1 files changed, 13 insertions, 270 deletions

diff --git a/src/armnn/test/RuntimeTests.cpp b/src/armnn/test/RuntimeTests.cpp
index 76f5774a49..8a4e85ee23 100644
--- a/src/armnn/test/RuntimeTests.cpp
+++ b/src/armnn/test/RuntimeTests.cpp
@@ -2,21 +2,22 @@
 // Copyright © 2017 Arm Ltd. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
-#include <boost/test/unit_test.hpp>
 
-#include "armnn/TypesUtils.hpp"
+#include <armnn/Descriptors.hpp>
+#include <armnn/IRuntime.hpp>
+#include <armnn/INetwork.hpp>
+#include <armnn/Runtime.hpp>
+#include <armnn/TypesUtils.hpp>
 
-#include "armnn/IRuntime.hpp"
-#include "armnn/INetwork.hpp"
-#include "armnn/Descriptors.hpp"
-#include "Runtime.hpp"
-#include "HeapProfiling.hpp"
-#include "LeakChecking.hpp"
+#include <armnnUtils/HeapProfiling.hpp>
+#include <armnnUtils/LeakChecking.hpp>
 
 #ifdef WITH_VALGRIND
-#include "valgrind/memcheck.h"
+#include <valgrind/memcheck.h>
 #endif
 
+#include <boost/test/unit_test.hpp>
+
 namespace armnn
 {
 
@@ -71,35 +72,6 @@ struct DisableGlobalLeakChecking
 
 BOOST_GLOBAL_FIXTURE(DisableGlobalLeakChecking);
 
-void CreateAndDropDummyNetwork(const std::vector<armnn::BackendId>& backends, armnn::Runtime& runtime)
-{
-    armnn::NetworkId networkIdentifier;
-    {
-        armnn::TensorInfo inputTensorInfo(armnn::TensorShape({ 7, 7 }), armnn::DataType::Float32);
-        armnn::TensorInfo outputTensorInfo(armnn::TensorShape({ 7, 7 }), armnn::DataType::Float32);
-
-        armnn::INetworkPtr network(armnn::INetwork::Create());
-
-        armnn::IConnectableLayer* input = network->AddInputLayer(0, "input");
-        armnn::IConnectableLayer* layer = network->AddActivationLayer(armnn::ActivationDescriptor(), "test");
-        armnn::IConnectableLayer* output = network->AddOutputLayer(0, "output");
-
-        input->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
-        layer->GetOutputSlot(0).Connect(output->GetInputSlot(0));
-
-        // Sets the tensors in the network.
-        input->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
-        layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
-        // optimize the network
-        armnn::IOptimizedNetworkPtr optNet = Optimize(*network, backends, runtime.GetDeviceSpec());
-
-        runtime.LoadNetwork(networkIdentifier, std::move(optNet));
-    }
-
-    runtime.UnloadNetwork(networkIdentifier);
-}
-
 BOOST_AUTO_TEST_CASE(RuntimeHeapMemoryUsageSanityChecks)
 {
     BOOST_TEST(ARMNN_LEAK_CHECKER_IS_ACTIVE());
@@ -121,173 +93,9 @@ BOOST_AUTO_TEST_CASE(RuntimeHeapMemoryUsageSanityChecks)
     }
 }
 
