32 // Calls CreateWorkload for a layer, and checks the returned pointer is of the correct type.
34 std::unique_ptr<Workload> MakeAndCheckWorkload(Layer& layer,  in MakeAndCheckWorkload()  argument
38     std::unique_ptr<IWorkload> workload = layer.CreateWorkload(factory);
42     layer.SetBackendId(factory.GetBackendId());
43     CHECK(factory.IsLayerSupported(layer, layer.GetDataType(), reasonIfUnsupported, modelOptions));
52     for (auto&& layer : graph.TopologicalSort())  in CreateTensorHandles()
54         layer->CreateTensorHandles(tmpRegistry, factory);  in CreateTensorHandles()
69     // Creates the layer we're testing.  in CreateActivationWorkloadTest()
75     ActivationLayer* const layer = graph.AddLayer<ActivationLayer>(layerDesc, "layer");  in CreateActivationWorkloadTest()  local
78     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateActivationWorkloadTest()
79     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateActivationWorkloadTest()
84     Connect(input, layer, tensorInfo);  in CreateActivationWorkloadTest()
85     Connect(layer, output, tensorInfo);  in CreateActivationWorkloadTest()
90     auto workload = MakeAndCheckWorkload<ActivationWorkload>(*layer, factory);  in CreateActivationWorkloadTest()
110     // Creates the layer we're testing.  in CreateElementwiseWorkloadTest()
111     Layer* const layer = graph.AddLayer<LayerType>("layer");  in CreateElementwiseWorkloadTest()  local
114     Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");  in CreateElementwiseWorkloadTest()
115     Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");  in CreateElementwiseWorkloadTest()
116     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateElementwiseWorkloadTest()
120     Connect(input1, layer, tensorInfo, 0, 0);  in CreateElementwiseWorkloadTest()
121     Connect(input2, layer, tensorInfo, 0, 1);  in CreateElementwiseWorkloadTest()
122     Connect(layer, output, tensorInfo);  in CreateElementwiseWorkloadTest()
126     auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);  in CreateElementwiseWorkloadTest()
141     // Creates the layer we're testing.  in CreateElementwiseBinaryWorkloadTest()
145     Layer* const layer = graph.AddLayer<ElementwiseBinaryLayer>(descriptor, "layer");  in CreateElementwiseBinaryWorkloadTest()  local
148     Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");  in CreateElementwiseBinaryWorkloadTest()
149     Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");  in CreateElementwiseBinaryWorkloadTest()
150     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateElementwiseBinaryWorkloadTest()
154     Connect(input1, layer, tensorInfo, 0, 0);  in CreateElementwiseBinaryWorkloadTest()
155     Connect(input2, layer, tensorInfo, 0, 1);  in CreateElementwiseBinaryWorkloadTest()
156     Connect(layer, output, tensorInfo);  in CreateElementwiseBinaryWorkloadTest()
160     auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);  in CreateElementwiseBinaryWorkloadTest()
176     // Creates the layer we're testing.  in CreateSubtractionWithBlobWorkloadTest()
177     SubtractionLayer* const layer = graph.AddLayer<SubtractionLayer>("layer");  in CreateSubtractionWithBlobWorkloadTest()  local
184     layer->SetAdditionalInfoForObject(activationDesc);  in CreateSubtractionWithBlobWorkloadTest()
187     Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");  in CreateSubtractionWithBlobWorkloadTest()
188     Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");  in CreateSubtractionWithBlobWorkloadTest()
189     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateSubtractionWithBlobWorkloadTest()
193     Connect(input1, layer, tensorInfo, 0, 0);  in CreateSubtractionWithBlobWorkloadTest()
194     Connect(input2, layer, tensorInfo, 0, 1);  in CreateSubtractionWithBlobWorkloadTest()
195     Connect(layer, output, tensorInfo);  in CreateSubtractionWithBlobWorkloadTest()
198     // Check that the additional information can be queried from the layer  in CreateSubtractionWithBlobWorkloadTest()
200         activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();  in CreateSubtractionWithBlobWorkloadTest()
209     auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);  in CreateSubtractionWithBlobWorkloadTest()
235     // Creates the layer we're testing.  in CreateMultiplicationWithBlobWorkloadTest()
236     MultiplicationLayer* const layer = graph.AddLayer<MultiplicationLayer>("layer");  in CreateMultiplicationWithBlobWorkloadTest()  local
243     layer->SetAdditionalInfoForObject(activationDesc);  in CreateMultiplicationWithBlobWorkloadTest()
246     Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");  in CreateMultiplicationWithBlobWorkloadTest()
247     Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");  in CreateMultiplicationWithBlobWorkloadTest()
248     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateMultiplicationWithBlobWorkloadTest()
252     Connect(input1, layer, tensorInfo, 0, 0);  in CreateMultiplicationWithBlobWorkloadTest()
253     Connect(input2, layer, tensorInfo, 0, 1);  in CreateMultiplicationWithBlobWorkloadTest()
254     Connect(layer, output, tensorInfo);  in CreateMultiplicationWithBlobWorkloadTest()
257     // Check that the additional information can be queried from the layer  in CreateMultiplicationWithBlobWorkloadTest()
259         activationDescPtr = layer->GetAdditionalInformation<ActivationDescriptor>();  in CreateMultiplicationWithBlobWorkloadTest()
268     auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);  in CreateMultiplicationWithBlobWorkloadTest()
291     // Creates the layer we're testing.  in CreateAdditionWithBlobWorkloadTest()
292     AdditionLayer* const layer = graph.AddLayer<AdditionLayer>("layer");  in CreateAdditionWithBlobWorkloadTest()  local
