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-rw-r--r--src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp213
1 files changed, 213 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
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+++ b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp
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+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include <Graph.hpp>
+
+#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/WorkloadData.hpp>
+
+#include <cl/ClWorkloadFactory.hpp>
+
+#include <boost/cast.hpp>
+#include <boost/test/unit_test.hpp>
+
+#include <utility>
+
+using namespace armnn;
+using namespace std;
+
+// connects two layers
+void Connect(Layer* from, Layer* to, const TensorInfo& tensorInfo, unsigned int fromIndex = 0, unsigned int toIndex = 0)
+{
+ from->GetOutputSlot(fromIndex).Connect(to->GetInputSlot(toIndex));
+ from->GetOutputHandler(fromIndex).SetTensorInfo(tensorInfo);
+}
+
+/////////////////////////////////////////////////////////////////////////////////////////////
+// The following test are created specifically to test ReleaseConstantData() method in the Layer
+// They build very simple graphs including the layer will be checked.
+// Checks weights and biases before the method called and after.
+/////////////////////////////////////////////////////////////////////////////////////////////
+
+BOOST_AUTO_TEST_SUITE(LayerReleaseConstantDataTest)
+
+BOOST_AUTO_TEST_CASE(ReleaseBatchNormalizationLayerConstantDataTest)
+{
+ Graph graph;
+ ClWorkloadFactory factory;
+
+ // create the layer we're testing
+ BatchNormalizationDescriptor layerDesc;
+ layerDesc.m_Eps = 0.05f;
+ BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer");
+
+ armnn::TensorInfo weightInfo({3}, armnn::DataType::Float32);
+ layer->m_Mean = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
+ layer->m_Variance = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
+ layer->m_Beta = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
+ layer->m_Gamma = std::make_unique<ScopedCpuTensorHandle>(weightInfo);
+ layer->m_Mean->Allocate();
+ layer->m_Variance->Allocate();
+ layer->m_Beta->Allocate();
+ layer->m_Gamma->Allocate();
+
+ // create extra layers
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // connect up
+ armnn::TensorInfo tensorInfo({2, 3, 1, 1}, armnn::DataType::Float32);
+ Connect(input, layer, tensorInfo);
+ Connect(layer, output, tensorInfo);
+
+ // check the constants that they are not NULL
+ BOOST_CHECK(layer->m_Mean != nullptr);
+ BOOST_CHECK(layer->m_Variance != nullptr);
+ BOOST_CHECK(layer->m_Beta != nullptr);
+ BOOST_CHECK(layer->m_Gamma != nullptr);
+
+ // free up the constants..
+ layer->ReleaseConstantData();
+
+ // check the constants that they are NULL now
+ BOOST_CHECK(layer->m_Mean == nullptr);
+ BOOST_CHECK(layer->m_Variance == nullptr);
+ BOOST_CHECK(layer->m_Beta == nullptr);
+ BOOST_CHECK(layer->m_Gamma == nullptr);
+
+ }
+
+
+ BOOST_AUTO_TEST_CASE(ReleaseConvolution2dLayerConstantDataTest)
+ {
+ Graph graph;
+ ClWorkloadFactory factory;
+
+ // create the layer we're testing
+ Convolution2dDescriptor layerDesc;
+ layerDesc.m_PadLeft = 3;
+ layerDesc.m_PadRight = 3;
+ layerDesc.m_PadTop = 1;
+ layerDesc.m_PadBottom = 1;
+ layerDesc.m_StrideX = 2;
+ layerDesc.m_StrideY = 4;
+ layerDesc.m_BiasEnabled = true;
+
+ Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer");
+
+ layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({2, 3, 5, 3},
+ armnn::DataType::Float32));
+ layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>
+ (TensorInfo({2}, GetBiasDataType(armnn::DataType::Float32)));
+
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+
+ // create extra layers
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // connect up
+ Connect(input, layer, TensorInfo({2, 3, 8, 16}, armnn::DataType::Float32));
+ Connect(layer, output, TensorInfo({2, 2, 2, 10}, armnn::DataType::Float32));
+
+ // check the constants that they are not NULL
+ BOOST_CHECK(layer->m_Weight != nullptr);
+ BOOST_CHECK(layer->m_Bias != nullptr);
+
+ // free up the constants..
