IVGCVSW-3623 Implement NeonTensorHandle::Import
Signed-off-by: David Monahan <david.monahan@arm.com>
Change-Id: I7213788725fd4e4cf1176998604e999d0b7ed6cc
diff --git a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
index ecc8806..3bdd48b 100644
--- a/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
+++ b/src/backends/backendsCommon/test/EndToEndTestImpl.hpp
@@ -185,40 +185,42 @@
IConnectableLayer* input = net->AddInputLayer(0);
- NormalizationDescriptor descriptor;
- IConnectableLayer* norm = net->AddNormalizationLayer(descriptor);
+ ActivationDescriptor descriptor;
+ descriptor.m_Function = ActivationFunction::Square;
+ IConnectableLayer* pooling = net->AddActivationLayer(descriptor);
IConnectableLayer* output = net->AddOutputLayer(0);
- input->GetOutputSlot(0).Connect(norm->GetInputSlot(0));
- norm->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+ input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
+ pooling->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));
+ input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32));
+ pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32));
// Optimize the network
IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec());
+ BOOST_CHECK(optNet);
// Loads it into the runtime.
NetworkId netId;
std::string ignoredErrorMessage;
// Enable Importing
- INetworkProperties networkProperties(true, true);
+ INetworkProperties networkProperties(true, false);
runtime->LoadNetwork(netId, std::move(optNet), ignoredErrorMessage, networkProperties);
// Creates structures for input & output
std::vector<float> inputData
{
- 1.0f, 2.0f, 3.0f, 4.0f, 5.0f
+ 1.0f, 2.0f, 3.0f, 4.0f
};
// Misaligned input
float* misalignedInputData = reinterpret_cast<float*>(reinterpret_cast<char*>(inputData.data()) + 1);
- std::vector<float> outputData(5);
+ std::vector<float> outputData(4);
// Aligned output
- float * alignedOutputData = outputData.data();
+ float* alignedOutputData = outputData.data();
InputTensors inputTensors
{
@@ -229,8 +231,6 @@
{0,armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), alignedOutputData)}
};
- // 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 and expect it to fail with a ImportMemoryException
@@ -250,24 +250,26 @@
IConnectableLayer* input = net->AddInputLayer(0);
- NormalizationDescriptor descriptor;
- IConnectableLayer* norm = net->AddNormalizationLayer(descriptor);
+ ActivationDescriptor descriptor;
+ descriptor.m_Function = ActivationFunction::Square;
+ IConnectableLayer* pooling = net->AddActivationLayer(descriptor);
IConnectableLayer* output = net->AddOutputLayer(0);
- input->GetOutputSlot(0).Connect(norm->GetInputSlot(0));
- norm->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+ input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
+ pooling->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));
+ input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32));
+ pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32));
// Optimize the network
IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec());
+ BOOST_CHECK(optNet);
// Loads it into the runtime.
NetworkId netId;
std::string ignoredErrorMessage;
- // Enable Importing
+ // Enable Importing and Exporting
INetworkProperties networkProperties(true, true);
runtime->LoadNetwork(netId, std::move(optNet), ignoredErrorMessage, networkProperties);
@@ -278,7 +280,7 @@
};
// Aligned input
- float * alignedInputData = inputData.data();
+ float* alignedInputData = inputData.data();
std::vector<float> outputData(5);
@@ -294,10 +296,6 @@
{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 and expect it to fail with a ImportMemoryException
BOOST_CHECK_THROW(runtime->EnqueueWorkload(netId, inputTensors, outputTensors), MemoryExportException);
}
@@ -315,19 +313,21 @@
IConnectableLayer* input = net->AddInputLayer(0);
- NormalizationDescriptor descriptor;
- IConnectableLayer* norm = net->AddNormalizationLayer(descriptor);
+ ActivationDescriptor descriptor;
+ descriptor.m_Function = ActivationFunction::Square;
+ IConnectableLayer* pooling = net->AddActivationLayer(descriptor);
IConnectableLayer* output = net->AddOutputLayer(0);
- input->GetOutputSlot(0).Connect(norm->GetInputSlot(0));
- norm->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+ input->GetOutputSlot(0).Connect(pooling->GetInputSlot(0));
+ pooling->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));
+ input->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32));
+ pooling->GetOutputSlot(0).SetTensorInfo(TensorInfo({ 1, 1, 1, 4 }, DataType::Float32));
// Optimize the network
IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec());
+ BOOST_CHECK(optNet);
// Loads it into the runtime.
NetworkId netId;
@@ -366,8 +366,8 @@
profilerManager.GetProfiler()->Print(ss);;
std::string dump = ss.str();
- // Contains RefNormalizationWorkload
- std::size_t found = dump.find("RefNormalizationWorkload");
+ // Contains ActivationWorkload
+ std::size_t found = dump.find("ActivationWorkload");
BOOST_TEST(found != std::string::npos);
// Contains SyncMemGeneric
found = dump.find("SyncMemGeneric");