299     layer->SetAdditionalInfoForObject(activationDesc);  in CreateAdditionWithBlobWorkloadTest()
302     Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");  in CreateAdditionWithBlobWorkloadTest()
303     Layer* const input2 = graph.AddLayer<InputLayer>(2, "input2");  in CreateAdditionWithBlobWorkloadTest()
304     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateAdditionWithBlobWorkloadTest()
308     Connect(input1, layer, tensorInfo, 0, 0);  in CreateAdditionWithBlobWorkloadTest()
309     Connect(input2, layer, tensorInfo, 0, 1);  in CreateAdditionWithBlobWorkloadTest()
310     Connect(layer, output, tensorInfo);  in CreateAdditionWithBlobWorkloadTest()
313     // Check that the additional information can be queried from the layer  in CreateAdditionWithBlobWorkloadTest()
315         activationDescPtr = layer->template GetAdditionalInformation<ActivationDescriptor>();  in CreateAdditionWithBlobWorkloadTest()
324     auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);  in CreateAdditionWithBlobWorkloadTest()
349     Layer* const layer = graph.AddLayer<armnn::ElementwiseUnaryLayer>(desc, "layer");  in CreateElementwiseUnaryWorkloadTest()  local
351     Layer* const input  = graph.AddLayer<InputLayer>(0, "input");  in CreateElementwiseUnaryWorkloadTest()
352     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateElementwiseUnaryWorkloadTest()
355     Connect(input, layer, tensorInfo, 0, 0);  in CreateElementwiseUnaryWorkloadTest()
356     Connect(layer, output, tensorInfo, 0, 0);  in CreateElementwiseUnaryWorkloadTest()
359     auto workload = MakeAndCheckWorkload<WorkloadType>(*layer, factory);  in CreateElementwiseUnaryWorkloadTest()
383     // Creates the layer we're testing.  in CreateBatchNormalizationWorkloadTest()
388 …BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer");  in CreateBatchNormalizationWorkloadTest()  local
391     layer->m_Mean     = std::make_unique<ScopedTensorHandle>(weightInfo);  in CreateBatchNormalizationWorkloadTest()
392     layer->m_Variance = std::make_unique<ScopedTensorHandle>(weightInfo);  in CreateBatchNormalizationWorkloadTest()
393     layer->m_Beta     = std::make_unique<ScopedTensorHandle>(weightInfo);  in CreateBatchNormalizationWorkloadTest()
394     layer->m_Gamma    = std::make_unique<ScopedTensorHandle>(weightInfo);  in CreateBatchNormalizationWorkloadTest()
395     layer->m_Mean->Allocate();  in CreateBatchNormalizationWorkloadTest()
396     layer->m_Variance->Allocate();  in CreateBatchNormalizationWorkloadTest()
397     layer->m_Beta->Allocate();  in CreateBatchNormalizationWorkloadTest()
398     layer->m_Gamma->Allocate();  in CreateBatchNormalizationWorkloadTest()
401     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateBatchNormalizationWorkloadTest()
402     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateBatchNormalizationWorkloadTest()
406     Connect(input, layer, tensorInfo);  in CreateBatchNormalizationWorkloadTest()
407     Connect(layer, output, tensorInfo);  in CreateBatchNormalizationWorkloadTest()
411     auto workload = MakeAndCheckWorkload<BatchNormalizationWorkloadType>(*layer, factory);  in CreateBatchNormalizationWorkloadTest()
441     // Creates the layer we're testing.  in CreateBatchNormalizationWithBlobWorkloadTest()
446 …BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer");  in CreateBatchNormalizationWithBlobWorkloadTest()  local
449     layer->m_Mean     = std::make_unique<ScopedTensorHandle>(weightInfo);  in CreateBatchNormalizationWithBlobWorkloadTest()
450     layer->m_Variance = std::make_unique<ScopedTensorHandle>(weightInfo);  in CreateBatchNormalizationWithBlobWorkloadTest()
451     layer->m_Beta     = std::make_unique<ScopedTensorHandle>(weightInfo);  in CreateBatchNormalizationWithBlobWorkloadTest()
452     layer->m_Gamma    = std::make_unique<ScopedTensorHandle>(weightInfo);  in CreateBatchNormalizationWithBlobWorkloadTest()
453     layer->m_Mean->Allocate();  in CreateBatchNormalizationWithBlobWorkloadTest()
454     layer->m_Variance->Allocate();  in CreateBatchNormalizationWithBlobWorkloadTest()
455     layer->m_Beta->Allocate();  in CreateBatchNormalizationWithBlobWorkloadTest()
456     layer->m_Gamma->Allocate();  in CreateBatchNormalizationWithBlobWorkloadTest()
463     layer->SetAdditionalInfoForObject(activationDesc);  in CreateBatchNormalizationWithBlobWorkloadTest()
465     // Check that the additional information can be queried from the layer  in CreateBatchNormalizationWithBlobWorkloadTest()
466 …std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<Activati…  in CreateBatchNormalizationWithBlobWorkloadTest()
474     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateBatchNormalizationWithBlobWorkloadTest()
475     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateBatchNormalizationWithBlobWorkloadTest()
479     Connect(input, layer, tensorInfo);  in CreateBatchNormalizationWithBlobWorkloadTest()
480     Connect(layer, output, tensorInfo);  in CreateBatchNormalizationWithBlobWorkloadTest()
484     auto workload = MakeAndCheckWorkload<BatchNormalizationWorkloadType>(*layer, factory);  in CreateBatchNormalizationWithBlobWorkloadTest()
513     // Creates the layer we're testing.
527     Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");  local
537     Layer* const input = graph.AddLayer<InputLayer>(0, "input");
539     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
545     Connect(input, layer, TensorInfo(inputShape, DataType, inputsQScale));
546     Connect(weights, layer, weightsTensorInfo, 0, 1);
547     Connect(layer, output, TensorInfo(outputShape, DataType, outputQScale));
551     auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
577     // Creates the layer we're testing.