-#ifdef ARMCOMPUTECL_ENABLED
-BOOST_AUTO_TEST_CASE(RuntimeMemoryLeaksGpuAcc)
-{
-    BOOST_TEST(ARMNN_LEAK_CHECKER_IS_ACTIVE());
-    armnn::IRuntime::CreationOptions options;
-    armnn::Runtime runtime(options);
-    armnn::RuntimeLoadedNetworksReserve(&runtime);
-
-    std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc};
-    {
-        // Do a warmup of this so we make sure that all one-time
-        // initialization happens before we do the leak checking.
-        CreateAndDropDummyNetwork(backends, runtime);
-    }
-
-    {
-        ARMNN_SCOPED_LEAK_CHECKER("LoadAndUnloadNetworkGpuAcc");
-        BOOST_TEST(ARMNN_NO_LEAKS_IN_SCOPE());
-        // In the second run we check for all remaining memory
-        // in use after the network was unloaded. If there is any
-        // then it will be treated as a memory leak.
-        CreateAndDropDummyNetwork(backends, runtime);
-        BOOST_TEST(ARMNN_NO_LEAKS_IN_SCOPE());
-        BOOST_TEST(ARMNN_BYTES_LEAKED_IN_SCOPE() == 0);
-        BOOST_TEST(ARMNN_OBJECTS_LEAKED_IN_SCOPE() == 0);
-    }
-}
-#endif // ARMCOMPUTECL_ENABLED
-
-#ifdef ARMCOMPUTENEON_ENABLED
-BOOST_AUTO_TEST_CASE(RuntimeMemoryLeaksCpuAcc)
-{
-    BOOST_TEST(ARMNN_LEAK_CHECKER_IS_ACTIVE());
-    armnn::IRuntime::CreationOptions options;
-    armnn::Runtime runtime(options);
-    armnn::RuntimeLoadedNetworksReserve(&runtime);
-
-    std::vector<armnn::BackendId> backends = {armnn::Compute::CpuAcc};
-    {
-        // Do a warmup of this so we make sure that all one-time
-        // initialization happens before we do the leak checking.
-        CreateAndDropDummyNetwork(backends, runtime);
-    }
-
-    {
-        ARMNN_SCOPED_LEAK_CHECKER("LoadAndUnloadNetworkCpuAcc");
-        BOOST_TEST(ARMNN_NO_LEAKS_IN_SCOPE());
-        // In the second run we check for all remaining memory
-        // in use after the network was unloaded. If there is any
-        // then it will be treated as a memory leak.
-        CreateAndDropDummyNetwork(backends, runtime);
-        BOOST_TEST(ARMNN_NO_LEAKS_IN_SCOPE());
-        BOOST_TEST(ARMNN_BYTES_LEAKED_IN_SCOPE() == 0);
-        BOOST_TEST(ARMNN_OBJECTS_LEAKED_IN_SCOPE() == 0);
-    }
-}
-#endif // ARMCOMPUTENEON_ENABLED
-
-BOOST_AUTO_TEST_CASE(RuntimeMemoryLeaksCpuRef)
-{
-    BOOST_TEST(ARMNN_LEAK_CHECKER_IS_ACTIVE());
-
-    armnn::IRuntime::CreationOptions options;
-    armnn::Runtime runtime(options);
-    armnn::RuntimeLoadedNetworksReserve(&runtime);
-
-    std::vector<armnn::BackendId> backends = {armnn::Compute::CpuRef};
-    {
-        // Do a warmup of this so we make sure that all one-time
-        // initialization happens before we do the leak checking.
-        CreateAndDropDummyNetwork(backends, runtime);
-    }
-
-    {
-        ARMNN_SCOPED_LEAK_CHECKER("LoadAndUnloadNetworkCpuRef");
-        BOOST_TEST(ARMNN_NO_LEAKS_IN_SCOPE());
-        // In the second run we check for all remaining memory
-        // in use after the network was unloaded. If there is any
-        // then it will be treated as a memory leak.
-        CreateAndDropDummyNetwork(backends, runtime);
-        BOOST_TEST(ARMNN_NO_LEAKS_IN_SCOPE());
-        BOOST_TEST(ARMNN_BYTES_LEAKED_IN_SCOPE() == 0);
-        BOOST_TEST(ARMNN_OBJECTS_LEAKED_IN_SCOPE() == 0);
-    }
-}
-
 #endif // ARMNN_LEAK_CHECKING_ENABLED
 
