IVGCVSW-3175 Add Regression Tests for Zero Copy
Signed-off-by: Ferran Balaguer <ferran.balaguer@arm.com>
Change-Id: I6f16ea0dca359283a3b187e2f046f82a7dc2ff7c
diff --git a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
index f8673d6..8a3e44f 100644
--- a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
@@ -8,6 +8,7 @@
#include <armnn/ArmNN.hpp>
#include <armnn/INetwork.hpp>
+#include <Profiling.hpp>
#include <backendsCommon/test/QuantizeHelper.hpp>
@@ -171,4 +172,156 @@
}
}
+inline void ImportNonAlignedPointerTest(std::vector<BackendId> backends)
+{
+ using namespace armnn;
+
+ // Create runtime in which test will run
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(armnn::IRuntime::Create(options));
+
+ // build up the structure of the network
+ INetworkPtr net(INetwork::Create());
+
+ IConnectableLayer* input = net->AddInputLayer(0);
+
+ NormalizationDescriptor descriptor;
+ IConnectableLayer* norm = net->AddNormalizationLayer(descriptor);
+
+ IConnectableLayer* output = net->AddOutputLayer(0);
+
+ input->GetOutputSlot(0).Connect(norm->GetInputSlot(0));
+ norm->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32));
+ norm->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32));
+
+ // Optimize the network
+ IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec());
+
+ // Loads it into the runtime.
+ NetworkId netId;
+ runtime->LoadNetwork(netId, std::move(optNet));
+
+ // Creates structures for input & output
+ std::vector<float> inputData
+ {
+ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f
+ };
+
+ // Misaligned input
+ float * misalignedInputData = inputData.data();
+ misalignedInputData++;
+
+ std::vector<float> outputData(5);
+
+ // Misaligned output
+ float * misalignedOutputData = outputData.data();
+ misalignedOutputData++;
+
+ InputTensors inputTensors
+ {
+ {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), misalignedInputData)},
+ };
+ OutputTensors outputTensors
+ {
+ {0,armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), misalignedOutputData)}
+ };
+
+ // The result of the inference is not important, just the fact that there
+ // should not be CopyMemGeneric workloads.
+ runtime->GetProfiler(netId)->EnableProfiling(true);
+
+ // Do the inference
+ runtime->EnqueueWorkload(netId, inputTensors, outputTensors);
+
+ // Retrieve the Profiler.Print() output to get the workload execution
+ ProfilerManager& profilerManager = armnn::ProfilerManager::GetInstance();
+ std::stringstream ss;
+ profilerManager.GetProfiler()->Print(ss);;
+ std::string dump = ss.str();
+
+ // Contains RefNormalizationWorkload
+ std::size_t found = dump.find("RefNormalizationWorkload");
+ BOOST_TEST(found != std::string::npos);
+ // No Contains SyncMemGeneric (Created when importing the output tensor handle)
+ found = dump.find("SyncMemGeneric");
+ BOOST_TEST(found == std::string::npos);
+ // Contains CopyMemGeneric
+ found = dump.find("CopyMemGeneric");
+ BOOST_TEST(found != std::string::npos);
+}
+
+inline void ImportAlignedPointerTest(std::vector<BackendId> backends)
+{
+ using namespace armnn;
+
+ // Create runtime in which test will run
+ IRuntime::CreationOptions options;
+ IRuntimePtr runtime(armnn::IRuntime::Create(options));
+
+ // build up the structure of the network
+ INetworkPtr net(INetwork::Create());
+
+ IConnectableLayer* input = net->AddInputLayer(0);
+
+ NormalizationDescriptor descriptor;
+ IConnectableLayer* norm = net->AddNormalizationLayer(descriptor);
+
+ IConnectableLayer* output = net->AddOutputLayer(0);
+
+ input->GetOutputSlot(0).Connect(norm->GetInputSlot(0));
+ norm->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32));
+ norm->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 4, 1 }, DataType::Float32));
+
+ // Optimize the network
+ IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec());
+
+ // Loads it into the runtime.
+ NetworkId netId;
+ runtime->LoadNetwork(netId, std::move(optNet));
+
+ // Creates structures for input & output
+ std::vector<float> inputData
+ {
+ 1.0f, 2.0f, 3.0f, 4.0f
+ };
+
+ std::vector<float> outputData(4);
+
+ InputTensors inputTensors
+ {
+ {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), inputData.data())},
+ };
+ OutputTensors outputTensors
+ {
+ {0,armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), outputData.data())}
+ };
+
+ // The result of the inference is not important, just the fact that there
+ // should not be CopyMemGeneric workloads.
+ runtime->GetProfiler(netId)->EnableProfiling(true);
+
+ // Do the inference
+ runtime->EnqueueWorkload(netId, inputTensors, outputTensors);
+
+ // Retrieve the Profiler.Print() output to get the workload execution
+ ProfilerManager& profilerManager = armnn::ProfilerManager::GetInstance();
+ std::stringstream ss;
+ profilerManager.GetProfiler()->Print(ss);;
+ std::string dump = ss.str();
+
+ // Contains RefNormalizationWorkload
+ std::size_t found = dump.find("RefNormalizationWorkload");
+ BOOST_TEST(found != std::string::npos);
+ // Contains SyncMemGeneric
+ found = dump.find("SyncMemGeneric");
+ BOOST_TEST(found != std::string::npos);
+ // No contains CopyMemGeneric
+ found = dump.find("CopyMemGeneric");
+ BOOST_TEST(found == std::string::npos);
+}
+
} // anonymous namespace