591     Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");  local
607     layer->SetAdditionalInfoForObject(activationDesc);
609     // Check that the additional information can be queried from the layer
610 …std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<Activati…
619     Layer* const input = graph.AddLayer<InputLayer>(0, "input");
622     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
630     Connect(input, layer, TensorInfo(inputShape, DataType, inputsQScale));
631     Connect(weights, layer, weightsTensorInfo, 0, 1);
632     Connect(bias, layer, biasTensorInfo, 0, 2);
633     Connect(layer, output, TensorInfo(outputShape, DataType, outputQScale));
637     auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
670     // Creates the layer we're testing.
684     Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");  local
697     Layer* const input = graph.AddLayer<InputLayer>(0, "input");
700     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
703     Connect(input, layer, TensorInfo(inputShape, DataType));
704     Connect(weights, layer, weightsTensorInfo, 0, 1);
705     Connect(bias, layer, biasTensorInfo, 0, 2);
706     Connect(layer, output, TensorInfo(outputShape, DataType, outputQScale));
710     auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory, modelOptions);
740     LstmLayer* const layer = graph.AddLayer<LstmLayer>(layerDesc, "layer");  in CreateLstmWorkloadTest()  local
746     layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
748     layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
750     layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
752     layer->m_BasicParameters.m_RecurrentToForgetWeights = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
754     layer->m_BasicParameters.m_RecurrentToCellWeights = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
756     layer->m_BasicParameters.m_RecurrentToOutputWeights = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
758     layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
760     layer->m_BasicParameters.m_CellBias = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
762     layer->m_BasicParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
765     layer->m_BasicParameters.m_InputToForgetWeights->Allocate();  in CreateLstmWorkloadTest()
766     layer->m_BasicParameters.m_InputToCellWeights->Allocate();  in CreateLstmWorkloadTest()
767     layer->m_BasicParameters.m_InputToOutputWeights->Allocate();  in CreateLstmWorkloadTest()
768     layer->m_BasicParameters.m_RecurrentToForgetWeights->Allocate();  in CreateLstmWorkloadTest()
769     layer->m_BasicParameters.m_RecurrentToCellWeights->Allocate();  in CreateLstmWorkloadTest()
770     layer->m_BasicParameters.m_RecurrentToOutputWeights->Allocate();  in CreateLstmWorkloadTest()
771     layer->m_BasicParameters.m_ForgetGateBias->Allocate();  in CreateLstmWorkloadTest()
772     layer->m_BasicParameters.m_CellBias->Allocate();  in CreateLstmWorkloadTest()
773     layer->m_BasicParameters.m_OutputGateBias->Allocate();  in CreateLstmWorkloadTest()
778         layer->m_PeepholeParameters.m_CellToForgetWeights = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
780         layer->m_PeepholeParameters.m_CellToOutputWeights = std::make_unique<ScopedTensorHandle>  in CreateLstmWorkloadTest()
782         layer->m_PeepholeParameters.m_CellToForgetWeights->Allocate();  in CreateLstmWorkloadTest()
783         layer->m_PeepholeParameters.m_CellToOutputWeights->Allocate();  in CreateLstmWorkloadTest()
787     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateLstmWorkloadTest()
788     Layer* const outputStateIn = graph.AddLayer<InputLayer>(1, "outputStateIn");  in CreateLstmWorkloadTest()
789     Layer* const cellStateIn = graph.AddLayer<InputLayer>(2, "cellStateIn");  in CreateLstmWorkloadTest()
790     Layer* const scratchBuffer = graph.AddLayer<OutputLayer>(0, "scratchBuffer");  in CreateLstmWorkloadTest()
791     Layer* const outputStateOut = graph.AddLayer<OutputLayer>(1, "outputStateOut");  in CreateLstmWorkloadTest()
792     Layer* const cellStateOut = graph.AddLayer<OutputLayer>(2, "cellStateOut");  in CreateLstmWorkloadTest()
793     Layer* const output = graph.AddLayer<OutputLayer>(3, "output");  in CreateLstmWorkloadTest()
801     Connect(input, layer, lstmTensorInfo1, 0, 0);  in CreateLstmWorkloadTest()
802     Connect(cellStateIn, layer, lstmTensorInfo2, 0, 1);  in CreateLstmWorkloadTest()
803     Connect(outputStateIn, layer, lstmTensorInfo3, 0, 2);  in CreateLstmWorkloadTest()
804     Connect(layer, scratchBuffer, lstmTensorInfoScratchBuff, 0, 0);  in CreateLstmWorkloadTest()
805     Connect(layer, outputStateOut, lstmTensorInfo3, 1, 0);  in CreateLstmWorkloadTest()
806     Connect(layer, cellStateOut, lstmTensorInfo2, 2, 0);  in CreateLstmWorkloadTest()
807     Connect(layer, output, lstmTensorInfo3, 3, 0);  in CreateLstmWorkloadTest()
812     auto workload = MakeAndCheckWorkload<LstmWorkload>(*layer, factory);  in CreateLstmWorkloadTest()
832     auto layer = graph.AddLayer<QuantizedLstmLayer>("quantizedLstmlayer");  in CreateQuantizedLstmWorkloadTest()  local
867     layer->m_QuantizedLstmParameters.m_InputToInputWeights =  in CreateQuantizedLstmWorkloadTest()
869     layer->m_QuantizedLstmParameters.m_InputToForgetWeights =  in CreateQuantizedLstmWorkloadTest()
871     layer->m_QuantizedLstmParameters.m_InputToCellWeights =  in CreateQuantizedLstmWorkloadTest()