 // Note: this part of the code is due to be removed when we fully trust the gperftools based results.
-#if defined(ARMCOMPUTECL_ENABLED) && defined(WITH_VALGRIND)
-BOOST_AUTO_TEST_CASE(RuntimeMemoryUsage)
-{
-    // From documentation:
-
-    // This means that no pointer to the block can be found. The block is classified as "lost",
-    // because the programmer could not possibly have freed it at program exit, since no pointer to it exists.
-    unsigned long leakedBefore = 0;
-    unsigned long leakedAfter = 0;
-
-    // A start-pointer or chain of start-pointers to the block is found. Since the block is still pointed at,
-    // the programmer could, at least in principle, have freed it before program exit.
-    // We want to test this in case memory is not freed as early as it could have been.
-    unsigned long reachableBefore = 0;
-    unsigned long reachableAfter = 0;
-
-    // Needed as out params but we don't test them.
-    unsigned long dubious = 0;
-    unsigned long suppressed = 0;
-
-    // Ensure that runtime is large enough before checking for memory leaks.
-    // Otherwise, when loading the network, it will automatically reserve memory that won't be released
-    // until destruction.
-    armnn::NetworkId networkIdentifier;
-    armnn::IRuntime::CreationOptions options;
-    armnn::Runtime runtime(options);
-    armnn::RuntimeLoadedNetworksReserve(&runtime);
-
-    // Checks for leaks before we load the network and record them so that we can see the delta after unloading.
-    VALGRIND_DO_QUICK_LEAK_CHECK;
-    VALGRIND_COUNT_LEAKS(leakedBefore, dubious, reachableBefore, suppressed);
-
-    // build a mock-network and load it into the runtime
-    std::vector<armnn::BackendId> backends = {armnn::Compute::GpuAcc};
-    {
-        armnn::TensorInfo inputTensorInfo(armnn::TensorShape({ 7, 7 }), armnn::DataType::Float32);
-        armnn::TensorInfo outputTensorInfo(armnn::TensorShape({ 7, 7 }), armnn::DataType::Float32);
-
-        armnn::INetworkPtr mockNetwork(armnn::INetwork::Create());
-
-        armnn::IConnectableLayer* input = mockNetwork->AddInputLayer(0, "input");
-        armnn::IConnectableLayer* layer = mockNetwork->AddActivationLayer(armnn::ActivationDescriptor(), "test");
-        armnn::IConnectableLayer* output = mockNetwork->AddOutputLayer(0, "output");
-
-        input->GetOutputSlot(0).Connect(layer->GetInputSlot(0));
-        layer->GetOutputSlot(0).Connect(output->GetInputSlot(0));
-
-        // Sets the tensors in the network.
-        input->GetOutputSlot(0).SetTensorInfo(inputTensorInfo);
-        layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
-
-        // optimize the network
-        armnn::IOptimizedNetworkPtr optNet = Optimize(*mockNetwork, backends, runtime.GetDeviceSpec());
-
-        runtime.LoadNetwork(networkIdentifier, std::move(optNet));
-    }
-
-    runtime.UnloadNetwork(networkIdentifier);
-
-    VALGRIND_DO_ADDED_LEAK_CHECK;
-    VALGRIND_COUNT_LEAKS(leakedAfter, dubious, reachableAfter, suppressed);
-
-    // If we're not running under Valgrind, these vars will have been initialised to 0, so this will always pass.
-    BOOST_TEST(leakedBefore == leakedAfter);
-
-    // Add resonable threshold after and before running valgrind with the ACL clear cache function.
-    // TODO Threshold set to 80k until the root cause of the memory leakage is found and fixed. Revert threshold
-    // value to 1024 when fixed.
-    BOOST_TEST(static_cast<long>(reachableAfter) - static_cast<long>(reachableBefore) < 81920);
-
-    // These are needed because VALGRIND_COUNT_LEAKS is a macro that assigns to the parameters
-    // so they are assigned to, but still considered unused, causing a warning.
-    boost::ignore_unused(dubious);
-    boost::ignore_unused(suppressed);
-}
-#endif
-
-// Note: this part of the code is due to be removed when we fully trust the gperftools based results.
 #ifdef WITH_VALGRIND
 // Run with the following command to get all the amazing output (in the devenv/build folder) :)
 // valgrind --leak-check=full --show-leak-kinds=all --log-file=Valgrind_Memcheck_Leak_Report.txt armnn/test/UnitTests
@@ -341,80 +149,15 @@ BOOST_AUTO_TEST_CASE(RuntimeMemoryLeak)
     VALGRIND_COUNT_LEAKS(leakedAfter, dubious, reachableAfter, suppressed);
 
