDescriptor& descriptor,
686  const WorkloadInfo& info) const
687 {
688  return std::make_unique<RefCastWorkload>(descriptor, info);
689 }
690 
691 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateChannelShuffle(const ChannelShuffleQueueDescriptor &descriptor,
692  const WorkloadInfo &info) const
693 {
694  return std::make_unique<RefChannelShuffleWorkload>(descriptor,info);
695 }
696 
697 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateComparison(const ComparisonQueueDescriptor& descriptor,
698  const WorkloadInfo& info) const
699 {
700  return std::make_unique<RefComparisonWorkload>(descriptor, info);
701 }
702 
703 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateConcat(const ConcatQueueDescriptor& descriptor,
704  const WorkloadInfo& info) const
705 {
706  return std::make_unique<RefConcatWorkload>(descriptor, info);
707 }
708 
709 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateConstant(const ConstantQueueDescriptor& descriptor,
710  const WorkloadInfo& info) const
711 {
712  return std::make_unique<RefConstantWorkload>(descriptor, info);
713 }
714 
715 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateConvertFp16ToFp32(
716  const ConvertFp16ToFp32QueueDescriptor& descriptor,
717  const WorkloadInfo& info) const
718 {
719  return std::make_unique<RefConvertFp16ToFp32Workload>(descriptor, info);
720 }
721 
722 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateConvertFp32ToFp16(
723  const ConvertFp32ToFp16QueueDescriptor& descriptor,
724  const WorkloadInfo& info) const
725 {
726  return std::make_unique<RefConvertFp32ToFp16Workload>(descriptor, info);
727 }
728 
729 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateConvolution2d(const Convolution2dQueueDescriptor& descriptor,
730  const WorkloadInfo& info) const
731 {
732  return std::make_unique<RefConvolution2dWorkload>(descriptor, info);
733 }
734 
735 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateConvolution3d(const Convolution3dQueueDescriptor& descriptor,
736  const WorkloadInfo& info) const
737 {
738  return std::make_unique<RefConvolution3dWorkload>(descriptor, info);
739 }
740 
741 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateDebug(const DebugQueueDescriptor& descriptor,
742  const WorkloadInfo& info) const
743 {
744  if (IsBFloat16(info))
745  {
746  return std::make_unique<RefDebugBFloat16Workload>(descriptor, info);
747  }
748  if (IsFloat16(info))
749  {
750  return std::make_unique<RefDebugFloat16Workload>(descriptor, info);
751  }
752  if (IsQSymmS16(info))
753  {
754  return std::make_unique<RefDebugQSymmS16Workload>(descriptor, info);
755  }
756  if (IsQSymmS8(info))
757  {
758  return std::make_unique<RefDebugQSymmS8Workload>(descriptor, info);
759  }
760  if (IsQAsymmU8(info))
761  {
762  return std::make_unique<RefDebugQAsymmU8Workload>(descriptor, info);
763  }
764  if (IsQAsymmS8(info))
765  {
766  return std::make_unique<RefDebugQAsymmS8Workload>(descriptor, info);
767  }
768  if (IsSigned32(info))
769  {
770  return std::make_unique<RefDebugSigned32Workload>(descriptor, info);
771  }
772 
773  return MakeWorkload<RefDebugFloat32Workload, RefDebugQAsymmU8Workload>(descriptor, info);
774 }
775 
776 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateDepthToSpace(const DepthToSpaceQueueDescriptor& descriptor,
777  const WorkloadInfo& info) const
778 {
779  return std::make_unique<RefDepthToSpaceWorkload>(descriptor, info);
780 }
781 
782 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateDepthwiseConvolution2d(
783  const DepthwiseConvolution2dQueueDescriptor& descriptor,
784  const WorkloadInfo& info) const
785 {
786  return std::make_unique<RefDepthwiseConvolution2dWorkload>(descriptor, info);
787 }
788 
789 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateDequantize(const DequantizeQueueDescriptor& descriptor,
790  const WorkloadInfo& info) const
791 {
792  return std::make_unique<RefDequantizeWorkload>(descriptor, info);