873     layer->m_QuantizedLstmParameters.m_InputToOutputWeights =  in CreateQuantizedLstmWorkloadTest()
876     layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights =  in CreateQuantizedLstmWorkloadTest()
878     layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights =  in CreateQuantizedLstmWorkloadTest()
880     layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights =  in CreateQuantizedLstmWorkloadTest()
882     layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights =  in CreateQuantizedLstmWorkloadTest()
885 … layer->m_QuantizedLstmParameters.m_InputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);  in CreateQuantizedLstmWorkloadTest()
886 …layer->m_QuantizedLstmParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);  in CreateQuantizedLstmWorkloadTest()
887     layer->m_QuantizedLstmParameters.m_CellBias = std::make_unique<ScopedTensorHandle>(biasInfo);  in CreateQuantizedLstmWorkloadTest()
888 …layer->m_QuantizedLstmParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);  in CreateQuantizedLstmWorkloadTest()
891     layer->m_QuantizedLstmParameters.m_InputToInputWeights->Allocate();  in CreateQuantizedLstmWorkloadTest()
892     layer->m_QuantizedLstmParameters.m_InputToForgetWeights->Allocate();  in CreateQuantizedLstmWorkloadTest()
893     layer->m_QuantizedLstmParameters.m_InputToCellWeights->Allocate();  in CreateQuantizedLstmWorkloadTest()
894     layer->m_QuantizedLstmParameters.m_InputToOutputWeights->Allocate();  in CreateQuantizedLstmWorkloadTest()
896     layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights->Allocate();  in CreateQuantizedLstmWorkloadTest()
897     layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights->Allocate();  in CreateQuantizedLstmWorkloadTest()
898     layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights->Allocate();  in CreateQuantizedLstmWorkloadTest()
899     layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights->Allocate();  in CreateQuantizedLstmWorkloadTest()
901     layer->m_QuantizedLstmParameters.m_InputGateBias->Allocate();  in CreateQuantizedLstmWorkloadTest()
902     layer->m_QuantizedLstmParameters.m_ForgetGateBias->Allocate();  in CreateQuantizedLstmWorkloadTest()
903     layer->m_QuantizedLstmParameters.m_CellBias->Allocate();  in CreateQuantizedLstmWorkloadTest()
904     layer->m_QuantizedLstmParameters.m_OutputGateBias->Allocate();  in CreateQuantizedLstmWorkloadTest()
907     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateQuantizedLstmWorkloadTest()
908     Layer* const cellStateIn = graph.AddLayer<InputLayer>(1, "cellStateIn");  in CreateQuantizedLstmWorkloadTest()
909     Layer* const outputStateIn = graph.AddLayer<InputLayer>(2, "outputStateIn");  in CreateQuantizedLstmWorkloadTest()
911     Layer* const cellStateOut = graph.AddLayer<OutputLayer>(0, "cellStateOut");  in CreateQuantizedLstmWorkloadTest()
912     Layer* const outputStateOut = graph.AddLayer<OutputLayer>(1, "outputStateOut");  in CreateQuantizedLstmWorkloadTest()
931     Connect(input, layer, inputInfo, 0, 0);  in CreateQuantizedLstmWorkloadTest()
932     Connect(cellStateIn, layer, cellStateInfo, 0, 1);  in CreateQuantizedLstmWorkloadTest()
933     Connect(outputStateIn, layer, outputStateInfo, 0, 2);  in CreateQuantizedLstmWorkloadTest()
935     Connect(layer, cellStateOut, cellStateInfo, 0, 0);  in CreateQuantizedLstmWorkloadTest()
936     Connect(layer, outputStateOut, outputStateInfo, 1, 0);  in CreateQuantizedLstmWorkloadTest()
940     // Create workload and check layer support  in CreateQuantizedLstmWorkloadTest()
941     auto workload = MakeAndCheckWorkload<QuantizedLstmWorkload>(*layer, factory);  in CreateQuantizedLstmWorkloadTest()
988     QLstmLayer* const layer = graph.AddLayer<QLstmLayer>(layerDesc, "qLstm");  in CreateQLstmWorkloadTest()  local
1031 …layer->m_BasicParameters.m_InputToForgetWeights = std::make_unique<ScopedTensorHandle>(inputWeight…  in CreateQLstmWorkloadTest()
1032 …layer->m_BasicParameters.m_InputToCellWeights = std::make_unique<ScopedTensorHandle>(inputWeightsI…  in CreateQLstmWorkloadTest()
1033 …layer->m_BasicParameters.m_InputToOutputWeights = std::make_unique<ScopedTensorHandle>(inputWeight…  in CreateQLstmWorkloadTest()
1035     layer->m_BasicParameters.m_RecurrentToForgetWeights =  in CreateQLstmWorkloadTest()
1037     layer->m_BasicParameters.m_RecurrentToCellWeights =  in CreateQLstmWorkloadTest()
1039     layer->m_BasicParameters.m_RecurrentToOutputWeights =  in CreateQLstmWorkloadTest()
1042     layer->m_BasicParameters.m_ForgetGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);  in CreateQLstmWorkloadTest()
1043     layer->m_BasicParameters.m_CellBias = std::make_unique<ScopedTensorHandle>(biasInfo);  in CreateQLstmWorkloadTest()
1044     layer->m_BasicParameters.m_OutputGateBias = std::make_unique<ScopedTensorHandle>(biasInfo);  in CreateQLstmWorkloadTest()
1046     layer->m_LayerNormParameters.m_ForgetLayerNormWeights =  in CreateQLstmWorkloadTest()
1048     layer->m_LayerNormParameters.m_CellLayerNormWeights =  in CreateQLstmWorkloadTest()
1050     layer->m_LayerNormParameters.m_OutputLayerNormWeights =  in CreateQLstmWorkloadTest()
1053     layer->m_BasicParameters.m_InputToForgetWeights->Allocate();  in CreateQLstmWorkloadTest()
1054     layer->m_BasicParameters.m_InputToCellWeights->Allocate();  in CreateQLstmWorkloadTest()
1055     layer->m_BasicParameters.m_InputToOutputWeights->Allocate();  in CreateQLstmWorkloadTest()
1057     layer->m_BasicParameters.m_RecurrentToForgetWeights->Allocate();  in CreateQLstmWorkloadTest()
