Fix graph copy memory spike
* Change layer storage of ConstTensors to std::shared_ptr<ConstCpuTensorHandle>
* Change clone to share ConstTensor rather than copy
* Remove uses of non-const GetTensor() call
* Reduce scope of non-optimized network in ExeNet, so memory can be released after use
Signed-off-by: Finn Williams <Finn.Williams@arm.com>
Change-Id: Ibb2c7309d12411d21405bd6024c76bcdf5404545
diff --git a/src/armnn/Network.cpp b/src/armnn/Network.cpp
index 18a4d02..b9a0e47 100644
--- a/src/armnn/Network.cpp
+++ b/src/armnn/Network.cpp
@@ -663,7 +663,7 @@
std::vector<float> newValues(info.GetNumElements());
armnnUtils::FloatingPointConverter::ConvertBFloat16ToFloat32(
- layer->m_Weight->template GetTensor<armnn::BFloat16>(), info.GetNumElements(), newValues.data());
+ layer->m_Weight->template GetConstTensor<armnn::BFloat16>(), info.GetNumElements(), newValues.data());
TensorInfo newInfo(info.GetShape(), DataType::Float32);
ConstTensor newInput(newInfo, newValues);
@@ -1742,10 +1742,10 @@
if (fullyConnectedDescriptor.m_ConstantWeights)
{
- layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights.value());
+ layer->m_Weight = std::make_shared<ScopedCpuTensorHandle>(weights.value());
if (fullyConnectedDescriptor.m_BiasEnabled)
{
- layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.value());
+ layer->m_Bias = std::make_shared<ScopedCpuTensorHandle>(biases.value());
}
}
@@ -1806,11 +1806,11 @@
const auto layer = m_Graph->AddLayer<Convolution2dLayer>(convolution2dDescriptor, name);
- layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights);
+ layer->m_Weight = std::make_shared<ScopedCpuTensorHandle>(weights);
if (convolution2dDescriptor.m_BiasEnabled)
{
- layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.value());
+ layer->m_Bias = std::make_shared<ScopedCpuTensorHandle>(biases.value());
}
return layer;
@@ -1854,11 +1854,11 @@
const auto layer = m_Graph->AddLayer<DepthwiseConvolution2dLayer>(convolution2dDescriptor, name);
- layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights);
+ layer->m_Weight = std::make_shared<ScopedCpuTensorHandle>(weights);
if (convolution2dDescriptor.m_BiasEnabled)
{
- layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.value());
+ layer->m_Bias = std::make_shared<ScopedCpuTensorHandle>(biases.value());
}
return layer;
@@ -1903,7 +1903,7 @@
{
const auto layer = m_Graph->AddLayer<DetectionPostProcessLayer>(descriptor, name);
- layer->m_Anchors = std::make_unique<ScopedCpuTensorHandle>(anchors);
+ layer->m_Anchors = std::make_shared<ScopedCpuTensorHandle>(anchors);
return layer;
}
@@ -2001,10 +2001,10 @@
{
const auto layer = m_Graph->AddLayer<BatchNormalizationLayer>(desc, name);
- layer->m_Mean = std::make_unique<ScopedCpuTensorHandle>(mean);
- layer->m_Variance = std::make_unique<ScopedCpuTensorHandle>(variance);
- layer->m_Beta = std::make_unique<ScopedCpuTensorHandle>(beta);
- layer->m_Gamma = std::make_unique<ScopedCpuTensorHandle>(gamma);
+ layer->m_Mean = std::make_shared<ScopedCpuTensorHandle>(mean);
+ layer->m_Variance = std::make_shared<ScopedCpuTensorHandle>(variance);
+ layer->m_Beta = std::make_shared<ScopedCpuTensorHandle>(beta);
+ layer->m_Gamma = std::make_shared<ScopedCpuTensorHandle>(gamma);
return layer;
}
@@ -2061,7 +2061,7 @@
{
auto layer = m_Graph->AddLayer<ConstantLayer>(name);
- layer->m_LayerOutput = std::make_unique<ScopedCpuTensorHandle>(input);
+ layer->m_LayerOutput = std::make_shared<ScopedCpuTensorHandle>(input);
return layer;
}
@@ -2097,23 +2097,23 @@
//Lstm Basic Parameters
layer->m_BasicParameters.m_InputToForgetWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToForgetWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputToForgetWeights));
layer->m_BasicParameters.m_InputToCellWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToCellWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputToCellWeights));
layer->m_BasicParameters.m_InputToOutputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToOutputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputToOutputWeights));
layer->m_BasicParameters.m_RecurrentToForgetWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToForgetWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_RecurrentToForgetWeights));
layer->m_BasicParameters.m_RecurrentToCellWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToCellWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_RecurrentToCellWeights));
layer->m_BasicParameters.m_RecurrentToOutputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToOutputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_RecurrentToOutputWeights));
layer->m_BasicParameters.m_ForgetGateBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_ForgetGateBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_ForgetGateBias));
layer->m_BasicParameters.m_CellBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellBias));
layer->m_BasicParameters.m_OutputGateBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_OutputGateBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_OutputGateBias));
