IVGCVSW-5818 Enable import on GPU
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I4e4eb107aa2bfa09625840d738001f33152e6792
diff --git a/src/backends/cl/test/ClImportTensorHandleTests.cpp b/src/backends/cl/test/ClImportTensorHandleTests.cpp
index bfb74af..85ff35f 100644
--- a/src/backends/cl/test/ClImportTensorHandleTests.cpp
+++ b/src/backends/cl/test/ClImportTensorHandleTests.cpp
@@ -11,6 +11,9 @@
#include <boost/test/unit_test.hpp>
+#include <armnn/IRuntime.hpp>
+#include <armnn/INetwork.hpp>
+
using namespace armnn;
BOOST_AUTO_TEST_SUITE(ClImportTensorHandleTests)
@@ -38,7 +41,7 @@
const size_t totalBytes = tensor.info()->total_size();
const size_t alignment =
arm_compute::CLKernelLibrary::get().get_device().getInfo<CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE>();
- size_t space = totalBytes + alignment;
+ size_t space = totalBytes + alignment + alignment;
auto testData = std::make_unique<uint8_t[]>(space);
void* alignedPtr = testData.get();
BOOST_CHECK(std::align(alignment, totalBytes, alignedPtr, space));
@@ -57,7 +60,7 @@
// Validate result by checking that the output has no negative values
for(unsigned int i = 0; i < numElements; ++i)
{
- BOOST_ASSERT(typedPtr[i] >= 0);
+ BOOST_TEST(typedPtr[i] >= 0);
}
}
@@ -78,7 +81,7 @@
const size_t totalBytes = tensor.info()->total_size();
const size_t alignment =
arm_compute::CLKernelLibrary::get().get_device().getInfo<CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE>();
- size_t space = totalBytes + alignment;
+ size_t space = totalBytes + alignment + alignment;
auto testData = std::make_unique<uint8_t[]>(space);
void* alignedPtr = testData.get();
BOOST_CHECK(std::align(alignment, totalBytes, alignedPtr, space));
@@ -108,4 +111,105 @@
BOOST_CHECK_THROW(handle->Import(inputData.data(), invalidMemSource), MemoryImportException);
}
-BOOST_AUTO_TEST_SUITE_END()
\ No newline at end of file
+BOOST_FIXTURE_TEST_CASE(ClImportEndToEnd, ClContextControlFixture)
+{
+ // 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, "Input");
+
+ ActivationDescriptor descriptor;
+ descriptor.m_Function = ActivationFunction::ReLu;
+ IConnectableLayer* activation = net->AddActivationLayer(descriptor, "Activation");
+
+ IConnectableLayer* output = net->AddOutputLayer(0, "Output");
+
+ input->GetOutputSlot(0).Connect(activation->GetInputSlot(0));
+ activation->GetOutputSlot(0).Connect(output->GetInputSlot(0));
+
+ TensorInfo tensorInfo = TensorInfo({ 1, 24, 16, 3 }, DataType::Float32);
+ unsigned int numElements = tensorInfo.GetNumElements();
+ size_t totalBytes = numElements * sizeof(float);
+
+ input->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+ activation->GetOutputSlot(0).SetTensorInfo(tensorInfo);
+
+ // Optimize the network
+ OptimizerOptions optOptions;
+ optOptions.m_ImportEnabled = true;
+ std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc};
+ IOptimizedNetworkPtr optNet = Optimize(*net, backends, runtime->GetDeviceSpec(), optOptions);
+ BOOST_CHECK(optNet);
+
+ // Loads it into the runtime.
+ NetworkId netId;
+ std::string ignoredErrorMessage;
+ // Enable Importing
+ INetworkProperties networkProperties(false, MemorySource::Malloc, MemorySource::Malloc);
+ runtime->LoadNetwork(netId, std::move(optNet), ignoredErrorMessage, networkProperties);
+
+ // Creates structures for input & output
+ const size_t alignment =
+ arm_compute::CLKernelLibrary::get().get_device().getInfo<CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE>();
+ size_t space = totalBytes + alignment + alignment;
+ auto inputData = std::make_unique<uint8_t[]>(space);
+ void* alignedInputPtr = inputData.get();
+ BOOST_CHECK(std::align(alignment, totalBytes, alignedInputPtr, space));
+
+ // Input with negative values
+ auto* intputPtr = reinterpret_cast<float*>(alignedInputPtr);
+ std::fill_n(intputPtr, numElements, -5.0f);
+
+ auto outputData = std::make_unique<uint8_t[]>(space);
+ void* alignedOutputPtr = outputData.get();
+ BOOST_CHECK(std::align(alignment, totalBytes, alignedOutputPtr, space));
+
+ InputTensors inputTensors
+ {
+ {0,armnn::ConstTensor(runtime->GetInputTensorInfo(netId, 0), alignedInputPtr)},
+ };
+ OutputTensors outputTensors
+ {
+ {0,armnn::Tensor(runtime->GetOutputTensorInfo(netId, 0), alignedOutputPtr)}
+ };
+
+ 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 ActivationWorkload
+ std::size_t found = dump.find("ActivationWorkload");
+ BOOST_TEST(found != std::string::npos);
+
+ // Contains SyncMemGeneric
+ found = dump.find("SyncMemGeneric");
+ BOOST_TEST(found != std::string::npos);
+
+ // Does not contain CopyMemGeneric
+ found = dump.find("CopyMemGeneric");
+ BOOST_TEST(found == std::string::npos);
+
+ // Check output is as expected
+ // Validate result by checking that the output has no negative values
+ auto* outputResult = reinterpret_cast<float*>(alignedOutputPtr);
+ BOOST_TEST(outputResult);
+ for(unsigned int i = 0; i < numElements; ++i)
+ {
+ BOOST_TEST(outputResult[i] >= 0);
+ }
+
+ runtime->UnloadNetwork(netId);
+}
+
+BOOST_AUTO_TEST_SUITE_END()