1058     layer->m_BasicParameters.m_RecurrentToCellWeights->Allocate();  in CreateQLstmWorkloadTest()
1059     layer->m_BasicParameters.m_RecurrentToOutputWeights->Allocate();  in CreateQLstmWorkloadTest()
1061     layer->m_BasicParameters.m_ForgetGateBias->Allocate();  in CreateQLstmWorkloadTest()
1062     layer->m_BasicParameters.m_CellBias->Allocate();  in CreateQLstmWorkloadTest()
1063     layer->m_BasicParameters.m_OutputGateBias->Allocate();  in CreateQLstmWorkloadTest()
1065     layer->m_LayerNormParameters.m_ForgetLayerNormWeights->Allocate();  in CreateQLstmWorkloadTest()
1066     layer->m_LayerNormParameters.m_CellLayerNormWeights->Allocate();  in CreateQLstmWorkloadTest()
1067     layer->m_LayerNormParameters.m_OutputLayerNormWeights->Allocate();  in CreateQLstmWorkloadTest()
1070     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateQLstmWorkloadTest()
1071     Layer* const outputStateIn = graph.AddLayer<InputLayer>(1, "outputStateIn");  in CreateQLstmWorkloadTest()
1072     Layer* const cellStateIn = graph.AddLayer<InputLayer>(2, "cellStateIn");  in CreateQLstmWorkloadTest()
1074     Layer* const outputStateOut = graph.AddLayer<OutputLayer>(0, "outputStateOut");  in CreateQLstmWorkloadTest()
1075     Layer* const cellStateOut = graph.AddLayer<OutputLayer>(1, "cellStateOut");  in CreateQLstmWorkloadTest()
1076     Layer* const output = graph.AddLayer<OutputLayer>(2, "output");  in CreateQLstmWorkloadTest()
1095     Connect(input, layer, inputInfo, 0, 0);  in CreateQLstmWorkloadTest()
1096     Connect(outputStateIn, layer, outputStateInfo, 0, 1);  in CreateQLstmWorkloadTest()
1097     Connect(cellStateIn, layer, cellStateInfo, 0, 2);  in CreateQLstmWorkloadTest()
1099     Connect(layer, outputStateOut, outputStateInfo, 0, 0);  in CreateQLstmWorkloadTest()
1100     Connect(layer, cellStateOut, cellStateInfo, 1, 0);  in CreateQLstmWorkloadTest()
1101     Connect(layer, output, outputStateInfo, 2, 0);  in CreateQLstmWorkloadTest()
1106     auto workload = MakeAndCheckWorkload<QLstmWorkload>(*layer, factory);  in CreateQLstmWorkloadTest()
1132     // Creates the layer we're testing.  in CreateDirectConvolution2dWorkloadTest()
1142     Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");  in CreateDirectConvolution2dWorkloadTest()  local
1155     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateDirectConvolution2dWorkloadTest()
1158     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateDirectConvolution2dWorkloadTest()
1166     Connect(input, layer, TensorInfo({2, 3, 6, 6}, DataType, inputsQScale));  in CreateDirectConvolution2dWorkloadTest()
1167     Connect(weights, layer, weightsTensorInfo, 0, 1);  in CreateDirectConvolution2dWorkloadTest()
1168     Connect(bias, layer, biasTensorInfo, 0, 2);  in CreateDirectConvolution2dWorkloadTest()
1169     Connect(layer, output, TensorInfo({2, 2, 6, 6}, DataType, outputQScale));  in CreateDirectConvolution2dWorkloadTest()
1173     auto workload = MakeAndCheckWorkload<Convolution2dWorkload>(*layer, factory);  in CreateDirectConvolution2dWorkloadTest()
1195     // Creates the layer we're testing.  in CreateDepthwiseConvolution2dWorkloadTest()
1215 …DepthwiseConvolution2dLayer* const layer = graph.AddLayer<DepthwiseConvolution2dLayer>(layerDesc, …  in CreateDepthwiseConvolution2dWorkloadTest()  local
1219     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateDepthwiseConvolution2dWorkloadTest()
1220     Layer* const weights = graph.AddLayer<ConstantLayer>("weights");  in CreateDepthwiseConvolution2dWorkloadTest()
1221     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateDepthwiseConvolution2dWorkloadTest()
1224     Connect(input, layer, TensorInfo(inputShape, DataType, inputsQScale));  in CreateDepthwiseConvolution2dWorkloadTest()
1225     Connect(weights, layer, TensorInfo(weightShape, DataType, inputsQScale, 0.0f, true), 0, 1);  in CreateDepthwiseConvolution2dWorkloadTest()
1226     Connect(layer, output, TensorInfo(outputShape, DataType, outputQScale));  in CreateDepthwiseConvolution2dWorkloadTest()
1230     auto workload = MakeAndCheckWorkload<DepthwiseConvolution2dFloat32Workload>(*layer, factory);  in CreateDepthwiseConvolution2dWorkloadTest()
1253     // Creates the layer we're testing.  in CreateFullyConnectedWorkloadTest()
1258     FullyConnectedLayer* const layer = graph.AddLayer<FullyConnectedLayer>(layerDesc, "layer");  in CreateFullyConnectedWorkloadTest()  local
1267     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateFullyConnectedWorkloadTest()
1269     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateFullyConnectedWorkloadTest()
1275     Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);  in CreateFullyConnectedWorkloadTest()
1276     Connect(weights, layer, weightsTensorInfo, 0, 1);  in CreateFullyConnectedWorkloadTest()
1277     Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));  in CreateFullyConnectedWorkloadTest()
1281     auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);  in CreateFullyConnectedWorkloadTest()
1298     // Creates the layer we're testing.  in CreateFullyConnectedWithBlobWorkloadTest()
1303     FullyConnectedLayer* const layer = graph.AddLayer<FullyConnectedLayer>(layerDesc, "layer");  in CreateFullyConnectedWithBlobWorkloadTest()  local
1318     layer->SetAdditionalInfoForObject(activationDesc);  in CreateFullyConnectedWithBlobWorkloadTest()
1320     // Check that the additional information can be queried from the layer  in CreateFullyConnectedWithBlobWorkloadTest()