     // If we're not running under Valgrind, these vars will have been initialised to 0, so this will always pass.
-    BOOST_TEST(leakedBefore == leakedAfter);
-
-    #if defined(ARMCOMPUTECL_ENABLED)
-        // reachableBefore == reachableAfter should hold, but on OpenCL with Android we are still
-        // not entirely able to control the memory in the OpenCL driver. Testing is showing that
-        // after this test (which clears all OpenCL memory) we are clearing a little bit more than
-        // we expect, probably depending on the order in which other tests are run.
-        BOOST_TEST(reachableBefore - reachableAfter <= 24);
-    #else
-        BOOST_TEST(reachableBefore == reachableAfter);
-    #endif
-
-    BOOST_TEST(reachableBefore >= reachableAfter);
+    BOOST_TEST(leakedBefore    == leakedAfter);
+    BOOST_TEST(reachableBefore == reachableAfter);
 
     // These are needed because VALGRIND_COUNT_LEAKS is a macro that assigns to the parameters
     // so they are assigned to, but still considered unused, causing a warning.
     boost::ignore_unused(dubious);
     boost::ignore_unused(suppressed);
 }
-#endif
-
-#if ARMCOMPUTENEON_ENABLED
-BOOST_AUTO_TEST_CASE(RuntimeValidateCpuAccDeviceSupportLayerNoFallback)
-{
-    // build up the structure of the network
-    armnn::INetworkPtr net(armnn::INetwork::Create());
-
-    armnn::IConnectableLayer* input = net->AddInputLayer(0);
-
-    armnn::IConnectableLayer* output = net->AddOutputLayer(0);
-
-    input->GetOutputSlot(0).Connect(output->GetInputSlot(0));
-
-    input->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo({ 1, 1, 4, 4 }, armnn::DataType::Float32));
-
-    armnn::IRuntime::CreationOptions options;
-    armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
-
-    std::vector<armnn::BackendId> backends = { armnn::Compute::CpuAcc };
-    armnn::IOptimizedNetworkPtr optNet = armnn::Optimize(*net, backends, runtime->GetDeviceSpec());
-    BOOST_CHECK(optNet);
-
-    // Load it into the runtime. It should success.
-    armnn::NetworkId netId;
-    BOOST_TEST(runtime->LoadNetwork(netId, std::move(optNet)) == armnn::Status::Success);
-}
-#endif // ARMCOMPUTENEON_ENABLED
-
-#if ARMCOMPUTECL_ENABLED
-BOOST_AUTO_TEST_CASE(RuntimeValidateGpuDeviceSupportLayerNoFallback)
-{
-    // build up the structure of the network
-    armnn::INetworkPtr net(armnn::INetwork::Create());
-
-    armnn::IConnectableLayer* input = net->AddInputLayer(0);
-
-    armnn::IConnectableLayer* output = net->AddOutputLayer(0);
-
-    input->GetOutputSlot(0).Connect(output->GetInputSlot(0));
-
-    input->GetOutputSlot(0).SetTensorInfo(armnn::TensorInfo({ 1, 1, 4, 4 }, armnn::DataType::Float32));
-
-    armnn::IRuntime::CreationOptions options;
-    armnn::IRuntimePtr runtime(armnn::IRuntime::Create(options));
-
-    std::vector<armnn::BackendId> backends = { armnn::Compute::GpuAcc };
-    armnn::IOptimizedNetworkPtr optNet = armnn::Optimize(*net, backends, runtime->GetDeviceSpec());
-    BOOST_CHECK(optNet);
-
-    // Load it into the runtime. It should success.
-    armnn::NetworkId netId;
-    BOOST_TEST(runtime->LoadNetwork(netId, std::move(optNet)) == armnn::Status::Success);
-}
-#endif // ARMCOMPUTECL_ENABLED
+#endif // WITH_VALGRIND
 
 BOOST_AUTO_TEST_CASE(RuntimeCpuRef)
 {