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

1 files changed, 4 insertions, 4 deletions

diff --git a/src/armnn/layers/BatchNormalizationLayer.cpp b/src/armnn/layers/BatchNormalizationLayer.cpp
index 6df5195a55..680d9e56a0 100644
--- a/src/armnn/layers/BatchNormalizationLayer.cpp
+++ b/src/armnn/layers/BatchNormalizationLayer.cpp
@@ -41,10 +41,10 @@ BatchNormalizationLayer* BatchNormalizationLayer::Clone(Graph& graph) const
 {
     auto layer = CloneBase<BatchNormalizationLayer>(graph, m_Param, GetName());
 
-    layer->m_Mean = m_Mean ? std::make_unique<ScopedCpuTensorHandle>(*m_Mean) : nullptr;
-    layer->m_Variance = m_Variance ? std::make_unique<ScopedCpuTensorHandle>(*m_Variance) : nullptr;
-    layer->m_Beta = m_Beta ? std::make_unique<ScopedCpuTensorHandle>(*m_Beta) : nullptr;
-    layer->m_Gamma = m_Gamma ? std::make_unique<ScopedCpuTensorHandle>(*m_Gamma) : nullptr;
+    layer->m_Mean = m_Mean ? m_Mean : nullptr;
+    layer->m_Variance = m_Variance ? m_Variance : nullptr;
+    layer->m_Beta = m_Beta ? m_Beta : nullptr;
+    layer->m_Gamma = m_Gamma ? m_Gamma : nullptr;
 
     return std::move(layer);
 }