1321 …std::shared_ptr<ActivationDescriptor> activationDescPtr = layer->GetAdditionalInformation<Activati…  in CreateFullyConnectedWithBlobWorkloadTest()
1328     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateFullyConnectedWithBlobWorkloadTest()
1331     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateFullyConnectedWithBlobWorkloadTest()
1339     Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);  in CreateFullyConnectedWithBlobWorkloadTest()
1340     Connect(weights, layer, weightsTensorInfo, 0, 1);  in CreateFullyConnectedWithBlobWorkloadTest()
1341     Connect(biases, layer, biasesTensorInfo, 0, 2);  in CreateFullyConnectedWithBlobWorkloadTest()
1342     Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));  in CreateFullyConnectedWithBlobWorkloadTest()
1346     auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);  in CreateFullyConnectedWithBlobWorkloadTest()
1373     // Creates the layer we're testing.  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1379     FullyConnectedLayer* const layer = graph.AddLayer<FullyConnectedLayer>(layerDesc, "layer");  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()  local
1385     Layer* const input   = graph.AddLayer<InputLayer>(1, "input");  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1386     Layer* const weights = graph.AddLayer<InputLayer>(2, "weights");  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1387     Layer* const biases  = graph.AddLayer<InputLayer>(3, "biases");  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1388     Layer* const output  = graph.AddLayer<OutputLayer>(0, "output");  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1391     Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType, inputsQScale), 0, 0);  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1392     Connect(weights, layer, TensorInfo({7, 20}, DataType, inputsQScale), 0, 1);  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1393     Connect(biases, layer, TensorInfo({7}, GetBiasDataType(DataType), inputsQScale), 0, 2);  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1394     Connect(layer, output, TensorInfo({3, 7}, DataType, outputQScale));  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1398     auto workload = MakeAndCheckWorkload<FullyConnectedWorkload>(*layer, factory);  in CreateFullyConnectedWorkloadWeightsBiasesAsInputsTest()
1418     // Creates the layer we're testing.  in CreateNormalizationWorkloadTest()
1428     NormalizationLayer* layer = graph.AddLayer<NormalizationLayer>(layerDesc, "layer");  in CreateNormalizationWorkloadTest()  local
1431     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateNormalizationWorkloadTest()
1432     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateNormalizationWorkloadTest()
1442     Connect(input, layer, inputTensorInfo);  in CreateNormalizationWorkloadTest()
1443     Connect(layer, output, outputTensorInfo);  in CreateNormalizationWorkloadTest()
1447     auto workload = MakeAndCheckWorkload<NormalizationWorkload>(*layer, factory);  in CreateNormalizationWorkloadTest()
1470     // Creates the layer we're testing.  in CreatePooling2dWorkloadTest()
1484     Pooling2dLayer* const layer = graph.AddLayer<Pooling2dLayer>(layerDesc, "layer");  in CreatePooling2dWorkloadTest()  local
1487     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreatePooling2dWorkloadTest()
1488     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreatePooling2dWorkloadTest()
1494     Connect(input, layer, TensorInfo(inputShape, DataType));  in CreatePooling2dWorkloadTest()
1495     Connect(layer, output, TensorInfo(outputShape, DataType));  in CreatePooling2dWorkloadTest()
1499     auto workload = MakeAndCheckWorkload<Pooling2dWorkload>(*layer, factory);  in CreatePooling2dWorkloadTest()
1525     // Create the layer we're testing.  in CreateSoftmaxWorkloadTest()
1533     Layer* const layer = graph.AddLayer<SoftmaxLayer>(softmaxDescriptor, "layer");  in CreateSoftmaxWorkloadTest()  local
1535     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateSoftmaxWorkloadTest()
1536     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateSoftmaxWorkloadTest()
1551     Connect(input, layer, tensorInfo);  in CreateSoftmaxWorkloadTest()
1552     Connect(layer, output, tensorInfo);  in CreateSoftmaxWorkloadTest()
1556     auto workload = MakeAndCheckWorkload<SoftmaxWorkload>(*layer, factory);  in CreateSoftmaxWorkloadTest()
1570     // Create the layer we're testing.  in CreateSplitterWorkloadTest()
1582     Layer* const layer = graph.AddLayer<SplitterLayer>(layerDesc, "layer");  in CreateSplitterWorkloadTest()  local
1585     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateSplitterWorkloadTest()
1586     Layer* const output0 = graph.AddLayer<OutputLayer>(0, "output0");  in CreateSplitterWorkloadTest()
1587     Layer* const output1 = graph.AddLayer<OutputLayer>(1, "output1");  in CreateSplitterWorkloadTest()
1588     Layer* const output2 = graph.AddLayer<OutputLayer>(2, "output2");  in CreateSplitterWorkloadTest()
1592     Connect(input, layer, tensorInfo);  in CreateSplitterWorkloadTest()
1598     Connect(layer, output0, output0Info, 0, 0);  in CreateSplitterWorkloadTest()
1599     Connect(layer, output1, output1Info, 1, 0);  in CreateSplitterWorkloadTest()
1600     Connect(layer, output2, output2Info, 2, 0);  in CreateSplitterWorkloadTest()
1605     auto workload = MakeAndCheckWorkload<SplitterWorkload>(*layer, factory);  in CreateSplitterWorkloadTest()