+ layer->ReleaseConstantData();
+
+ // check the constants that they are NULL now
+ BOOST_CHECK(layer->m_Weight == nullptr);
+ BOOST_CHECK(layer->m_Bias == nullptr);
+}
+
+BOOST_AUTO_TEST_CASE(ReleaseDepthwiseConvolution2dLayerConstantDataTest)
+{
+ Graph graph;
+ ClWorkloadFactory factory;
+
+ // create the layer we're testing
+ DepthwiseConvolution2dDescriptor layerDesc;
+ layerDesc.m_PadLeft = 3;
+ layerDesc.m_PadRight = 3;
+ layerDesc.m_PadTop = 1;
+ layerDesc.m_PadBottom = 1;
+ layerDesc.m_StrideX = 2;
+ layerDesc.m_StrideY = 4;
+ layerDesc.m_BiasEnabled = true;
+
+ DepthwiseConvolution2dLayer* const layer = graph.AddLayer<DepthwiseConvolution2dLayer>(layerDesc, "layer");
+
+ layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({3, 3, 5, 3}, DataType::Float32));
+ layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({9}, DataType::Float32));
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+
+ // create extra layers
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // connect up
+ Connect(input, layer, TensorInfo({2, 3, 8, 16}, armnn::DataType::Float32));
+ Connect(layer, output, TensorInfo({2, 9, 2, 10}, armnn::DataType::Float32));
+
+ // check the constants that they are not NULL
+ BOOST_CHECK(layer->m_Weight != nullptr);
+ BOOST_CHECK(layer->m_Bias != nullptr);
+
+ // free up the constants..
+ layer->ReleaseConstantData();
+
+ // check the constants that they are NULL now
+ BOOST_CHECK(layer->m_Weight == nullptr);
+ BOOST_CHECK(layer->m_Bias == nullptr);
+}
+
+BOOST_AUTO_TEST_CASE(ReleaseFullyConnectedLayerConstantDataTest)
+{
+ Graph graph;
+ ClWorkloadFactory factory;
+
+ // create the layer we're testing
+ FullyConnectedDescriptor layerDesc;
+ layerDesc.m_BiasEnabled = true;
+ layerDesc.m_TransposeWeightMatrix = true;
+
+ FullyConnectedLayer* const layer = graph.AddLayer<FullyConnectedLayer>(layerDesc, "layer");
+
+ float inputsQScale = 1.0f;
+ float outputQScale = 2.0f;
+
+ layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({7, 20},
+ DataType::QuantisedAsymm8, inputsQScale, 0));
+ layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({7},
+ GetBiasDataType(DataType::QuantisedAsymm8), inputsQScale));
+ layer->m_Weight->Allocate();
+ layer->m_Bias->Allocate();
+
+ // create extra layers
+ Layer* const input = graph.AddLayer<InputLayer>(0, "input");
+ Layer* const output = graph.AddLayer<OutputLayer>(0, "output");
+
+ // connect up
+ Connect(input, layer, TensorInfo({3, 1, 4, 5}, DataType::QuantisedAsymm8, inputsQScale));
+ Connect(layer, output, TensorInfo({3, 7}, DataType::QuantisedAsymm8, outputQScale));
+
+ // check the constants that they are not NULL
+ BOOST_CHECK(layer->m_Weight != nullptr);
+ BOOST_CHECK(layer->m_Bias != nullptr);
+
+ // free up the constants..
+ layer->ReleaseConstantData();
+
+ // check the constants that they are NULL now
+ BOOST_CHECK(layer->m_Weight == nullptr);
+ BOOST_CHECK(layer->m_Bias == nullptr);
+}
+
+BOOST_AUTO_TEST_SUITE_END()
+
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-16 19:22:26 +0000