793 }
794 
795 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateDetectionPostProcess(
796  const DetectionPostProcessQueueDescriptor& descriptor,
797  const WorkloadInfo& info) const
798 {
799  return std::make_unique<RefDetectionPostProcessWorkload>(descriptor, info);
800 }
801 
802 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateDivision(const DivisionQueueDescriptor& descriptor,
803  const WorkloadInfo& info) const
804 {
805  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
806  {
807  return std::make_unique<RefDivisionWorkload<int32_t>>(descriptor, info);
808  }
809  else
810  {
811  return std::make_unique<RefDivisionWorkload<float>>(descriptor, info);
812  }
813 }
814 
815 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateElementwiseUnary(const ElementwiseUnaryQueueDescriptor& descriptor,
816  const WorkloadInfo& info) const
817 {
818  if (descriptor.m_Parameters.m_Operation == UnaryOperation::LogicalNot)
819  {
820  return std::make_unique<RefLogicalUnaryWorkload>(descriptor, info);
821  }
822  return std::make_unique<RefElementwiseUnaryWorkload>(descriptor, info);
823 }
824 
825 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateFakeQuantization(const FakeQuantizationQueueDescriptor& descriptor,
826  const WorkloadInfo& info) const
827 {
828  return MakeWorkload<RefFakeQuantizationFloat32Workload, NullWorkload>(descriptor, info);
829 }
830 
831 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateFill(const FillQueueDescriptor& descriptor,
832  const WorkloadInfo& info) const
833 {
834  return std::make_unique<RefFillWorkload>(descriptor, info);
835 }
836 
837 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateFloor(const FloorQueueDescriptor& descriptor,
838  const WorkloadInfo& info) const
839 {
840  if(IsQuantizedType(info.m_InputTensorInfos[0].GetDataType()))
841  {
842  return nullptr;
843  }
844  else
845  {
846  return std::make_unique<RefFloorWorkload>(descriptor, info);
847  }
848 }
849 
850 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateFullyConnected(
851  const FullyConnectedQueueDescriptor& descriptor,
852  const WorkloadInfo& info) const
853 {
854  return std::make_unique<RefFullyConnectedWorkload>(descriptor, info);
855 }
856 
857 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateGather(const GatherQueueDescriptor& descriptor,
858  const WorkloadInfo& info) const
859 {
860  return std::make_unique<RefGatherWorkload>(descriptor, info);
861 }
862 
863 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateInput(const InputQueueDescriptor& descriptor,
864  const WorkloadInfo& info) const
865 {
866  if (info.m_InputTensorInfos.empty() )
867  {
868  throw InvalidArgumentException("RefWorkloadFactory::CreateInput: Input cannot be zero length");
869  }
870  if (info.m_OutputTensorInfos.empty())
871  {
872  throw InvalidArgumentException("RefWorkloadFactory::CreateInput: Output cannot be zero length");
873  }
874 
875  if (info.m_InputTensorInfos[0].GetNumBytes() != info.m_OutputTensorInfos[0].GetNumBytes())
876  {
877  throw InvalidArgumentException("RefWorkloadFactory::CreateInput: data input and output differ in byte count.");
878  }
879 
880  return std::make_unique<CopyMemGenericWorkload>(descriptor, info);
881 }
882 
883 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateInstanceNormalization(
884  const InstanceNormalizationQueueDescriptor& descriptor,
885  const WorkloadInfo& info) const
886 {
887  return std::make_unique<RefInstanceNormalizationWorkload>(descriptor, info);
888 }
889 
890 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateL2Normalization(const L2NormalizationQueueDescriptor& descriptor,
891  const WorkloadInfo& info) const
892 {
893  return std::make_unique<RefL2NormalizationWorkload>(descriptor, info);
894 }
895 
896 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateLogicalBinary(const LogicalBinaryQueueDescriptor& descriptor,
897  const WorkloadInfo& info) const