1637     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateSplitterConcatWorkloadTest()
1650     // create splitter layer  in CreateSplitterConcatWorkloadTest()
1651     Layer* const splitter = graph.AddLayer<SplitterLayer>(splitterViews, "splitter");  in CreateSplitterConcatWorkloadTest()
1665     // create concat layer  in CreateSplitterConcatWorkloadTest()
1666     Layer* const concat = graph.AddLayer<ConcatLayer>(concatViews, "concat");  in CreateSplitterConcatWorkloadTest()
1669     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateSplitterConcatWorkloadTest()
1710     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1724     Layer* const splitter = graph.AddLayer<SplitterLayer>(splitterViews, "splitter");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1728     Layer* const activ0_0 = graph.AddLayer<ActivationLayer>(activationDesc, "activ0_0");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1729     Layer* const activ0_1 = graph.AddLayer<ActivationLayer>(activationDesc, "activ0_1");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1730     Layer* const activ1_0 = graph.AddLayer<ActivationLayer>(activationDesc, "activ1_0");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1731     Layer* const activ1_1 = graph.AddLayer<ActivationLayer>(activationDesc, "activ1_1");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1733     Layer* const output1 = graph.AddLayer<OutputLayer>(1, "output1");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1734     Layer* const output2 = graph.AddLayer<OutputLayer>(2, "output2");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1735     Layer* const output3 = graph.AddLayer<OutputLayer>(3, "output3");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1736     Layer* const output4 = graph.AddLayer<OutputLayer>(4, "output4");  in CreateSplitterMultipleInputsOneOutputWorkloadTest()
1785     // Creates the layer we're testing.  in CreateResizeBilinearWorkloadTest()
1792     Layer* const layer = graph.AddLayer<ResizeLayer>(resizeDesc, "resize");  in CreateResizeBilinearWorkloadTest()  local
1795     Layer* const input  = graph.AddLayer<InputLayer>(0, "input");  in CreateResizeBilinearWorkloadTest()
1796     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateResizeBilinearWorkloadTest()
1801     Connect(input, layer, inputTensorInfo);  in CreateResizeBilinearWorkloadTest()
1802     Connect(layer, output, outputTensorInfo);  in CreateResizeBilinearWorkloadTest()
1806     auto workload = MakeAndCheckWorkload<ResizeWorkload>(*layer, factory);  in CreateResizeBilinearWorkloadTest()
1822     Layer* const layer = graph.AddLayer<BatchToSpaceNdLayer>(desc, "batchToSpace");  in CreateBatchToSpaceNdWorkloadTest()  local
1825     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateBatchToSpaceNdWorkloadTest()
1826     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateBatchToSpaceNdWorkloadTest()
1831     Connect(input, layer, tensorInfo);  in CreateBatchToSpaceNdWorkloadTest()
1832     Connect(layer, output, tensorInfo);  in CreateBatchToSpaceNdWorkloadTest()
1837     auto workload = MakeAndCheckWorkload<BatchToSpaceNdWorkload>(*layer, factory);  in CreateBatchToSpaceNdWorkloadTest()
1850     // Create the layer we're testing.  in CreateLogSoftmaxWorkloadTest()
1858     Layer* const layer = graph.AddLayer<LogSoftmaxLayer>(logSoftmaxDescriptor, "layer");  in CreateLogSoftmaxWorkloadTest()  local
1860     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateLogSoftmaxWorkloadTest()
1861     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateLogSoftmaxWorkloadTest()
1866     Connect(input, layer, tensorInfo);  in CreateLogSoftmaxWorkloadTest()
1867     Connect(layer, output, tensorInfo);  in CreateLogSoftmaxWorkloadTest()
1871     auto workload = MakeAndCheckWorkload<LogSoftmaxWorkload>(*layer, factory);  in CreateLogSoftmaxWorkloadTest()
1885     // Creates the layer we're testing.  in CreateL2NormalizationWorkloadTest()
1889     Layer* const layer = graph.AddLayer<L2NormalizationLayer>(layerDesc, "l2norm");  in CreateL2NormalizationWorkloadTest()  local
1892     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateL2NormalizationWorkloadTest()
1893     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateL2NormalizationWorkloadTest()
1903     Connect(input, layer, inputTensorInfo);  in CreateL2NormalizationWorkloadTest()
1904     Connect(layer, output, outputTensorInfo);  in CreateL2NormalizationWorkloadTest()
1908     auto workload = MakeAndCheckWorkload<L2NormalizationWorkload>(*layer, factory);  in CreateL2NormalizationWorkloadTest()
1923     // Creates the layer we're testing.  in CreateReshapeWorkloadTest()
1927     Layer* const layer = graph.AddLayer<ReshapeLayer>(reshapeDesc, "layer");  in CreateReshapeWorkloadTest()  local
1930     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateReshapeWorkloadTest()
1931     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateReshapeWorkloadTest()
1936     Connect(input, layer, inputTensorInfo);  in CreateReshapeWorkloadTest()
1937     Connect(layer, output, outputTensorInfo);  in CreateReshapeWorkloadTest()
1941     auto workload = MakeAndCheckWorkload<ReshapeWorkload>(*layer, factory);  in CreateReshapeWorkloadTest()
1955     // Creates the layer we're testing.  in CreateConvertFp16ToFp32WorkloadTest()
1956 …ConvertFp16ToFp32Layer* const layer = graph.AddLayer<ConvertFp16ToFp32Layer>("Fp16ToFp32Converter"…  in CreateConvertFp16ToFp32WorkloadTest()  local
