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| author | Sadik Armagan <sadik.armagan@arm.com> | 2022-08-03 11:27:05 +0100 |
|---|---|---|
| committer | Nikhil Raj <nikhil.raj@arm.com> | 2022-08-29 10:12:21 +0100 |
| commit | b016157f1eea1acc6a84308521c0b90543161da4 (patch) | |
| tree | fe228d1014f4fa9a4f74227d0640719d1d92193c /src/armnn/Network.cpp | |
| parent | ee480d2d6538b0192d40a00ed696b30e2587430c (diff) | |
| download | armnn-b016157f1eea1acc6a84308521c0b90543161da4.tar.gz | |
IVGCVSW-6954 'Arm NN SL Improvements'
* Move the Conv2D and DepthwiseConv2D validation to Optimization level
when the weights and tensors are as constant inputs
* Take into account offset and scales values when doing INT8 to FP32 dequantization
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I1f81f15640395ac041923b10dbe9151159715117
Diffstat (limited to 'src/armnn/Network.cpp')
| -rw-r--r-- | src/armnn/Network.cpp | 20 |
1 files changed, 12 insertions, 8 deletions
diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp index 22fc0a3ed4..c4869fae04 100644 --- a/src/armnn/Network.cpp +++ b/src/armnn/Network.cpp @@ -2058,16 +2058,18 @@ IConnectableLayer* NetworkImpl::AddConvolution2dLayer(const Convolution2dDescrip auto layer = m_Graph->AddLayer<Convolution2dLayer>(convolution2dDescriptor, name); // Add a constant layer for weights ConstantLayer* weightsLayer = m_Graph->AddLayer<ConstantLayer>("Weights"); - weightsLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(weights); - layer->m_Weight = std::make_shared<ScopedTensorHandle>(weights); + auto weightsTensorHandle = std::make_shared<ScopedTensorHandle>(weights); + weightsLayer->m_LayerOutput = weightsTensorHandle; + layer->m_Weight = weightsTensorHandle; weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsLayer->m_LayerOutput->GetTensorInfo()); weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1)); // Add a constant layer for biases if (biases.has_value() && convolution2dDescriptor.m_BiasEnabled) { ConstantLayer* biasLayer = m_Graph->AddLayer<ConstantLayer>("Bias"); - biasLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(biases.value()); - layer->m_Bias = std::make_shared<ScopedTensorHandle>(biases.value()); + auto biasTensorHandle = std::make_shared<ScopedTensorHandle>(biases.value()); + biasLayer->m_LayerOutput = biasTensorHandle; + layer->m_Bias = biasTensorHandle; biasLayer->GetOutputSlot(0).SetTensorInfo(biasLayer->m_LayerOutput->GetTensorInfo()); biasLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(2)); } @@ -2113,8 +2115,9 @@ IConnectableLayer* NetworkImpl::AddDepthwiseConvolution2dLayer( // Add a constant layer for weights ConstantLayer* weightsLayer = m_Graph->AddLayer<ConstantLayer>("Weights"); - weightsLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(weights); - layer->m_Weight = std::make_shared<ScopedTensorHandle>(weights); + auto weightsTensorHandle = std::make_shared<ScopedTensorHandle>(weights); + weightsLayer->m_LayerOutput = weightsTensorHandle; + layer->m_Weight = weightsTensorHandle; weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsLayer->m_LayerOutput->GetTensorInfo()); weightsLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(1)); @@ -2123,8 +2126,9 @@ IConnectableLayer* NetworkImpl::AddDepthwiseConvolution2dLayer( if (biases.has_value() && convolution2dDescriptor.m_BiasEnabled) { ConstantLayer* biasLayer = m_Graph->AddLayer<ConstantLayer>("Bias"); - biasLayer->m_LayerOutput = std::make_shared<ScopedTensorHandle>(biases.value()); - layer->m_Bias = std::make_shared<ScopedTensorHandle>(biases.value()); + auto biasTensorHandle = std::make_shared<ScopedTensorHandle>(biases.value()); + biasLayer->m_LayerOutput = biasTensorHandle; + layer->m_Bias = biasTensorHandle; biasLayer->GetOutputSlot(0).SetTensorInfo(biasLayer->m_LayerOutput->GetTensorInfo()); biasLayer->GetOutputSlot(0).Connect(layer->GetInputSlot(2)); |