898 {
899  return std::make_unique<RefLogicalBinaryWorkload>(descriptor, info);
900 }
901 
902 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateLogSoftmax(const LogSoftmaxQueueDescriptor& descriptor,
903  const WorkloadInfo& info) const
904 {
905  return std::make_unique<RefLogSoftmaxWorkload>(descriptor, info);
906 }
907 
908 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateLstm(const LstmQueueDescriptor& descriptor,
909  const WorkloadInfo& info) const
910 {
911  return std::make_unique<RefLstmWorkload>(descriptor, info);
912 }
913 
914 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateMaximum(const MaximumQueueDescriptor& descriptor,
915  const WorkloadInfo& info) const
916 {
917  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
918  {
919  return std::make_unique<RefMaximumWorkload<int32_t>>(descriptor, info);
920  }
921  else
922  {
923  return std::make_unique<RefMaximumWorkload<float>>(descriptor, info);
924  }
925 }
926 
927 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateMean(const MeanQueueDescriptor& descriptor,
928  const WorkloadInfo& info) const
929 {
930  return std::make_unique<RefMeanWorkload>(descriptor, info);
931 }
932 
933 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateMemCopy(const MemCopyQueueDescriptor& descriptor,
934  const WorkloadInfo& info) const
935 {
936  if (descriptor.m_Inputs.empty())
937  {
938  throw InvalidArgumentException("RefWorkloadFactory: CreateMemCopy() expected an input tensor.");
939  }
940  return std::make_unique<CopyMemGenericWorkload>(descriptor, info);
941 }
942 
943 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateMemImport(const MemImportQueueDescriptor& descriptor,
944  const WorkloadInfo& info) const
945 {
946  if (descriptor.m_Inputs.empty())
947  {
948  throw InvalidArgumentException("RefWorkloadFactory: CreateMemImport() expected an input tensor.");
949  }
950  return std::make_unique<ImportMemGenericWorkload>(descriptor, info);
951 }
952 
953 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateMinimum(const MinimumQueueDescriptor& descriptor,
954  const WorkloadInfo& info) const
955 {
956  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
957  {
958  return std::make_unique<RefMinimumWorkload<int32_t>>(descriptor, info);
959  }
960  else
961  {
962  return std::make_unique<RefMinimumWorkload<float>>(descriptor, info);
963  }
964 }
965 
966 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateMultiplication(const MultiplicationQueueDescriptor& descriptor,
967  const WorkloadInfo& info) const
968 {
969  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
970  {
971  return std::make_unique<RefMultiplicationWorkload<int32_t>>(descriptor, info);
972  }
973  else
974  {
975  return std::make_unique<RefMultiplicationWorkload<float>>(descriptor, info);
976  }
977 }
978 
979 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateNormalization(const NormalizationQueueDescriptor& descriptor,
980  const WorkloadInfo& info) const
981 {
982  return std::make_unique<RefNormalizationWorkload>(descriptor, info);
983 }
984 
985 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateOutput(const OutputQueueDescriptor& descriptor,
986  const WorkloadInfo& info) const
987 {
988  if (info.m_InputTensorInfos.empty() )
989  {
990  throw InvalidArgumentException("RefWorkloadFactory::CreateOutput: Input cannot be zero length");
991  }
992  if (info.m_OutputTensorInfos.empty())
993  {
994  throw InvalidArgumentException("RefWorkloadFactory::CreateOutput: Output cannot be zero length");
995  }
996  if (info.m_InputTensorInfos[0].GetNumBytes() != info.m_OutputTensorInfos[0].GetNumBytes())
997  {
998  throw InvalidArgumentException("RefWorkloadFactory::CreateOutput: data input and output differ in byte count.");
999  }
1000 
1001  return std::make_unique<CopyMemGenericWorkload>(descriptor, info);
1002 }
1003 
1004 std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePad(const PadQueueDescriptor& descriptor,
