IVGCVSW-6145 ConstTensorsAsInput: Optimizer Fix - GetConstantTensorsByRef
* Add functionality to check for ConstantTensorsAsInputs to GetConstantTensorsByRef
* Reorder optimizations so RedirectMembersToConstantInputs occurs after
Conversion of Constants
* Ensure graph is in topological order after loading in OptimizedNet
* Fixed test to check release of m_LayerOutputs.
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
Change-Id: I7cff50798d7217e8ea0d2f9b153eabd10174a566
diff --git a/src/armnn/Graph.cpp b/src/armnn/Graph.cpp
index ae773cc..b5769f7 100644
--- a/src/armnn/Graph.cpp
+++ b/src/armnn/Graph.cpp
@@ -652,4 +652,9 @@
return m_Profiler;
}
+void Graph::SetLayersOutOfOrder()
+{
+ m_LayersInOrder = false;
+}
+
} // namespace armnn
diff --git a/src/armnn/Graph.hpp b/src/armnn/Graph.hpp
index 5edf34c..4623461 100644
--- a/src/armnn/Graph.hpp
+++ b/src/armnn/Graph.hpp
@@ -229,6 +229,8 @@
const std::shared_ptr<IProfiler>& GetProfiler() const;
+ void SetLayersOutOfOrder();
+
private:
template <typename LayerT>
class LayerInGraphBase;
diff --git a/src/armnn/LoadedNetwork.cpp b/src/armnn/LoadedNetwork.cpp
index 228927d..ec79d5d 100644
--- a/src/armnn/LoadedNetwork.cpp
+++ b/src/armnn/LoadedNetwork.cpp
@@ -143,7 +143,10 @@
bool useExternalMemoryManager = false;
bool useInternalMemoryManager = false;
- Graph& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph().TopologicalSort();
+ Graph& order = m_OptimizedNetwork->pOptimizedNetworkImpl->GetGraph();
+ // Ensure Topological order
+ order.SetLayersOutOfOrder();
+ order.TopologicalSort();
if (!networkProperties.m_AsyncEnabled)
{
diff --git a/src/armnn/layers/Convolution2dLayer.cpp b/src/armnn/layers/Convolution2dLayer.cpp
index 7b3382b..dbbd009 100644
--- a/src/armnn/layers/Convolution2dLayer.cpp
+++ b/src/armnn/layers/Convolution2dLayer.cpp
@@ -139,6 +139,13 @@
Layer::ConstantTensors Convolution2dLayer::GetConstantTensorsByRef()
{
+ Layer::ConstantTensors tensors = GetConnectedConstantAsInputTensors();
+
+ if (!tensors.empty())
+ {
+ return tensors;
+ }
+
// For API stability DO NOT ALTER order and add new members to the end of vector
return {m_Weight, m_Bias};
}
diff --git a/src/armnn/layers/DepthwiseConvolution2dLayer.cpp b/src/armnn/layers/DepthwiseConvolution2dLayer.cpp
index 08f6faf..4fd2804 100644
--- a/src/armnn/layers/DepthwiseConvolution2dLayer.cpp
+++ b/src/armnn/layers/DepthwiseConvolution2dLayer.cpp
@@ -142,6 +142,13 @@
Layer::ConstantTensors DepthwiseConvolution2dLayer::GetConstantTensorsByRef()
{
+ Layer::ConstantTensors tensors = GetConnectedConstantAsInputTensors();
+
+ if (!tensors.empty())
+ {
+ return tensors;
+ }
+
// For API stability DO NOT ALTER order and add new members to the end of vector
return {m_Weight, m_Bias};
}
diff --git a/src/armnn/layers/FullyConnectedLayer.cpp b/src/armnn/layers/FullyConnectedLayer.cpp
index b1ae974..1f006c9 100644
--- a/src/armnn/layers/FullyConnectedLayer.cpp
+++ b/src/armnn/layers/FullyConnectedLayer.cpp
@@ -77,6 +77,13 @@
Layer::ConstantTensors FullyConnectedLayer::GetConstantTensorsByRef()
{
+ Layer::ConstantTensors tensors = GetConnectedConstantAsInputTensors();
+
+ if (!tensors.empty())
+ {
+ return tensors;
+ }
+
// For API stability DO NOT ALTER order and add new members to the end of vector
return {m_Weight, m_Bias};
}
diff --git a/src/armnn/layers/LayerWithParameters.hpp b/src/armnn/layers/LayerWithParameters.hpp
index 8d9ddff..40ade95 100644
--- a/src/armnn/layers/LayerWithParameters.hpp
+++ b/src/armnn/layers/LayerWithParameters.hpp
@@ -4,6 +4,7 @@
//
#pragma once
+#include "ConstantLayer.hpp"
#include <Layer.hpp>
namespace armnn
@@ -54,6 +55,34 @@
{
strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
}
+
+ Layer::ConstantTensors GetConnectedConstantAsInputTensors()
+ {
+ Layer::ConstantTensors tensors;
+ for (unsigned int i = 0; i < GetNumInputSlots(); ++i)
+ {
+ if (GetInputSlot(i).GetConnection() && GetInputSlot(i).GetConnection()->GetTensorInfo().IsConstant())
+ {
+ auto &inputLayer = GetInputSlot(i).GetConnectedOutputSlot()->GetOwningLayer();
+ if (inputLayer.GetType() == armnn::LayerType::Constant)
+ {
+ auto &constantLayer = static_cast<ConstantLayer&>(inputLayer);
+
+ tensors.push_back(constantLayer.m_LayerOutput);
+ }
+ }
+ }
+ if (tensors.empty())
+ {
+ const std::string warningMessage{"GetConnectedConstantAsInputTensors() called on Layer with no "
+ "connected Constants as Input Tensors."};
+ ARMNN_LOG(warning) << warningMessage;
+ }
+ return tensors;
+ }
};
+
+
+
} // namespace
diff --git a/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp b/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
index 531a0dd..34e5f6d 100644
--- a/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
+++ b/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
@@ -58,4 +58,68 @@
CHECK(data[3] == Half(4.0f));
}
+
+TEST_CASE("ConvertConstantsFloatToHalfTest_constant")
+{
+ armnn::Graph graph;
+
+ // Create the simple test network with Weights and Biases as inputs to a FullyConnected layer.
