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Diffstat (limited to 'delegate/opaque/src/Convolution.hpp')
-rw-r--r--delegate/opaque/src/Convolution.hpp54
1 files changed, 37 insertions, 17 deletions
diff --git a/delegate/opaque/src/Convolution.hpp b/delegate/opaque/src/Convolution.hpp
index 2eb5edabe0..384c62b678 100644
--- a/delegate/opaque/src/Convolution.hpp
+++ b/delegate/opaque/src/Convolution.hpp
@@ -154,14 +154,16 @@ TfLiteStatus VisitConv2dOperator(DelegateData& delegateData,
}
// Set up filter and biases
- armnn::IConnectableLayer* layer = delegateData.m_Network->AddConvolution2dLayer(descriptor);
+ auto layerName = GetName(armnn::LayerType::Convolution2d, nodeIndex);
+ armnn::IConnectableLayer* layer = delegateData.m_Network->AddConvolution2dLayer(descriptor, layerName.c_str());
layer->SetBackendId(setBackend);
if(filterTensorInfo.IsConstant())
{
auto filter = CreateConstTensor(tfLiteFilterTensor, filterTensorInfo);
- armnn::IConnectableLayer* weightsLayer = delegateData.m_Network->AddConstantLayer(filter);
+ auto filterName = GetName(armnn::LayerType::Constant, nodeIndex, "Filter");
+ armnn::IConnectableLayer* weightsLayer = delegateData.m_Network->AddConstantLayer(filter, filterName.c_str());
weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1u));
weightsLayer->GetOutputSlot(0).SetTensorInfo(filterTensorInfo);
}
@@ -171,7 +173,10 @@ TfLiteStatus VisitConv2dOperator(DelegateData& delegateData,
if (biasTensorInfo.IsConstant())
{
auto biasTensor = CreateConstTensor(tfLiteBiasTensor, biasTensorInfo);
- armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biasTensor);
+
+ auto biasName = GetName(armnn::LayerType::Constant, nodeIndex, "Bias");
+ armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biasTensor,
+ biasName.c_str());
ARMNN_ASSERT(biasLayer != nullptr);
biasLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(2u));
biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensorInfo);
@@ -183,7 +188,8 @@ TfLiteStatus VisitConv2dOperator(DelegateData& delegateData,
{
auto input = CreateConstTensor(tfLiteInputTensor, inputTensorInfo);
- armnn::IConnectableLayer* inputLayer = delegateData.m_Network->AddConstantLayer(input);
+ auto inputName = GetName(armnn::LayerType::Constant, nodeIndex, "Input");
+ armnn::IConnectableLayer* inputLayer = delegateData.m_Network->AddConstantLayer(input, inputName.c_str());
inputLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0u));
inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
}
@@ -205,7 +211,7 @@ TfLiteStatus VisitConv2dOperator(DelegateData& delegateData,
}
// Check and Create activation
- return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData);
+ return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData, nodeIndex);
}
TfLiteStatus VisitDepthwiseConv2dOperator(DelegateData& delegateData,
@@ -348,7 +354,9 @@ TfLiteStatus VisitDepthwiseConv2dOperator(DelegateData& delegateData,
return isSupported ? kTfLiteOk : kTfLiteError;
}
- armnn::IConnectableLayer* layer = delegateData.m_Network->AddDepthwiseConvolution2dLayer(descriptor);
+ auto layerName = GetName(armnn::LayerType::DepthwiseConvolution2d, nodeIndex);
+ armnn::IConnectableLayer* layer = delegateData.m_Network->AddDepthwiseConvolution2dLayer(descriptor,
+ layerName.c_str());
layer->SetBackendId(setBackend);
if(filterTensorInfo.IsConstant())
@@ -356,7 +364,8 @@ TfLiteStatus VisitDepthwiseConv2dOperator(DelegateData& delegateData,
// For depthwise the weights layout is the same as for tflite [1, H, W, I*M]. No permutation required.