1005  const WorkloadInfo& info) const
1006 {
1007  return std::make_unique<RefPadWorkload>(descriptor, info);
1008 }
1009 
1010 std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePermute(const PermuteQueueDescriptor& descriptor,
1011  const WorkloadInfo& info) const
1012 {
1013  if (IsQSymmS16(info))
1014  {
1015  return std::make_unique<RefPermuteQSymm16Workload>(descriptor, info);
1016  }
1017  else if (IsBFloat16(info))
1018  {
1019  return std::make_unique<RefPermuteBFloat16Workload>(descriptor, info);
1020  }
1021  else if (IsQAsymmS8(info))
1022  {
1023  return std::make_unique<RefPermuteQAsymmS8Workload>(descriptor, info);
1024  }
1026  NullWorkload, NullWorkload, NullWorkload>(descriptor, info);
1027 }
1028 
1029 std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePooling2d(const Pooling2dQueueDescriptor& descriptor,
1030  const WorkloadInfo& info) const
1031 {
1032  return std::make_unique<RefPooling2dWorkload>(descriptor, info);
1033 }
1034 
1035 std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePooling3d(const Pooling3dQueueDescriptor& descriptor,
1036  const WorkloadInfo& info) const
1037 {
1038  return std::make_unique<RefPooling3dWorkload>(descriptor, info);
1039 }
1040 
1041 std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePreCompiled(const PreCompiledQueueDescriptor& /*descriptor*/,
1042  const WorkloadInfo& /*info*/) const
1043 {
1044  return nullptr;
1045 }
1046 
1047 std::unique_ptr<IWorkload> RefWorkloadFactory::CreatePrelu(const PreluQueueDescriptor& descriptor,
1048  const WorkloadInfo& info) const
1049 {
1050  return std::make_unique<RefPreluWorkload>(descriptor, info);
1051 }
1052 
1053 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateQLstm(const QLstmQueueDescriptor& descriptor,
1054  const WorkloadInfo& info) const
1055 {
1056  return std::make_unique<RefQLstmWorkload>(descriptor, info);
1057 }
1058 
1059 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateQuantize(const QuantizeQueueDescriptor& descriptor,
1060  const WorkloadInfo& info) const
1061 {
1062  return std::make_unique<RefQuantizeWorkload>(descriptor, info);
1063 }
1064 
1065 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateRank(const RankQueueDescriptor& descriptor,
1066  const WorkloadInfo& info) const
1067 {
1068  return std::make_unique<RefRankWorkload>(descriptor, info);
1069 }
1070 
1071 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateReduce(const ReduceQueueDescriptor& descriptor,
1072  const WorkloadInfo& info) const
1073 {
1074  return std::make_unique<RefReduceWorkload>(descriptor, info);
1075 }
1076 
1077 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateReshape(const ReshapeQueueDescriptor& descriptor,
1078  const WorkloadInfo& info) const
1079 {
1080  return std::make_unique<RefReshapeWorkload>(descriptor, info);
1081 }
1082 
1083 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateResize(const ResizeQueueDescriptor& descriptor,
1084  const WorkloadInfo& info) const
1085 {
1086  return std::make_unique<RefResizeWorkload>(descriptor, info);
1087 }
1088 
1089 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateShape(const ShapeQueueDescriptor& descriptor,
1090  const WorkloadInfo& info) const
1091 {
1092  return std::make_unique<RefShapeWorkload>(descriptor, info);
1093 }
1094 
1095 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateSlice(const SliceQueueDescriptor& descriptor,
1096  const WorkloadInfo& info) const
1097 {
1098  return std::make_unique<RefSliceWorkload>(descriptor, info);
1099 }
1100 
1101 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateSoftmax(const SoftmaxQueueDescriptor& descriptor,
1102  const WorkloadInfo& info) const
1103 {
1104  return std::make_unique<RefSoftmaxWorkload>(descriptor, info);
1105 }
1106 
1107 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateSpaceToBatchNd(const SpaceToBatchNdQueueDescriptor& descriptor,