//Lstm Cifg parameters
if(!descriptor.m_CifgEnabled)
@@ -2135,11 +2135,11 @@
"when CIFG is disabled.");
}
layer->m_CifgParameters.m_InputToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToInputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputToInputWeights));
layer->m_CifgParameters.m_RecurrentToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToInputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_RecurrentToInputWeights));
layer->m_CifgParameters.m_InputGateBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputGateBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputGateBias));
}
//Lstm projection parameters
@@ -2151,11 +2151,11 @@
"when projection is enabled.");
}
layer->m_ProjectionParameters.m_ProjectionWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_ProjectionWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_ProjectionWeights));
if(params.m_ProjectionBias != nullptr)
{
layer->m_ProjectionParameters.m_ProjectionBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_ProjectionBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_ProjectionBias));
}
}
@@ -2171,7 +2171,7 @@
}
layer->m_PeepholeParameters.m_CellToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToInputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellToInputWeights));
}
if(params.m_CellToForgetWeights == nullptr)
@@ -2186,9 +2186,9 @@
}
layer->m_PeepholeParameters.m_CellToForgetWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToForgetWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellToForgetWeights));
layer->m_PeepholeParameters.m_CellToOutputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToOutputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellToOutputWeights));
}
//Lstm Layer Normalization params
@@ -2202,7 +2202,7 @@
"when layer normalization is enabled and CIFG disabled.");
}
layer->m_LayerNormParameters.m_InputLayerNormWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputLayerNormWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputLayerNormWeights));
}
if(params.m_ForgetLayerNormWeights == nullptr)
@@ -2221,11 +2221,11 @@
"when layer normalization is enabled.");
}
layer->m_LayerNormParameters.m_ForgetLayerNormWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_ForgetLayerNormWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_ForgetLayerNormWeights));
layer->m_LayerNormParameters.m_CellLayerNormWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellLayerNormWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellLayerNormWeights));
layer->m_LayerNormParameters.m_OutputLayerNormWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_OutputLayerNormWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_OutputLayerNormWeights));
}
return layer;
}
@@ -2320,11 +2320,11 @@
const auto layer = m_Graph->AddLayer<TransposeConvolution2dLayer>(descriptor, name);
- layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(weights);
+ layer->m_Weight = std::make_shared<ScopedCpuTensorHandle>(weights);
if (descriptor.m_BiasEnabled)
{
- layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(biases.value());
+ layer->m_Bias = std::make_shared<ScopedCpuTensorHandle>(biases.value());
}
return layer;
@@ -2356,33 +2356,33 @@
// InputToX weights
layer->m_QuantizedLstmParameters.m_InputToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(params.GetInputToInputWeights());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetInputToInputWeights());
layer->m_QuantizedLstmParameters.m_InputToForgetWeights =
- std::make_unique<ScopedCpuTensorHandle>(params.GetInputToForgetWeights());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetInputToForgetWeights());
layer->m_QuantizedLstmParameters.m_InputToCellWeights =
- std::make_unique<ScopedCpuTensorHandle>(params.GetInputToCellWeights());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetInputToCellWeights());
layer->m_QuantizedLstmParameters.m_InputToOutputWeights =
- std::make_unique<ScopedCpuTensorHandle>(params.GetInputToOutputWeights());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetInputToOutputWeights());
// RecurrentToX weights
layer->m_QuantizedLstmParameters.m_RecurrentToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToInputWeights());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetRecurrentToInputWeights());
layer->m_QuantizedLstmParameters.m_RecurrentToForgetWeights =
- std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToForgetWeights());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetRecurrentToForgetWeights());
layer->m_QuantizedLstmParameters.m_RecurrentToCellWeights =
- std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToCellWeights());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetRecurrentToCellWeights());
layer->m_QuantizedLstmParameters.m_RecurrentToOutputWeights =
- std::make_unique<ScopedCpuTensorHandle>(params.GetRecurrentToOutputWeights());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetRecurrentToOutputWeights());
// Bias
layer->m_QuantizedLstmParameters.m_InputGateBias =
- std::make_unique<ScopedCpuTensorHandle>(params.GetInputGateBias());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetInputGateBias());
layer->m_QuantizedLstmParameters.m_ForgetGateBias =
- std::make_unique<ScopedCpuTensorHandle>(params.GetForgetGateBias());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetForgetGateBias());
layer->m_QuantizedLstmParameters.m_CellBias =
- std::make_unique<ScopedCpuTensorHandle>(params.GetCellBias());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetCellBias());
layer->m_QuantizedLstmParameters.m_OutputGateBias =
- std::make_unique<ScopedCpuTensorHandle>(params.GetOutputGateBias());
+ std::make_shared<ScopedCpuTensorHandle>(params.GetOutputGateBias());
return layer;
}
@@ -2395,23 +2395,23 @@
// QLstm Basic Parameters
layer->m_BasicParameters.m_InputToForgetWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToForgetWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputToForgetWeights));
layer->m_BasicParameters.m_InputToCellWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToCellWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputToCellWeights));
layer->m_BasicParameters.m_InputToOutputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToOutputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputToOutputWeights));
layer->m_BasicParameters.m_RecurrentToForgetWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToForgetWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_RecurrentToForgetWeights));
layer->m_BasicParameters.m_RecurrentToCellWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToCellWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_RecurrentToCellWeights));
layer->m_BasicParameters.m_RecurrentToOutputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToOutputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_RecurrentToOutputWeights));
layer->m_BasicParameters.m_ForgetGateBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_ForgetGateBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_ForgetGateBias));
layer->m_BasicParameters.m_CellBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellBias));
layer->m_BasicParameters.m_OutputGateBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_OutputGateBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_OutputGateBias));
// QLstm Cifg parameters
if(!descriptor.m_CifgEnabled)
@@ -2433,11 +2433,11 @@
}
layer->m_CifgParameters.m_InputToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputToInputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputToInputWeights));
layer->m_CifgParameters.m_RecurrentToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_RecurrentToInputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_RecurrentToInputWeights));
layer->m_CifgParameters.m_InputGateBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputGateBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputGateBias));
}
// QLstm Projection parameters
@@ -2449,13 +2449,13 @@
}
layer->m_ProjectionParameters.m_ProjectionWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_ProjectionWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_ProjectionWeights));
// Projection bias is optional even if projection is enabled
if(params.m_ProjectionWeights != nullptr)
{
layer->m_ProjectionParameters.m_ProjectionBias =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_ProjectionBias));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_ProjectionBias));
}
}
@@ -2481,13 +2481,13 @@
}
layer->m_PeepholeParameters.m_CellToInputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToInputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellToInputWeights));
}
layer->m_PeepholeParameters.m_CellToForgetWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToForgetWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellToForgetWeights));
layer->m_PeepholeParameters.m_CellToOutputWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellToOutputWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellToOutputWeights));
}
// QLstm Layer Normalization params
@@ -2516,15 +2516,15 @@
}
layer->m_LayerNormParameters.m_InputLayerNormWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_InputLayerNormWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_InputLayerNormWeights));
}
layer->m_LayerNormParameters.m_ForgetLayerNormWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_ForgetLayerNormWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_ForgetLayerNormWeights));
layer->m_LayerNormParameters.m_CellLayerNormWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_CellLayerNormWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_CellLayerNormWeights));
layer->m_LayerNormParameters.m_OutputLayerNormWeights =
- std::make_unique<ScopedCpuTensorHandle>(*(params.m_OutputLayerNormWeights));
+ std::make_shared<ScopedCpuTensorHandle>(*(params.m_OutputLayerNormWeights));
}
return layer;
}