auto filter = CreateConstTensor(tfLiteFilterTensor, filterTensorInfo);
- armnn::IConnectableLayer* weightsLayer = delegateData.m_Network->AddConstantLayer(filter);
+ auto filterName = GetName(armnn::LayerType::Constant, nodeIndex, "Filter");
+ armnn::IConnectableLayer* weightsLayer = delegateData.m_Network->AddConstantLayer(filter, filterName.c_str());
weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1u));
weightsLayer->GetOutputSlot(0).SetTensorInfo(filterTensorInfo);
}
@@ -367,7 +376,9 @@ TfLiteStatus VisitDepthwiseConv2dOperator(DelegateData& delegateData,
{
auto biasTensor = CreateConstTensor(tfLiteBiasTensor, biasTensorInfo);
- armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biasTensor);
+ auto biasName = GetName(armnn::LayerType::Constant, nodeIndex, "Bias");
+ armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biasTensor,
+ biasName.c_str());
ARMNN_ASSERT(biasLayer != nullptr);
biasLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(2u));
biasLayer->GetOutputSlot(0).SetTensorInfo(biasTensorInfo);
@@ -379,7 +390,8 @@ TfLiteStatus VisitDepthwiseConv2dOperator(DelegateData& delegateData,
{
auto input = CreateConstTensor(tfLiteInputTensor, inputTensorInfo);
- armnn::IConnectableLayer* inputLayer = delegateData.m_Network->AddConstantLayer(input);
+ auto inputName = GetName(armnn::LayerType::Constant, nodeIndex, "Input");
+ armnn::IConnectableLayer* inputLayer = delegateData.m_Network->AddConstantLayer(input, inputName.c_str());
inputLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0u));
inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
}
@@ -400,7 +412,7 @@ TfLiteStatus VisitDepthwiseConv2dOperator(DelegateData& delegateData,
return kTfLiteOk;
}
// Check and create activation
- return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData);
+ return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData, nodeIndex);
}
TfLiteStatus VisitConv3dOperator(DelegateData& delegateData,
@@ -552,7 +564,8 @@ TfLiteStatus VisitConv3dOperator(DelegateData& delegateData,
return isSupported ? kTfLiteOk : kTfLiteError;
}
- armnn::IConnectableLayer* layer = delegateData.m_Network->AddConvolution3dLayer(descriptor);
+ auto layerName = GetName(armnn::LayerType::Convolution3d, nodeIndex);
+ armnn::IConnectableLayer* layer = delegateData.m_Network->AddConvolution3dLayer(descriptor, layerName.c_str());
layer->SetBackendId(setBackend);
ARMNN_ASSERT(layer != nullptr);
@@ -563,7 +576,8 @@ TfLiteStatus VisitConv3dOperator(DelegateData& delegateData,
auto filter = CreateConstTensor(tfLiteFilterTensor,
filterTensorInfo);
- armnn::IConnectableLayer* weightsLayer = delegateData.m_Network->AddConstantLayer(filter);
+ auto filterName = GetName(armnn::LayerType::Constant, nodeIndex, "Filter");
+ armnn::IConnectableLayer* weightsLayer = delegateData.m_Network->AddConstantLayer(filter, filterName.c_str());
ARMNN_ASSERT(weightsLayer != nullptr);
weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1u));
@@ -576,7 +590,9 @@ TfLiteStatus VisitConv3dOperator(DelegateData& delegateData,
{
auto biasTensor = CreateConstTensor(tfLiteBiasTensor, biasTensorInfo);
- armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biasTensor);
+ auto biasName = GetName(armnn::LayerType::Constant, nodeIndex, "Bias");
+ armnn::IConnectableLayer* biasLayer = delegateData.m_Network->AddConstantLayer(biasTensor,
+ biasName.c_str());
ARMNN_ASSERT(biasLayer != nullptr);
biasLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(2u));
@@ -589,7 +605,8 @@ TfLiteStatus VisitConv3dOperator(DelegateData& delegateData,
{
auto input = CreateConstTensor(tfLiteInputTensor, inputTensorInfo);
- armnn::IConnectableLayer* inputLayer = delegateData.m_Network->AddConstantLayer(input);
+ auto inputName = GetName(armnn::LayerType::Constant, nodeIndex, "Input");
+ armnn::IConnectableLayer* inputLayer = delegateData.m_Network->AddConstantLayer(input, inputName.c_str());
inputLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0u));
inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
}
@@ -609,7 +626,7 @@ TfLiteStatus VisitConv3dOperator(DelegateData& delegateData,
}
// Check and create activation
- return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData);
+ return FusedActivation(tfLiteContext, tfLiteNode, activationType, layer, 0, delegateData, nodeIndex);
}
@@ -781,9 +798,11 @@ TfLiteStatus VisitTransposeConv2dOperator(DelegateData& delegateData,
return isSupported ? kTfLiteOk : kTfLiteError;
}
+ auto layerName = GetName(armnn::LayerType::TransposeConvolution2d, nodeIndex);
armnn::IConnectableLayer* layer = delegateData.m_Network->AddTransposeConvolution2dLayer(descriptor,
filterTensor,
- armnn::EmptyOptional());
+ armnn::EmptyOptional(),
+ layerName.c_str());
layer->SetBackendId(setBackend);
ARMNN_ASSERT(layer != nullptr);
@@ -792,7 +811,8 @@ TfLiteStatus VisitTransposeConv2dOperator(DelegateData& delegateData,
{
auto input = CreateConstTensor(tfLiteInputTensor, inputTensorInfo);
- armnn::IConnectableLayer *inputLayer = delegateData.m_Network->AddConstantLayer(input);
+ auto inputName = GetName(armnn::LayerType::Constant, nodeIndex, "Input");
+ armnn::IConnectableLayer *inputLayer = delegateData.m_Network->AddConstantLayer(input, inputName.c_str());
inputLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(0u));
inputLayer->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-01 01:21:15 +0000