1108  const WorkloadInfo& info) const
1109 {
1110  return std::make_unique<RefSpaceToBatchNdWorkload>(descriptor, info);
1111 }
1112 
1113 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateSpaceToDepth(const SpaceToDepthQueueDescriptor& descriptor,
1114  const WorkloadInfo& info) const
1115 {
1116  return std::make_unique<RefSpaceToDepthWorkload>(descriptor, info);
1117 }
1118 
1119 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateSplitter(const SplitterQueueDescriptor& descriptor,
1120  const WorkloadInfo& info) const
1121 {
1122  return std::make_unique<RefSplitterWorkload>(descriptor, info);
1123 }
1124 
1125 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateStack(const StackQueueDescriptor& descriptor,
1126  const WorkloadInfo& info) const
1127 {
1128  return std::make_unique<RefStackWorkload>(descriptor, info);
1129 }
1130 
1131 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateStridedSlice(const StridedSliceQueueDescriptor& descriptor,
1132  const WorkloadInfo& info) const
1133 {
1134  return std::make_unique<RefStridedSliceWorkload>(descriptor, info);
1135 }
1136 
1137 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateSubtraction(const SubtractionQueueDescriptor& descriptor,
1138  const WorkloadInfo& info) const
1139 {
1140  if (info.m_InputTensorInfos[0].GetDataType() == armnn::DataType::Signed32)
1141  {
1142  return std::make_unique<RefSubtractionWorkload<int32_t>>(descriptor, info);
1143  }
1144  else
1145  {
1146  return std::make_unique<RefSubtractionWorkload<float>>(descriptor, info);
1147  }
1148 }
1149 
1150 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateTranspose(const TransposeQueueDescriptor& descriptor,
1151  const WorkloadInfo& info) const
1152 {
1153  if (IsQSymmS16(info))
1154  {
1155  return std::make_unique<RefTransposeQSymm16Workload>(descriptor, info);
1156  }
1157  else if (IsBFloat16(info))
1158  {
1159  return std::make_unique<RefTransposeBFloat16Workload>(descriptor, info);
1160  }
1161  else if (IsQAsymmS8(info))
1162  {
1163  return std::make_unique<RefTransposeQAsymmS8Workload>(descriptor, info);
1164  }
1166  NullWorkload, NullWorkload, NullWorkload>(descriptor, info);
1167 }
1168 
1169 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateTransposeConvolution2d(
1170  const TransposeConvolution2dQueueDescriptor& descriptor,
1171  const WorkloadInfo& info) const
1172 {
1173  return std::make_unique<RefTransposeConvolution2dWorkload>(descriptor, info);
1174 }
1175 
1176 std::unique_ptr<IWorkload> RefWorkloadFactory::CreateUnidirectionalSequenceLstm(
1177  const UnidirectionalSequenceLstmQueueDescriptor& descriptor,
1178  const WorkloadInfo& info) const
1179 {
1180  return std::make_unique<RefUnidirectionalSequenceLstmWorkload>(descriptor, info);;
1181 }
1182 
1183 } // namespace armnn
armnn::LayerType::Floor
@ Floor
armnn::LayerType::MemCopy
@ MemCopy
armnn::BackendId
Definition: BackendId.hpp:75
armnn::LayerType::Softmax
@ Softmax
armnn::LayerType::Pooling3d
@ Pooling3d
armnn::LayerType::FullyConnected
@ FullyConnected
armnn::LayerType::Transpose
@ Transpose
armnn::LayerType::ChannelShuffle
@ ChannelShuffle
armnn::RefWorkloadFactory::CreateTensorHandle
std::unique_ptr< ITensorHandle > CreateTensorHandle(const TensorInfo &tensorInfo, const bool IsMemoryManaged=true) const override
Definition: RefWorkloadFactory.cpp:113
armnn::DataLayout
DataLayout
Definition: Types.hpp:62
armnn::IsQAsymmS8
bool IsQAsymmS8(const WorkloadInfo &info)
Definition: RefWorkloadFactory.cpp:73
armnn::LayerType::ConvertFp32ToFp16
@ ConvertFp32ToFp16
armnn::LayerType::L2Normalization
@ L2Normalization
armnn::LayerType::TransposeConvolution2d
@ TransposeConvolution2d
armnn::IsDataType
bool IsDataType(const WorkloadInfo &info)
Definition: RefWorkloadFactory.cpp:32
armnn::LayerType::Input
@ Input
armnn::LayerType::Slice
@ Slice
armnn::IConnectableLayer
Interface for a layer that is connectable to other layers via InputSlots and OutputSlots.