1959     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateConvertFp16ToFp32WorkloadTest()
1960     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateConvertFp16ToFp32WorkloadTest()
1965     Connect(input, layer, inputTensorInfo);  in CreateConvertFp16ToFp32WorkloadTest()
1966     Connect(layer, output, outputTensorInfo);  in CreateConvertFp16ToFp32WorkloadTest()
1970     auto workload = MakeAndCheckWorkload<ConvertFp16ToFp32Float32Workload>(*layer, factory);  in CreateConvertFp16ToFp32WorkloadTest()
1984     // Creates the layer we're testing.  in CreateConvertFp32ToFp16WorkloadTest()
1985 …ConvertFp32ToFp16Layer* const layer = graph.AddLayer<ConvertFp32ToFp16Layer>("Fp32ToFp16Converter"…  in CreateConvertFp32ToFp16WorkloadTest()  local
1988     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateConvertFp32ToFp16WorkloadTest()
1989     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateConvertFp32ToFp16WorkloadTest()
1994     Connect(input, layer, inputTensorInfo);  in CreateConvertFp32ToFp16WorkloadTest()
1995     Connect(layer, output, outputTensorInfo);  in CreateConvertFp32ToFp16WorkloadTest()
1999     auto workload = MakeAndCheckWorkload<ConvertFp32ToFp16Float16Workload>(*layer, factory);  in CreateConvertFp32ToFp16WorkloadTest()
2015     // Creates the layer we're testing.  in CreateMeanWorkloadTest()
2016     Layer* const layer = graph.AddLayer<MeanLayer>(descriptor, "mean");  in CreateMeanWorkloadTest()  local
2019     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateMeanWorkloadTest()
2020     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateMeanWorkloadTest()
2025     Connect(input, layer, inputTensorInfo);  in CreateMeanWorkloadTest()
2026     Connect(layer, output, outputTensorInfo);  in CreateMeanWorkloadTest()
2030     auto workload = MakeAndCheckWorkload<MeanWorkload>(*layer, factory);  in CreateMeanWorkloadTest()
2052     Layer* const input0 = graph.AddLayer<InputLayer>(0, "input0");  in CreateConcatWorkloadTest()
2053     Layer* const input1 = graph.AddLayer<InputLayer>(1, "input1");  in CreateConcatWorkloadTest()
2062     // create concat layer  in CreateConcatWorkloadTest()
2063     Layer* const concat = graph.AddLayer<ConcatLayer>(descriptor, "concat");  in CreateConcatWorkloadTest()
2066     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateConcatWorkloadTest()
2097     // Add an input layer  in CreatePreCompiledWorkloadTest()
2098     armnn::IConnectableLayer* const inputLayer = net->AddInputLayer(0, "input layer");  in CreatePreCompiledWorkloadTest()
2116     // Add a layer that can be used in the PreCompiled layer  in CreatePreCompiledWorkloadTest()
2124     const std::string convLayerName("conv layer");  in CreatePreCompiledWorkloadTest()
2154     // Add an output layer  in CreatePreCompiledWorkloadTest()
2155     armnn::IConnectableLayer* const outputLayer = net->AddOutputLayer(0, "output layer");  in CreatePreCompiledWorkloadTest()
2189     // Find the PreCompiled layer in the optimised graph  in CreatePreCompiledWorkloadTest()
2191     Layer* preCompiledLayer = nullptr;  in CreatePreCompiledWorkloadTest()
2192     for (auto& layer : optimisedGraph)  in CreatePreCompiledWorkloadTest()  local
2194         if (layer->GetType() == LayerType::PreCompiled)  in CreatePreCompiledWorkloadTest()
2196             preCompiledLayer = layer;  in CreatePreCompiledWorkloadTest()
2224     // create constant layer  in CreateConstantWorkloadTest()
2229     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateConstantWorkloadTest()
2253     // Creates the PReLU layer  in CreatePreluWorkloadTest()
2254     Layer* const layer = graph.AddLayer<PreluLayer>("prelu");  in CreatePreluWorkloadTest()  local
2255     CHECK(layer != nullptr);  in CreatePreluWorkloadTest()
2258     Layer* const input  = graph.AddLayer<InputLayer> (0, "input");  in CreatePreluWorkloadTest()
2259     Layer* const alpha  = graph.AddLayer<InputLayer> (1, "alpha");  in CreatePreluWorkloadTest()
2260     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreatePreluWorkloadTest()
2269     Connect(input, layer,  inputTensorInfo,  0, 0);  in CreatePreluWorkloadTest()
2270     Connect(alpha, layer,  alphaTensorInfo,  0, 1);  in CreatePreluWorkloadTest()
2271     Connect(layer, output, outputTensorInfo, 0, 0);  in CreatePreluWorkloadTest()
2275     auto workload = MakeAndCheckWorkload<PreluWorkload>(*layer, factory);  in CreatePreluWorkloadTest()
2291     Layer* const layer = graph.AddLayer<SpaceToDepthLayer>(desc, "spaceToDepth");  in CreateSpaceToDepthWorkloadTest()  local
2294     Layer* const input = graph.AddLayer<InputLayer>(0, "input");  in CreateSpaceToDepthWorkloadTest()
2295     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateSpaceToDepthWorkloadTest()
2301     Connect(input, layer, inputTensorInfo);  in CreateSpaceToDepthWorkloadTest()
2302     Connect(layer, output, outputTensorInfo);  in CreateSpaceToDepthWorkloadTest()
2307     auto workload = MakeAndCheckWorkload<SpaceToDepthWorkload>(*layer, factory);  in CreateSpaceToDepthWorkloadTest()
2327     // Constructs the Stack layer.  in CreateStackWorkloadTest()
2329     Layer* const stackLayer = graph.AddLayer<StackLayer>(descriptor, "stack");  in CreateStackWorkloadTest()
2332     // Constructs layer inputs and output.  in CreateStackWorkloadTest()
2333     std::vector<Layer*> inputs;  in CreateStackWorkloadTest()
2342     Layer* const output = graph.AddLayer<OutputLayer>(0, "output");  in CreateStackWorkloadTest()