+ auto input = graph.AddLayer<armnn::InputLayer>(0, "Input");
+ auto weights = graph.AddLayer<armnn::ConstantLayer>("Weights");
+ auto biases = graph.AddLayer<armnn::ConstantLayer>("Biases");
+
+ armnn::FullyConnectedDescriptor desc;
+ desc.m_BiasEnabled = true;
+ desc.m_ConstantWeights = true;
+ auto fcLayer = graph.AddLayer<armnn::FullyConnectedLayer>(desc, "FullyConnected");
+ auto output = graph.AddLayer<armnn::OutputLayer>(1, "Output");
+
+ float expectedWeightsData[] = { 1.0f, 2.0f, 3.0f, 4.0f };
+ float expectedBiasesData[] = { 2.0f, 2.0f };
+
+ const armnn::TensorInfo inputInfo ({ 1, 2, 2, 3 }, armnn::DataType::Float16);
+ const armnn::TensorInfo outputInfo ({ 1, 2, 2, 3 }, armnn::DataType::Float16);
+ const armnn::TensorInfo weightsInfo({ 4 }, armnn::DataType::Float32, 0.0f, 0, true);
+ const armnn::TensorInfo biasesInfo ({ 2 }, armnn::DataType::Float32, 0.0f, 0, true);
+
+ // Set the m_LayerOutput for the optimizer to point to.
+ armnn::ConstTensor weightsTensor(weightsInfo, &expectedWeightsData);
+ armnn::ConstTensor biasesTensor(biasesInfo, &expectedBiasesData);
+ weights->m_LayerOutput = std::make_unique<armnn::ScopedTensorHandle>(weightsTensor);
+ biases->m_LayerOutput = std::make_unique<armnn::ScopedTensorHandle>(biasesTensor);
+
+ input->GetOutputSlot().SetTensorInfo(inputInfo);
+ weights->GetOutputSlot().SetTensorInfo(weightsInfo);
+ biases->GetOutputSlot().SetTensorInfo(biasesInfo);
+ fcLayer->GetOutputSlot().SetTensorInfo(outputInfo);
+
+ // Connect up the layers
+ input->GetOutputSlot(0).Connect(fcLayer->GetInputSlot(0));
+ weights->GetOutputSlot(0).Connect(fcLayer->GetInputSlot(1));
+ biases->GetOutputSlot(0).Connect(fcLayer->GetInputSlot(2));
+ fcLayer->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ // Check tensor data type before conversion
+ CHECK(weights->m_LayerOutput->GetTensorInfo().GetDataType() == armnn::DataType::Float32);
+
+ // Run the optimizer
+ armnn::Optimizer::Pass(graph, armnn::MakeOptimizations(ConvertConstantsFloatToHalf()));
+
+ // Check tensor data type after conversion
+ CHECK(weights->m_LayerOutput->GetTensorInfo().GetDataType() == armnn::DataType::Float16);
+
+ // Check whether weights data matches expected fp16 data
+ const Half* data = weights->m_LayerOutput->GetConstTensor<Half>();
+ CHECK(data[0] == Half(1.0f));
+ CHECK(data[1] == Half(2.0f));
+ CHECK(data[2] == Half(3.0f));
+ CHECK(data[3] == Half(4.0f));
+
+ // Check whether bias data matches expected fp16 data
+ const Half* biasData = biases->m_LayerOutput->GetConstTensor<Half>();
+ CHECK(biasData[0] == Half(2.0f));
+ CHECK(biasData[1] == Half(2.0f));
+}
+
+
}
\ No newline at end of file
diff --git a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
index 5ceb8ae..abfb621 100644
--- a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
+++ b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
@@ -108,7 +108,6 @@
TensorInfo biasInfo = biasLayer->m_LayerOutput->GetTensorInfo();
biasInfo.SetConstant();
-
weightsLayer->GetOutputSlot(0).SetTensorInfo(weightsInfo);
biasLayer->GetOutputSlot(0).SetTensorInfo(biasInfo);
@@ -123,15 +122,15 @@
Connect(layer, output, TensorInfo({ 2, 2, 2, 10 }, armnn::DataType::Float32));
// check the constants that they are not NULL
- CHECK(layer->m_Weight != nullptr);
- CHECK(layer->m_Bias != nullptr);
+ CHECK(weightsLayer->m_LayerOutput != nullptr);
+ CHECK(biasLayer->m_LayerOutput != nullptr);
// free up the constants..
layer->ReleaseConstantData();
// check the constants that they are NULL now
- CHECK(layer->m_Weight == nullptr);
- CHECK(layer->m_Bias == nullptr);
+ CHECK(weightsLayer->m_LayerOutput == nullptr);
+ CHECK(biasLayer->m_LayerOutput == nullptr);
}
TEST_CASE("ReleaseDepthwiseConvolution2dLayerConstantDataTest")