Definition: INetwork.hpp:68
armnn::LayerType::Maximum
@ Maximum
armnn::LayerType::Quantize
@ Quantize
armnn::RefWorkloadFactory::RefWorkloadFactory
RefWorkloadFactory()
Definition: RefWorkloadFactory.cpp:88
armnn::IsQuantizedType
constexpr bool IsQuantizedType()
Definition: TypesUtils.hpp:284
armnn::IsSigned32
bool IsSigned32(const WorkloadInfo &info)
Definition: RefWorkloadFactory.cpp:48
armnn::LayerType::ArgMinMax
@ ArgMinMax
armnn::LayerType::Subtraction
@ Subtraction
armnn::LayerType::SpaceToBatchNd
@ SpaceToBatchNd
armnn::LayerType::Convolution2d
@ Convolution2d
armnn::RefWorkloadFactory::CreateWorkload
std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const override
Definition: RefWorkloadFactory.cpp:144
armnn::RefBackendId
constexpr const char * RefBackendId()
Definition: RefBackendId.hpp:10
armnn::LayerType::Shape
@ Shape
armnn::Layer
Definition: Layer.hpp:217
RefBackendId.hpp
armnn::ModelOptions
std::vector< BackendOptions > ModelOptions
Definition: BackendOptions.hpp:18
armnn::IgnoreUnused
void IgnoreUnused(Ts &&...)
Definition: IgnoreUnused.hpp:14
RefWorkloads.hpp
armnn::DataType::Signed32
@ Signed32
TensorHandle.hpp
armnn::LayerType::Permute
@ Permute
armnn::IsQSymmS8
bool IsQSymmS8(const WorkloadInfo &info)
Definition: RefWorkloadFactory.cpp:68
armnn::LayerType::ConvertFp16ToFp32
@ ConvertFp16ToFp32
armnn::LayerType::QLstm
@ QLstm
armnn::LayerType::Pad
@ Pad
armnn::IsFloat16
bool IsFloat16(const WorkloadInfo &info)
Definition: RefWorkloadFactory.cpp:58
armnn::LayerType::Addition
@ Addition
armnn::LayerType::BatchNormalization
@ BatchNormalization
armnn::LayerType::Reduce
@ Reduce
armnn::RefMemoryManager
Definition: RefMemoryManager.hpp:16
armnn::LayerType::Division
@ Division
armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6
RefWorkloadFactory.hpp
armnn::LayerType::Debug
@ Debug
armnn::LayerType::InstanceNormalization
@ InstanceNormalization
armnn::LayerType::Activation
@ Activation
armnn::LayerType::Normalization
@ Normalization
armnn::LayerType::Comparison
@ Comparison
armnn::LayerType::Stack
@ Stack
armnn::RefWorkloadFactory::GetBackendId
const BackendId & GetBackendId() const override
Definition: RefWorkloadFactory.cpp:93
armnn::IsBFloat16
bool IsBFloat16(const WorkloadInfo &info)
Definition: RefWorkloadFactory.cpp:53
armnn::LayerType
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.
Definition: Types.hpp:466
armnn::RefPermuteFloat16Workload
RefPermuteWorkload< DataType::Float16 > RefPermuteFloat16Workload
Definition: RefPermuteWorkload.hpp:34
armnn::LayerType::Reshape
@ Reshape
armnn::LayerType::Gather
@ Gather
armnn::LayerType::DepthwiseConvolution2d
@ DepthwiseConvolution2d
armnn::LayerType::Fill
@ Fill
armnn::LayerType::Resize
@ Resize
armnn::RefTransposeQAsymm8Workload
RefTransposeWorkload< DataType::QAsymmU8 > RefTransposeQAsymm8Workload
Definition: RefTransposeWorkload.hpp:37
armnn::LayerType::Rank
@ Rank
armnn::RefTransposeFloat16Workload
RefTransposeWorkload< DataType::Float16 > RefTransposeFloat16Workload
Definition: RefTransposeWorkload.hpp:34
armnn::RefPermuteQAsymm8Workload
RefPermuteWorkload< DataType::QAsymmU8 > RefPermuteQAsymm8Workload
Definition: RefPermuteWorkload.hpp:37
armnn::IsQSymmS16
bool IsQSymmS16(const WorkloadInfo &info)
Definition: RefWorkloadFactory.cpp:63
armnn::LayerType::LogicalBinary
@ LogicalBinary
armnn::LayerType::UnidirectionalSequenceLstm
@ UnidirectionalSequenceLstm
armnn::InputQueueDescriptor
MemCopyQueueDescriptor InputQueueDescriptor
Definition: WorkloadData.hpp:91
armnn::LayerType::Pooling2d
@ Pooling2d
armnn::IWorkloadFactory::IsLayerSupported
static bool IsLayerSupported(const BackendId &backendId, const IConnectableLayer &layer, Optional< DataType > dataType, std::string &outReasonIfUnsupported)
Definition: WorkloadFactory.cpp:1518
armnn::LayerType::GatherNd
@ GatherNd
armnn::QueueDescriptor
Definition: WorkloadData.hpp:24
armnn::TensorInfo
Definition: Tensor.hpp:152
armnn::LayerType::Minimum
@ Minimum
armnn::LayerType::Constant
@ Constant
armnn::NullWorkload
Definition: Workload.hpp:27
Layer.hpp
armnn::LayerType::Lstm
@ Lstm
armnn::LayerType::ElementwiseUnary
@ ElementwiseUnary
armnn::LayerType::SpaceToDepth
@ SpaceToDepth
armnn::LayerType::FakeQuantization
@ FakeQuantization
armnn::RefTransposeFloat32Workload
RefTransposeWorkload< DataType::Float32 > RefTransposeFloat32Workload
Definition: RefTransposeWorkload.hpp:35
armnn::WorkloadInfo
Contains information about TensorInfos of a layer.
Definition: WorkloadInfo.hpp:16
armnn::LayerType::StridedSlice
@ StridedSlice
RefTensorHandle.hpp
armnn::LayerType::DetectionPostProcess
@ DetectionPostProcess
armnn::LayerType::Mean
@ Mean
MakeWorkloadHelper.hpp
armnn::LayerType::BatchToSpaceNd
@ BatchToSpaceNd
armnn::RefPermuteFloat32Workload
RefPermuteWorkload< DataType::Float32 > RefPermuteFloat32Workload
Definition: RefPermuteWorkload.hpp:35
armnn::LayerType::DepthToSpace
@ DepthToSpace
armnn::UnaryOperation::LogicalNot
@ LogicalNot
armnn::Optional
Definition: Optional.hpp:270
armnn::ActivationQueueDescriptor
Definition: WorkloadData.hpp:158
armnn::LayerType::Concat
@ Concat
armnn::LayerType::Cast
@ Cast
armnn::LayerType::BatchMatMul
@ BatchMatMul
armnn::LayerType::Convolution3d
@ Convolution3d
armnn::LayerType::Splitter
@ Splitter
armnn::LayerType::LogSoftmax
@ LogSoftmax
MemImportWorkload.hpp
armnn::LayerType::Output
@ Output
armnn::InvalidArgumentException
Definition: Exceptions.hpp:80
armnn::LayerType::Multiplication
@ Multiplication
armnn::LayerType::MemImport
@ MemImport
armnn::LayerType::Prelu
@ Prelu
armnn::LayerType::Dequantize
@ Dequantize
armnn::IsQAsymmU8
bool IsQAsymmU8(const WorkloadInfo &info)
Definition: RefWorkloadFactory.cpp:78
armnn::OutputQueueDescriptor
MemCopyQueueDescriptor OutputQueueDescriptor
Definition: WorkloadData.hpp:92
armnn::QueueDescriptor::m_Inputs
std::vector< ITensorHandle * > m_Inputs
Definition: WorkloadData.hpp:26
armnn::BoostLogSeverityMapping::info
@ info
MemCopyWorkload.hpp
armnn::LayerType::PreCompiled
@ PreCompiled
armnn::RefWorkloadFactory::IsLayerSupported
static bool IsLayerSupported(const Layer &layer, Optional< DataType > dataType, std::string &outReasonIfUnsupported)
Definition: RefWorkloadFactory.cpp:98